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Warburg Effect Revisited – 2

Writer and Curator: Larry H. Bernstein, MD, FCAP

Finding Dysregulation in the Cancer Cell

2.1.         Warburg Effect Revisited

One of the great observations of the 20th century was the behavior of cancer cells to proliferate and rely on anaerobic glycolysis for the source of energy.  This was a restatement of the Pasteur effect, described 60 years earlier by the great French scientist in yeast experiments.  The experiments with yeast were again reperformed by Jose EDS Roselino, a Brazilian biochemist, who established an explanation for it 50 years after Warburg.  It is quite amazing the mitochondria were not yet discovered at the time that Warburg carried out the single-cell thickness measurements in his respiratory apparatus. He concluded from the observation that the cancer cells grew in a media that became acidic from producing lactic acid, that the cells were dysfunctional in the utilization of oxygen, as nonmalignant cells efficiently utilized oxygen. He also related the metabolic events to observations made by Meyerhof.  The mitochondria and the citric acid cycle at this time had not yet been discovered, and the latter was, worked out by Hans Krebs and Albert Szent-Gyorgi, both of whom worked with him on mitochondrial metabolism.  The normal cell utilizes glucose efficiently and lipids as well, generating energy through oxidative phosphorylation, with the production of ATP in a manner previously described in these posts.  Greater clarity was achieved with the discovery of Coenzyme A, and finally the electron transport chain (ETC).  This requires that the pyruvate be directed into the tricarboxylic acid cycle and to go through a series of reactions producing succinate and finally malate.

The following great achievements were made with regard to elucidating these processes:

1922 Archibald Vivian Hill United Kingdom “for his discovery relating to the production of heat in the muscle[26]
Otto Fritz Meyerhof Germany “for his discovery of the fixed relationship between the consumption of oxygen and the metabolism of lactic acid in the muscle”[26]
1931 Otto Heinrich Warburg Germany “for his discovery of the nature and mode of action of the respiratory enzyme[34]
1937 Albert Szent-Györgyi von Nagyrapolt Hungary “for his discoveries in connection with the biological combustion processes, with special reference to vitamin C and the catalysis of fumaric acid[40]
1953 Sir Hans Adolf Krebs United Kingdom “for his discovery of the citric acid cycle[53]
Fritz Albert Lipmann United States “for his discovery of co-enzyme A and its importance for intermediary metabolism”[53]
1955 Axel Hugo Theodor Theorell Sweden “for his discoveries concerning the nature and mode of action of oxidation enzymes”[55]
1978 Peter D. Mitchell United Kingdom “for his contribution to the understanding of biological energy transfer through the formulation of the chemiosmotic theory[77]
1997 Paul D. Boyer United States “for their elucidation of the enzymatic mechanism underlying the synthesis of adenosine triphosphate (ATP)”[96]
John E. Walker United Kingdom

 

 1967  Manfred Eigen   and the other half jointly to:

Ronald George Wreyford Norrish and Lord George Porter for their studies of extremely fast chemical reactions, effected by disturbing the equlibrium by means of very short pulses of energy.

1965   FRANÇOIS JACOB , ANDRÉ LWOFF And JACQUES MONOD for their discoveries concerning genetic control of enzyme and virus synthesis.

1964 KONRAD BLOCH And FEODOR LYNEN for their discoveries concerning the mechanism and regulation of the cholesterol and fatty acid metabolism.

If there is a more immediate need for energy (as in stressed muscular activity) with net oxygen insufficiency, the pyruvate is converted to lactic acid, with acidemia, and with much less ATP production, but the lactic academia and the energy deficit is subsequently compensated for.    The observation made by Jose EDS Rosalino was that yeast grown in a soil deficient in oxygen don’t put down roots.

^I. Topisirovic and N. Sonenberg

Cold Spring Harbor Symposia on Quantitative Biology, Volume LXXVI

http://dx.doi.org:/10.1101/sqb.2011.76.010785 ”A prominent feature of cancer cells is the use of aerobic glycolysis under conditions in which oxygen levels are sufficient to support energy production in the mitochondria (Jones and Thompson 2009; Cairns et al. 2010). This phenomenon, named the “Warburg effect,” after its discoverer Otto Warburg, is thought to fuel the biosynthetic requirements of the neoplastic growth (Warburg 1956; Koppenol et al. 2011) and has recently been acknowledged as one of the hallmarks of cancer (Hanahan and Weinberg 2011). mRNA translation is the most energy-demanding process in the cell (Buttgereit and Brand 1995).

Again, the use of aerobic glycolysis expression has been twisted.”

To understand my critical observation consider this: Aerobic glycolysis is the carbon flow that goes from Glucose to CO2 and water (includes Krens cycle and respiratory chain for the restoration of NAD, FAD etc.

Anerobic glyclysis is the carbon flow that goes from glucose to lactate. It uses conversion of pyruvate to lactate to regenerate NAD.

“Pasteur effect” is an expression coined by Warburg, which refers to the reduction in the carbon flow from glucose when oxygen is offered to yeasts. The major reason for that is in general terms, derived from the fact that carbon flow is regulated by several cell requirements but mainly by the ATP needs of the cell. Therefore, as ATP is generated 10 more efficiently in aerobiosis than under anaerobiosis, less carbon flow is required under aerobiosis than under anaerobiosis to maintain ATP levels. Warburg, after searching for the same regulatory mechanism in normal and cancer cells for comparison found that transformed cell continued their large flow of glucose carbons to lactate despite the presence of oxygen.

So, it is wrong to describe that aerobic glycolysis continues in the presence of oxygen. It is what it is expected to occur. The wrong thing is that anaerobic glycolysis continues under aerobiosis.
^Aurelian Udristioiu (comment)
In cells, the immediate energy sources involve glucose oxidation. In anaerobic metabolism, the donor of the phosphate group is adenosine triphosphate (ATP), and the reaction is catalyzed via the hexokinase or glucokinase: Glucose +ATP-Mg²+ = Glucose-6-phosphate (ΔGo = – 3.4 kcal/mol with hexokinase as the co-enzyme for the reaction.).

In the following step, the conversion of G-6-phosphate into F-1-6-bisphosphate is mediated by the enzyme phosphofructokinase with the co-factor ATP-Mg²+. This reaction has a large negative free energy difference and is irreversible under normal cellular conditions. In the second step of glycolysis, phosphoenolpyruvic acid in the presence of Mg²+ and K+ is transformed into pyruvic acid. In cancer cells or in the absence of oxygen, the transformation of pyruvic acid into lactic acid alters the process of glycolysis.

The energetic sum of anaerobic glycolysis is ΔGo = -34.64 kcal/mol. However a glucose molecule contains 686kcal/mol and, the energy difference (654.51 kcal) allows the potential for un-controlled reactions during carcinogenesis. The transfer of electrons from NADPH in each place of the conserved unit of energy transmits conformational exchanges in the mitochondrial ATPase. The reaction ADP³+ P²¯ + H²à ATP + H2O is reversible. The terminal oxygen from ADP binds the P2¯ by forming an intermediate pentacovalent complex, resulting in the formation of ATP and H2O. This reaction requires Mg²+ and an ATP-synthetase, which is known as the H+-ATPase or the Fo-F1-ATPase complex. Intracellular calcium induces mitochondrial swelling and aging. [12].

The known marker of monitoring of treatment in cancer diseases, lactate dehydrogenase (LDH) is an enzyme that is localized to the cytosol of human cells and catalyzes the reversible reduction of pyruvate to lactate via using hydrogenated nicotinamide deaminase (NADH) as co-enzyme.

The causes of high LDH and high Mg levels in the serum include neoplastic states that promote the high production of intracellular LDH and the increased use of Mg²+ during molecular synthesis in processes pf carcinogenesis (Pyruvate acid>> LDH/NADH >>Lactate acid + NAD), [13].

The material we shall discuss explores in more detail the dysmetabolism that occurs in cancer cells.

Is the Warburg Effect the Cause or the Effect of Cancer: A 21st Century View?
http://pharmaceuticalintelligence.com/2014/06/21/is-the-warburg-effect-the-cause-or-the-effect-of-cancer-a-21st-century-view-2/

Warburg Effect Revisited
http://pharmaceuticalintelligence.com/2013/11/28/warburg-effect-revisited/

AMPK Is a Negative Regulator of the Warburg Effect and Suppresses Tumor Growth In Vivo
http://pharmaceuticalintelligence.com/2013/03/12/ampk-is-a-negative-regulator-of-the-warburg-effect-and-suppresses-tumor-growth-in-vivo/

AKT Signaling Variable Effects
http://pharmaceuticalintelligence.com/2013/03/04/akt-signaling-variable-effects/

Otto Warburg, A Giant of Modern Cellular Biology
http://pharmaceuticalintelligence.com/2012/11/02/otto-warburg-a-giant-of-modern-cellular-biology/

The Metabolic View of Epigenetic Expression
http://pharmaceuticalintelligence.com/2015/03/28/the-metabolic-view-of-epigenetic-expression/

Metabolomics Summary and Perspective
http://pharmaceuticalintelligence.com/2014/10/16/metabolomics-summary-and-perspective/

2.1.1       Cancer Metabolism

2.1.1.1  Oncometabolites: linking altered  metabolism with cancer

Ming Yang, Tomoyoshi Soga, and Patrick J. Pollard
J Clin Invest Sep 2013; 123(9):3652–3658
http://dx.doi.org:/10.1172/JCI67228

The discovery of cancer-associated mutations in genes encoding key metabolic enzymes has provided a direct link between altered metabolism and cancer. Advances in mass spectrometry and nuclear magnetic resonance technologies have facilitated high-resolution metabolite profiling of cells and tumors and identified the accumulation of metabolites associated with specific gene defects. Here we review the potential roles of such “oncometabolites” in tumor evolution and as clinical biomarkers for the detection of cancers characterized by metabolic dysregulation.

The emerging interest in metabolites whose abnormal accumulation causes both metabolic and nonmetabolic dysregulation and potential transformation to malignancy (herein termed “oncometabolites”) has been fueled by the identification of cancerassociated mutations in genes encoding enzymes with significant roles in cellular metabolism (1–5). Loss-of-function mutations in genes encoding the Krebs cycle enzymes fumarate hydratase (FH) and succinate dehydrogenase (SDH) cause the accumulation of fumarate and succinate, respectively (6), whereas gain-offunction isocitrate dehydrogenase (IDH) mutations increase levels of D–2-hydroxyglutarate (D-2HG) (7, 8). These metabolites have been implicated in the dysregulation of cellular processes including the competitive inhibition of α-ketoglutarate–dependent (α-KG–dependent) dioxygenase enzymes (also known as 2-oxoglutarate–dependent dioxgenases) and posttranslational modification of proteins (1, 4, 9–11). To date, several lines of biochemical and genetic evidence support roles for fumarate, succinate, and D-2HG in cellular transformation and oncogenesis (3, 12).

The Journal of Clinical Investigation   http://www.jci.org   Volume 123   Number 9   September 2013

ventional gene sequencing methods may lead to false positives due to genetic polymorphism and sequencing artifacts (98). In comparison, screening for elevated 2HG levels is a sensitive and specific approach to detect IDH mutations in tumors. Whereas patient sera/plasma can be assessed in the case of AML (7, 8, 21, 99), exciting advances with proton magnetic resonance spectroscopy (MRS) have been made in the noninvasive detection of 2HG in patients with gliomas (100–103). Using MRS sequence optimization and spectral fitting techniques, Maher and colleagues examined 30 patients with glioma and showed that the detection of 2HG correlated 100% with the presence of IDH1 or IDH2 mutations (102). Andronesi et al. further demonstrated that two-dimensional correlation spectroscopy could effectively distinguish 2HG from chemically similar metabolites present in the brain (103). Negative IHC staining for SDHB correlates with the presence of SDH mutations, whether in SDHB, SDHC, or SDHD (104). This finding is most likely explained by the fact that mutations in any of the four subunits of SDH can destabilize the entire enzyme complex. PGLs/PCCs associated with an SDHA mutation show negative staining for SDHA as well as SDHB (105). Therefore, IHC staining for SDHB is a useful diagnostic tool to triage patients for genetic testing of any SDH mutation, and subsequent staining for the other subunits may further narrow the selection of genes to be tested. In contrast, detection of FH protein is often evident in HLRCC tumors due to retention of the nonfunctional mutant allele (106). However, staining of cysts and tumors for 2SC immunoreactivity reveals a striking correlation between FH inactivation and the presence of 2SC-modified protein (2SCP), which is absent in non-HLRCC tumors and normal tissue controls (106). IHC staining for 2SCP thus provides a robust diagnostic biomarker for FH deficiency (107).

Therapeutic targeting Because D-2HG is a product of neomorphic enzyme activities, curtailing the D-2HG supply by specifically inhibiting the mutant IDH enzymes provides an elegant approach to target IDH-mutant cancers. Indeed, recent reports of small-molecule inhibitors against mutant forms of IDH1 and IDH2 demonstrated the feasibility of this method. An inhibitor against IDH2 R140Q was shown to reduce both intracellular and extracellular levels of D-2HG, suppress cell growth, and increase differentiation of primary human AML cells (108). Similarly, small-molecule inhibition of IDH1 R132H suppressed colony formation and increased tumor cell differentiation in a xenograft model for IDH1 R132H glioma (58). The inhibitors exhibited a cytostatic rather than cytotoxic effect, and therefore their therapeutic efficacy over longer time periods may need further assessment (109). Letouzé et al. showed that the DNA methytransferase inhibitor decitabine could repress the migration capacities of SDHB-mutant cells (40). However, for SDH- and FH-associated cancers, a synthetic lethality approach is worth exploring because of the pleiotrophic effects associated with succinate and fumarate accumulation.

Outlook The application of next-generation sequencing technologies in the field of cancer genomics has substantially increased our understanding of cancer biology. Detection of germline and somatic mutations in specific tumor types not only expands the current repertoire of driver mutations and downstream effectors in tumorigenesis, but also sheds light on how oncometabolites may exert their oncogenic roles. For example, the identification of mutually exclusive mutations in IDH1 and TET2 in AML led to the characterization of TET2 as a major pathological target of D-2HG (34, 110). Additionally, the discovery of somatic CUL3, SIRT1, and NRF2 mutations in sporadic PRCC2 converges with FH mutation in HLRCC, in which NRF2 activation is a consequence of fumarate-mediated succination of KEAP1, indicating the functional prominence of the NRF2 pathway in PRCC2 (73). In light of this, the identification of somatic mutations in genes encoding the chromatin-modifying enzymes histone H3K36 methyltransferase (SETD2), histone H3K4 demethylase JARID1C (KDM5C), histone H3K27 demethylase UTX (KDM6A), and the SWI/SNF chromatin remodelling complex gene PBRM1 in clear cell renal cell carcinoma (111–113) highlights the importance of epigenetic modulation in human cancer and raises the potential for systematic testing in other types of tumors such as those associated with FH mutations. Technological advances such as those in gas and liquidchromatography mass spectrometry (114, 115) and nuclear magnetic resonance imaging (102) have greatly improved the ability to measure low-molecular-weight metabolites in tumor samples with high resolution (116). Combined with metabolic flux analyses employing isotope tracers and mathematical modeling, modern-era metabolomic approaches can provide direct pathophysiological insights into tumor metabolism and serve as an excellent tool for biomarker discovery. Using a data-driven approach, Jain and colleagues constructed the metabolic profiles of 60 cancer cell lines and discovered glycine consumption as a key metabolic event in rapidly proliferating cancer cells (117), thus demonstrating the power of metabolomic analyses and the relevance to future cancer research and therapeutics.

Acknowledgments The Cancer Biology and Metabolism Group is funded by Cancer Research UK and the European Research Council under the European Community’s Seventh Framework Programme (FP7/20072013)/ERC grant agreement no. 310837 to Dr. Pollard. Professor Soga receives funding from a Grant-in-Aid for scientific research on Innovative Areas, Japan (no. 22134007), and the Yamagata Prefectural Government and City of Tsuruoka.

Address correspondence to: Patrick J. Pollard, Cancer Biology and Metabolism Group, Nuffield Department of Medicine, Henry Wellcome Building for Molecular Physiology, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, United Kingdom. Phone: 44.0.1865287780; Fax: 44.0.1865287787; E-mail:  patrick.pollard@well.ox.ac.uk.

  1. Yang M, Soga T, Pollard PJ, Adam J. The emerging role of fumarate as an oncometabolite. Front Oncol. 2012;2:85. 2. Ward PS, Thompson CB. Metabolic reprogramming: a cancer hallmark even warburg did not anticipate. Cancer Cell. 2012;21(3):297–308. 3. Vander Heiden MG, Cantley LC, Thompson CB. Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science. 2009; 324(5930):1029–1033. 4. Thompson CB. Metabolic enzymes as oncogenes or tumor suppressors. N Engl J Med. 2009; 360(8):813–815. 5. Schulze A, Harris AL. How cancer metabolism is tuned for proliferation and vulnerable to disruption. Nature. 2012;491(7424):364–373.
  1. Pollard PJ, et al. Accumulation of Krebs cycle intermediates and over-expression of HIF1alpha in tumours which result from germline FH and SDH mutations. Hum Mol Genet. 2005; 14(15):2231–2239. 7. Ward PS, et al. The common feature of leukemiaassociated IDH1 and IDH2 mutations is a neomorphic enzyme activity converting alpha-ketoglutarate to 2-hydroxyglutarate. Cancer Cell. 2010; 17(3):225–234.

Because D-2HG is a product of neomorphic enzyme activities, curtailing the D-2HG supply by specifically inhibiting the mutant IDH enzymes provides an elegant approach to target IDH-mutant cancers. Indeed, recent reports of small-molecule inhibitors against mutant forms of IDH1 and IDH2 demonstrated the feasibility of this method. An inhibitor against IDH2 R140Q was shown to reduce both intracellular and extracellular levels of D-2HG, suppress cell growth, and increase differentiation of primary human AML cells (108). Similarly, small-molecule inhibition of IDH1 R132H suppressed colony formation and increased tumor cell differentiation in a xenograft model for IDH1 R132H glioma (58). The inhibitors exhibited a cytostatic rather than cytotoxic effect, and therefore their therapeutic efficacy over longer time periods may need further assessment (109). Letouzé et al. showed that the DNA methytransferase inhibitor decitabine could repress the migration capacities of SDHB-mutant cells (40). However, for SDH- and FH-associated cancers, a synthetic lethality approach is worth exploring because of the pleiotrophic effects associated with succinate and fumarate accumulation.

Technological advances such as those in gas and liquid chromatography mass spectrometry (114, 115) and nuclear magnetic resonance imaging (102) have greatly improved the ability to measure low-molecular-weight metabolites in tumor samples with high resolution (116). Combined with metabolic flux analyses employing isotope tracers and mathematical modeling, modern-era metabolomic approaches can provide direct pathophysiological insights into tumor metabolism and serve as an excellent tool for biomarker discovery. Using a data-driven approach, Jain and colleagues constructed the metabolic profiles of 60 cancer cell lines and discovered glycine consumption as a key metabolic event in rapidly proliferating cancer cells (117), thus demonstrating the power of metabolomic analyses and the relevance to future cancer research and therapeutics.

Figure 1 D-2HG produced by mutant IDH1/2 affects metabolism and epigenetics by modulating activities of α-KG–dependent oxygenases. Wild-type IDH1 and IDH2 catalyze the NADP+-dependent reversible conversion of isocitrate to α-KG, whereas cancer-associated gain-of-function mutations enable mutant IDH1/2 (mIDH1/2) to catalyze the oxidation of α-KG to D-2HG, using NADPH as a cofactor. Because D-2HG is structurally similar to α-KG, its accumulation can modulate the activities of α-KG–utilizing dioxygenases. Inhibition of 5mC hydroxylase TET2 and the KDMs results in increased CpG island methylation and increased histone methylation marks, respectively, thus blocking lineage-specific cell differentiation. Inhibition of collagen prolyl and lysyl hydroxylases (C-P4Hs and PLODs, respectively) leads to impaired collagen maturation and disrupted basement membrane formation. D-2HG can also stimulate the activities of HIF PHDs, leading to enhanced HIF degradation and a diminished HIF response, which are associated with increased soft agar growth of human astrocytes and growth factor independence of leukemic cells. Together these processes exert pleiotrophic effects on cell signaling and gene expression that probably contribute to the malignancy of IDH1/2-mutant cells.
Figure 2 Candidate oncogenic mechanisms of succinate and fumarate accumulation. SDH and FH are Krebs cycle enzymes and tumor suppressors. Loss-of-function mutations in SDH and FH result in abnormal accumulation of Krebs cycle metabolites succinate (Succ) and fumarate (Fum), respectively, both of which can inhibit the activities of α-KG–dependent oxygenases. Inhibition of HIF PHDs leads to activation of HIF-mediated pseudohypoxic response, whereas inhibition of KDMs and TET family of 5mC hydroxylases causes epigenetic alterations. Fumarate is electrophilic and can also irreversibly modify cysteine residues in proteins by succination. Succination of KEAP1 in FH deficiency results in the constitutive activation of the antioxidant defense pathway mediated by NRF2, conferring a reductive milieu that promotes cell proliferation. Succination of the Krebs cycle enzyme Aco2 impairs aconitase activity in Fh1-deficient MEFs. Fumarate accumulation may also affect cytosolic pathways by inhibiting the reactions involved in the biosynthesis of arginine and purine. AcCoA, acetyl CoA; Mal, malate; OAA, oxaloacetate; Succ-CA, succinyl CoA.

2.1.1.2. Emerging concepts: linking hypoxic signaling and cancer metabolism.

Lyssiotis CA, Vander-Heiden MG, Muñoz-Pinedo C, Emerling BM.
Cell Death Dis. 2012 May 3; 3:e303
http://dx.doi.org:/10.1038/cddis.2012.41

The Joint Keystone Symposia on Cancer and Metabolism and Advances in Hypoxic Signaling: From Bench to Bedside were held in Banff, Alberta, Canada from 12 to 17 February 2012. Drs. Reuben Shaw and David Sabatini organized the Cancer and Metabolism section, and Drs. Volker Haase, Cormac Taylor, Johanna Myllyharju and Paul Schumacker organized the Advances in Hypoxic Signaling section. Accumulating data illustrate that both hypoxia and rewired metabolism influence cancer biology. Indeed, these phenomena are tightly coupled, and a joint meeting was held to foster interdisciplinary interactions and enhance our understanding of these two processes in neoplastic disease. In this report, we highlight the major themes of the conference paying particular attention to areas of intersection between hypoxia and metabolism in cancer.

One opening keynote address was delivered by Craig Thompson (Memorial Sloan-Kettering, USA), in which he provided a comprehensive perspective on the current thinking around how altered metabolism supports cancer cell growth and survival, and discussed areas likely to be important for future discovery. In particular, Thompson highlighted the essential roles of glucose and glutamine in cell growth, how glucose- and glutamine-consuming processes are rewired in cancer and how this rewiring facilitates anabolic metabolism. These topics were at the core of many of the metabolism presentations that described in detail how some metabolic alterations contribute to the properties of transformed cells.

The other keynote address was delivered by Peter Ratcliffe (University of Oxford, UK), in which he provided a historical perspective on the progress of how signaling events sense oxygen. Mammals have evolved multiple acute and long-term adaptive responses to low oxygen levels (hypoxia). This response prevents a disparity in ATP utilization and production that would otherwise result in a bioenergetic collapse when oxygen level is low. Multiple effectors have been proposed to mediate the response to hypoxia including prolyl hydroxylases, AMPK, NADPH oxidases and the mitochondrial complex III. Currently, however, the precise mechanism by which oxygen is sensed in various physiological contexts remains unknown. Indeed, this was an active point of debate, with Peter Ratcliffe favoring the prolyl hydroxylase PHD2 as the primary cellular oxygen sensor.

Anabolic glucose metabolism and the Warburg effect

Nearly a century ago, Warburg noted that cancer tissues take up glucose in excess than most normal tissues and secrete much of the carbon as lactate. Recently, headway has been made toward determining how the enhanced glucose conversion to lactate occurs and contributes to cell proliferation and survival. Heather Christofk (University of California, Los Angeles, USA) and John Cleveland (the Scripps Research Institute, USA) described a role for the lactate/pyruvate transporter MCT-1 in carbon secretion, and suggested that blocking lactate or pyruvate transport may be a strategy to target glucose metabolism in cancer cells. Kun-Liang Guan (University of California, San Diego, USA) described a novel feedback loop to control glucose metabolism in highly glycolytic cells. Specifically, he discussed how glucose-derived acetyl-CoA can be used as a substrate to modify two enzymes involved in glucose metabolism, pyruvate kinase M2 (PKM2) and phosphoenolpyruvate carboxylase (PEPCK). In both cases, acetylation leads to protein degradation and decreased glycolysis and gluconeogenesis, respectively. Data presented from Matthew Vander Heiden’s laboratory (Koch Institute/MIT, USA) illustrated that loss of pyruvate kinase activity can accelerate tumor growth, suggesting that the regulation of glycolysis may be more complex than previously appreciated. Almut Schulze (London Research Institute, UK) discussed a novel regulatory role for phosphofructokinase in controlling glucose metabolism and Jeffrey Rathmell (Duke University, USA) discussed parallels between glucose metabolism in cancer cells and lymphocytes that suggest many of these phenotypes could be a feature of rapidly dividing cells.

Glutamine addiction

Cancer cells also consume glutamine to support proliferation and survival. Alfredo Csibi (Harvard Medical School, USA) described how mTORC1 promotes glutamine utilization by indirectly regulating the activity of glutamate dehydrogenase. This work united two major themes at the meeting, mTOR signaling and glutamine metabolism, highlighting the interconnectedness of signal transduction and metabolic regulation. Richard Cerione (Cornell University, USA) described a small molecule inhibitor of glutaminase that can be used to target glutamine-addicted cancer cells. Christian Metallo (University of California, San Diego, USA), Andrew Mullen (University of Texas Southwestern Medical School, USA) and Patrick Ward (Memorial Sloan-Kettering, USA) presented data demonstrating that the carbon skeleton of glutamine can be incorporated into newly synthesized lipids. This contribution of glutamine to lipid synthesis was most pronounced in hypoxia or when the mitochondrial electron transport chain was compromised.

Signal transduction and metabolism

The protein kinases AMPK and mTOR can function as sensors of metabolic impairment, whose activation by energy stress controls multiple cellular functions. Grahame Hardie (University of Dundee, UK) and Reuben Shaw (Salk Institute, USA) highlighted novel roles for AMPK, including inhibition of viral replication, and the control of histone acetylation via phosphorylation of class IIa HDACs, respectively. Brandon Faubert (McGill University, USA) reported on an AMPK-dependent effect on glucose metabolism in unstressed cells. Brendan Manning (Harvard Medical School, USA) found that chronic activation of mTOR in the mouse liver, due to genetic ablation of this complex, promotes the development of liver cancer. Kevin Williams (University of California, Los Angeles, USA) discussed how growth signaling can control both lipid and glucose metabolism by impinging on SREBP-1, a transcription factor downstream of mTOR. AMPK-independent control of mTOR was addressed by John Blenis (Harvard Medical School, USA), who discussed the possible role of mTOR stabilizing proteins as mediators of mTOR inactivation upon energetic stress. David Sabatini (Whitehead Institute/MIT, USA) discussed several aspects of amino-acid sensing by Rag GTPases and showed that constitutive activation of the Rag GTPases leads to metabolic defects in mice.

One of the outcomes of AMPK activation and mTOR inhibition is autophagy, which can provide amino acids and fatty acids to nutrient-deprived cells. Ana Maria Cuervo (Albert Einstein College of Medicine, USA) and Eileen White (Rutgers University, USA) illuminated the role of chaperone-mediated autophagy (CMA) and macroautophagy, respectively, in tumor survival. White described a role for macroautophagy in the regulation of mitochondrial fitness, maintenance of TCA cycle and tumorigenesis induced by oncogenic Ras. Cuervo described how CMA is consistently elevated in tumor cells, and how its inactivation leads to metabolic impairment via p53-mediated downregulation of glycolytic enzymes.

Oncogene-specific changes to metabolism

Lewis Cantley (Harvard Medical School, USA) described a metabolic role for oncogenic Kras in the rewiring of glucose metabolism in pancreatic cancer. Specifically, Myc-mediated transcription (downstream of MEK-ERK signaling) both enhances glucose uptake and diverts glucose carbon into the nonoxidative pentose phosphate pathway to facilitate nucleotide biosynthesis. Alejandro Sweet-Cordero (Stanford University, USA) described how oncogenic Kras increases glycolysis and represses mitochondrial respiration (via decreased pyruvate dehydrogenase phosphatase 1 (PDP1) expression) in colon cancer. While these studies indicate that hyperstimulation of the Erk pathway suppresses PDH flux through suppression of PDP1, Joan Brugge (Harvard Medical School, USA) described studies showing that reduction of Erk signaling in normal epithelial cells also causes suppression of PDH flux, in this case through loss of repression of PDK4. The seemingly contradictory nature of these results highlighted an important theme emphasized throughout the week-long conference—that cellular context has an important role in shaping how oncogenic mutations or pathway activation rewires metabolism.

Targeting cancer metabolism

There was extensive discussion around targeting metabolism for cancer therapy. Metformin and phenformin, which act in part by mitochondrial complex I inhibition, can activate AMPK and influence cancer cell metabolism. Kevin Struhl (Harvard Medical School, USA) described how metformin can selectively target cancer stem cells, whereas Jessica Howell (Harvard Medical School, USA) described how the therapeutic activity of metformin relies on both AMPK and mTOR signaling to mediate its effect. Similarly, David Shackelford (University of California, Los Angeles, USA) demonstrated efficacy for phenformin in LKB1-deficient mouse models.

Several presentations, including those by Taru Muranen (Harvard Medical School, USA), Karen Vousden and Eyal Gottlieb (both from the Beatson Institute for Cancer Research, UK), provided insight into genetic control mechanisms that cancer cells use to promote survival under conditions of increased biosynthesis. As an example, Vousden illustrated how p53 loss can make cancer cells more dependent on exogenous serine. Several additional presentations, including those by Gottlieb, Richard Possemato (Whitehead Institute/MIT, USA), Michael Pollak (McGill University, USA) and Kevin Marks (Agios Pharmaceuticals, USA), also included data highlighting the important role of serine biosynthesis and metabolism in cancer growth. Collectively, these data highlight a metabolic addiction that may be therapeutically exploitable. Similarly, Cristina Muñoz-Pinedo (Institut d’Investigació Biomèdica, Spain) described how mimicking glucose deprivation with 2-deoxyglucose can cause programmed cell death and may be an effective cancer treatment.

Regulation of hypoxic responses

Peter Carmeliet (University of Leuven, Belgium) highlighted the mechanisms of resistance against VEGF-targeted therapies. Roland Wenger (University of Zurich, Switzerland) discussed the oxygen-responsive transcriptional networks and, in particular, the difference between the transcription factors HIF-1α and HIF-2α. Importantly, he demonstrated a rapid role for HIF-1α, and a later and more persistent response for HIF-2α. These results were central to a recurrent theme calling for the distinction of HIF-1α and HIF-2α target genes and how these responses mediate divergent hypoxic adaptations.

Advances in hypoxic signaling

Brooke Emerling (Harvard Medical School, USA) introduced CUB domain-containing protein 1 (CDCP1) and showed persuasive data on CDCP1 being a HIF-2α target gene involved in cell migration and metastasis, and suggested CDCP1 regulation as an attractive therapeutic target. Johannes Schodel (University of Oxford, UK) described an elegant HIF-ChIP-Seq methodology to define direct transcriptional targets of HIF in renal cancer.

Randall Johnson (University of Cambridge, UK) emphasized that loss of HIF-1α results in decreased lung metastasis. Lorenz Poellinger (Karolinska Institutet, Sweden) focused on how hypoxia can alter the epigenetic landscape of cells, and furthermore, how the disruption of the histone demethylase JMJD1A and/or the H3K9 methyltransferase G9a has opposing effects on tumor growth and HIF target gene expression.

Paul Schumacker (Northwestern University, USA) further emphasized the importance of mitochondrial ROS signaling under hypoxic conditions showing that ROS could be detected in the inter-membrane space of the mitochondria before activating signaling cascades in the cytosol. He also presented evidence for mitochondria as a site of oxygen sensing in diverse cell types. Similarly, Margaret Ashcroft (University College London, UK) argued for a critical role of mitochondria in hypoxic signaling. She presented on a family of mitochondrial proteins (CHCHD4) that influence hypoxic signaling and tumorigenesis and suggested that CHCHD4 is important for HIF and tumor progression.

2.1.1.3  Glutaminolysis: supplying carbon or nitrogen or both for cancer cells?

Dang CV
Cell Cycle. 2010 Oct 1; 9(19):3884-6

A cancer cell comprising largely of carbon, hydrogen, oxygen, phosphorus, nitrogen and sulfur requires not only glucose, which is avidly transported and converted to lactate by aerobic glycolysis or the Warburg effect, but also glutamine as a major substrate. Glutamine and essential amino acids, such as methionine, provide energy through the TCA cycle as well as nitrogen, sulfur and carbon skeletons for growing and proliferating cancer cells. The interplay between utilization of glutamine and glucose is likely to depend on the genetic make-up of a cancer cell. While the MYC oncogene induces both aerobic glycolysis and glutaminolysis, activated β-catenin induces glutamine synthesis in hepatocellular carcinoma. Cancer cells that have elevated glutamine synthetase can use glutamate and ammonia to synthesize glutamine and are hence not addicted to glutamine. As such, cancer cells have many degrees of freedom for re-programming cell metabolism, which with better understanding will result in novel therapeutic approaches.

Figure 1. Glutamine, glucose and glutamate are imported into the cytoplasm of a cell. Glucose is depicted to be converted primarily (large powder blue arrow) to lactate via aerobic glycolysis or the Warburg effect or channeled into the mitochondrion as pyruvate and converted to acetyl-CoA for oxidation. Glutamine is shown imported and used for different processes including glutaminolysis, which involves the conversion of glutamine to glutamate and ammonia by glutaminase (GLS). Glutamate is further oxidized via the TCA cycle to produce ATP and contribute anabolic carbon skeletons. Some cells can import glutamate and use ammonia to generate glutamine through glutamine synthetase (GLUL); glutamine could then be used for different purposes including glutathione synthesis (not shown).

The liver is organized into lobules, which have zones of cells around the perivenous region enriched with glutamine synthetase, which detoxifies ammonia by converting it to glutamine through the amination of glutamate (Fig. 1). As such, liver cancers vary in the degree of glutamine synthetase expression depending on the extent of anaplasia or de-differentiation. Highly undifferentiated liver cancers tend to be more glycolytic than those that retain some of the differentiated characteristics of liver cells. Furthermore, glutamine synthetase (considered as a direct target of activated β-catenin, which also induces ornithine aminotransferase and glutamate transporters) expression in liver cancers has been directly linked to β-catenin activation or mutations.  Hence, the work by Meng et al. illustrates, first and foremost, the metabolic heterogeneity amongst cancer cell lines, such that the ability to utilize ammonia instead of glutamine by Hep3B cells depends on the expression of glutamine synthetase. The Hep3B cells are capable of producing glutamine from glutamate and ammonia, as suggested by the observation that a glutamine-independent derivative of Hep3B has high expression of glutamine synthetase. In this regard, Hep3B could utilize glutamate directly for the production of α-ketoglutarate or to generate glutamine for protein synthesis or other metabolic processes, such as to import essential amino acids.  In contrast to Hep3B, other cell lines in the Meng et al. study were not demonstrated to be glutamine independent and thus become ammonia auxotrophs. Hence, the mode of glutamine or glucose utilization is dependent on the metabolic profile of cancer cells.
The roles of glutamine in different cancer cell lines are likely to be different depending on their genetic and epigenetic composition. In fact, well-documented isotopic labeling studies have demonstrated a role for glutamine to provide anapleurotic carbons in certain cancer and mammalian cell types. But these roles of glutaminolysis, whether providing nitrogen or anabolic carbons, should not be generalized as mutually exclusive features of all cancer cells. From these considerations, it is surmised that the expression of glutamine synthetase in different cancers will determine the extent by which these cancers are addicted to exogenous glutamine.

2.1.1.4  The Warburg effect and mitochondrial stability in cancer cells

Gogvadze V, Zhivotovsky B, Orrenius S.
Mol Aspects Med. 2010 Feb; 31(1):60-74
http://dx.doi.org:/10.1016/j.mam.2009.12.004

The last decade has witnessed a renaissance of Otto Warburg’s fundamental hypothesis, which he put forward more than 80 years ago, that mitochondrial malfunction and subsequent stimulation of cellular glucose utilization lead to the development of cancer. Since most tumor cells demonstrate a remarkable resistance to drugs that kill non-malignant cells, the question has arisen whether such resistance might be a consequence of the abnormalities in tumor mitochondria predicted by Warburg. The present review discusses potential mechanisms underlying the upregulation of glycolysis and silencing of mitochondrial activity in cancer cells, and how pharmaceutical intervention in cellular energy metabolism might make tumor cells more susceptible to anti-cancer treatment.

mitochondrial stabilization gr1

mitochondrial stabilization gr1

http://ars.els-cdn.com/content/image/1-s2.0-S0098299709000934-gr1.sml

Fig. 1. (1) Oligomerization of Bax is mediated by the truncated form of the BH3-only, pro-apoptotic protein Bid (tBid); (2) Bcl-2, Bcl-XL, Mcl-1, and Bcl-w, interact with the pro-apoptotic proteins, Bax and Bak, to prevent their oligomerization; (3) The anti-apoptotic protein Bcl-XL prevents tBid-induced closure of VDAC and apoptosis by maintaining VDAC in open configuration allowing ADT/ATP exchange and normal mitochondrial functioning; (4) MPT pore is a multimeric complex, composed of VDAC located in the OMM, ANT, an integral protein of the IMM, and a matrix protein, CyPD; (5) Interaction with VDAC allows hexokinase to use exclusively intramitochondrial ATP to phosphorylate glucose, thereby maintaining high rate of glycolysis.

mitochodrial stabilization gr2

mitochodrial stabilization gr2

http://ars.els-cdn.com/content/image/1-s2.0-S0098299709000934-gr2.sml

Fig. 2. Different sites of therapeutic intervention in cancer cell metabolism. (1) The non-metabolizable analog of glucose, 2-deoxyglucose, decreases ATP level in the cell; (2) 3-bromopyruvate suppresses the activity of hexokinase, and respiration in isolated mitochondria; (3) Phloretin a glucose transporter inhibitor, decreases ATP level in the cell and markedly enhances the anti-cancer effect of daunorubicin; (4) Dichloroacetate (DCA) shifts metabolism from glycolysistoglucoseoxidation;(5)Apoptolidin,aninhibitorofmitochondrialATPsynthase,inducescelldeathindifferentmalignantcelllineswhenapplied together with the LDH inhibitor oxamate (6).

Warburg Symposium

https://youtu.be/LpE6w6J3jU0

2.1.1.5 Oxidative phosphorylation in cancer cells

Giancarlo Solaini Gianluca SgarbiAlessandra Baracca

BB Acta – Bioenergetics 2011 Jun; 1807(6): 534–542
http://dx.doi.org/10.1016/j.bbabio.2010.09.003

Research Highlights

►Mitochondrial hallmarks of tumor cells.►Complex I of the respiratory chain is reduced in many cancer cells.►Oligomers of F1F0ATPase are reduced in cancer cells.►Mitochondrial membranes are critical to the life or death of cancer cells.

Evidence suggests that mitochondrial metabolism may play a key role in controlling cancer cells life and proliferation. Recent evidence also indicates how the altered contribution of these organelles to metabolism and the resistance of cancer mitochondria against apoptosis-associated permeabilization are closely related. The hallmarks of cancer growth, increased glycolysis and lactate production in tumours, have raised attention due to recent observations suggesting a wide spectrum of oxidative phosphorylation deficit and decreased availability of ATP associated with malignancies and tumour cell expansion. More specifically, alteration in signal transduction pathways directly affects mitochondrial proteins playing critical roles in controlling the membrane potential as UCP2 and components of both MPTP and oxphos complexes, or in controlling cells life and death as the Bcl-2 proteins family. Moreover, since mitochondrial bioenergetics and dynamics, are also involved in processes of cells life and death, proper regulation of these mitochondrial functions is crucial for tumours to grow. Therefore a better understanding of the key pathophysiological differences between mitochondria in cancer cells and in their non-cancer surrounding tissue is crucial to the finding of tools interfering with these peculiar tumour mitochondrial functions and will disclose novel approaches for the prevention and treatment of malignant diseases. Here, we review the peculiarity of tumour mitochondrial bioenergetics and the mode it is linked to the cell metabolism, providing a short overview of the evidence accumulated so far, but highlighting the more recent advances. This article is part of a Special Issue entitled: Bioenergetics of Cancer.

Mitochondria are essential organelles and key integrators of metabolism, but they also play vital roles in cell death and cell signaling pathways critically influencing cell fate decisions [1][2] and [3]. Mammalian mitochondria contain their own DNA (mtDNA), which encodes 13 polypeptides of oxidative phosphorylation complexes, 12S and 16S rRNAs, and 22 tRNAs required for mitochondrial function [4]. In order to synthesize ATP through oxidative phosphorylation (oxphos), mitochondria consume most of the cellular oxygen and produce the majority of reactive oxygen species (ROS) as by-products [5]. ROS have been implicated in the etiology of carcinogenesis via oxidative damage to cell macromolecules and through modulation of mitogenic signaling pathways [6][7] and [8]. In addition, a number of mitochondrial dysfunctions of genetic origin are implicated in a range of age-related diseases, including tumours [9]. How mitochondrial functions are associated with cancer is a crucial and complex issue in biomedicine that is still unravelled [10] and [11], but it warrants an extraordinary importance since mitochondria play a major role not only as energy suppliers and ROS “regulators”, but also because of their control on cellular life and death. This is of particular relevance since tumour cells can acquire resistance to apoptosis by a number of mechanisms, including mitochondrial dysfunction, the expression of anti-apoptotic proteins or by the down-regulation or mutation of pro-apoptotic proteins [12].

Cancer cells must adapt their metabolism to produce all molecules and energy required to promote tumor growth and to possibly modify their environment to survive. These metabolic peculiarities of cancer cells are recognized to be the outcome of mutations in oncogenes and tumor suppressor genes which regulate cellular metabolism. Mutations in genes including P53, RAS, c-MYC, phosphoinosine 3-phosphate kinase (PI3K), and mTOR can directly or through signaling pathways affect metabolic pathways in cancer cells as discussed in several recent reviews [13][14][15][16] and [17]. Cancer cells harboring the genetic mutations are also able to thrive in adverse environments such as hypoxia inducing adaptive metabolic alterations which include glycolysis up-regulation and angiogenesis factor release [18] and [19]. In response to hypoxia, hypoxia-induced factor 1 (HIF-1) [20], a transcription factor, is up-regulated, which enhances expression of glycolytic enzymes and concurrently it down regulates mitochondrial respiration through up-regulation of pyruvate dehydrogenase kinase 1 (PDK1) (see recent reviews [21] and [22]). However, several tumours have been reported to display high HIF-1 activity even in normoxic condition, now referred to as pseudohypoxia [23][24] and [25]. In addition, not only solid tumours present a changed metabolism with respect to matched normal tissues, hematological cell malignancies also are characterized by peculiar metabolisms, in which changes of mitochondrial functions are significant [26],[27] and [28], therefore indicating a pivotal role of mitochondria in tumours independently from oxygen availability.

Collectively, actual data show a great heterogeneity of metabolism changes in cancer cells, therefore comprehensive cellular and molecular basis for the association of mitochondrial bioenergetics with tumours is still undefined, despite the numerous studies carried out. This review briefly revisits the data which are accumulating to account for this association and highlights the more recent advances, particularly focusing on the metabolic and structural changes of mitochondria.

Mitochondria-related metabolic changes of cancer cells

Accumulating evidence indicate that many cancer cells have an higher glucose consumption under normoxic conditions with respect to normal differentiated cells, the so-called “aerobic glycolysis” (Warburg effect), a phenomenon that is currently exploited to detect and diagnose staging of solid and even hematological malignancies [27]. Since the initial publication by Otto Warburg over half a century ago [29], an enormous amount of studies on many different tumours have been carried out to explain the molecular basis of the Warburg effect. Although the regulatory mechanisms underlying aerobic and glycolytic pathways of energy production are complex, making the prediction of specific cellular responses rather difficult, the actual data seem to support the view that in order to favour the production of biomass, proliferating cells are commonly prone to satisfy the energy requirement utilizing substrates other than the complete oxidation of glucose (to CO2 and H2O). More precisely, only part (40 to 75%, according to [30]) of the cells need of ATP is obtained through the scarcely efficient catabolism of glucose to pyruvate/lactate in the cytoplasm and the rest of the ATP need is synthesized in the mitochondria through both the tricarboxylic acid (TCA) cycle (one ATP produced each acetyl moiety oxidized) and the associated oxidative phosphorylation that regenerates nicotinamide- and flavin-dinucleotides in their oxidized state(NAD+ and FAD). This might be due to the substrate availability as it was shown in HeLa cells, where replacing glucose with galactose/glutamine in the culture medium induced increased expression of oxphos proteins, suggesting an enhanced energy production from glutamine [31]. As a conclusion the authors proposed that energy substrate can modulate mitochondrial oxidative capacity in cancer cells. A direct evidence of this phenomenon was provided a few years later in glioblastoma cells, in which it was demonstrated that the TCA cycle flux is significantly sustained by anaplerotic alfa-ketoglutarate produced from glutamine and by acetyl moieties derived from the pyruvate dehydrogenase reaction where pyruvate may have an origin other than glucose [32]. The above changes are the result of genetic alteration and environmental conditions that induce many cancer cells to change their metabolism in order to synthesize molecules necessary to survive, grow and proliferate, including ribose and NADPH to synthesize nucleotides, and glycerol-3 phosphate to produce phospholipids. The synthesis of the latter molecules requires major amount of acetyl moieties that are derived from beta-oxidation of fatty acids and/or from cytosolic citrate (citrate lyase reaction) and/or from the pyruvate dehydrogenase reaction. Given the important requirement for NADPH in macromolecular synthesis and redox control, NADPH production in cancer cells besides being produced through the phosphate pentose shunt, may be significantly sustained by cytosolic isocitrate dehydrogenases and by the malic enzyme (see Ref. [33] for a recent review). Therefore, many cancer cells tend to have reduced oxphos in the mitochondria due to either or both reduced flux within the tricarboxylic acid cycle and/or respiration (Fig. 1). The latter being also caused by reduced oxygen availability, a typical condition of solid tumors, that will be discussed below.

Schematic illustration of mitochondrial metabolism and metabolic reprogramming in tumours gr1

Schematic illustration of mitochondrial metabolism and metabolic reprogramming in tumours gr1

http://ars.els-cdn.com/content/image/1-s2.0-S0005272810007024-gr1.jpg

Fig. 1. Schematic illustration of mitochondrial metabolism and metabolic reprogramming in tumours. In normal cells (A), glucose is phosphorylated by HK-I, then the major part is degraded via glycolysis to pyruvate, which prevalently enters the mitochondria, it is decarboxylated and oxidized by PDH to acetyl-coenzyme A, which enters the TCA cycle where the two carbons are completely oxidized to CO2 whereas hydrogen atoms reduce NAD+ and FAD, which feed the respiratory chain (turquoise). Minor part of glycolytic G-6P is diverted to produce ribose 5-phosphate (R-5P) and NADPH, that will be used to synthesize nucleotides, whereas triose phosphates in minimal part will be used to synthesize lipids and phospholipids with the contribution of NADPH and acetyl-coenzyme A. Amino acids, including glutamine (Gln) will follow the physiological turnover of the proteins, in minimal part will be used to synthesize the nucleotides bases, and the excess after deamination will be used to produce energy. In the mitochondria inner membranes are located the respiratory chain complexes and the ATP synthase (turquoise), which phosphorylates ADP releasing ATP, that in turn is carried to the cytosol by ANT (green) in exchange for ADP. About 1–2% O2 uptaken by the mitochondria is reduced to superoxide anion radical and ROS. In cancer cells (B), where anabolism is enhanced, glucose is mostly phosphorylated by HK-II (red), which is up-regulated and has an easy access to ATP being more strictly bound to the mitochondria. Its product, G-6P, is only in part oxidized to pyruvate. This, in turn, is mostly reduced to lactate being both LDH and PDH kinase up-regulated. A significant part of G-6P is used to synthesize nucleotides that also require amino acids and glutamine. Citrate in part is diverted from the TCA cycle to the cytosol, where it is a substrate of citrate lyase, which supplies acetyl-coenzyme A for lipid and phospholipid synthesis that also requires NADPH. As indicated, ROS levels in many cancer cells increase.

Of particular relevance in the study of the metabolic changes occurring in cancer cells, is the role of hexokinase II. This enzyme is greatly up-regulated in many tumours being its gene promoter sensitive to typical tumour markers such as HIF-1 and P53 [30]. It plays a pivotal role in both the bioenergetic metabolism and the biosynthesis of required molecules for cancer cells proliferation. Hexokinase II phosphorylates glucose using ATP synthesized by the mitochondrial oxphos and it releases the product ADP in close proximity of the adenine nucleotide translocator (ANT) to favour ATP re-synthesis within the matrix (Fig. 1). Obviously, the expression level, the location, the substrate affinity, and the kinetics of the enzyme are crucial to the balancing of the glucose fate, to either allowing intermediates of the glucose oxidation pathway towards required metabolites for tumour growth or coupling cytoplasmic glycolysis with further oxidation of pyruvate through the TCA cycle, that is strictly linked to oxphos. This might be possible if the mitochondrial-bound hexokinase activity is reduced and/or if it limits ADP availability to the mitochondrial matrix, to inhibit the TCA cycle and oxphos. However, the mechanism is still elusive, although it has been shown that elevated oncogene kinase signaling favours the binding of the enzyme to the voltage-dependent anion channel (VDAC) by AKT-dependent phosphorylation [34] (Fig. 2). VDAC is a protein complex of the outer mitochondrial membrane which is in close proximity of ANT that exchanges ADP for ATP through the inner mitochondrial membrane [35]. However, the enzyme may also be detached from the mitochondrial membrane, to be redistributed to the cytosol, through the catalytic action of sirtuin-3 that deacylates cyclophilin D, a protein of the inner mitochondrial membrane required for binding hexokinase II to VDAC (Fig. 2[36]. Removing hexokinase from the mitochondrial membrane has also another important consequence in cancer cells: whatever mechanism its removal activates, apoptosis is induced [37] and [38]. These observations indicate hexokinase II as an important tool used by cancer cells to survive and proliferate under even adverse conditions, including hypoxia, but it may result an interesting target to hit in order to induce cells cytotoxicity. Indeed, a stable RNA interference of hexokinase II gene showed enhanced apoptosis indices and inhibited growth of human colon cancer cells; in accordance in vivo experiments indicated a decreased tumour growth [39].

Schematic illustration of the main mitochondrial changes frequently occurring in cancer cells gr2

Schematic illustration of the main mitochondrial changes frequently occurring in cancer cells gr2

http://ars.els-cdn.com/content/image/1-s2.0-S0005272810007024-gr2.jpg

Fig. 2. Schematic illustration of the main mitochondrial changes frequently occurring in cancer cells. The reprogramming of mitochondrial metabolism in many cancer cells comprises reduced pyruvate oxidation by PDH followed by the TCA cycle, increased anaplerotic feeding of the same cycle, mostly from Gln, whose entry in the mitochondrial matrix is facilitated by UCP2 up-regulation. This increases also the free fatty acids uptake by mitochondria, therefore β-oxidation is pushed to produce acetyl-coenzyme A, whose oxidation contributes to ATP production. In cancer cells many signals can converge on the mitochondrion to regulate the mitochondrial membrane permeability, which may respond by elevating the MPTP (PTP) threshold, with consequent enhancement of apoptosis resistance. ROS belong to this class of molecules since it can enhance Bcl2 and may induce DNA mutations. Dotted lines indicate regulation; solid lines indicate reaction(s).

Respiratory chain complexes and ATP synthase

Beyond transcriptional control of metabolic enzyme expression by oncogenes and tumour suppressors, it is becoming evident that environmental conditions affect the mitochondrial energy metabolism, and many studies in the last decade indicate that mitochondrial dysfunction is one of the more recurrent features of cancer cells, as reported at microscopic, molecular, biochemical, and genetic level [7], [40] and [41]. Although cancer cells under several conditions, including hypoxia, oncogene activation, and mDNA mutation, may substantially differ in their ability to use oxygen, only few reports have been able to identify a strict association between metabolic changes and mitochondrial complexes composition and activity. In renal oncocytomas [42] and in lung epidermoid carcinoma [43], the NADH dehydrogenase activity and protein content of Complex I were found to be strongly depressed; subsequently, in a thyroid oncocytoma cell line [44] a similar decrease of Complex I activity was ascribed to a specific mutation in the ND1 gene of mitochondrial DNA. However, among the respiratory chain complexes, significant decrease of the only Complex I content and activity was found in K-ras transformed cells in our laboratory [45], and could not be ascribed to mtDNA mutations, but rather, based on microarray analysis of oxphos genes, we proposed that a combination of genetic (low transcription of some genes) and biochemical events (assembly factors deficiency, disorganization of structured supercomplexes, and ROS-induced structural damage) might cause the Complex I defects.

In some hereditary tumours (renal cell carcinomas) a correlation has been identified between mitochondrial dysfunctions and content of oxphos complexes [46]. For instance, the low content of ATP synthase, often observed in clear cell type renal cell carcinomas and in chromophilic tumours, seems to indicate that the mitochondria are in an inefficient structural and functional state [46]. However, it cannot be excluded that, in some cases, the structural alteration of ATP synthase may offer a functional advantage to cells exhibiting a deficient respiratory chain for instance to preserve the transmembrane electrical potential (Δψm) [47]. It is likely that low levels of ATP synthases may play a significant role in cancer cell metabolism since it has been reported that in tumours from many different tissues, carcinogenesis specifically affects the expression of F1-ATPase β subunit, suggesting alterations in the mechanisms that control mitochondrial differentiation (see for a detailed review [48]). What it seems intriguing is the overexpression of the inhibitor protein, IF1, reported in hepatocellular carcinomas [49] and [50] and in Yoshida sarcoma [51]. Normally, this protein binds to the F1 domain of the ATP synthase inhibiting its activity [52], and it is believed to limit the ATP hydrolysis occurring in the mitochondria of hypoxic cells, avoiding ATP depletion and maintaining Δψm to a level capable to avoid the induction of cell death [5]. But why is its expression in cancer cells enhanced in front of a reduced F1-ATPase β subunit?

The first possibility is that IF1 has a function similar to that in normal cells, simply avoiding excessive ATP hydrolysis therefore limiting Δψm enhancement, but in cancer cells this is unlikely due to both the reduced level of ATP synthase [46] and the high affinity of IF1 for the enzyme. A second possibility might be that cancer cells need strongly reduced oxphos to adapt their metabolism and acquire a selective growth advantage under adverse environmental conditions such as hypoxia, as it has been experimentally shown [53]. Finally, IF1 might contribute to the saving of the inner mitochondrial membrane structure since it has been reported its capability to stabilize oligomers of ATP synthase, which in turn can determine cristae shapes [54]. In this regard, recent experimental evidence has shed some light on a critical role of mitochondrial morphology in the control of important mitochondrial functions including apoptosis [55] and oxidative phosphorylation [56]. In particular, dysregulated mitochondrial fusion and fission events can now be regarded as playing a role in cancer onset and progression [57]. Accordingly, mitochondria-shaping proteins seem to be an appealing target to modulate the mitochondrial phase of apoptosis in cancer cells. In fact, several cancer tissues: breast, head-and-neck, liver, ovarian, pancreatic, prostate, renal, skin, and testis, showed a pattern suggestive of enlarged mitochondria resulting from atypical fusion [58].

Mitochondrial membrane potential in cancer cells

Critical mitochondrial functions, including ATP synthesis, ion homeostasis, metabolites transport, ROS production, and cell death are highly dependent on the electrochemical transmembrane potential, a physico-chemical parameter consisting of two components, the major of which being the transmembrane electrical potential (Δψm) (see for a recent review [59]). In normal cells, under normoxic conditions, Δψm is build up by the respiratory chain and is mainly used to drive ATP synthesis, whereas in anoxia or severe hypoxia it is generated by the hydrolytic activity of the ATP synthase complex and by the electrogenic transport of ATP in exchange for ADP from the cytosol to the matrix, operated by the adenine nucleotide translocator [17]. Dissipation of the mitochondrial membrane potential (proton leak) causes uncoupling of the respiratory chain electron transport from ADP phosphorylation by the ATP synthase complex. Proton leak functions as a regulator of mitochondrial ROS production and its modulation by uncoupling proteins may be involved in pathophysiology, including tumours. In addition, Δψm plays a role in the control of the mitochondrial permeability transition pore (MPTP), that might be critical in determining reduced sensitivity to stress stimuli that were described in neoplastic transformation [60], implying that dysregulation of pore opening might be a strategy used by tumour cells to escape death. Indeed, it has recently been reported that ERK is constitutively activated in the mitochondria of several cancer cell types, where it inhibits glycogen synthase kinase-3-dependent phosphorylation of CyP-D and renders these cells more refractory to pore opening and to the ensuing cell death [61].

It is worth mentioning a second protein of the inner mitochondrial membrane, the uncoupling protein, UCP2 (Fig. 2), which contributes to regulate Δψm. Indeed, recent observations evidenced its overexpression in various chemoresistent cancer cell lines and in primary human colon cancer. This overexpression was associated with an increased apoptotic threshold [62]. Moreover, UCP2 has been reported to be involved in metabolic reprogramming of cells, and appeared necessary for efficient oxidation of glutamine [63]. On the whole, these results led to hypothesize an important role of the uncoupling protein in the molecular mechanism at the basis of the Warburg effect, that suppose a reduced Δψm-dependent entry of pyruvate into the mitochondria accompanied by enhanced fatty acid oxidation and high oxygen consumption (see for a review [64]). However, in breast cancer Sastre-Serra et al. [65] suggested that estrogens by down-regulating UCPs, increase mitochondrial Δψm, that in turn enhances ROS production, therefore increasing tumorigenicity. While the two above points of view concur to support increased tumorigenicity, the mechanisms at the basis of the phenomenon appear on the opposite of the other. Therefore, although promising for the multiplicity of metabolic effects in which UCPs play a role (see for a recent review [66]), at present it seems that much more work is needed to clarify how UCPs are related to cancer.

A novel intriguing hypothesis has recently been put forward regarding effectors of mitochondrial function in tumours. Wegrzyn J et al. [67] demonstrated the location of the transcription factor STAT3 within the mitochondria and its capability to modulate respiration by regulating the activity of Complexes I and II, and Gough et al. [68] reported that human ras oncoproteins depend on mitochondrial STAT3 for full transforming potential, and that cancer cells expressing STAT3 have increased both Δψm and lactate dehydrogenase level, typical hallmarks of malignant transformation (Fig. 2). A similar increase of Δψm was recently demonstrated in K-ras transformed fibroblasts [45]. In this study, the increased Δψm was somehow unexpected since the cells had shown a substantial decrease of NADH-linked substrate respiration rate due to a compatible reduced Complex I activity with respect to normal fibroblasts. The authors associated the reduced activity of the enzyme to its peculiar low level in the extract of the cells that was confirmed by oxphos nuclear gene expression analysis. This significant and peculiar reduction of Complex I activity relative to other respiratory chain complexes, is recurrent in a number of cancer cells of different origin [42][44][45] and [69]. Significantly, all those studies evidenced an overproduction of ROS in cancer cells, which was consistent with the mechanisms proposed by Lenaz et al. [70] who suggested that whatever factor (i.e. genetic or environmental) initiate the pathway, if Complex I is altered, it does not associate with Complex III in supercomplexes, consequently it does not channel correctly electrons from NADH through coenzyme Q to Complex III redox centres, determining ROS overproduction. This, in turn, enhances respiratory chain complexes alteration resulting in further ROS production, thus establishing a vicious cycle of oxidative stress and energy depletion, which can contribute to further damaging cells pathways and structures with consequent tumour progression and metastasis [69].

Hypoxia and oxidative phosphorylation in cancer cells

Tumour cells experience an extensive heterogeneity of oxygen levels, from normoxia (around 2–4% oxygen tension), through hypoxia, to anoxia (< 0.1% oxygen tension). The growth of tumours beyond a critical mass > 1–2 mm3 is dependent on adequate blood supply to receive nutrients and oxygen by diffusion [88]. Cells adjacent to capillaries were found to exhibit a mean oxygen concentration of 2%, therefore, beyond this distance, hypoxia occurs: indeed, cells located at 200 μm displayed a mean oxygen concentration of 0.2%, which is a condition of severe hypoxia [89]. Oxygen shortage results in hypoxia-dependent inhibition of mitochondrial activity, mostly mediated by the hypoxia-inducible factor 1 (HIF-1)[90] and [91]. More precisely, hypoxia affects structure, dynamics, and function of the mitochondria, and in particular it has a significant inhibitory effect on the oxidative phosphorylation machinery, which is the main energy supplier of cells (see Ref. [22] for a recent review). The activation of HIF-1 occurs in the cytoplasmic region of the cell, but the contribution of mitochondria is critical being both cells oxygen sensors and suppliers of effectors of HIF-1α prolyl hydroxylase like α-ketoglutarate and probably ROS, that inhibit HIF-1α removal [92]. As reported above, mitochondria can also promote HIF-1α stabilization if the TCA flux is severely inhibited with release of intermediate molecules like succinate and fumarate into the cytosol. On the other hand, HIF-1 can modulate mitochondrial functions through different mechanisms, that besides metabolic reprogramming [7][22][93] and [94], include alteration of mitochondrial structure and dynamics[58], induction of microRNA-210 that decreases the cytochrome c oxidase (COX) activity by inhibiting the gene expression of the assembly protein COX10 [95], that also increases ROS generation. Moreover, these stress conditions could induce the anti-apoptotic protein Bcl-2, which has also been reported to regulate COX activity and mitochondrial respiration [96] conferring resistance to cells death in tumours (Fig. 2). This effect might be further enhanced upon severe hypoxia conditions, since COX is also inhibited by NO, the product of activated nitric oxide synthases [97].

The reduced respiration rate occurring in hypoxia favours the release of ROS also by Complex III, which contribute to HIF stabilization and induction of Bcl-2 [98]. In addition, hypoxia reduces oxphos by inhibiting the ATP synthase complex through its natural protein inhibitor IF1 (discussed in a previous section), which contributes to the enhancement of the “aerobic glycolysis”, all signatures of cancer transformation.

The observations reported to date indicate that cancer cells exhibit large varieties of metabolic changes which are associated with alterations in the mitochondrial structure, dynamics and function, and with tumour growth and survival. On one hand, mitochondria can regulate tumour growth through modulation of the TCA cycle and oxidative phosphorylation. The altered TCA cycle provides intermediates for both macromolecular biosynthesis and regulation of transcription factors such as HIF, and it allows cytosolic reductive power enhancement. Oxphos provides significant amounts of ATP which varies among tumour types. On the other hand, mitochondria are crucial in controlling redox homeostasis in the cell, inducing them to be either resistant or sensitive to apoptosis. All these reasons locate mitochondria at central stage to understanding the molecular basis of tumour growth and to seeking for novel therapeutical approaches.

Due to the complexity and variability of mitochondrial roles in cancer, careful evaluation of mitochondrial function in each cancer type is crucial. Deeper and more integrated knowledge of mitochondrial mechanisms and cancer-specific mitochondrial modulating means are expected for reducing tumorigenicity and/or improving anticancer drugs efficacy at the mitochondrial level. Although the great variability of biochemical changes found in tumour mitochondria, some highlighted peculiarities such as reduced TCA cycle flux, reduced oxphos rate, and reduced Complex I activity with respect to tissue specific normal counterparts are more frequent. In addition, deeper examination of supramolecular organization of the complexes in the inner mitochondrial membrane has to be considered in relation to oxphos dysfunction.

2.1.1.6  Oxidation–reduction states of NADH in vivo: From animals to clinical use

Mayevsky A, Chance B.
Mitochondrion. 2007 Sep; 7(5):330-9
http://dx.doi.org:/10.1016/j.mito.2007.05.001

Mitochondrial dysfunction is part of many pathological states in patients, such as sepsis or stroke. Presently, the monitoring of mitochondrial function in patients is extremely rare, even though NADH redox state is routinely measured in experimental animals. In this article, we describe the scientific backgrounds and practical use of mitochondrial NADH fluorescence measurement that was applied to patients in the past few years. In addition to NADH, we optically measured the microcirculatory blood flow and volume, as well as HbO(2) oxygenation, from the same tissue area. The four detected parameters provide real time data on tissue viability, which is critical for patients monitoring.

(very important article)

2.1.1.7  Mitochondria in cancer. Not just innocent bystanders

Frezza C, and Gottlieb E
Sem Cancer Biol 2009; 19: 4-11
http://dx.doi.org:/10.1016/j.semcancer.2008.11.008

The first half of the 20th century produced substantial breakthroughs in bioenergetics and mitochondria research. During that time, Otto Warburg observed abnormally high glycolysis and lactate production in oxygenated cancer cells, leading him to suggest that defects in mitochondrial functions are at the heart of malignant cell transformation. Warburg’s hypothesis profoundly influenced the present perception of cancer metabolism, positioning what is termed aerobic glycolysis in the mainstream of clinical oncology. While some of his ideas stood the test of time, they also frequently generated misconceptions regarding the biochemical mechanisms of cell transformation. This review examines experimental evidence which supports or refutes the Warburg effect and discusses the possible advantages conferred on cancer cells by ‘metabolic transformation’.

Fig.1. Mitochondria as a crossroad for catabolic and anabolic pathways in normal and cancer cells. Glucose and glutamine are important carbon sources which are metabolized in cells for the generation of energy and anabolic precursors. The pathways discussed in the text are illustrated and colour coded: red, glycolysis; white, TCA cycle; pink, non-essential amino acids synthesis; orange, pentose phosphate pathway and nucleotide synthesis; green, fatty acid and lipid synthesis; blue, pyruvate oxidation in the mitochondria; brown, glutaminolysis; black, malic enzyme reaction. Solid arrows indicate a single step reaction;dashed-dotted arrows indicate transport across membranes and dotted arrows indicate multi-step reactions. Abbreviations: HK, hexokinase; AcCoA, acetyl co-enzyme A; OAA, oxaloacetate; αKG, α-ketoglutarate.

http://ars.els-cdn.com/content/image/1-s2.0-S1044579X08001041-gr1.sml

Fig. 2. Mitochondria as a target for multiple metabolic transformation events. Principal metabolic perturbations of cancer cells are induced by genetic reprogramming and environmental changes. The activation of Akt and MYC oncogenes and the loss of p53 tumor suppressor gene are among the most frequent events in cancer. Furthermore, all solid tumors are exposed to oxidative stress and hypoxia hence to HIF activation.These frequent changes in cancer cells trigger a dramatic metabolic shift from oxidative phosphorylation to glycolysis. In addition, direct genetic lesions of mtDNA or of nuclear encoded mitochondrial enzyme (SDH or FH) can directly abrogate oxidative phosphorylation in cancer. 3- D structures of the respiratory complexes in the scheme were retrieved from Protein DataBank (PDB:www.rcsb.org) except for complex I which was retrieved from [87]. PDB codes are as follow: SDH (II), 1 LOV; complex III (III), 1BGY; COX (IV), 1OCC; ATP synthase (V), 1QO1.

http://ars.els-cdn.com/content/image/1-s2.0-S1044579X08001041-gr2.sml

Fig. 3. The physiological roles of SDH in the TCA cycle and the ETC and its potential roles in cancer. (A) Ribbon diagram of SDH structure (PBD code: 1LOV). The catalytic subunits: the flavoprotein (SDHA) and the iron-sulphur protein (SDHB) are depicted in red and yellow, respectively, and the membrane anchors and ubiquinone binding proteins SDHC and SDHD are depicted in cyan and green, respectively. (B) Other than being a TCA enzyme, SDH is an additional entry point to the ETC (most electrons are donated from NADH to complex I—not shown in this diagram). The electron flow in and out of complex II and III is depicted by the yellow arrows. During succinate oxidation to fumarate by SDHA, a two-electron reduction of FAD to FADH2 occurs. Electrons are transferred through their on–Sulphur centres on SDHB to ubiquinone (Q) bound to SDHC and SDHD in the inner mitochondrial membrane (IMM), reducing it to ubiquinol (QH2). Ubiquinol transfers its electrons through complex III, in a mechanism named the Q cycle, to cytochrome c (PDB: 1CXA). Electrons then flow from cytochrome c to COX where the final four-electron reduction of molecular oxygen to water occurs (not shown in this diagram). Complex III is the best characterized site of ROS production in the ETC, where a single electron reduction of oxygen to superoxide can occur (red arrow). It was proposed that obstructing electron flow within complex II might support a single electron reduction of oxygen at the FAD site (red arrow). Superoxide is dismutated to hydrogen peroxide which can then leave the mitochondria and inhibit PHD in the cytosol, leading to HIF[1] stabilization. Succinate or fumarate, which accumulate in SDH- or FH-deficient tumors, can also leave the mitochondria and inhibit PHD activity in the cytosol. The red dotted line represents the outer mitochondrial membrane (OMM).

2.1.1.8  Mitochondria in cancer cells: what is so special about them?

Gogvadze V, Orrenius S, Zhivotovsky B.
Trends Cell Biol. 2008 Apr; 18(4):165-73
http://dx.doi.org:/10.1016/j.tcb.2008.01.006

The past decade has revealed a new role for the mitochondria in cell metabolism–regulation of cell death pathways. Considering that most tumor cells are resistant to apoptosis, one might question whether such resistance is related to the particular properties of mitochondria in cancer cells that are distinct from those of mitochondria in non-malignant cells. This scenario was originally suggested by Otto Warburg, who put forward the hypothesis that a decrease in mitochondrial energy metabolism might lead to development of cancer. This review is devoted to the analysis of mitochondrial function in cancer cells, including the mechanisms underlying the upregulation of glycolysis, and how intervention with cellular bioenergetic pathways might make tumor cells more susceptible to anticancer treatment and induction of apoptosis.

Glucose utilization pathway

Glucose utilization pathway

http://www.cell.com/cms/attachment/591821/4554537/gr1.sml

Figure 1. Glucose utilization pathway. When glucose enters the cell, it is phosphorylated by hexokinase to glucose-6-phosphate, which is further metabolized by glycolysis to pyruvate. Under aerobic conditions, most of the pyruvate in non-malignant cells enters the mitochondria, with only a small amount being metabolized to lactic acid. In mitochondria, pyruvate dehydrogenase (PDH) converts pyruvate into acetyl-CoA, which feeds into the Krebs cycle. Oxidation of Krebs cycle substrates by the mitochondrial respiratory chain builds up the mitochondrial membrane potential (Dc) – the driving force for ATP synthesis. By contrast, in tumor cells, the oxidative (mitochondrial) pathway of glucose utilization is suppressed, and most of the pyruvate is converted into lactate. Thus, the fate of pyruvate is determined by the relative activities of two key enzymes – lactate dehydrogenase and pyruvate dehydrogenase.

Mechanisms of mitochondrial silencing in tumors

Mechanisms of mitochondrial silencing in tumors

http://www.cell.com/cms/attachment/591821/4554539/gr2.sml

Figure 2. Mechanisms of mitochondrial silencing in tumors. The activity of PDH is regulated by pyruvate dehydrogenase kinase 1 (PDK1), the enzyme that phosphorylates and inactivates pyruvate dehydrogenase. HIF-1 inactivates PDH through PDK1 induction, resulting in suppression of the Krebs cycle and mitochondrial respiration. In addition, HIF-1 stimulates expression of the lactate dehydrogenase A gene, facilitating conversion of pyruvate into lactate by lactate dehydrogenase (LDH). Mutation of p53 can suppress the mitochondrial respiratory activity through downregulation of the Synthesis of Cytochrome c Oxidase 2 (SCO2) gene, the product of which is required for the assembly of cytochrome c oxidase (COX) of the mitochondrial respiratory chain. Thus, mutation of p53 can suppress mitochondrial respiration and shift cellular energy metabolism towards glycolysis.

Production of ROS by mitochondria

In any cell, the majority of ROS are by-products of mitochondrial respiration. Approximately 2% of the molecular oxygen consumed during respiration is converted into the superoxide anion radical, the precursor of most ROS. Normally, a four-electron reduction of O2, resulting in the production of two molecules of water, is catalyzed by complex IV (COX) of the mitochondrial respiratory chain. However, the electron transport chain contains several redox centers (e.g. in complex I and III) that can leak electrons to molecular oxygen, serving as the primary source of superoxide production in most tissues. The one-electron reduction of oxygen is thermodynamically favorable for most mitochondrial oxidoreductases. Superoxide-producing sites and enzymes were recently analyzed in detail in a comprehensive review [87]. ROS, if not detoxified, oxidize cellular proteins, lipids, and nucleic acids and, by doing so, cause cell dysfunction or death. A cascade of water and lipid soluble antioxidants and antioxidant enzymes suppresses the harmful ROS activity. An imbalance that favors the production of ROS over antioxidant defenses, defined as oxidative stress, is implicated in a wide variety of pathologies, including malignant diseases. It should be mentioned that mitochondria are not only a major source of ROS but also a sensitive target for the damaging effects of oxygen radicals. ROS produced by mitochondria can oxidize proteins and induce lipid peroxidation, compromising the barrier properties of biological membranes. One of the targets of ROS is mitochondrial DNA (mtDNA), which encodes several proteins essential for the function of the mitochondrial respiratory chain and, hence, for ATP synthesis by oxidative phosphorylation. mtDNA, therefore, represents a crucial cellular target for oxidative damage, which might lead to lethal cell injury through the loss of electron transport and ATP generation. mtDNA is especially susceptible to attack by ROS, owing to its close proximity to the electron transport chain, the major locus for free-radical production, and the lack of protective histones. For example, mitochondrially generated ROS can trigger the formation of 8-hydroxydeoxyguanosine as a result of oxidative DNA damage; the level of oxidatively modified bases in mtDNA is 10- to 20-fold higher than that in nuclear DNA. Oxidative damage induced by ROS is probably a major source of mitochondrial genomic instability leading to respiratory dysfunction.

Figure 3. Stabilization of mitochondria against OMM permeabilization in tumor cells. OMM permeabilization is a key event in apoptotic cell death. (a) During apoptosis, tBid-mediated oligomerization of Bax causes OMM permeabilization and release of cytochrome c (red circles). (b) Bcl-2 protein binds Bax and prevents its oligomerization. A shift in the balance between pro- apoptotic and antiapoptotic proteins in cancer cells, in favor of the latter, reduces the availability of Bax and prevents OMM permeabilization. (c) Upregulation of hexokinase in tumors and its binding to VDAC in the OMM not only facilitates glucose phosphorylation using mitochondrially generated ATP but keeps VDAC in the open state, preventing its interaction with tBid (de).

http://www.cell.com/cms/attachment/591821/4554543/gr4.sml

Figure 4. Shifting metabolism from glycolysis to glucose oxidation. Utilization of pyruvate is controlled by the relative activities of two enzymes, PDH and LDH. In cancer cells, PDH activity is suppressed by PDH kinase-mediated phosphorylation, and, therefore, instead of entering the Krebs cycle, pyruvate is converted into lactate. Several attempts have been made to redirect pyruvate towards oxidation in the mitochondria. Thus, inhibition of PDK1 by dichloroacetate might stimulate the activity of PDH and, hence, direct pyruvate to the mitochondria. A similar effect can be achieved by inhibition of LDH by oxamate. Overall, suppression of PDK1 and LDH activities will stimulate mitochondrial ATP production and might be lethal to tumor cells, even if these inhibitors are used at non-toxic doses. In addition, stimulation of mitochondrial function, for example though overexpression of mitochondrial frataxin, a protein associated with Friedreich ataxia, was shown to stimulate oxidative metabolism and inhibited growth in several cancer cell lines [86].
2.1.1.9  Glucose avidity of carcinomas

Ortega AD1, Sánchez-Aragó M, Giner-Sánchez D, Sánchez-Cenizo L, et al.
Cancer Letters 276 (2009) 125–135
http://dx.doi.org:/10.1016/j.canlet.2008.08.007

The cancer cell phenotype has been summarized in six hallmarks [D. Hanahan, R.A. Weinberg, The hallmarks of cancer, Cell 100 (1) (2000) 57-70]. Following the conceptual trait established in that review towards the comprehension of cancer, herein we summarize the basis of an underlying principle that is fulfilled by cancer cells and tumors: its avidity for glucose. Our purpose is to push forward that the metabolic reprogramming that operates in the cancer cell represents a seventh hallmark of the phenotype that offers a vast array of possibilities for the future treatment of the disease. We summarize the metabolic pathways that extract matter and energy from glucose, paying special attention to the concerted regulation of these pathways by the ATP mass-action ratio. The molecular and functional evidences that support the high glucose uptake and the “abnormal” aerobic glycolysis of the carcinomas are detailed discussing also the role that some oncogenes and tumor suppressors have in these pathways. We overview past and present evidences that sustain that mitochondria of the cancer cell are impaired, supporting the original Warburg’s formulation that ascribed the high glucose uptake of cancer cells to a defective mitochondria. A simple proteomic approach designed to assess the metabolic phenotype of cancer, i.e., its bioenergetic signature, molecularly and functionally supports Warburg’s hypothesis. Furthermore, we discuss the clinical utility that the bioenergetic signature might provide. Glycolysis is presented as the “selfish” pathway used for cellular proliferation, providing both the metabolic precursors and the energy required for biosynthetic purposes, in the context of a plethora of substrates. The glucose avidity of carcinomas is thus presented as the result of both the installment of glycolysis for cellular proliferation and of the impairment of mitochondrial activity in the cancer cell. At the end, the repression of mitochondrial activity affords the cancer cell with a cell-death resistant phenotype making them prone to malignant growth.

Fig. 1. Pathways of glucose metabolism. The model shows some of the relevant aspects of the metabolism of glucose. After entering the cell by specific transporters, glucose can be (i) catabolized by the pentose phosphate pathway (PPP) to obtain reducing power in the form of NADPH, (ii) used for the synthesis of carbohydrates or (iii) utilized by glycolysis to generate pyruvate and other metabolic intermediates that could be used in different anabolic processes (blue rectangles). In the cytoplasm, the generated pyruvate can be reduced to lactate and further exported from the cell or oxidized in the mitochondria by pyruvate dehydrogenase to generate acetyl-CoA, which is condensed with oxaloacetate in the tricarboxylic acid cycle (TCA cycle). The operation of the TCA cycle completes the oxidation of mitochondrial pyruvate. Different pathways that drain intermediates of the TCA cycle (oxaloacetate, succinyl-CoA, a-ketoglutarate and citrate) for biosynthetic purposes (blue rectangles) are represented. The transfer of electrons obtained in biological oxidations (NADH/FADH2) to molecular oxygen by respiratory complexes of the inner mitochondrial membrane (in green) is depicted by yellow lines. The utilization of the proton gradient generated by respiration for the synthesis of ATP by the H+-ATP synthase (in orange) in oxidative phosphorylation (OXPHOS) is also indicated. The incorporation of glutamine carbon skeletons into the TCA cycle is shown. The utilization of NADPH in anabolic pathways is also indicated.

Fig. 3. Fluxes of matter and energy in differentiated, proliferating and cancer cells. In differentiated cells, the flux of glycolysis is low because the requirement for precursors for anabolic purposes is low and there is a high energy yield by the oxidation of pyruvate in mitochondrial oxidative phosphorylation (OXPHOS). In this situation, mitochondrial activity produces large amounts of ROS that are normally quenched by the cellular antioxidant defense. In proliferating and cancer cells, there is a high demand of glucose to provide metabolic precursors for the biosynthesis of the macromolecules of daughter cells and because most of the energy required for anabolic purposes derives from non-efficient non-respiratory modes (glycolysis, pentose phosphate pathway) of energy generation. Limiting mitochondrial activity in these situations ensures less ROS production and their further downstream consequences. In addition, cancer cells have less overall mitochondrial complement or activity than normal cells by repressing the biogenesis of mitochondria.

Fig. 2. Genetic alterations underlying the glycolytic phenotype of cancer cells. The diagram represents the impact of gain-of-function mutations in oncogenes (ovals) and loss-of-function mutations in tumor suppressors (rectangles) in glycolysis and in the mitochondrial utilization of pyruvate in cancer cells. Hypoxia (low O2) induces the stabilization of HIF-1, which promotes transcriptional activation of the glucose transporter, glycolytic genes and PDK1. The expression of PDK1 results in the inactivation of pyruvate dehydrogenase and thus in a decreased oxidation of pyruvate in the TCA cycle concurrent to its enhanced cytoplasmic reduction to lactate by lactate dehydrogenase (LDHA). In addition, HIF1a reciprocally regulates the expression of two isoforms of the cytochrome c oxidase complex. The oncogen myc also supports an enhanced glycolytic pathway by transcriptional activation of glycolytic genes. High levels of c-myc could also promote the production of reactive oxygen species (ROS) that could damage nuclear (nDNA) and mitochondrial (mtDNA). The loss-of-function of the tumor suppressor p53 promotes an enhanced glycolytic phenotype by the repression of TIGAR expression. Likewise, loss-of-function of p53 diminished the expression of SCO2, a gene required for the appropriate assembly of cytochrome c oxidase, and thus limits the activity of mitochondria in the cancer cell.
Discussion:

Jose E S Roselino

  1. Warburg Effect revisited
    It is very interesting the series of commentaries following Warburg Effect revisited. However, it comes as no surprise that almost all of them have small or greater emphasis in the molecular biology (changes in gene expression) events of the metabolic regulation involved.
    I would like to comment on some aspects: 1- Warburg did the initial experiments following Pasteur line of reasoning that aimed at carbon flow through the cell (yeast in his case) instead of describing anything inside the cell. It is worth to recall that for the sake of his study, Pasteur considered anything inside the cell under the domain of divine forces. He, at least in defence of his work, entirely made outside the cell, considered that inside the cells was beyond human capability of understanding – He has followed vitalism as his line of reasoning in defence of his work – Interestingly, the same scientist that has ruled out spontaneous generation when Pasteurization was started. Therefore, Pasteur measured everything outside the cell (mainly sugar, ethanol – the equivalent of our lactic acid end product of anaerobic metabolism) and found that as soon as yeasts were placed in the presence of oxygen, sugar was consumed at low speed in comparison with the speed measured in anaerobiosis and ethanol was also produced at reduced speed. This is an indication of a fast biological regulatory mechanism that obviously, do not require changes in gene expression. As previously said, Warburg work translated for republishing in the Journal Biological Chemistry mentioned “grana” for mitochondria calling attention on an “inside-the-cell” component. It seems that, there is not a unique, single site of metabolism, where the Pasteur Effect – Warburg Effect seems to be elicited by the shift from anaerobiosis to aerobiosis or vice versa.
    In order to find a core for the mechanism the best approach seems to take into account one of the most important contributions of one of the greatest north-American biochemists, Briton Chance. He has made it with his polarographic method of following continuously the oxygen consumption of the cell´s mitochondria.
    Mitochondria burn organic carbon molecules under a very stringent control mechanism of oxidative-phosphorylation ATP production. Measured in the form of changes in the speed of oxygen consumption over time as Respiratory Control Ratio (RCR). When no ATP is required by the cell, oxygen consumption goes at low speed (basal or state II or IV). When ADP is offered to the mitochondria as an indication that ATP synthesis is necessary, oxygen consumption is activated in state III respiration. Low respiration means low burning activity of organic (carbon) molecules what in this case, means indirectly low glucose consumption. While high respiration is the converse – greater glucose consumption.
    Aerobic metabolism of glucose to carbonic acid and water provides a change in free energy enough for 38 molecules of ATP (the real production is +/- 32 ATP in aerobic condition) while glucose to lactic acid metabolism in anaerobiosis leads to 2 ATP production after discounting the other 2 required at initial stages of glucose metabolism.
    The low ATP yield in anaerobiosis explains the fast glucose metabolism in anaerobiosis while the control by RCR in mitochondria explains the reduction in glucose metabolism under aerobiosis as long as the ATP requirements of the cell remains the same – This is what it is assumed to happen in quiescent cells. Not necessarily in fast growing cells as cancer cells are. However, this will not be discussed here. In my first experiments in the early seventies, with M. Rouxii a dimorphic mold-yeast biological system the environmental change (aerobic – anaerobic) led to morphogenetic change presented as morphogenetic expression of the Pasteur Effect. In this case, the enzyme that replaces mitochondria in ATP production (Pyruvate Kinase) converting phosphoenolpyruvate into pyruvate together with ADP into ATP, shows changes that can be interpreted as change in gene expression together with new self-assembly of enzyme subunits. (Dimer AA – yeast in anaerobic growth or sporangiospores- converted into dimer AB in aerobic mold). In Leloir opinions at that time, PK I (AA) was only highly glycosylated, while PK II (AB) was less glycosylated without changes in gene expression.

    In case you read comments posted, you will see that the reference to aerobic glycolysis, continues to be made together with, new deranged forms of reasoning as is indicated by referring to: Mitochondrial role in ion homeostasis…
    Homeostasis is a regulation of something, ions, molecules, pH etc. that is kept outside the cell, therefore any role for mitochondria on it is only made indirectly, by its ATP production.
    However, mitochondria has a role together with other cell components in the regulation of for instance, intracellular Ca levels (Something that is not a homeostatic regulation). This is a very important point for the following reason: Homeostasis is maintained as a composite result of several differentiated cellular, tissue and organ functions. Differentiated function is something clearly missing in cancer cells. The best form to refer to the mitochondrial function regarding ions is to indicate a mitochondrial role in ion fluxes.
    In short, to indicate how an environmental event or better saying condition could favour genetic changes instead of being caused by genetic changes is to follow the same line of reasoning that is followed in understanding the role of cardioplegia. To stop heart beating is adequate for heart surgery it is also adequate for heart cells by sparing the ATP use during surgery and therefore, offering better recovery condition to the heart afterwards.
    In the case, here considered, even assuming that the genome is not made more unstable during hypoxic condition it is quite possible to understand that sharing ATP with both differentiated cell function and replication may led quality control of DNA in short supply of much needed ATP and this led to maintenance of mutations as well as less organized genome.

    • Thank you. I enjoy reading your comments. They are very instructive. I don’t really think that I comprehend the use of the term “epigenetics” and longer. In fact, it was never clear to me when I first heard it used some years ago.

      The term may have been closely wedded to the classic hypothesis of a unidirectional DNA–> RNA–> protein model that really has lost explanatory validity for the regulated cell in its environment. The chromatin has an influence, and protein-protein interactions are everywhere. As you point out, these are adjusting to a fast changing substrate milieu, and the genome is not involved. But in addition, the proteins may well have a role in suppression or activation of signaling pathways, and thereby, may well have an effect on gene expression. I don’t have any idea about how it would work, but mutations would appear to follow the metabolic condition of the cell over time. It would appear to be – genomic modification.

  2. In aerobic glucose metabolism, the oxidation of citric acid requires ADP and Mg²+, which will increase the speed of the reaction: Iso-citric acid + NADP (NAD) — isocitrate dehydrogenase (IDH) = alpha-ketoglutaric acid. In the Krebs cycle (the citric cycle), IDH1 and IDH2 are NADP+-dependent enzymes that normally catalyze the inter-conversion of D-isocitrate and alpha-ketoglutarate (α-KG). The IDH1 and IDH2 genes are mutated in > 75% of different malignant diseases. Two distinct alterations are caused by tumor-derived mutations in IDH1 or IDH2: the loss of normal catalytic activity in the production of α-ketoglutarate (α-KG) and the gain of catalytic activity to produce 2-hydroxyglutarate (2-HG), [22].
    This product is a competitive inhibitor of multiple α-KG-dependent dioxygenases, including demethylases, prolyl-4-hydroxylase and the TET enzymes family (Ten-Eleven Translocation-2), resulting in genome-wide alternations in histones and DNA methylation. [23]
    IDH1 and IDH2 mutations have been observed in myeloid malignancies, including de novo and secondary AML (15%–30%), and in pre-leukemic clone malignancies, including myelodysplastic syndrome and myeloproliferative neoplasm (85% of the chronic phase and 20% of transformed cases in acute leukemia), [24].
    Normally, cells in the body communicate via intra-cytoplasmic channels and maintain the energetic potential across cell membranes, which is 1-2.5 µmol of ATP in the form of ATP-ADP/ATP-ADP-IMP. These normal energetic values occur during normal cell division. If the intra-cellular and extra-cellular levels of Mg2+ are high, the extra-cellular charges of the cells will not be uniformly distributed.
    This change in distribution induces a high net positive charge for the cell and induces a loss of contact inhibition via the electromagnetic induction of oscillation [28, 29, 30]. Thereafter, malignant cells become invasive and metastasize.
    ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
    -22. Hartmann C, Meyer J, Balss J. Capper D, et al. Type and frequency of IDH1 and IDH2 mutations are related to astrocytic and oligodendroglial differentiation and age: a study of 1,010 diffuse gliomas. Acta Neuropathol 2009; 118: 464-474.

    23. Raymakers R.A, Langemeijer S.M., Kuiper R.P, Berends M, et al. Acquired mutations in TET2 are common in myelodysplastic syndromes. Nat. Genet 2009; 41; 838–849.

    24 Wagner K, Damm F, Gohring G., Gorlich K et al. Impact of IDH1 R132 mutations and an IDH1 single nucleotide polymorphism in cytogenetically normal acute myeloid leukemia: SNP rs11554137 is an adverse prognostic factor. J. Clin. Oncol.2010; 28: 2356–2364.
    Plant Molecular Biology 1989; 1: 271–303.

    29. Chien MM, Zahradka CE, Newel MC, Fred JW. Fas induced in B cells apoptosis require an increase in free cytosolic magnesium as in early event. J Biol Chem.1999; 274: 7059-7066.

    30. Milionis H J, Bourantas C L, Siamopoulos C K, Elisaf MS. Acid bases and electrolytes abnormalities in Acute Leukemia. Am J Hematol 1999; (62): 201-207.

    31. Thomas N Seyfried; Laura M Shelton.Cancer as a Metabolic Disease. Nutr Metab 2010; 7: 7

    – Aurelian Udristioiu, M.D,
    – Lab Director, EuSpLM,
    – City Targu Jiu, Romania
    AACC, National Academy of Biochemical Chemistry (NACB) Member, Washington D.C, USA.

 

 

 

 

 

 

 

 

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The Metabolic View of Epigenetic Expression

Writer and Curator: Larry H Bernstein, MD, FCAP

Introduction

This is the fifth contribution to a series of articles on cancer, genomics, and metabolism.   I begin this after reading an article by Stephen Williams “War on Cancer May Need to Refocus Says Cancer Expert on NPR”, and after listening to NPR “On the Media”. This is an unplanned experience, perhaps partly related to an Op-Ed in the New York Times two days before by Angelina Jolie Pittman.  Taking her article prior to pre-emptive breast surgery for the BRCA1 mutation two years ago and her salpingo-oophorectomy at age 39 years with her family history, and her adoption of several children even prior to her marriage to Brad Pitt, reveals an unusual self-knowledge as well as perspective on the disease risk balanced with her maternal instincts.  I sense (but don’t know) that she had a good knowledge not stated about the estrogen sensitivity of breast cancer for some years, and balanced that knowledge in her life decisions.

Tracing the history of cancer and the Lyndon Johnson initiated “War on Cancer” the initiative is presented as misguided.  Moreover, the imbalance is posed aas focused overly on genomics, and there is an imbalnced in the attention to the types of cancer, bladder cancer (urothelial) receiving too little attention. However, the events that drive this are complex, and not surprising.  The funding is driven partly by media attention (a film star or President’s wife) and not to be overlooked, watch where the money flows.  People who have the ability to donate and also have a family experience will give, regardless of the statistics because it is 100 percent in their eyes.

Insofar as the scientific endeavor goes, young scientists are committed to a successful research career, and they also need funding, so they have to balance the risk of success and failure in the choice of problems they choose to work on.  But until the 20th century, the biological sciences were largely descriptive. The emergence of a “Molecular Biology” is a unique 20th century development. The work of Pathology – pioneered by Rokitansky, Virchow, and to an extent also the anatomist/surgeon John Harvey – was observational science.  The description of Hodgkin’s lymphoma was observational, and it was a breakthrough in medicine.

With the emergence of genomics from biochemistry and genetics in molecular biology (biology at the subcellular level), a part of medicine that was well founded became an afterthought.  After all, after many years of the history of medicine and pathology, it is well known that cancers are not only a dysmetabolism of cellular replication and cellular regulation, but cancers have a natural history related to organ system, tissue specificity, sex, and age of occurrence. This should be well known to the experienced practitioner, but not necessarily to the basic researcher with no little clinical exposure.  Consequently, it was quite remarkable to me to find that the truly amazing biochemist who gave a “Harvey Lecture” at Harvard on the pyridine nucleotide transhydrogenases, and who shared in the discovery of Coenzyme A, had made the observation that organs that are primarily involved with synthetic activity -adrenal, pituitary, and thyroid, testis, ovary, breast (most notably) – have a more benign course than those of stomach, colon, pancreas, melanoma, hematopoietic, and sarcomas. The liver is highly synthetic, but doesn’t fit so nicely because of the role in detoxification and the large role in glucose and fat catabolism.  Further, this was at a time that we knew nothing about the cell death pathway and cellular repair, and how is it in concert with cell proliferation.

The first important reasoning about cancer metabolism was opened by Otto Warburg in the late 1920s.  I have  little reason to doubt his influence on Nathan Kaplan, who used the terms DPN(+/H) and TPN(+/H), disregarding the terms NAD(+/H) and NADP(+/H), although I was told it was because of the synthesis of the pyridine nucleotide adducts for study (APDPN, etc.).

In a recent article, I had an interesting response from Jose ES Rosalino:

In mRNA Translation and Energy Metabolism in Cancer

Topisirovic and N. Sonenberg – Cold Spring Harbor Symposia on Quantitative Biology, Volume LXXVI – http://dx.doi.org:/10.1101/sqb.2011.76.010785

“A prominent feature of cancer cells is the use of aerobic glycolysis under conditions in which oxygen levels are sufficient to support energy production in the mitochondria (Jones and Thompson 2009; Cairns et al. 2010). This phenomenon, named the “Warburg effect,” after its discoverer Otto Warburg, is thought to fuel the biosynthetic requirements of the neoplastic growth (Warburg 1956; Koppenol et al. 2011) and has recently been acknowledged as one of the hallmarks of cancer (Hanahan and Weinberg 2011). mRNA translation is the most energy-demanding process in the cell (Buttgereit and Brand 1995). Again, the use of aerobic glycolysis expression has being twisted.”

To understand my critical observation consider this: Aerobic glycolysis is the carbon flow that goes from Glucose to CO2 and water (includes Krebs cycle and respiratory chain for the restoration of NAD, FAD etc.

Anerobic glyclysis is the carbon flow that goes from glucose to lactate. It uses conversion of pyruvate to lactate to regenerate NAD.

“Pasteur effect” is an expression coined by Warburg it refers to the reduction in the carbon flow from glucose when oxygen is offered to yeasts. The major reason for that is in general terms, derived from the fact that carbon flow is regulated by several cell requirements but majorly by the ATP needs of the cell. Therefore, as ATP is generated 10 more efficiently in aerobiosis than under anaerobiosis, less carbon flow is required under aerobiosis than under anaerobiosis to maintain ATP levels. Warburg, after searching for the same regulatory mechanism in normal and cancer cells for comparison found that transformed cell continued their large flow of glucose carbons to lactate despite of the presence of oxygen.

So, it is wrong to describe that aerobic glycolysis continues in the presence of oxygen. It is what it is expected to occur. The wrong thing is that anaerobic glycolysis continues under aerobiosis.

In our discussion of transcription and cell regulatory processes, we have already encountered a substantial amount of “enzymology” that drives what is referred to as “epigenetics”.  Enzymatic reactions are involved almost everywhere we look at the processes involved in RNA nontranscriptional affairs.

Enzyme catalysis

Pyruvate carboxylase is critical for non–small-cell lung cancer proliferation
K Sellers,…, TW-M Fan
J Clin Invest. Jan 2015; xx
http://dx.doi.org:/10.1172/JCI72873

Anabolic biosynthesis requires precursors supplied by the Krebs cycle, which in turn requires anaplerosis to replenish precursor intermediates. The major anaplerotic sources are pyruvate and glutamine, which require the activity of pyruvate carboxylase (PC) and glutaminase 1 (GLS1), respectively. Due to their rapid proliferation, cancer cells have increased anabolic and energy demands; however, different cancer cell types exhibit differential requirements for PC- and GLS-mediated pathways for anaplerosis and cell proliferation. Here, we infused patients with early-stage non–small-cell lung cancer (NSCLC) with uniformly 13C-labeled glucose before tissue resection and determined that the cancerous tissues in these patients had enhanced PC activity. Freshly resected paired lung tissue slices cultured in 13C6-glucose or 13C5, 15N2-glutamine tracers confirmed selective activation of PC over GLS in NSCLC. Compared with noncancerous tissues, PC expression was greatly enhanced in cancerous tissues, whereas GLS1 expression showed no trend. Moreover, immunohistochemical analysis of paired lung tissues showed PC overexpression in cancer cells rather than in stromal cells of tumor tissues. PC knockdown induced multinucleation, decreased cell proliferation and colony formation in human NSCLC cells, and reduced tumor growth in a mouse xenograft model. Growth inhibition was accompanied by perturbed Krebs cycle activity, inhibition of lipid and nucleotide biosynthesis, and altered glutathione homeostasis. These findings indicate that PC-mediated anaplerosis in early stage NSCLC is required for tumor survival and proliferation.

Accelerated glycolysis under aerobic conditions (the “Warburg effect”) has been a hallmark of cancer for many decades (1). It is now recognized that cancer cells must undergo many other metabolic reprograming changes (2) to meet the increased anabolic and energetic demands of proliferation (3, 4). It is also becoming clear that different cancer types may utilize a variety of metabolic adaptations that are context dependent, commensurate with the notion that altered metabolism is a hallmark of cancer (12). Enhanced glucose uptake and aerobic glycolysis generates both energy (i.e., ATP) and molecular precursors for the biosynthesis of complex carbohydrates, sugar nucleotides, lipids, proteins, and nucleic acids. However, increased glycolysis alone is insufficient to meet the total metabolic demands of proliferating cancer cells. The Krebs cycle is also a source of energy via the oxidation of pyruvate, fatty acids, and amino acids such as glutamine. Moreover, several Krebs cycle intermediates are essential for anabolic and glutathione metabolism, including citrate, oxaloacetate, and α-ketoglutarate (Figure 1A).

Figure 1. PC is activated in human NSCLC tumors. (A) PC and GLS1 catalyze the major anaplerotic inputs (blue) into the Krebs cycle to support the anabolic demand for biosynthesis (green). Also shown is the fate of 13C from 13C6-glucose through glycolysis and into the Krebs cycle via PC (red).
(B) Representative Western blots of PC and GLS1 protein expression levels in human NC lung (N) and NSCLC (C) tissues. (C) Pairwise PC and GLS1 expression (n = 86) was normalized to α-tubulin and plotted as the log10 ratio of CA/NC tissues. For PC, nearly all log ratios were positive (82 of 86), with a clustering in the 0.5–1 range (i.e., typically 3- to 10-fold higher expression in the tumor tissue; Wilcoxon test, P < 0.0001). In contrast, GLS1 expression was nearly evenly distributed between positive and negative log10 ratios and showed no statistically significant difference between the CA and NC tissues (Wilcoxon test, P = 0.213). Horizontal bar represents the median. (D) In vivo PC activity was enhanced in CA tissue compared with that in paired NC lung tissues (n = 34) resected from the same human patients given 13C6-glucose 2.5–3 hours before tumor resection. PC activity was inferred from the enrichment of 13C3-citrate (Cit+3), 13C5-Cit (Cit+5), 13C3-malate (Mal+3), and 13C3-aspartate (Asp+3) as determined by GC-MS. *P < 0.05 and **P < 0.01 by paired Student t test. Error bars represent the SEM.

Continued functioning of the Krebs cycle requires the replenishment of intermediates that are diverted for anabolic uses or glutathione synthesis. This replenishment process, or anaplerosis, is accomplished via 2 major pathways: glutaminolysis (deamidation of glutamine via glutaminase [GLS] plus transamination of glutamate to α-ketoglutarate) and carboxylation of pyruvate to oxaloacetate via ATP-dependent pyruvate carboxylase (PC) (EC 6.4.1.1) (refs. 3, 20, 21, and Figure 1A). The relative importance of these pathways is likely to depend on the nature of the cancer and its specific metabolic adaptations, including those to the microenvironment (20, 22). For example, glutaminolysis was shown to be activated in the glioma cell line SF188, while PC activity was absent, despite the high PC activity present in normal astrocytes. However, SF188 cells use PC to compensate for GLS1 suppression or glutamine restriction (20), and PC, rather than GLS1, was shown to be the major anaplerotic input to the Krebs cycle in primary glioma xenografts in mice. It is also unclear as to the relative importance of PC and GLS1 in other cancer cell types or, most relevantly, in human tumor tissues in situ. Our preliminary evidence from 5 non–small-cell lung cancer (NSCLC) patients indicated that PC expression and activity are upregulated in cancerous (CA) compared with paired noncancerous (NC) lung tissues (21), although it was unclear whether PC activation applies to a larger NSCLC cohort or whether PC expression was associated with the cancer and/or stromal cells

Here, we have greatly extended our previous findings (21) in a larger cohort (n = 86) by assessing glutaminase 1 (GLS1) status and analyzing in detail the biochemical and phenotypic consequences of PC suppression in NSCLC. We found PC activity and protein expression levels to be, on average, respectively, 100% and 5- to 10-fold higher in cancerous (CA) lung tissues than in paired NC lung tissues resected from NSCLC patients, whereas GLS1 expression showed no significant trend. We have also applied stable isotope–resolved metabolomic (SIRM) analysis to paired freshly resected CA and NC lung tissue slices in culture (analogous to the Warburg slices; ref. 25) using either [U-13C] glucose or [U-13C,15N] glutamine as tracers. This novel method provided information about tumor metabolic pathways and dynamics without the complication of whole-body metabolism in vivo.

PC expression and activity, but not glutaminase expression, are significantly enhanced in early stages of malignant NSCLC tumors. PC protein expression was significantly higher in primary NSCLC tumors than in paired adjacent NC lung tissues (n = 86, P < 0.0001, Wilcoxon test) (Figure 1, B and C). The median PC expression was 7-fold higher in the tumor, and the most probable (modal) overexpression in the tumor was approximately 3-fold higher (see Supple-mental Table 1; supplemental material available online with this article; http://dx.doi.org:/10.1172/JCI72873DS1). We found that PC expression was also higher in the tumor tissue compared with that detected in the NC tissue in 82 of 86 patients. In contrast, GLS1 expression was not significantly different between the tumor and NC tissues (P = 0.213, Wilcoxon test) (Figure 1C and Supplemental Table 1). The 13C3-Asp produced from 13C6-glucose (Figure 1A) infused into NSCLC patients was determined by gas chromatography–mass spectrometry (GC-MS) to estimate in vivo PC activity. A bolus injection of 10 g 13C6-glucose in 50 ml saline led to an average of 44% 13C enrichment in the plasma glucose immediately after infusion (Supplemental Table 2). Because the labeled glucose was absorbed by various tissues over the approximately 2.5 hours between infusion and tumor resection, plasma glucose enrichment dropped to 17% (Supplemental Table 2). The labeled glucose in both CA and NC lung tissues was metabolized to labeled lactate, but this occurred to a much greater extent in the CA tissues (Supplemental Figure 1A), which indicates accelerated glycolysis in these tissues.

Fresh tissue (Warburg) slices confirm enhanced PC and Krebs cycle activity in NSCLC. To further assess PC activity relative to GLS1 activity in human lung tissues, thin (<1 mm thick) slices of paired CA and NC lung tissues freshly resected from 13 human NSCLC patients were cultured in 13C6-glucose or 13C5,15N2-glutamine for 24 hours. These tissues maintain biochemical activity and histological integrity for at least 24 hours under culture conditions (Figure 2A, Supplemental Figure 2, A and B, and ref. 26). When the tissues were incubated with 13C6-glucose, CA slices showed a significantly greater percentage of enrichment in glycolytic 13C3-lactate (3 in Figure 2B) than did the NC slices, indicative of the Warburg effect. In addition, the CA tissues had significantly higher fractions of 13C4-, 13C5-, and 13C6-citrate (4, 5, and 6 of citrate, respectively, in Figure 2B) than did the NC tissues. These isotopologs require the combined action of PDH, PC, and multiple turns of the Krebs cycle (Figure 2C). Consistent with the labeled citrate data, the increase in the percentage of enrichment of 13C3-, 13C4-, and 13C5-glutamate (3, 4, and 5 of glutamate, respectively, in Figure 2B) in the CA tissues indicates enhanced Krebs cycle and PC activity.

Figure 2. Ex vivo CA lung tissue slices have enhanced oxidation of glucose through glycolysis and the Krebs cycle with and without PC input compared with that of paired NC lung slices. Thin slices of CA and NC lung tissues freshly resected from 13 human NSCLC patients were incubated with 13C6-glucose for 24 hours as described in the Methods. The percentage of enrichment of lactate, citrate, glutamate, and aspartate was determined by GC-MS. (A) 1H{13C} HSQC NMR showed an increase in labeled lactate, glutamate, and aspartate. In addition, CA tissues had elevated 13C abundance in the ribose moiety of the adenine-containing nucleotides (1′-AXP), indicating that the tissues were viable and had enhanced capacity for nucleotide synthesis. (B) CA tissue slices (n = 13) showed increased glucose metabolism through glycolysis based on the increased percentage of enrichment of 13C3-lactate (“3”), and through the Krebs cycle based on the increased percentage of enrichment of 13C4–6-citrate (“4–6”) and 13C3–5-glutamate (“3–5”) (see 13C fate tracing in C). *P < 0.05 and **P < 0.01 by paired Student’s t test. Error bars represent the SEM. (C) An atom-resolved map illustrates how PC, PDH, and 2 turns of the Krebs cycle activity produced the 13C isotopologs of citrate and glutamate in B, whose enrichment were significantly enhanced in CA tissue slices.

Figure 4. PC suppression via shRNA inhibits proliferation and tumorigenicity of human NSCLC cell lines in vitro and in vivo. Proliferation and colony-formation assays were initiated 1 week after transduction and selection with puromycin. A549 xenograft in NSG mice was performed 8 days after transduction. *P < 0.01, **P < 0.001, ***P < 0.0001, and ****P < 0.00001 by Student t test, assuming unequal variances. Error bars represent the SEM. (A) NSCLC cells lines were transduced with shPC55 or shEV. Proliferation assays (n = 6) revealed substantial growth inhibition induced by PC knockdown in all 5 cell lines after a relatively long latency period. (B) Colony-formation assays indicated that PC knockdown reduced the capacity of A549 and PC9 cells to form colonies in soft agar (n = 3). (C) Tumor xenografts from shPC55-transduced A549 cells showed a 2-fold slower growth rate than did control shEV tumors (P < 0.001 by the unpaired Welch version of the t test). Tumor size was calculated as πab/4, where a and b are the x,y diameters. Each point represents an average of 6 mice. The solid lines are the nonlinear regression fits to the equation: size = a + bt2, as described in the Methods. (D) The extent of PC knockdown in the mouse xenografts (n = 6) was lesser than that in cell cultures, leading to less attenuation of PC expression (30%–60% of control) and growth inhibition. In addition, PC expression in the excised tumors correlated with the individual growth rates, as determined by Pearson’s correlation coefficient.

Fatty acyl synthesis from 13C5-glutamine (“Even” in Figure 6B) via glutaminolysis and the Krebs cycle was greatly attenuated in PC-suppressed cells. Taken together, these results suggest that PC knockdown severely inhibits lipid production by blocking the biosynthesis of fatty acyl components but not the glucose-derived glycerol backbone. This is consistent with decreased Krebs cycle activity (Figure 5), which in turn curtails citrate export from the mitochondria to supply the fatty acid precursor acetyl CoA in the cytoplasm.

Figure 5. PC knockdown perturbs glucose and glutamine flux through the Krebs cycle. 13C Isotopolog concentrations were determined by GC-MS (n = 3). Values represent the averages of triplicates, with standard errors. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001 by Student’s t test, assuming unequal variances. The experiments were repeated 3 times. (A) A549 cells were transduced with shPC55 for 10 days before incubation with 13C6-glucose for 24 hours. As expected, the 13C isotopologs of Krebs cycle metabolites produced via PC and Krebs cycle activity were depleted in PC-deficient cells (tracked by blue dots in the atom-resolved map and blue circles in the bar graphs; see also Figure 2C). In addition, 13C6-glucose metabolism via PDH was also perturbed (indicated by red dots and circles). (B) Treatment of PC-knockdown cells with 13C5,15N2-glutamine revealed that anaplerotic input via GLS did not compensate for the loss of PC activity, since GLS activity was attenuated, as inferred from the activity markers (indicated by red dots and circles). Decarboxylation of glutamine-derived malate by malic enzyme (ME) and reentry of glutamine-derived pyruvate into the Krebs cycle via PC or PDH (shown in blue and green, respectively) were also attenuated. Purple diamonds denote 15N; black diamonds denote 14N.

Figure 6. PC suppression hinders Krebs cycle–fueled biosynthesis. (A) 13C atom–resolved pyrimidine biosynthesis from 13C6-glucose and 13C5-glutamine is depicted with a 13C5-ribose moiety (red dots) produced via the pentose phosphate pathway (PPP) and 13C1-3  uracil ring (blue dots) derived from  13C2-4-aspartate produced via the Krebs cycle or the combined action of ME and PC (blue dots). A549 cells transduced with shPC55 or shEV were incubated with 13C6-glucose or 13C5-glutamine for 24 hours. Fractional enrichment of UTP and CTP isotopologs from FT-ICR-MS analysis of polar cell extracts showed reduced enrichment of 13C6-glucose–derived 13C5-ribose (the “5” isotopolog) and 13C6-glucose– or 13C5-glutamine–derived 13C1-3-pyrimidine rings (the “6–8” or “1–3” isotopologs, highlighted by dashed green rectangles; for the “6–8” isotopologs, 5 13Cs arose from ribose and 1–3 13Cs from the ring) (10, 45). These data suggest that PC knockdown inhibits de novo pyrimidine biosynthesis from both glucose and glutamine. (B) Glucose and glutamine carbons enter fatty acids via citrate. FT-ICR-MS analysis of labeled lipids from the nonpolar cell extracts showed that PC knockdown severely inhibited the incorporation of glucose and glutamine carbons into the fatty acyl chains (even) and fatty acyl chains plus glycerol backbone (odd >3) of phosphatidylcholine lipids. However, synthesis of the 13C3-glycerol backbone (the “3” isotopolog) or its precursor 13C3-α-glycerol-3-phosphate (αG3P, m+3) from 13C6-glucose was enhanced rather than inhibited by PC knockdown. These data suggest that PC suppression specifically hinders fatty acid synthesis in A549 cells. Values represent the averages of triplicates (n = 3), with standard errors. *P < 0.05, **P < 0.01,  and ***P < 0.001 by Student’s t test, assuming unequal variances.

De novo glutathione synthesis was analyzed by 1H{13C} HSQC NMR. Glutathione synthesis from both glucose and glutamine was suppressed by PC knockdown (Supplemental Figure 9, A and B). Reduced de novo synthesis led to a large decrease in the total level of reduced glutathione (GSH; Supplemental Figure 12, A and B). At the same time, PC-knockdown cells accumulated slightly more oxidized GSH (GSSG; Supplemental Figure 12, A and B), leading to a significantly reduced GSH/GSSG ratio both in cell culture and in vivo (Supplemental Figure 12C). To determine whether this perturbation of glutathione homeostasis compromises the ability of PC-suppressed cells to handle oxidative stress, we measured ROS production by DCFDA fluorescence. PC-knockdown cells had over 70% more basal ROS than did control cells (0 mM H2O2; Supplemental Figure 12D). When cells were exposed to increasing concentrations of H2O2, the knockdown cells were less able to quench ROS, as they produced up to 300% more ROS than did control cells (Supplemental Figure 12D). However, N-acetylcysteine (NAC) at 10 mM did not rescue the growth of PC-knockdown cells, suggesting that such a growth effect is not simply related to an inability to regenerate GSH from GSSG. Altogether, these results show that PC suppression compromises anaplerotic input into the Krebs cycle, which in turn reduces the activity of the Krebs cycle, while limiting the ability of A549 cells to synthesize nucleotides, lipids, and glutathione. These downstream effects of PC knockdown were also evident when comparing the metabolism of shPC55-transduced A549 cells against that of A549 cells transduced with a scrambled vector (shScr) (Supplemental Figure 13), which suggests that they are on-target effects of PC knockdown.

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In vivo HIF-mediated reductive carboxylation is regulated by citrate levels and sensitizes VHL-deficient cells to glutamine deprivation.
Gameiro PA, Yang J, Metelo AM,…, Stephanopoulos G, Iliopoulos O.
Cell Metab. 2013 Mar 5; 17(3):372-85.
http://dx.doi.org:/10.1016/j.cmet.2013.02.002

Hypoxic and VHL-deficient cells use glutamine to generate citrate and lipids through reductive carboxylation (RC) of α-ketoglutarate. To gain insights into the role of HIF and the molecular mechanisms underlying RC, we took advantage of a panel of disease-associated VHL mutants and showed that HIF expression is necessary and sufficient for the induction of RC in human renal cell carcinoma (RCC) cells. HIF expression drastically reduced intracellular citrate levels. Feeding VHL-deficient RCC cells with acetate or citrate or knocking down PDK-1 and ACLY restored citrate levels and suppressed RC. These data suggest that HIF-induced low intracellular citrate levels promote the reductive flux by mass action to maintain lipogenesis. Using [(1-13)C]glutamine, we demonstrated in vivo RC activity in VHL-deficient tumors growing as xenografts in mice. Lastly, HIF rendered VHL-deficient cells sensitive to glutamine deprivation in vitro, and systemic administration of glutaminase inhibitors suppressed the growth of RCC cells as mice xenografts.

Cancer cells undergo fundamental changes in their metabolism to support rapid growth, adapt to limited nutrient resources, and compete for these supplies with surrounding normal cells. One of the metabolic hallmarks of cancer is the activation of glycolysis and lactate production even in the presence of adequate oxygen. This is termed the Warburg effect, and efforts in cancer biology have revealed some of the molecular mechanisms responsible for this phenotype (Cairns et al., 2011). More recently, 13C isotopic studies have elucidated the complementary switch of glutamine metabolism that supports efficient carbon utilization for anabolism and growth (DeBerardinis and Cheng, 2010). Acetyl-CoA is a central biosynthetic precursor for lipid synthesis, being generated from glucose-derived citrate in well-oxygenated cells (Hatzivassiliou et al., 2005). Warburg-like cells, and those exposed to hypoxia, divert glucose to lactate, raising the question of how the tricarboxylic acid (TCA) cycle is supplied with acetyl-CoA to support lipogenesis. We and others demonstrated, using 13C isotopic tracers, that cells under hypoxic conditions or defective mitochondria primarily utilize glutamine to generate citrate and lipids through reductive carboxylation (RC) of α-ketoglutarate by isocitrate dehydrogenase 1 (IDH1) or 2 (IDH2) (Filipp et al., 2012; Metallo et al., 2012; Mullen et al., 2012; Wise et al., 2011).

The transcription factors hypoxia inducible factors 1α and 2α (HIF-1α, HIF-2α) have been established as master regulators of the hypoxic program and tumor phenotype (Gordan and Simon, 2007; Semenza, 2010). In addition to tumor-associated hypoxia, HIF can be directly activated by cancer-associated mutations. The von Hippel-Lindau (VHL) tumor suppressor is inactivated in the majority of sporadic clear-cell renal carcinomas (RCC), with VHL-deficient RCC cells exhibiting constitutive HIF-1α and/or HIF-2α activity irrespective of oxygen availability (Kim and Kaelin, 2003). Previously, we showed that VHL-deficient cells also relied on RC for lipid synthesis even under normoxia. Moreover, metabolic profiling of two isogenic clones that differ in pVHL expression (WT8 and PRC3) suggested that reintroduction of wild-type VHL can restore glucose utilization for lipogenesis (Metallo et al., 2012). The VHL tumor suppressor protein (pVHL) has been reported to have several functions other than the well-studied targeting of HIF. Specifically, it has been reported that pVHL regulates the large subunit of RNA polymerase (Pol) II (Mikhaylova et al., 2008), p53 (Roe et al., 2006), and the Wnt signaling regulator Jade-1. VHL has also been implicated in regulation of NF-κB signaling, tubulin polymerization, cilia biogenesis, and proper assembly of extracellular fibronectin (Chitalia et al., 2008; Kim and Kaelin, 2003; Ohh et al., 1998; Thoma et al., 2007; Yang et al., 2007). Hypoxia inactivates the α-ketoglutarate-dependent HIF prolyl hydroxylases, leading to stabilization of HIF. In addition to this well-established function, oxygen tension regulates a larger family of α-ketoglutarate-dependent cellular oxygenases, leading to posttranslational modification of several substrates, among which are chromatin modifiers (Melvin and Rocha, 2012). It is therefore conceivable that the effect of hypoxia on RC that was reported previously may be mediated by signaling mechanisms independent of the disruption of the pVHL-HIF interaction. Here we

  • demonstrate that HIF is necessary and sufficient for RC,
  • provide insights into the molecular mechanisms that link HIF to RC,
  • detected RC activity in vivo in human VHL-deficient RCC cells growing as tumors in nude mice,
  • provide evidence that the reductive phenotype of VHL-deficient cells renders them sensitive to glutamine restriction in vitro, and
  • show that inhibition of glutaminase suppresses growth of VHL-deficient cells in nude mice.

These observations lay the ground for metabolism-based therapeutic strategies for targeting HIF-driven tumors (such as RCC) and possibly the hypoxic compartment of solid tumors in general.

HIF Inactivation Is Necessary for Downregulation of Reductive Carboxylation by pVHL

(A) Expression of HIF-1 α, HIF-2α, and their target protein GLUT1 in UMRC2-derived cell lines, as indicated.

(B) Carbon atom transition map: the fate of [1-13C1] and [5-13C1]glutamine used to trace reductive carboxylation in this work (carbon atoms are represented by circles). The [1-13C1] (green circle) and [5-13C1] (red circle) glutamine-derived isotopic labels are retained during the reductive TCA cycle (bold red pathway). Metabolites containing the acetyl-CoA carbon skeleton are highlighted by dashed circles.

(C) Relative contribution of reductive carboxylation.

(D and E) Relative contribution of glucose oxidation to the carbons of indicated metabolites (D) and citrate (E). Student’s t test compared VHL-reconstituted to vector-only or to VHL mutants (Y98N/Y112N). Error bars represent SEM. Pyr, pyruvate; Lac, lactate; AcCoA, acetyl-CoA, Cit, citrate; IsoCit, isocitrate; Akg, α-ketoglutarate; Suc, succinate; Fum, fumarate; Mal, malate; OAA, oxaloacetate; Asp, aspartate; Glu, glutamate; PDH, pyruvate dehydrogenase; ME, malic enzyme; IDH, isocitrate dehydrogenase enzymes; ACO, aconitase enzymes; ACLY, ATP-citrate lyase; GLS, glutaminase.

To test the effect of HIF activation on the overall glutamine incorporation in the TCA cycle, we labeled an isogenic pair of VHL-deficient and VHL-reconstituted UMRC2 cells with [U-13C5]glutamine, which generates M4 fumarate, M4 malate, M4 aspartate, and M4 citrate isotopomers through glutamine oxidation. As seen in Figure S1B, VHL-deficient/VHL-positive UMRC2 cells exhibit similar enrichment of M4 fumarate, M4 malate, and M4 asparate (but not citrate) showing that VHL-deficient cells upregulate reductive carboxylation without compromising oxidative metabolism from glutamine. Next, we tested whether HIF inactivation by pVHL is necessary to regulate the reductive utilization of glutamine for lipogenesis. To this end, we traced the relative incorporation of [U-13C6]glucose or [5-13C1]glutamine into palmitate. Labeled carbon derived from [5-13C1]glutamine can be incorporated into fatty acids exclusively through RC, and the labeled carbon cannot be transferred to palmitate through the oxidative TCA cycle (Figure 1B, red carbons). Tracer incorporation from [5-13C1]glutamine occurs in the one carbon (C1) of acetyl-CoA, which results in labeling of palmitate at M1, M2, M3, M4, M5, M6, M7, and M8 mass isotopomers. In contrast, lipogenic acetyl-CoA molecules originating from [U-13C6]glucose are fully labeled, and the labeled palmitate is represented by M2, M4, M6, M8, M10, M12, M14, and M16 mass isotopomers. VHL-deficient control cells and cells expressing pVHL type 2B mutants exhibited high palmitate labeling from the [5-13C1]glutamine; conversely, reintroduction of wild-type or type 2C pVHL mutant (L188V) resulted in high labeling from [U-13C6]glucose (Figures 2A and 2B, box inserts highlight the heavier mass isotopomers).

hif-inactivation-is-necessary-for-downregulation-of-reductive-carboxylation-by-pvhl

hif-inactivation-is-necessary-for-downregulation-of-reductive-carboxylation-by-pvhl

Figure 2.  HIF Inactivation Is Necessary for Downregulation of Reductive Lipogenesis by pVHL

Next, to determine the specific contribution from glucose oxidation or glutamine reduction to lipogenic acetyl-CoA, we performed isotopomer spectral analysis (ISA) of palmitate labeling patterns. ISA indicates that wild-type pVHL or pVHL L188V mutant-reconstituted UMRC2 cells relied mainly on glucose oxidation to produce lipogenic acetyl-CoA, while UMRC2 cells reconstituted with a pVHL mutant defective in HIF inactivation (Y112N or Y98N) primarily employed RC. Upon disruption of the pVHL-HIF interaction, glutamine becomes the preferred substrate for lipogenesis, supplying 70%–80% of the lipogenic acetyl-CoA (Figure 2C). This is not a cell-line-specific phenomenon, but it applies to VHL-deficient human RCC cells in general; the same changes are observed in 786-O cells reconstituted with wild-type pVHL or mutant pVHL or infected with vector only as control (Figure S2). Type 2A pVHL mutants (Y112H, which retain partial HIF binding) confer an intermediate reductive phenotype between wild-type VHL (which inactivates HIF) and type 2B pVHL mutants (which are totally defective in HIF regulation) as seen in Figures 1 and ​and 2.2. Taken together, these data demonstrate that the ability of pVHL to regulate reductive carboxylation and lipogenesis from glutamine tracks genetically with its ability to bind and degrade HIF, at least in RCC cells.

HIF Is Sufficient to Induce RC from Glutamine in RCC Cells

To test the hypothesis that HIF-2α is sufficient to promote RC from glutamine, we expressed a pVHL-insensitive HIF-2α mutant (HIF-2α P405A/P531A, marked as HIF-2α P-A) in VHL-reconstituted 786-O cells (Figure 3). HIF-2α P-A is constitutively expressed in this polyclonal cell population, despite the reintroduction of wild-type VHL, reflecting a pseudohypoxia condition (Figure 3A). We confirmed that this mutant is transcriptionally active by assaying for the expression of its targets genes GLUT1, LDHA, HK1, EGLN, HIG2, and VEGF (Figures 3B and S3A). As shown in Figure 3C, reintroduction of wild-type VHLinto 786-O cells suppressed RC, whereas the expression of the constitutively active HIF-2α mutant was sufficient to stimulate this reaction, restoring the M1 enrichment of TCA cycle metabolites observed in VHL-deficient 786-O cells. Expression of HIF-2α P-A also led to a concomitant decrease in glucose oxidation, corroborating the metabolic alterations observed in glutamine metabolism (Figures 3D and 3E). Additional evidence of the HIF2α-regulation on the reductive phenotype was obtained with [U-13C5]glutamine, which generates M5 citrate, M3 fumarate, M3 malate, and M3 aspartate through RC (Figure 3F).

Our current work showed that HIF-2α is sufficient to induce the reductive program in RCC cells that express only the HIF-2α paralog, while mouse NEK cells appeared to use HIF-1α preferentially to promote RC. Together with the evidence that HIF-1α and HIF-2α may have opposite roles in tumor growth, it is possible that the cellular context dictates which paralog activates RC. It is also possible that HIF-2α adopts the RC regulatory function of HIF-1α upon deletion of the latter in RCC cells. Further studies are warranted in understanding the relative role of HIF-α paralogs in regulating RC in different cell types.

Finally, the selective sensitivity to glutaminase inhibitors exhibited by VHL-deficient cells, together with the observed RC activity in vivo, strongly suggests that reductive glutamine metabolism may fuel tumor growth. Investigating whether the reductive flux correlates with tumor hypoxia and/or contributes to the actual cell survival under low oxygen conditions is warranted. Together, our findings underscore the biological significance of reductive carboxylation in VHL-deficient RCC cells. Targeting this metabolic signature of HIF may open viable therapeutic opportunities for the treatment of hypoxic and VHL-deficient tumors.

Elevated levels of 14-3-3 proteins, serotonin, gamma enolase and pyruvate kinase identified in clinical samples from patients diagnosed with colorectal cancer
Dowling P, Hughes DJ, Larkin AM, Meiller J, …, Clynes M
Clin Chim Acta. 2015 Feb 20;441:133-41.
http://dx.doi.org:/10.1016/j.cca.2014.12.005.

Highlights

  • Identification of a number of significant proteins and metabolites in CRC patients
  • 14-3-3 proteins, serotonin, gamma enolase and pyruvate kinase all significant
  • Intense staining for 14-3-3 epsilon in tissue specimens from CRC patients
  • Tissue 14-3-3 epsilon levels concordant with abundance in the circulation
  • Biomolecules provide insight into the biology associated with tumor development

Background: Colorectal cancer (CRC), a heterogeneous disease that is common in both men and women, continues to be one of the predominant cancers worldwide. Lifestyle, diet, environmental factors and gene defects all contribute towards CRC development risk. Therefore, the identification of novel biomarkers to aid in the management of CRC is crucial. The aim of the present study was to identify candidate biomarkers for CRC, and to develop a better understanding of their role in tumorogenesis. Methods: In this study, both plasma and tissue samples from patients diagnosed with CRC, together with non-malignant and normal controls were examined using mass spectrometry based proteomics and metabolomics approaches.
Results: It was established that the level of several biomolecules, including serotonin, gamma enolase, pyruvate kinase and members of the 14-3-3 family of proteins, showed statistically significant changes when comparing malignant versus non-malignant patient samples, with a distinct pattern emerging mirroring cancer cell energy production. Conclusion: The diagnosis and management of CRC could be enhanced by the discovery and validation of new candidate biomarkers, as found in this study, aimed at facilitating early detection and/or patient stratification together with providing information on the complex behavior of cancer cells.

Table 2 – List of proteins found to show statistically significant differences between control (n=10) and CRC (n=16; 8 stage III/8 stage IV) patient plasma samples fractionated using Proteominer beads. Information provided in the table includes accession number, discovery platform used, protein description, the number of unique peptides for quantitation, a mascot score for protein identification (confidence number), ANOVA p-values(≥0.05), fold change in protein abundance (≥2-fold) and highest/lowest mean change.

Table 3 – List of metabolites found to show statistically significant differences between control (n=8) and CRC (n=16; 8 stage III/8 stage IV) patient plasma samples. Included in the table is the Human Metabolome Database (HMDB) entry, platform used to analyse the biochemicals, biochemical name, ANOVA p-values (≥0.05), fold-change and highest/lowest mean change.

Fig.1. Box and whisker plots for: (A) M2-PK, (B) gamma enolase, (C) 14-3-3 (pan) and (D) serotonin. ELISA analysisofM2-PK, gamma enolase, serotonin and 14-3-3 (pan) in plasma samples from control (n = 20), polyps (n = 10), adenoma (n = 10), stage I/II CRC (n= 20) and stage III/IV (n= 20)patients. The figures show statistically significant p-value for various comparisons between the different sample groups. This ELISA measurement for 14-3-3 detects all known isoforms of mammalian 14-3-3 proteins (β/α, γ, ε, η, ζ/δ, θ/τ and σ).

Role of lipid peroxidation derived 4-hydroxynonenal (4-HNE) in cancer- Focusing on mitochondria
Huiqin Zhonga, Huiyong Yin
Redox Biol Apr 2015; 4: 193–199

Oxidative stress-induced lipid peroxidation has been associated with human physiology and diseases including cancer. Overwhelming data suggest that reactive lipid mediators generated from this process, such as 4-hydroxynonenal (4-HNE), are biomarkers for oxidative stress and important players for mediating a number of signaling pathways. The biological effects of 4-HNE are primarily due to covalent modification of important biomolecules including proteins, DNA, and phospholipids containing amino group. In this review, we summarize recent progress on the role of 4-HNE in pathogenesis of cancer and focus on the involvement of mitochondria: generation of 4-HNE from oxidation of mitochondria-specific phospholipid cardiolipin; covalent modification of mitochondrial proteins, lipids, and DNA; potential therapeutic strategies for targeting mitochondrial ROS generation, lipid peroxidation, and 4-HNE.

Reactive oxygen species (ROS), such as superoxide anion, hydrogen peroxide, hydroxyl radicals, singlet oxygen, and lipid peroxyl radicals, are ubiquitous and considered as byproducts of aerobic life [1]. Most of these chemically reactive molecules are short-lived and react with surrounding molecules at the site of formation while some of the more stable molecules diffuse and cause damages far away from their sites of generation. Overproduction of these ROS, termed oxidative stress, may provoke oxidation of polyunsaturated fatty acids (PUFAs) in cellular membranes through free radical chain reactions and form lipid hydroperoxides as primary products [2]; some of these primary oxidation products may decompose and lead to the formation of reactive lipid electrophiles. Among these lipid peroxidation (LPO) products, 4-hydroxy-2-nonenals (4-HNE) represents one of the most bioactive and well-studied lipid alkenals [3]. 4-HNE can modulate a number of signaling processes mainly through forming covalent adducts with nucleophilic functional groups in proteins, nucleic acids, and membrane lipids. These properties have been extensively summarized in some excellent reviews [4], [5], [6], [7], [8], [9] and [10].

Conclusions

Lipid peroxidation-derived 4-HNE is a prototypical reactive lipid electrophile that readily forms covalent adducts with nucleophilic functional groups in macromolecule such as proteins, DNA, and lipids (Fig. 3). A body of work have shown that generation of 4-HNE macromolecule adducts plays important pathological roles in cancer through interactions with mitochondria. First of all, mitochondria are one of the most important cellular sites of 4-HNE production, presumably from oxidation of abundant PUFA-containing lipids, such as L4CL. Emerging evidence suggest that this process play a critical role in apoptosis. Secondly, in response to the toxicity of 4-HNE, mitochondria have developed a number of defense mechanisms to convert 4-HNE to less reactive chemical species and minimize its toxic effects. Thirdly, 4-HNE macromolecule adducts in mitochondria are involved in the cancer initiation and progression by modulating mitochondrial function and metabolic reprogramming. 4-HNE protein adducts have been widely studied but the mtDNA modification by lipid electrophiles has yet to emerge. The biological consequence of PE modification remains to be defined, especially in the context of cancer. Last but not the least, manipulation of mitochondrial ROS generation, lipid peroxidation, and production of lipid electrophiles may be a viable approach for cancer prevention and treatment.

K.J. Davies. Oxidative stress, antioxidant defenses, and damage removal, repair, and replacement systems. IUBMB Life, 50 (4–5) (2000): 279–289. http://dx.doi.org/10.1080/713803728.1132732

Shoeb, N.H. Ansari, S.K. Srivastava, K.V. Ramana. 4-hydroxynonenal in the pathogenesis and progression of human diseases. Current Medicinal Chemistry, 21 (2) (2014):230–237 http://dx.doi.org/10.2174/09298673113209990181 23848536

J.D. West, L.J. Marnett. Endogenous reactive intermediates as modulators of cell signaling and cell death. Chemical Research in Toxicology, 19 (2)(2006): 173–194 http://dx.doi.org/10.1021/tx050321u.16485894

Barrera, S. Pizzimenti,…, A. Lepore, et al. Role of 4-hydroxynonenal-protein adducts in human diseases. Antioxidants & Redox Signaling (2014) http://dx.doi.org/10.1089/ars.2014.6166 25365742

J.R. Roede, D.P. Jones. Reactive species and mitochondrial dysfunction: mechanistic significance of 4-hydroxynonenal. Environmental and Molecular Mutagenesis, 51 (5) (2010):380–390 http://dx.doi.org/10.1002/em.20553 20544880

Guéraud, M. Atalay, N. Bresgen, …, I. Jouanin, W. Siems, K. Uchida. Chemistry and biochemistry of lipid peroxidation products. Free Radical Research, 44 (10) (2010): 1098–1124 http://dx.doi.org/10.3109/10715762.2010.498477.20836659

Z.H. Chen, E. Niki. 4-hydroxynonenal (4-HNE) has been widely accepted as an inducer of oxidative stress. Is this the whole truth about it or can 4-HNE also exert protective effects? IUBMB Life, 58 (5–6) (2006): 372–373. http://dx.doi.org/10.1080/15216540600686896 16754333

Aldini, M. Carini, K.-J. Yeum, G. Vistoli. Novel molecular approaches for improving enzymatic and nonenzymatic detoxification of 4-hydroxynonenal: toward the discovery of a novel class of bioactive compounds. Free Radical Biology and Medicine, 69 (0) (2014): 145–156 http://dx.doi.org/10.1016/j.freeradbiomed.2014.01.017 24456906

Fig. 2.   Catabolism of 4-HNE in mitochondria. ROS induced lipid peroxidation in IMM and OMM (outer membrane of mitochondria) leads to 4-HNE formation. In matrix, 4-HNE conjugation with GSH produces glutathionyl-HNE (GS-HNE); this process occurs spontaneously or can be catalyzed by GSTs. 4-HNE is reduced to 1,4-dihydroxy-2-nonene (DHN) catalyzed ADH or AKRs. ALDH2 catalyzes the oxidation of 4-HNE to form 4-hydroxy-2-nonenoic acid (HNA).

Role of 4-hydroxynonenal in cancer focusing on mitochondria

Role of 4-hydroxynonenal in cancer focusing on mitochondria

http://ars.els-cdn.com/content/image/1-s2.0-S2213231714001359-gr2.jpg

Role of 4-hydroxynonenal in cancer focusing on mitochondria

http://ars.els-cdn.com/content/image/1-s2.0-S2213231714001359-gr3.jpg

Fig. 3. A schematic view of 4-HNE macromolecule adducts in cancer cell. 4-HNE macromolecule adducts are involved in cancer initiation, progression, metabolic reprogramming, and cell death. 4-HNE (depicted as a zigzag line) is produced through ROS-induced lipid peroxidation of mitochondrial and plasma membranes. Biological consequences of 4-HNE adduction:

  1. reducing membrane integrity;
  2. affecting protein function in cytosol;
  3. causing nuclear and mitochondrial DNA damage;
  4. inhibiting ETC activity;
  5. activating UCPs activity;
  6. reducing TCA activity;
  7. inhibiting ALDH2 activity.

DNA methylation paradigm shift: 15-lipoxygenase-1 upregulation in prostatic intraepithelial neoplasia and prostate cancer by atypical promoter hypermethylation.
Kelavkar UP1, Harya NS, … , Chandran U, Dhir R, O’Keefe DS.
Prostaglandins Other Lipid Mediat. 2007 Jan; 82(1-4):185-97

Fifteen (15)-lipoxygenase type 1 (15-LO-1, ALOX15), a highly regulated, tissue- and cell-type-specific lipid-peroxidating enzyme has several functions ranging from physiological membrane remodeling, pathogenesis of atherosclerosis, inflammation and carcinogenesis. Several of our findings support a possible role for 15-LO-1 in prostate cancer (PCa) tumorigenesis. In the present study, we identified a CpG island in the 15-LO-1 promoter and demonstrate that the methylation status of a specific CpG within this island region is associated with transcriptional activation or repression of the 15-LO-1 gene. High levels of 15-LO-1 expression was exclusively correlated with one of the CpG dinucleotides within the 15-LO-1 promoter in all examined PCa cell-lines expressing 15-LO-1 mRNA. We examined the methylation status of this specific CpG in microdissected high grade prostatic intraepithelial neoplasia (HGPIN), PCa, metastatic human prostate tissues, normal prostate cell lines and human donor (normal) prostates. Methylation of this CpG correlated with HGPIN, PCa and metastatic human prostate tissues, while this CpG was unmethylated in all of the normal prostate cell lines and human donor (normal) prostates that either did not display or had minimal basal 15-LO-1 expression. Immunohistochemistry for 15-LO-1 was performed in prostates from PCa patients with Gleason scores 6, 7 [(4+3) and (3+4)], >7 with metastasis, (8-10) and 5 normal (donor) individual males. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was used to detect 15-LO-1 in PrEC, RWPE-1, BPH-1, DU-145, LAPC-4, LNCaP, MDAPCa2b and PC-3 cell lines. The specific methylated CpG dinucleotide within the CpG island of the 15-LO-1 promoter was identified by bisulfite sequencing from these cell lines. The methylation status was determined by COBRA analyses of one specific CpG dinucleotide within the 15-LO-1 promoter in these cell lines and in prostates from patients and normal individuals. Fifteen-LO-1, GSTPi and beta-actin mRNA expression in BPH-1, LNCaP and MDAPCa2b cell lines with or without 5-aza-2′-deoxycytidine (5-aza-dC) and trichostatin-A (TSA) treatment were investigated by qRT-PCR. Complete or partial methylation of 15-LO-1 promoter was observed in all PCa patients but the normal donor prostates showed significantly less or no methylation. Exposure of LNCAP and MDAPCa2b cell lines to 5-aza-dC and TSA resulted in the downregulation of 15-LO-1 gene expression. Our results demonstrate that 15-LO-1 promoter methylation is frequently present in PCa patients and identify a new role for epigenetic phenomenon in PCa wherein hypermethylation of the 15-LO-1 promoter leads to the upregulation of 15-LO-1 expression and enzyme activity contributes to PCa initiation and progression.

Transcriptional regulation of 15-lipoxygenase expression by promoter methylation.
Liu C1, Xu D, Sjöberg J, Forsell P, Björkholm M, Claesson H
Exp Cell Res. 2004 Jul 1; 297(1):61-7.

15-Lipoxygenase type 1 (15-LO), a lipid-peroxidating enzyme implicated in physiological membrane remodeling and the pathogenesis of atherosclerosis, inflammation, and carcinogenesis, is highly regulated and expressed in a tissue- and cell-type-specific fashion. It is known that interleukins (IL) 4 and 13 play important roles in transactivating the 15-LO gene. However, the fact that they only exert such effects on a few types of cells suggests additional mechanism(s) for the profile control of 15-LO expression. In the present study, we demonstrate that hyper- and hypomethylation of CpG islands in the 15-LO promoter region is intimately associated with the transcriptional repression and activation of the 15-LO gene, respectively. The 15-LO promoter was exclusively methylated in all examined cells incapable of expressing 15-LO (certain solid tumor and human lymphoma cell lines and human T lymphocytes) while unmethylated in 15-LO-competent cells (the human airway epithelial cell line A549 and human monocytes) where 15-LO expression is IL4-inducible. Inhibition of DNA methylation in L428 lymphoma cells restores IL4 inducibility to 15-LO expression. Consistent with this, the unmethylated 15-LO promoter reporter construct exhibited threefold higher activity in A549 cells compared to its methylated counterpart. Taken together, demethylation of the 15-LO promoter is a prerequisite for the gene transactivation, which contributes to tissue- and cell-type-specific regulation of 15-LO expression.

mechanism of the lipoxygenase reaction

Radical mechanism of the lipoxygenase reaction pattabhiraman

Radical mechanism of the lipoxygenase reaction pattabhiraman

http://edoc.hu-berlin.de/dissertationen/pattabhiraman-shankaranarayanan-2003-11-03/HTML/pattabhiraman_html_705b7fbd.png

Position determinants of lipoxygenase reaction pattabhiraman

Position determinants of lipoxygenase reaction pattabhiraman

http://edoc.hu-berlin.de/dissertationen/pattabhiraman-shankaranarayanan-2003-11-03/HTML/pattabhiraman_html_m3642741b.jpg

Position determinants of lipoxygenase reaction

This suggests that the space inside the active site cavity plays an important role in the positional specificity (Borngräber et al., 1999). The reverse process on 12-LOX works equally well (Suzuki et al., 1994; Watanabe and Haeggstrom, 1993). However, conversion to 5-LOX by mutagenesis has not been successful. The positional determinant residues on 15-LOX were mutated to those of 5-LOX but the enzyme was inactive (Sloane et al., 1990). 15-LOX possess the ability to oxygenate 15-HpETE to form 5, 15-diHpETE. Methylation of carboxy end of the substrate increased the activity significantly. This phenomenon was hypothesised to be due to an inverse orientation of the substrate at the active site. In this case the caroboxy end may slide into the cavity as suggested by experiments with modified [page 6↓]substrates and site directed mutagenesis (Schwarz et al., 1998; Walther et al., 2001). Thus, the determinant of positional specificity is not only the volume but also the orientation of the substrate in the active site.

The N-terminal domain of the enzyme does not play a major role in the dioxygenation reaction of 12/15 lipoxygenase. N-terminal domain truncations did not impair the lipoxygenase activity. The ability of the enzyme to bind to membranes, however, is impaired in the mutants (point and truncations) of the N-ternimal domain without significant alterations to the catalytic activity (Walther et al., 2002). Mutation to Trp 181, which is localised in the catalytic domain, also impaired membrane binding function. This suggests that the C-terminal domain is responsible for the catalytic activity and a concerted action of N-terminal and C-terminal domain was necessary for effective membrane binding.

Metabolomic studies

New paradigms for metabolic modeling of human cells

Mardinoglu A, Nielsen J
Curr Opin Biotechnol. 2015 Jan 2; 34C:91-97.
http://dx.doi.org:/10.1016/j.copbio.2014

integration of genetic and biochemical knowledge

integration of genetic and biochemical knowledge

http://ars.els-cdn.com/content/image/1-s2.0-S0958166914002286-fx1.jpg

Highlights

  • We presented the timeline of generation and evaluation of global reconstructions of human metabolism.
  • We reviewed the generation of the context specific GEMs through the use of human generic GEMs.
  • We discussed the generation of multi-tissue GEMs in the context of whole-body metabolism.
  • We finally discussed the integration of GEMs with other biological networks.

Abnormalities in cellular functions are associated with the progression of human diseases, often resulting in metabolic reprogramming. GEnome-scale metabolic Models (GEMs) have enabled studying global metabolic reprogramming in connection with disease development in a systematic manner. Here we review recent work on reconstruction of GEMs for human cell/tissue types and cancer, and the use of GEMs for identification of metabolic changes occurring in response to disease development. We further discuss how GEMs can be used for the development of efficient therapeutic strategies. Finally, challenges in integration of cell/tissue models for simulation of whole body functions as well as integration of GEMs with other biological networks for generating complete cell/tissue models are presented.

http://ars.els-cdn.com/content/image/1-s2.0-S0958166914002286-gr2.sml

Inter- and intra-tumor profiling of multi-regional colon cancer and metastasis
Kogita A, Yoshioka Y, …, Nakai T, Okuno K, Nishio K
Biochem Biophys Res Commun. 2015 Feb 27; 458(1):52-6.
http://dx.doi.org:/10.1016/j.bbrc.2015.01.064

Highlights

  • Mutation profiling of tumors of multi-regional colon cancers using targeted sequencing.
  • Formalin-fixed paraffin embedded samples were available for next-generation sequencing.
  • Different clones existed in primary tumors and metastatic tumors.
  • Muti-clonalities between intra- and inter-tumors.

Intra- and inter-tumor heterogeneity may hinder personalized molecular-target treatment that depends on the somatic mutation profiles. We performed mutation profiling of formalin-fixed paraffin embedded tumors of multi-regional colon cancer and characterized the consequences of intra- and inter-tumor heterogeneity and metastasis using targeted re-sequencing. We performed targeted re-sequencing on multiple spatially separated samples obtained from multi-regional primary colon carcinoma and associated metastatic sites in two patients using next-generation sequencing. In Patient 1 with four primary tumors (P1-1, P1-2, P1-3, and P1-4) and one liver metastasis (H1), mutually exclusive pattern of mutations was observed in four primary tumors. Mutations in primary tumors were identified in three regions; KARS (G13D) and APC (R876*) in P1-2, TP53 (A161S) in P1-3, and KRAS (G12D), PIK3CA (Q546R), and ERBB4 (T272A) in P1-4. Similar combinatorial mutations were observed between P1-4 and H1. The ERBB4 (T272A) mutation observed in P1-4, however, disappeared in H1. In Patient 2 with two primary tumors (P2-1 and P2-2) and one liver metastasis (H2), mutually exclusive pattern of mutations were observed in two primary tumors. We identified mutations; KRAS (G12V), SMAD4 (N129K, R445*, and G508D), TP53 (R175H), and FGFR3 (R805W) in P2-1, and NRAS (Q61K) and FBXW7 (R425C) in P2-2. Similar combinatorial mutations were observed between P2-1 and H2. The SMAD4 (N129K and G508D) mutations observed in P2-1, however, were nor detected in H2. These results suggested that different clones existed in primary tumors and metastatic tumor in Patient 1 and 2 likely originated from P1-4 and P2-1, respectively. In conclusion, we detected the muti-clonalities between intra- and inter-tumors based on mutational profiling in multi-regional colon cancer using next-generation sequencing. Primary region from which metastasis originated could be speculated by mutation profile. Characterization of inter- and inter-tumor heterogeneity can lead to underestimation of the tumor genomics landscape and treatment strategy of personal medicine.

Fig.1. Treatment timelines for the two patients. A) Patient 1 (a 55-year-old man) had multifocal sigmoid colon cancers, and all of which were surgically resected in their entirety (P1-1, P1-2, P1-3, and P1-4). The patient received adjuvant chemotherapy (8 courses of XELOX). Eight months later, a single liver metastasis (H1) was detected, and the patients received neoadjuvant treatment of XELOX plus bevacizumab. Thereafter, he received a partial hepatectomy. B) Patient 2 (an 84-year-old woman) had cecal and sigmoid colon cancers (P2-1 and P2-2, respectively) with a single liver metastasis (H2). She received a subtotal colectomy and subsegmental hepatectomy.

Fig. 2. Schematic representation of intra-tumor heterogeneity in two patients. A) In patient 1, primary tumor (P1-4) contains two or more subclones. The clone without the ERBB4 (T272A) mutation created the liver metastasis. B) In patient 2, primary tumor (P2-1) contains two or more subclones. The clone without the SMAD4 (N129K and G508D) mutation created the liver metastasis.

Loss of Raf-1 Kinase Inhibitor Protein Expression Is Associated With Tumor Progression and Metastasis in Colorectal Cancer

Parham MinooInti ZlobecKristi BakerLuigi TornilloLuigi TerraccianoJeremy R. Jass, and Alessandro Lugli
American Journal of Clinical Pathology, 127, 820-827
http://dx.doi.org:/10.1309/5D7MM22DAVGDT1R8(2007)

Raf-1 kinase inhibitor protein (RKIP) is known as a critical down-regulator of the mitogen-activated protein kinase signaling pathway and a potential molecular determinant of malignant metastasis. The aim of this study was to determine the prognostic significance of RKIP expression in colorectal cancer (CRC). Immunohistochemical staining for RKIP was performed on a tissue microarray comprising 1,197 mismatch repair (MMR)-proficient and 141 MMR-deficient CRCs. The association of RKIP with clinicopathologic features was analyzed. Loss of cytoplasmic RKIP was associated with distant metastasis (P = .038), higher N stage (P = .032), vascular invasion (P = .01), and worse survival (P = .001) in the MMR-proficient group. In MMR-deficient CRCs, loss of cytoplasmic RKIP was associated with distant metastasis (P = .043) and independently predicted worse survival (P = .004). Methylation analysis of 28 cases showed that loss of RKIP expression is unlikely to be due to promoter methylation.

Raf-1 kinase inhibitor protein (RKIP) is a ubiquitously expressed and highly conserved protein that belongs to the phosphatidylethanolamine-binding protein family.1,2 RKIP is present in the cytoplasm and at the cell membrane3 and appears to have multiple biologic functions that implicate spermatogenesis, neural development, cardiac function, and membrane biogenesis.4-6 RKIP has also been shown to have a role in the regulation of multiple signaling pathways. Originally, RKIP was identified as a phospholipid-binding protein and, subsequently, as an interacting partner of Raf-1 kinase that blocks mitogen-activated protein kinase (MAPK) initiated by Raf-1.7 Initial studies showed that RKIP achieves this role by competitive interference with the binding of MEK to Raf-1.8 Recently, RKIP was shown to inhibit activation of Raf-1 by blocking phosphorylation of Raf-1 by p21-activated kinase and Src family kinases.9 It has also been suggested that RKIP could be involved in regulation of apoptosis by modulating the NF-κB pathway10 and in regulation of the spindle checkpoint via Aurora B.11 RKIP has also been implicated in tumor biology. In breast and prostate cancers, ectopic expression of RKIP sensitized cells to chemotherapeutic-induced apoptosis, and reduced expression of RKIP led to resistance to chemotherapy.12 A link between RKIP and cancer was first established in prostate cancer, with RKIP showing reduced expression in prostate cancer cells and the lowest expression levels in metastatic cells, suggesting that RKIP expression is inversely associated with the invasiveness of prostate cancer.13 Restoration of RKIP expression in metastatic prostate cancer cells inhibited invasiveness of the cells in vitro and in vivo in spontaneous lung metastasis but not the growth of the primary tumor in a murine model.13

Clinicopathologic Parameters The clinicopathologic data for 1,420 patients included T stage (T1, T2, T3, and T4), N stage (N0, N1, and N2), tumor grade (G1, G2, and G3), vascular invasion (presence or absence), and survival. The distribution of these features has been described previously.18-20 For 478 patients, information on local recurrence and distant metastasis was also available.

Methylation of RKIP Methylation of RKIP promoter was examined by methylation-specific polymerase chain reaction (PCR) using an AmpliTaq Gold kit (Roche, Branchburg, NJ) as described previously.25 The primers for amplification of the unmethylated sequence were 5′-TTTAGTGATATTTTTTGAGATATGA-3′ and 3′-CACTCCCTAACCTCTAATTAACCAA-5′ and for the methylated reaction were 5′-TTTAGCGATATTTTTTGAGATACGA-3′ and 3′-GCTCCCTAACCTCTAATTAACCG- 5′. The conditions for amplification were 10 minutes at 95°C followed by 39 cycles of denaturing at 95°C for 30 seconds, annealing at 52°C for 30 seconds, and 30 seconds of extension at 72°C. The PCR products were subjected to electrophoresis on 8% acrylamide gels and visualized by SYBR gold nucleic acid gel stain (Molecular Probes, Eugene, OR). CpGenome Universal Methylated DNA (Chemicon, Temecula, CA) was used as a positive control sample for methylation. Randomization of MMR-Proficient CRCs The 1,197 MMR-proficient CRCs were randomly assigned into 2 groups consisting of 599 (group 1) and 598 (group 2) cases and matched for sex, tumor location, T stage, N stage, tumor grade, vascular invasion, and survival ❚Table 1❚. Immunohistochemical cutoff scores for RKIP expression were determined for group 1, and the association of RKIP expression and T stage, N stage, tumor grade, vascular invasion, local recurrence, distant metastasis, and 10-year survival were studied in group 2.

❚Table 1❚ Characteristics of the Randomized Mismatch Repair–Proficient Subgroups of Colorectal Cancer Cases*

Variable p
Group Gp 1 (n=599) Gp 2 (n=598) 0.235
Sex M F M F
288 (48.3) 308

(51.7)

287

(48.2)

308

(51.8)

0.82
Tumor location Right-sided 417 (70.6) 417 (71.2) Left-sided 174 (29.4) 169 (28.8)
T1 T2 T3 T4
T stage 25 (4.3) 35 (6.0) 92(15.8) 97(16.7) 375(64.2)
365(62.8)
92(15.8)
84(14.5)
0.514
N stage N0 N1 N2
289(50.7) 154(27.0) 154(26.9) 127(22.3) 120(21.0) 0.847
Tumor grade G1 G2 G3
14 (2.4) 13 (2.2) 503(86.7) 507(86.7) 63 (10.9) 65 (11.1) 0.969
Vascular invasion Presence 412 (70.9) 422 (72.1) Absence 169 (29.1) 163 (27.9) 0.643
Median survival, mo 68.0 (57.0-91.0) 76.0 (62.0-88.0) 0.59

(95% confidence interval) * Data are given as number (percentage) unless otherwise indicated.
Data were not available for all cases; percentages are based on the number of cases available for the variable, not the total number of cases in the group. Cases were assigned into groups matched for all variables listed. †
The χ2 test was used for sex, tumor location, T stage, N stage, tumor grade, and vascular invasion and log-rank test for survival analysis. P > .05 indicates that there is no difference between groups 1 and 2.
Breast and prostate cancer: more similar than different

Gail P. Risbridger1, Ian D. Davis2, Stephen N. Birrell3 & Wayne D. Tilley3
Nature Reviews Cancer 10, 205-212 (March 2010)
http://dx.doi.org:/10.1038/nrc2795

Breast cancer and prostate cancer are the two most common invasive cancers in women and men, respectively. Although these cancers arise in organs that are different in terms of anatomy and physiological function both organs require gonadal steroids for their development, and tumours that arise from them are typically hormone-dependent and have remarkable underlying biological similarities. Many of the recent advances in understanding the pathophysiology of breast and prostate cancers have paved the way for new treatment strategies. In this Opinion article we discuss some key issues common to breast and prostate cancer and how new insights into these cancers could improve patient outcomes.

Emerging field of metabolomics. Big promise for cancer biomarker identification and drug discovery
Patel S, Ahmed S.
J Pharm Biomed Anal. 2015 Mar 25; 107C:63-74.
http://DX.doi.ORG:/10.1016/j.jpba.2014.12.020

Highlights

  • Mass spectrometry, nuclear magnetic resonance and chemometrics have enabled cancer biomarker discovery.
  • Metabolomics can non-invasively identify biomarkers for diagnosis, prognosis and treatment of cancer.
  • All major types of cancers and their biomarkers discovered by metabolomics have been discussed.
  • This review sheds light on the pitfalls and potentials of metabolomics with respect to oncology.

Most cancers are lethal and metabolic alterations are considered a hallmark of this deadly disease. Genomics and proteomics have contributed vastly to understand cancer biology. Still there are missing links as downstream to them molecular divergence occurs. Metabolomics, the omic science that furnishes a dynamic portrait of metabolic profile is expected to bridge these gaps and boost cancer research. Metabolites being the end products are more stable than mRNAs or proteins. Previous studies have shown the efficacy of metabolomics in identifying biomarkers associated with diagnosis, prognosis and treatment of cancer. Metabolites are highly informative about the functional status of the biological system, owing to their proximity to organismal phenotypes. Scores of publications have reported about high-throughput data generation by cutting-edge analytic platforms (mass spectrometry and nuclear magnetic resonance). Further sophisticated statistical softwares (chemometrics) have enabled meaningful information extraction from the metabolomic data. Metabolomics studies have demonstrated the perturbation in glycolysis, tricarboxylic acid cycle, choline and fatty acid metabolism as traits of cancer cells. This review discusses the latest progress in this field, the future trends and the deficiencies to be surmounted for optimally implementation in oncology. The authors scoured through the most recent, high-impact papers archived in Pubmed, ScienceDirect, Wiley and Springer databases to compile this review to pique the interest of researchers towards cancer metabolomics.

Table.  Novel Cancer Markers Identified by Metabolomics

Quantitative analysis of acetyl-CoA production in hypoxic cancer cells reveals substantial contribution from acetate
Jurre J Kamphorst, Michelle K Chung, Jing Fan and Joshua D Rabinowitz
Cancer & Metabolism 2014, 2:23
http://dx.doi.org:/10.1186/2049-3002-2-23

Background: Cell growth requires fatty acids for membrane synthesis. Fatty acids are assembled from 2-carbon units in the form of acetyl-CoA (AcCoA). In nutrient and oxygen replete conditions, acetyl-CoA is predominantly derived from glucose. In hypoxia, however, flux from glucose to acetyl-CoA decreases, and the fractional contribution of glutamine to acetyl-CoA increases. The significance of other acetyl-CoA sources, however, has not been rigorously evaluated. Here we investigate quantitatively, using 13C-tracers and mass spectrometry, the sources of acetyl-CoA in hypoxia. Results: In normoxic conditions, cultured cells produced more than 90% of acetyl-CoA from glucose and glutamine-derived carbon. In hypoxic cells, this contribution dropped, ranging across cell lines from 50% to 80%. Thus, under hypoxia, one or more additional substrates significantly contribute to acetyl-CoA production. 13C-tracer experiments revealed that neither amino acids nor fatty acids are the primary source of this acetyl-CoA. Instead, the main additional source is acetate. A large contribution from acetate occurs despite it being present in the medium at a low concentration (50–500 μM). Conclusions: Acetate is an important source of acetyl-CoA in hypoxia. Inhibition of acetate metabolism may impair tumor growth.

Cancer cells have genetic mutations that drive proliferation. Such proliferation creates a continuous demand for structural components to produce daughter cells [13]. This includes demand for fatty acids for lipid membranes. Cancer cells can obtain fatty acids both through uptake from extracellular sources and through de novo synthesis, with the latter as a major route by which non-essential fatty acids are acquired in many cancer types [4,5].

The first fatty acid to be produced by de novo fatty acid synthesis is palmitate. The enzyme fatty acid synthase (FAS) makes palmitate by catalyzing the ligation and reduction of 8-acetyl (2-carbon) units donated by cytosolic acetyl-CoA. This 16-carbon fatty acid palmitate is then incorporated into structural lipids or subjected to additional elongation (again using acetyl-CoA) and desaturation reactions to produce the diversity of fatty acids required by the cell.

Acetyl-CoA sits at the interface between central carbon and fatty acid metabolism. In well-oxygenated conditions with abundant nutrients, its 2-carbon acetyl unit is largely produced from glucose. First, pyruvate dehydrogenase produces acetyl-CoA from glucose-derived pyruvate in the mitochondrion, followed by ligation of the acetyl group to oxaloacetate to produce citrate. Citrate is then transported into the cytosol and cytosolic acetyl-CoA produced by ATP citrate lyase.

In hypoxia, flux from glucose to acetyl-CoA is impaired. Low oxygen leads to the stabilization of the HIF1 complex, blocking pyruvate dehydrogenase (PDH) activity via activation of HIF1-responsive pyruvate dehydrogenase kinase 1 (PDK1) [6,7]. As a result, the glucose-derived carbon is shunted towards lactate rather than being used for generating acetyl-CoA, affecting carbon availability for fatty acid synthesis.

To understand how proliferating cells rearrange metabolism to maintain fatty acid synthesis under hypoxia, multiple studies focused on the role of glutamine as an alternative carbon donor[810]. The observation that citrate M+5 labeling from U-13C-glutamine increased in hypoxia led to the hypothesis that reductive carboxylation of glutamine-derived α-ketoglutarate enables hypoxic cells to maintain citrate and acetyl-CoA production. As was noted later, though, dropping citrate levels in hypoxic cells make the α-ketoglutarate to citrate conversion more reversible and an alternative explanation of the extensive citrate and fatty acid labeling from glutamine in hypoxia is isotope exchange without a net reductive flux [11]. Instead, we and others found that hypoxic cells can at least in part bypass the need for acetyl-CoA for fatty acid synthesis by scavenging serum fatty acids [12,13].

In addition to increased serum fatty acid scavenging, we observed a large fraction of fatty acid carbon (20%–50% depending on the cell line) in hypoxic cells not coming from either glucose or glutamine. Here, we used 13C-tracers and mass spectrometry to quantify the contribution from various carbon sources to acetyl-CoA and hence identify this unknown source. We found only a minor contribution of non-glutamine amino acids and of fatty acids to acetyl-CoA in hypoxia. Instead, acetate is the major previously unaccounted for carbon donor. Thus, acetate assimilation is a route by which hypoxic cells can maintain lipogenesis and thus proliferation.

Figure 1. Percentage 13C-labeling of cytosolic acetyl-CoA can be quantified from palmitate labeling. (A) Increasing 13C2-acetyl-CoA labeling shifts palmitate labeling pattern to the right. 13C2-acetyl-CoA labeling can be quantified by determining a best fit between observed palmitate labeling and computed binomial distributions (shown on right-hand side) from varying fractions of acetyl-CoA (AcCoA) labeling. (B) Steady-state palmitate labeling from U-13C-glucose and U-13C-glutamine in MDA-MB-468 cells. (C) Percentage acetyl-CoA production from glucose and glutamine. For (B) and (C), data are means ± SD of n = 3.

Fraction palmitate M + x = (16/x)(p)x (1−p)(16−x)

We applied this approach to MDA-MB-468 cells grown in medium containing U-13C-glucose and U-13C-glutamine. The resulting steady-state palmitate labeling patterns showed multiple heavily 13C-labeled forms as well as a remaining unlabeled M0 peak (Figure 1B). The M0-labeled form results from scavenging of unlabeled serum fatty acids and can be disregarded for the purpose of determining AcCoA labeling. From the remaining labeling distribution, we calculated 87% AcCoA labeling from glucose and 6% from glutamine, with 93% collectively accounted for by these two major carbon sources (Additional file 1: Figure S1). Similar results were also obtained for HeLa and A549 cells (Figure 1C)

Figure 2. Acetyl-CoA labeling from 13C-glucose and 13C-glutamine decreases in hypoxia. (A) Steady-state palmitate labeling from U-13C-glucose and U-13C-glutamine in normoxic and hypoxic (1% O2) conditions. (B) Percentage acetyl-CoA production from glucose and glutamine in hypoxia. (C) One or more additional carbon donors contribute substantially to acetyl-CoA production in hypoxia. Abbreviations: Gluc, glucose; Gln, glutamine. Data are means ± SD of n = 3.

Figure 3.  Amino acids (other than glutamine) and fatty acids are not major sources of cytosolic acetyl-CoA in hypoxia. (A) Palmitate labeling in hypoxic (1% O2) MDA-MB-468 cells, grown for 48 h in medium where branched chain amino acids plus lysine and threonine were substituted with their respective U-13C-labeled forms. (B) Same conditions, except that glucose and glutamine only or glucose and all amino acids, were substituted with the U-13C-labeled forms. (C) Palmitate labeling in hypoxic (1% O2) MDA-MB-468 cells, grown in medium supplemented with 20 μM U-13C-palmitate for 48 h. Data are means ± SD of n = 3.

Acetate is the main additional AcCoA carbon source in hypoxia

We next investigated if hypoxic cells could activate acetate to AcCoA. Although we used dialyzed serum in our experiments and acetate is not a component of DMEM, we contemplated the possibility that trace levels could still be present or that acetate is produced as a catabolic intermediate from other sources (for example from protein de-acetylation). We cultured MDA-MB-468 cells in 1% O2 in DMEM containing U-13C-glucose and U-13C-glutamine and added increasing amounts of U-13C-acetate (Figure 4A). AcCoA labeling rose considerably with increasing U-13C-acetate concentrations, from approximately 50% to 86% with 500 μM U-13C-acetate. No significant increase in labeling of AcCoA was observed in normoxic cells following incubation with U-13C-acetate. Thus, acetate selectively contributes to AcCoA in hypoxia.

Figure 4.  The main additional AcCoA source in hypoxia is acetate. (A) Percentage 13C2-acetyl-CoA labeling quantified from palmitate labeling in hypoxic (1% O2) and normoxic MDA-MB-468 cells grown in medium with U-13C-glucose and U-13C-glutamine and additionally supplemented with indicated concentrations of U-13C-acetate. (B) Acetate concentrations in fresh 10% DFBS, DMEM, and DMEM with 10% DFBS. (C) Percentage 13C2-acetyl-CoA labeling for hypoxic (1% O2) HeLa and A549 cells. For (A) and (C), data are means ± SD of n ≥ 2. For (B), data are means ± SEM of n = 3.

Tumors require a constant supply of fatty acids to sustain cellular replication. It is thought that most cancers derive a considerable fraction of the non-essential fatty acids through de novo synthesis. This requires AcCoA with its 2-carbon acetyl group acting as the carbon donor. In nutrient replete and well-oxygenated conditions, AcCoA is predominantly made from glucose. However, tumor cells often experience hypoxia, causing limited entry of glucose-carbon into the TCA cycle. This in turn affects AcCoA production, and it has been proposed that hypoxic cells can compensate by increasing AcCoA production from glutamine-derived carbon in a pathway involving reductive carboxylation of α-ketoglutarate [810].

Irrespective of the precise net contribution of acetate in hypoxia, a remarkable aspect is that a significant contribution occurs based only on contaminating acetate (~300 μM) in the culturing medium. This is considerably less than glucose (25 mM) or glutamine (4 mM). Acetate concentrations in the plasma of human subjects have been reported in the range of 50 to 650 μM [2225], and therefore, significant acetate conversion to AcCoA may occur in human tumors. This is supported by clinical observations that 11C-acetate PET can be used to image tumors, in particular those where conventional FDG-PET typically fails [26]. Our results indicate that 11C-acetate PET could be particularly important in notoriously hypoxic tumors, such as pancreatic cancer. Preliminary results provide evidence in this direction [27].

Finally, as our measurements of fatty acid labeling reflect specifically cytosolic AcCoA, it is likely that the cytosolic acetyl-CoA synthetase ACSS2 plays an important role in the observed acetate assimilation. Accordingly, inhibition of ACSS2 merits investigation as a potential therapeutic approach.

In hypoxic cultured cancer cells, one-quarter to one-half of cytosolic acetyl-CoA is not derived from glucose, glutamine, or other amino acids. A major additional acetyl-CoA source is acetate. Low concentrations of acetate (e.g., 50–650 μM) are found in the human plasma and also occur as contaminants in typical tissue culture media. These amounts are avidly incorporated into cellular acetyl-CoA selectively in hypoxia. Thus, 11C-acetate PET imaging may be useful for probing hypoxic tumors or tumor regions. Moreover, inhibiting acetate assimilation by targeting acetyl-CoA synthetases (e.g., ACSS2) may impair tumor growth.

Differential metabolomic analysis of the potential antiproliferative mechanism of olive leaf extract on the JIMT-1 breast cancer cell line
Barrajón-Catalán E, Taamalli A, Quirantes-Piné R, …, Micol V, Zarrouk M
J Pharm Biomed Anal. 2015 Feb; 105:156-62.
http://dx.doi.org:/10.1016/j.jpba.2014.11.048

A new differential metabolomic approach has been developed to identify the phenolic cellular metabolites derived from breast cancer cells treated with a supercritical fluid extracted (SFE) olive leaf extract. The SFE extract was previously shown to have significant antiproliferative activity relative to several other olive leaf extracts examined in the same model. Upon SFE extract incubation of JIMT-1 human breast cancer cells, major metabolites were identified by using HPLC coupled to electrospray ionization quadrupole-time-of-flight mass spectrometry (ESI-Q-TOF-MS). After treatment, diosmetin was the most abundant intracellular metabolite, and it was accompanied by minor quantities of apigenin and luteolin. To identify the putative antiproliferative mechanism, the major metabolites and the complete extract were assayed for cell cycle, MAPK and PI3K proliferation pathways modulation. Incubation with only luteolin showed a significant effect in cell survival. Luteolin induced apoptosis, whereas the whole olive leaf extract incubation led to a significant cell cycle arrest at the G1 phase. The antiproliferative activity of both pure luteolin and olive leaf extract was mediated by the inactivation of the MAPK-proliferation pathway at the extracellular signal-related kinase (ERK1/2). However, the flavone concentration of the olive leaf extract did not fully explain the strong antiproliferative activity of the extract. Therefore, the effects of other compounds in the extract, probably at the membrane level, must be considered. The potential synergistic effects of the extract also deserve further attention. Our differential metabolomics approach identified the putative intracellular metabolites from a botanical extract that have antiproliferative effects, and this metabolomics approach can be expanded to other herbal extracts or pharmacological complex mixtures.

Pancreatic cancer early detection. Expanding higher-risk group with clinical and metabolomics parameters
Shiro Urayama
World J Gastroenterol. 2015 Feb 14; 21(6): 1707–1717.
http://dx.doi.org:/10.3748/wjg.v21.i6.1707

Pancreatic ductal adenocarcinoma (PDAC) is the fourth and fifth leading cause of cancer death for each gender in developed countries. With lack of effective treatment and screening scheme available for the general population, the mortality rate is expected to increase over the next several decades in contrast to the other major malignancies such as lung, breast, prostate and colorectal cancers. Endoscopic ultrasound, with its highest level of detection capacity of smaller pancreatic lesions, is the commonly employed and preferred clinical imaging-based PDAC detection method. Various molecular biomarkers have been investigated for characterization of the disease, but none are shown to be useful or validated for clinical utilization for early detection. As seen from studies of a small subset of familial or genetically high-risk PDAC groups, the higher yield and utility of imaging-based screening methods are demonstrated for these groups. Multiple recent studies on the unique cancer metabolism including PDAC, demonstrate the potential for utility of the metabolites as the discriminant markers for this disease. In order to generate an early PDAC detection screening strategy available for a wider population, we propose to expand the population of higher risk PDAC group with combination clinical and metabolomics parameters.

Core tip: This is a summary of current pancreatic cancer cohort early detection studies and a potential approach being considered for future application. This is an area that requires heightened efforts as lack of effective treatment and screening scheme for wider population is leading this particular disease to be the second lethal cancer by 2030.

Currently, pancreatic ductal adenocarcinoma (PDAC) is the fourth major cause of cancer mortality in the United States[1]. It is predicted that 46420 new cases and 39590 deaths would result from pancreatic cancer in the United States in 2014[2]. Worldwide, there were 277668 new cases and 266029 deaths from this cancer in 2008[3]. In comparison to other major malignancies such as breast, colon, lung and prostate cancers with their respective 89%, 64%, 16%, 99% 5-year survival rate, PDAC at 6% is conspicuously low[2]. For PDAC, the only curative option is surgical resection, which is applicable in only 10%-15% of patients due to the common discovery of late stage at diagnosis[4]. In fact, PDAC is notorious for late stage discovery as evidenced by the low percentage of localized disease at diagnosis, compared to other malignancies: breast (61%), colon (40%), lung (16%), ovarian (19%), prostate (91%), and pancreatic cancer (7%) [5]. With the existing effective screening methods, the decreasing trends of cancer death rate are seen in major malignancies such as breast, prostate and colorectal cancer. In contrast, it is estimated that PDAC is expected to be surfacing as the second leading cause of cancer death by 2030[6].

With the distinct contribution of late-stage discovery and general lack of effective medical therapy, a critical approach in reversing the poor outcome of pancreatic cancer is to develop an early detection scheme for the tumor. In support of this, we see the trend that despite the poor prognosis of the disease, for those who have undergone curative resection with negative margins, the 5-year survival rate is 22% in contrast to 2% for the advanced-stage with distant metastasis[7,8]. An earlier diagnosis with tumor less than 2 cm (T1) is associated with a better 5-year survival of 58% compared to 17% for stage IIB PDAC[9]. Ariyama et al. [10] reported complete survival of 79 patients with less than 1 cm tumors after surgical resection. Furthermore, as a recent report indicates, the estimated time from the transformation to pre-metastatic growths of pancreatic cancer is approximately 15 years[11]; there is a wide potential window of opportunity to apply developing technologies in early detection of this cancer.

Current screening programs have demonstrated that the EUS evaluation can detect premalignant lesions and early cancers in certain small subset of high-risk groups. However, as the overwhelming majority of PDAC cases involve patients who develop the disease sporadically without a recognized genetic abnormality, the application of this modality for PDAC detection screening is very limited for the general adult population.

Select population based approach

Identification of a higher-PDAC-risk group: As the prevalence of PDAC in the general United States population over the age 55 is approximately 68 per 100000, a candidate discriminant test with a specificity of 98% and a sensitivity of 100% would generate 1999 false-positive test results and 68 true-positives[74]. Thus, relying on a single determinant for distinguishing the PDAC early-stage cases from the general population would necessitate a highly accurate test with a specificity of greater than 99%. More practical approach, then, would be to begin with a subset of population with a higher prevalence, and in conjunction with novel surrogate markers to curtail the at-risk subset, we could begin to identify the group with significantly increased PDAC risk for whom the endoscopic/imaging-based screening strategy could be applied.

An initial approach in selection of the screening population is to utilize selective clinical parameters that could be used to curtail the subset of the general population at increased PDAC risk. For instance, based on the epidemiological evidence, such clinical parameters include hyperglycemia or diabetes, which are noted in 50%-80% of pancreatic cancer patients [7579]. Though not encompassing all PDAC patients, this subset includes a much larger proportion of PDAC patients for whom we may select further for screening. Similarly, patients with a history of chronic pancreatitis or obesity are reported to have increased PDAC risk during their lifetime[8085].

With the recent advancement in the technology and resumed interest in the cancer-associated metabolic abnormality [89,90], application of metabolomics in the cancer field has attracted more attention [91]. Cancer-related metabolic reprogramming, Warburg effect, has been known since nearly a century ago in association with various solid tumors including PDAC [92], as cancer cells undergo energetically inefficient glycolysis even in the presence of oxygen in the environment (aerobic glycolysis)[93]. A number of common cancer mutations including Akt1, HIF (hypoxia-inducible factor), and p53 have been shown to support the Warburg effect through glycolysis and down-regulation of metabolite flux through the Krebs cycle [94101]. In PDAC, increased phosphorylation or activation of Akt1 has also been reported (illuminating on the importance of enzyme functionality)[102] as well as involvement of HIF1 in the tumor growth via effects on glycolytic process [103,104] and membrane-bound glycoprotein (MUC17) regulation [105] – reflective of activation of metabolic pathways. Further evidences of loss-of-function genetic mutations in key mitochondrial metabolic enzymes such as succinate dehydrogenase and fumarate hydratase, isocitrate dehydrogenase, phosphoglycerate dehydrogenase support carcinogenesis and the Warburg effect [106110]. Other important alternative pathways in cancer metabolism such as glutaminolysis and pyruvate kinase isoform suppression have been shown to accumulate respective upstream intermediates and reduction of associated end products such as NADPH, ribose-5-phosphate and nucleic acids [111-116]. As such, various groups have reported metabolomics biomarker applications for different cancers [117,118].

As a major organ involved in metabolic regulation in a healthy individual, pancreatic disorder such as malignancy is anticipated to influence the normal metabolism, presenting further rationale and interest in elucidating the implication of malignant transformation and PDAC development. Proteomic analysis of the pancreatic cancer cells demonstrated alteration in proteins involved in metabolic pathways including increased expression of glycolytic and reduced Krebs cycle enzymes, and accumulation of key proteins involved in glutamine metabolism, in support of Warburg effect. These in turn play significant role in nucleotide and amino acid biosynthesis required for sustaining the proliferating cancer cells[119]. Applications of sensitive mass spectrometric techniques in metabolomics study of PDAC detection biomarkers have led to identification of a set of small molecules or metabolites (or biochemical intermediates) that are potent discriminants of developing PDAC and the controls (See Figure ​1  as an example of metabolomics based analysis, allowing segregation of PDAC from benign cases). Recent reports from our group as well as others have demonstrated that specific candidate metabolites consisting of amino acids, bile acids, and a number of lipids and fatty acids – suspected to be reflective of tumor proliferation as well as many systemic response yet to be determined – were identified as potential discriminant for blood-based PDAC biomarkers[120-123]. As a further supporting data, elucidation of lipids and fatty acids as discriminant factors from PDAC and benign lesions from the cancer tissue and adjacent normal tissue has been reported recently[124].

metabolomics based analysis for PDC WJG-21-1707-g001

metabolomics based analysis for PDC WJG-21-1707-g001

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4323446/bin/WJG-21-1707-g001.gif

Figure 1 Example of metabolomics based analysis, allowing segregation of pancreatic ductal adenocarcinoma from benign cases. Heat map illustration of discriminant capability of a metabolite set derived from gas chromatography and liquid chromatography/mass spectrometry …

By virtue of simultaneously depicting the multiple metabolite levels, metabolomics approach reveals various biochemical pathways that are uniquely involved in malignant conditions and has led to findings such as abnormalities of glycine and its mitochondrial biosynthetic pathway, as a potential therapeutic target in certain cancers[125]. Moreover, in combination with other systems biology approaches such as transcriptomics and proteomics, further refinement in characterization of cancer development and therapeutic targets as well as identification of potential biomarkers could be realized for PDAC. Since many enzymes in a metabolic network determine metabolites’ level and nonlinear quantitative relationship from the genes to the proteome and metabolome levels exist, a metabolome cannot be easily decomposed to a specific single marker, which will designate the cancer state[126]. Thus, in order to delineate a pathological state such as PDAC, multiple metabolomic features might be required for accurate depiction of a developing cancer. Future studies are anticipated to incorporate cancer systems’ biological knowledge, including metabolomics, for optimal designation of PDAC biomarkers, which would be utilized in conjunction with a clinical-parameter-derived population subset for establishing the PDAC screening population. Subsequently, further validation studies for the PDAC biomarkers need to be performed.

Current imaging-based detection and diagnostic methods for PDAC is effectively providing answers to clinical questions raised for patients with signs or symptoms of suspected pancreatic lesions. However, the endoscopic/imaging-based screening schemes are currently limited in applications to early PDAC detection in asymptomatic patients, aside from a small group of known genetically high-risk groups. There is a high demand for developing a method of selecting distinct subsets among the general population for implementing the endoscopic/imaging screening test effectively. Application of combinations of clinical risk parameters/factors with the developing molecular biomarkers from translational science such as metabolomics analysis brings hopes of providing us with early PDAC detection markers, and developing effective early detection screening scheme for the patients in the near future.

Serum metabolomic profiles evaluated after surgery may identify patients with estrogen receptor negative early breast cancer at increased risk of disease recurrence
Tenori L, Oakman C, Morris PG, …, Luchinat C, Di Leo A.
Mol Oncol. 2015 Jan; 9(1):128-39.
http://dx.doi.org:/10.1016/j.molonc.2014.07.012

Purpose: Metabolomics is a global study of metabolites in biological samples. In this study we explored whether serum metabolomic spectra could distinguish between early and metastatic breast cancer patients and predict disease relapse. Methods: Serum samples were analysed from women with metastatic (n = 95) and predominantly oestrogen receptor (ER) negative early stage (n = 80) breast cancer using high resolution nuclear magnetic resonance spectroscopy. Multivariate statistics and a Random Forest classifier were used to create a prognostic model for disease relapse in early patients.
Results: In the early breast cancer training set (n = 40), metabolomics correctly distinguished between early and metastatic disease in 83.7% of cases. A prognostic risk model predicted relapse with 90% sensitivity (95% CI 74.9-94.8%), 67% specificity (95% CI 63.0-73.4%) and 73% predictive accuracy (95% CI 70.6-74.8%). These results were reproduced in an independent early breast cancer set (n = 40), with 82% sensitivity, 72% specificity and 75% predictive accuracy. Disease relapse was associated with significantly lower levels of histidine (p = 0.0003) and higher levels of glucose (p = 0.01), and lipids (p = 0.0003), compared with patients with no relapse.
Conclusions: The performance of a serum metabolomic prognostic model for disease relapse in individuals with ER-negative early stage breast cancer is promising. A confirmation study is ongoing to better define the potential of metabolomics as a host and tumour-derived prognostic tool.

Figure 1 e Clusterization of serum metabolomic profiles. Discrimination between metastatic (green, n [ 95) and early (red, n [ 40) breast cancer patients using the random forest classifier. (a) CPMG; (b) NOESY1D; (c) Diffusion.

Figure 2 e Training set. Comparison between metabolomic classification and actual relapse. The receiver operator curves (ROC) and the area under the curve (AUC) scores are presented for CPMG, NOESY1D and Diffusion.

Figure 3 e Validation set. Comparison between CPMG random forest risk score metabolomic classification and actual relapse The receiver operator curve (ROC) and the area under the curve (AUC) score are presented for the CPMG analysis.

Figure 4 e Discriminant metabolites. Discriminant metabolites (p < 0.05) between profiles from early (green, n [ 80) and metastatic (red, n [ 95) breast cancer patients. Box and whisker plots: horizontal line within the box [ mean; bottom and top lines of the box [ 25th and 75th percentiles, respectively; bottom and top whiskers [ 5th and 95th percentiles, respectively. Median values (arbitrary units) are provided in the associated table, along with raw p values and p values adjusted for multiple testing. pts: patients.

Transparency in metabolic network reconstruction enables scalable biological discovery
Benjamin D Heavner, Nathan D Price
Current Opinion in Biotechnology, Aug 2015; 34: 105–109
Highlights

  • Assembling a network reconstruction can reveal knowledge gaps.
  • Building a functional metabolic model enables testable prediction.
  • Recent work has found that most models contain the same reactions.
  • Reconstruction and functional model building should be explicitly separated.

Reconstructing metabolic pathways has long been a focus of active research. Now, draft models can be generated from genomic annotation and used to simulate metabolic fluxes of mass and energy at the whole-cell scale. This approach has led to an explosion in the number of functional metabolic network models. However, more models have not led to expanded coverage of metabolic reactions known to occur in the biosphere. Thus, there exists opportunity to reconsider the process of reconstruction and model derivation to better support the less-scalable investigative processes of biocuration and experimentation. Realizing this opportunity to improve our knowledge of metabolism requires developing new tools that make reconstructions more useful by highlighting metabolic network knowledge limitations to guide future research.

metabolic network reconstruction

metabolic network reconstruction

http://ars.els-cdn.com/content/image/1-s2.0-S0958166914002250-fx1.jpg

Mapping metabolic pathways has been a focus of significant scientific efforts dating from the emergence of biochemistry as a distinct scientific field in the late 19th century [1]. This endeavor remains an important effort for at least two compelling reasons. First, cataloguing and characterizing the full range of metabolic processes across species (which because of genomics are being discovered at an incredible pace) is a fundamentally important step towards a complete understanding of our ecological environment. Second, mapping metabolic pathways in organisms — many of which can be found with specialized properties shaped by their environment — facilitates metabolic engineering to advance nascent industrial biotechnology efforts ranging from augmenting/replacing petroleum-derived chemical precursors or fuels to biopharmaceutical production [2]. However, despite laudable efforts to enable high-throughput ‘genomic enzymology’ [3•], the traditional biochemical approaches of enzyme expression, purification, and characterization remain time-intensive, capital-intensive, and labor-intensive, and have not expanded in scale like our ability to identify and characterize life genomically. Characterizing new metabolic function is further hampered by the challenge of cultivating environmental isolates in laboratory conditions [4]. Fortunately, recent efforts to leverage genome functional annotation and established knowledge of biochemistry have enabled the computational assembly of ‘draft metabolic reconstructions’ [5], which are parts lists of metabolic network components. In this context, a reconstruction is not just the information embodied in the stoichiometric matrix describing metabolic network structure, but also the associated metadata and annotation that entails an organism-specific knowledge base. Such a reconstruction can serve as the basis for making functional models amenable to mathematical simulation. Thus, a reconstruction is a bottom-up assembly of biochemical information, and a model can serve as a framework for integrating top-down information (for example, model constraints can be generated from statistically inferred gene regulatory networks [6]). Such computational approaches are significantly faster and less expensive than biochemical characterization [7]. They are also providing new resources facilitate cultivation of novel environmental isolates [8], and the scope of draft metabolic network coverage across the biome has increased much faster than wet lab characterization. If the distinction between reconstruction and model formulation can be strengthened and supported through software implementation, there is great opportunity for using both tasks to further advance rapid discovery of biological function.

The iterative process of manual curation of a draft metabolic network reconstruction to assemble a higher confidence compendium of organism-specific metabolism (a process termed ‘biocuration’ [9 and 10]) remains time-intensive and labor-intensive. Biocuration of metabolic reconstructions currently advances on a decadal time scale [11 and 12]. Thus, much research effort has focused instead on developing techniques for rapid development of models that are amenable to simulation [13 and 14]. Thousands of models have been derived from automatically assembled draft reconstructions [15], but most of these models consist of highly conserved portions of metabolism since they are propagated primarily via orthology. Though the number of models is large, they do not reflect the true diversity of cellular metabolic capabilities across different organisms [16•]. Applying the rapid and scalable process of draft network reconstruction to support and accelerate the less-scalable processes of biocuration and in vitro or in vivo experimentation remains an unrealized opportunity. The path forward should focus on increased emphasis on transparently documenting the reconstruction process and developing tools to highlight, rather than obscure, knowledge limitations that ultimately cause limitations to model predictive accuracy.

More explicit annotation of metabolic network reconstruction and model derivation steps can help direct research efforts

Testing implicit hypotheses arising from reconstruction assembly provides one opportunity for guiding experimental efforts. However, the very act of identifying ambiguous information in the literature should also be exploited to contribute to experimental efforts, independent of the choices a researcher makes in assembling a reconstruction. Preliminary steps to facilitate large-scale computational identification of biological uncertainty have been made, such as the development of the Evidence Ontology [18]. However, realizing the potential for using reconstruction assembly to highlight experimental opportunities will require a broader shift to emphasize the limits of our knowledge, rather than only the predictive power of a model that can be derived from a reconstruction. Computational reconstruction of metabolic networks provides two distinct opportunities for guiding experimental efforts even before a mathematically computable model is derived from the assembled knowledge: highlighting areas of uncertainty in the current knowledge of an organism, and introducing hypotheses of metabolic function as choices are made throughout biocuration efforts.

The subsequent process of deriving a mathematically computable model from a reconstruction provides additional opportunities for scalable hypothesis generation that could be exploited to inform experimental efforts. While stoichiometrically constrained models derived from reconstructions are ‘parameter-light’ when compared to dynamic enzyme kinetic models, they are not really ‘parameter free’ [19]. As modelers derive a model from an assembled reconstruction, they must make choices. And, like the ambiguities and choices that are made and should be highlighted in assembling a reconstruction, highlighting the choices made in deriving a model provides further opportunity for scalable hypothesis generation. Examples of choices that often arise in deriving a functional model include adding intracellular transport reactions, filling network gaps, or trimming network dead ends to improve network connectivity [20]. Researchers seeking to conduct Flux Balance Analysis (FBA) [21] or similar approaches must formulate an objective function, can include testable parameters such as ATP maintenance requirements, and can compare model predictions to designated reference phenotype observations. Each of these model-building and tuning activities presents opportunities to rapidly develop and prioritize new hypotheses of metabolic function.

The effort to computationally reconstruct biochemical knowledge to compile organism-specific reconstructions, and to derive computable models from these reconstructions, is a relatively young field of research with abundant opportunity for facilitating biological discovery of metabolic function. Judgment is required in assembling a reconstruction, and there should be careful consideration of the fact that judgment calls represent an implicit hypothesis. Making these hypotheses more explicit would help guide subsequent investigation. Bernhard Palsson and colleagues call for ‘an open discussion to define the minimal quality criteria for a genome scale reconstruction’ [16•] — an effort we fully support. We believe that such a beneficial ‘minimal quality criteria’ should be guided by the goals of reproducibility and transparency, including those aspects that can help to guide discovery of novel gene functions.

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CRISPR/Cas9: Contributions on Endoribonuclease Structure and Function, Role in Immunity and Applications in Genome Engineering

Writer and Curator:Larry H Bernstein, MD, FCAP 

2.2.25

2.2.25   CRISPR/Cas9: Contributions on Endoribonuclease Structure and Function, Role in Immunity and Applications in Genome Engineering, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 2: CRISPR for Gene Editing and DNA Repair

This is the fourth contribution to a series on transcriptional control and cellular remodeling. The previous dealt with RNAs – mRNA, miRNA, RNAi, siRNA, shRNA, small RNAs, lncRNAs, DICER, SLICER, RISC, recombination, and related processes.  It is clear that the classical model was limited, is history, and could not predict a large universe encompassing DNA, RNA, transcription, translation, signaling, proteins, protein conformation, mRNA-miRNA interactions, protein-protein interactions, inter- and intracellular interactions, and cellular remodeling.

Cutting it close: CRISPR-associated endoribonuclease structure and function
Hochstrasser ML and Doudna JA
Trends in Biochemical Sciences, Jan 2015; 40(1):58-66
http://dx.doi.org/10.1016/j.tibs.2014.10.007

RNAi pathways in eukaryotes, as in archaea, possess an adaptive immune system consisting of repetitive genetic elements known as clustered regularly clustered interspersed short palindromic repeats (CRISPERS) and CRISPR-associated (cas) proteins. CRISPR-cas systems require small RNAs for sequence-specific detection and degradation of complex nucleic acids. Cas 5 and cas 6 enzymes have evolved to specifically recognize and process CRISPR-derived transcripts to function as small RNAs used as guides by interference complexes.

Figure 1. Overview of CRISPR RNA (crRNA) processing and comparison between CRISPR–Cas interference systems. There are three main pathways of CRISPR adaptive immunity (Types I–III) and several subtypes, each typified by a different set of Cas proteins. The first stage of the CRISPR–Cas system is acquisition, in which a foreign DNA sequence is incorporated into the host CRISPR locus. Next, the entire repeat-spacer array is transcribed into a long precursor crRNA (pre-crRNA). A single cleavage within each repeat sequence generates shorter, mature crRNAs. Some crRNAs undergo an additional trimming step. The enzymes responsible for catalysis and exact mode of crRNA processing differ in each system. The crRNA is loaded into an interference complex where it serves as a guide for targeting invasive DNA, or in Type III-B systems, RNA.

Figure 2. Fundamental structural features of CRISPR endoRNases. (A) Topology diagram of a typical Cas6 C-terminal RRM fold with key structural features labeled. (B) Two views of Thermus thermophilus Cas6e (PDB: 2Y8W) colored as in (A). For clarity, the N-terminal RRM fold has been omitted in the left panel. (C) Comparison of structures of Cas6 and Cas5c enzymes associated with different CRISPR subtypes (in parentheses), highlighting shared structural elements, colored as in (A) and (B), with the Cas5 ‘thumb’ in black (PDB: 4ILL, 2XLK, 3UFC, 4F3M). Note that no active site residues are shown for Pyrococcus furiosus Cas6-3nc because this protein is non-catalytic.

Figure 3. Structure and sequence-specific RNA binding by Cas6 enzymes. (A) First two images: Thermus thermophilus Cas6A in the apo form and bound to its product CRISPR RNA (crRNA) (PDB: apo – 4C97, product-bound – 4C8Z). Second two images: electrostatic surface potential rendering of the same enzyme in two views with the first eight nucleotides of the Pyrococcus furiosus crRNA 30 handle (PDB: 3PKM) modeled onto the structure based on alignment of the two proteins, as in Niewoehner et al. [30]. For simplicity, only one subunit of the non-crystallographic dimer is shown. (B) Pseudomonas aeruginosa Cas6f bound to its cognate RNA (PDB: 2XLK). Close-up views highlight the active site and sequence-specific interactions by the groove-binding element. (C) Sulfolobus solfataricus Cas6-1A bound to its pre-crRNA substrate (PDB: 4ILL). The active site and sequence-specific contacts made by the glycine-rich loop are shown in detail. For simplicity, only one subunit of the SsoCas6-1A dimer is shown.

CRISPRs (clustered regularly interspaced short palindromic repeats) are DNA loci containing short repetitions of base sequences. Each repetition is followed by short segments of “spacer DNA” from previous exposures to a virus.[2]

CRISPRs are found in approximately 40% of sequenced bacteria genomes and 90% of sequenced archaea.[3][4]

CRISPRs are often associated with cas genes that code for proteins related to CRISPRs. The CRISPR/Cas system is a prokaryotic immune system that confers resistance to foreign genetic elements such as plasmids and phages[5][6] and provides a form of acquired immunity. CRISPR spacers recognize and cut these exogenous genetic elements in a manner analogous to RNAi in eukaryotic organisms.[2]

Since 2013, the CRISPR/Cas system has been used for gene editing (adding, disrupting or changing the sequence of specific genes) and gene regulation in species throughout the tree of life.[7] By delivering the Cas9 protein and appropriate guide RNAs into a cell, the organism’s genome can be cut at any desired location.

It may be possible to use CRISPR to build RNA-guided gene drives capable of altering the genomes of entire populations.

Gene-editing predecessors

In the early 2000s, researchers developed zinc finger nucleases, synthetic proteins whose DNA-binding domains enable them to cut DNA at specific spots. Later, synthetic nucleases called TALENs provided an easier way to target specific DNA and were predicted to surpass zinc fingers. They both depend on making custom proteins for each DNA target, a more cumbersome procedure than guide RNAs. CRISPRs are more efficient and can target more genes than these earlier techniques.

Repeats and spacers

CRISPR loci range in size from 24 to 48 base pairs. They usually show some dyad symmetry, implying the formation of a secondary structure such as a hairpin, but are not truly palindromic. Repeats are separated by spacers of similar length. Some CRISPR spacer sequences exactly match sequences from plasmids and phages, although some spacers match the prokaryote’s genome (self-targeting spacers). New spacers can be added rapidly in response to phage infection.

http://en.wikipedia.org/wiki/CRISPR

http://upload.wikimedia.org/wikipedia/commons/thumb/5/5f/Crispr.png/1024px-Crispr.png

http://www.frontiersin.org/files/Articles/58953/fgene-04-00193-r2/image_m/fgene-04-00193-g001.jpg

http://2013.igem.org/wiki/images/thumb/c/c0/CRISPR_Cooperativity_2.png/720px-CRISPR_Cooperativity_2.png

http://img.scoop.it/2Y0f1M2hXSr35d9-xn4WVTl72eJkfbmt4t8yenImKBVvK0kTmF0xjctABnaLJIm9

A CRISPR CASe for high-throughput silencing

A CRISPR CASe for high-throughput silencing

dual gRNA vector

dual gRNA vector

Genome editing with RNA-guided Cas9 nuclease in Zebrafish embryos

Genome editing with RNA-guided Cas9 nuclease in Zebrafish embryos

The role of CRISPR–Cas systems in adaptive immunity and beyond

Barrangue R
Current Opinion in Immunology 2015; 32:36–41
http://dx.doi.org/10.1016/j.coi.2014.12.008

CRISPR–Cas immune systems. CRISPR-encoded immunization and interference. In the adaptation stage, exogenous DNA is sampled and a novel spacer is integrated into the CRISPR locus; in the expression stage, the CRISPR array is transcribed and processed into small interfering CRISPR RNAs (crRNAs) that guide Cas endonucleases towards target complementary DNA in the interference stage.

Cas-mediated DNA targeting and cleavage. The Cas9 endonuclease forms a ribonucleoprotein complex in combination with the dual guide RNA (crRNA and tracrRNA), and the target dsDNA. First, the Cas9:guide RNA complex binds to proto-spacer adjacent motif (PAM) and drives the formation of an R-loop in the target DNA for genesis of a double stranded break using the RuvC and HNH nickase domains. The former primarily involves the recognition (REC) Cas9 lobe (top), and the latter is primarily driven by the nuclease (NUC) lobe (bottom). Cas-mediated targeting can aim at phage DNA for antiviral resistance (cleaved viral DNA cannot replicate), plasmid DNA to preclude the uptake and dissemination of plasmids (cleaved plasmid DNA cannot replicate), and chromosomal DNA for genome editing (insertion of mutations using endogenous DNA repair systems at the site of cleavage) or transcriptional control (dCas9 binding blocks RNA polymerase).

CRISPR-Cas9 Knockin Mice for Genome Editing and Cancer Modeling
Cell Oct 9, 2014; 159:440–455
http://dx.doi.org/10.1016/j.cell.2014.09.014

Figure2. Ex Vivo Genome Editing of Primary Immune Cells Derived from Constitutive Cas9-Expressing Mice (A) Schematic of ex vivo genome editing experimental flow. (B)Flow cytometry histogram of bone marrow cells from constitutive Cas9-expressing (green) and wild-type (blue) mice, showing Cas9-P2A-EGFP expressiononlyinCas9mice.Dataareplottedasa percentage of the total number of cells. (C) sgRNA design for targeting the mouse Myd88 locus. (D) sgRNA design for targeting the mouse A20 locus. (E) Myd88 indel analysis of constitutive Cas9expressing DCs transduced with either a Myd88targeting sgRNA (sgMyd88-1 and sgMyd88-2) or controls (CTR, average of four control sgRNAs), showing indel formation only in Myd88-targeted cells. Data are plotted as the percent of Illumina sequencing reads containing indels at the target site. Mutations are categorized as frameshift (fs, yellow bar) or non-frameshift (nfs, orange bar). (F) A20 indel analysis of constitutive Cas9-expressing DCs transduced with either an A20-targeting sgRNA (sgA20-1) or controls (CTR, average of four control sgRNAs), showing indel formation only in A20-targeted cells. Data are plotted as the percent of Illumina sequencing reads containing indels at the target site. Mutations are categorized as frameshift (fs, yellow bar) or non-frameshift (nfs, orange bar). (G) Myd88 mRNA quantification of constitutive Cas9-expressing DCs transduced with either Myd88-targeting sgRNA (sgMyd88-1 or sgMyd882) or controls (CTR, average of six control sgRNAs), showing reduced expression only in Myd88-targeted cells. Data are plotted as Myd88 mRNA levels from Nanostring nCounter analysis. (H) Immunoblot of constitutive Cas9-expressing DCs transduced with either Myd88-targeting sgRNA (sgMyd88-1 or sgMyd88-2) or controls (four control sgRNAs), showing depletion of MyD88 protein only in Myd88-targeted cells. b-actin was used as a loading control. (*) Overexposed, repeated-measurement. (I) Nanostring nCounter analysis of constitutive Cas9-expressing DCs transduced with either Myd88-targeting sgRNA (sgMyd88-1 or sgMyd882) or shRNA (shMyd88), A20-targeting sgRNA (sgA20-1 or sgA20-2), or shRNA (shA20), showing analtered LPS response.(Inset)Theclustershowing the highest difference between Myd88- and A20 targeting sgRNAs, including key inflammatory genes(IL1a,IL1b,Cxcl1,Tnf,etc.).(Red)High;(blue) low; (white) unchanged; based on fold change relative to measurements with six control sgRNAs. See also Figure S2.

Figure 5. In Vivo Tumor Formation in AAV9-KPL-Injected Mice (A) Lung mCT images of Cre-dependent Cas9 mice injected with either AAV9-KPL or AAV9-sgLacZ 2 months posttransduction, showing tumor formation (indicated by the arrowhead) only in AAV9-KPL injected mice. (B)LungmCT3DrenderingofCre-dependent Cas9 mice injected with AAV9-KPL 2 months posttransduction, showing tumor formation (indicated by a yellow oval). (C) Major tumor burden quantification of Cre-dependent Cas9 mice injected with either AAV9-KPL or AAV9-sgLacZ, showing significant tumor burden in AAV9KPL-injected mice. Data are plotted as mean ± SEM. **p < 0.005. (D) Representative lung H&E images of Cre-dependent Cas9 mice injected with either AAV9-KPL or AAV9-sgLacZ 9 weeks posttransduction, showing heterogeneous tumor formation in AAV9-KPL-injected mice. Arrowheads highlight a representative subset of tumors within the lungs of AAV9-KPL injected mice.

Development and Applications of CRISPR-Cas9 for Genome Engineering
Zhu PD, Lander ES, Zhang F
Cell Jun 5, 2014; 157:1262-1278
http://dx.doi.org/10.1016/j.cell.2014.05.010

Figure 1. Applications of Genome Engineering Genetic and epigenetic control of cells with genome engineering technologies is enabling a broad range of applications from basic biology to biotechnology and medicine. (Clockwise from top) Causal genetic mutations or epigenetic variants associated with altered biological function or disease phenotypes can nowberapidlyandefficientlyrecapitulated inanimalorcellularmodels (Animal models, Genetic variation). Manipulating biological circuits couldalso facilitate the generation of useful synthetic materials, such as algae-derived, silicabased diatoms for oral drug delivery (Materials). Additionally, precise genetic engineering of important agricultural crops could confer resistance to environmental deprivation or pathogenic infection, improving food security while avoiding the introduction of foreign DNA (Food). Sustainable and cost-effective biofuels are attractive sources for renewable energy, which could be achieved by creating efficient metabolic pathways for ethanol production in algae or corn (Fuel). Direct in vivo correction of genetic or epigenetic defects in somatic tissue would be permanent genetic solutions that address the root cause of genetically encoded disorders (Gene surgery). Finally, engineering cells to optimize high yield generation of drug precursors in bacterial factories could significantly reduce the cost and accessibility of useful therapeutics (Drug development).

Figure 2. Genome Editing Technologies Exploit Endogenous DNA Repair Machinery (A) DNA double-strand breaks (DSBs) are typically repaired by nonhomologous end-joining (NHEJ) or homology-directed repair (HDR). In the errorprone NHEJ pathway, Ku heterodimers bind to DSB ends and serve as a molecular scaffold for associated repair proteins. Indels are introduced when the complementary strands undergo end resection and misaligned repair due to microhomology, eventually leading to frameshift mutations and gene knockout. Alternatively, Rad51 proteins may bind DSB ends during the initial phase of HDR, recruiting accessory factors that direct genomic recombination with homology arms on an exogenous repair template. Bypassing the matching sister chromatid facilitates the introduction of precise gene modifications. (B) Zinc finger (ZF) proteins and transcription activator-like effectors (TALEs) are naturally occurring DNA-binding domains that can be modularly assembled to target specific sequences. ZF and TALE domains each recognize 3 and 1 bp of DNA, respectively. Such DNA-binding proteins can be fused to the FokI endonuclease to generate programmable site-specific nucleases. (C) The Cas9 nuclease from the microbial CRISPR adaptive immune system is localized to specific DNA sequences via the guide sequence on its guide RNA (red), directly base-pairing with the DNA target. Binding of a protospacer-adjacent motif (PAM, blue) downstream of the target locus helps to direct Cas9-mediated DSBs.

Figure 3. Key Studies Characterizing and Engineering CRISPR Systems Cas9 has also been referred to as Cas5, Csx12, and Csn1 in literature prior to 2012. For clarity, we exclusively adopt the Cas9 nomenclature throughout this Review. CRISPR, clustered regularly interspaced short palindromic repeats; Cas, CRISPR-associated; crRNA, CRISPR RNA; DSB, double-strand break; tracrRNA, trans-activating CRISPR RNA.

Figure 4. Natural Mechanisms of Microbial CRISPR Systems in Adaptive Immunity Following invasion of the cell by foreign genetic elements from bacteriophages or plasmids (step 1: phage infection), certain CRISPR-associated (Cas) enzymes acquire spacers from the exogenous protospacer sequences and install them into the CRISPR locus within the prokaryotic genome (step 2: spacer acquisition). These spacers are segregated between direct repeats that allow the CRISPR system to mediate self and nonself recognition. The CRISPR array is a noncoding RNA transcript that is enzymatically maturated through distinct pathways that are unique to each type of CRISPR system (step 3: crRNA biogenesis and processing). In types I and III CRISPR, the pre-crRNA transcript is cleaved within the repeats by CRISPR-associated ribonucleases, releasing multiple small crRNAs. Type III crRNA intermediates are further processed at the 30 end by yet-to-be-identified RNases to produce the fully mature transcript. In type II CRISPR, an associated trans-activating CRISPR RNA (tracrRNA) hybridizes with the direct repeats, forming an RNA duplex that is cleaved and processed by endogenous RNase III and other unknown nucleases. Maturated crRNAs from type I and III CRISPR systems are then loaded onto effector protein complexes for target recognition and degradation. In type II systems, crRNA-tracrRNA hybrids complex with Cas9 to mediate interference. Both type I and III CRISPR systems use multiprotein interference modules to facilitate target recognition. In type I CRISPR, the Cascade complex is loaded with a crRNA molecule, constituting a catalytically inert surveillance complex that recognizes target DNA. The Cas3 nuclease is then recruited to the Cascade-bound R loop, mediating target degradation. In type III CRISPR, crRNAs associate either with Csm or Cmr complexes that bind and cleave DNA and RNA substrates, respectively. In contrast, the type II system requires only the Cas9 nuclease to degrade DNA matching its dual guide RNA consisting of a crRNA-tracrRNA hybrid.

Figure 5. Structural and Metagenomic Diversity of Cas9 Orthologs (A) Crystal structure of Streptococcus pyogenes Cas9 in complex with guide RNA and target DNA. (B) Canonical CRISPR locus organization from type II CRISPR systems, which can be classified into IIA-IIC based on their cas gene clusters. Whereas type IIC CRISPR loci contain the minimal set of cas9, cas1, and cas2, IIA and IIB retain their signature csn2 and cas4 genes, respectively. (C) Histogram displaying length distribution of known Cas9 orthologs as described in UniProt, HAMAP protein family profile MF_01480. (D) Phylogenetic tree displaying the microbial origin of Cas9 nucleases from the type II CRISPR immune system. Taxonomic information was derived from greengenes 16S rRNA gene sequence alignment, and the tree was visualized using the Interactive Tree of Life tool (iTol). (E) Four Cas9 orthologs from families IIA, IIB, and IIC were aligned by ClustalW (BLOSUM). Domain alignment is based on the Streptococcus pyogenes Cas9, whereas residues highlighted in red indicate highly conserved catalytic residues within the RuvC I and HNH nuclease domains.

Figure 6. Applications ofCas9 as aGenome Engineering Platform (A) The Cas9 nuclease cleaves DNA via its RuvC and HNHnucleasedomains,eachofwhichnicks a DNA strand to generate blunt-end DSBs. Either catalytic domain can be inactivated to generate nickase mutants that cause single-strand DNA breaks. (B) Two Cas9 nickase complexes with appropriatelyspacedtargetsitescanmimictargetedDSBs viacooperative nicks, doubling thelengthof target recognition without sacrificing cleavage efficiency. (C) Expression plasmids encoding the Cas9 gene and a short sgRNA cassette driven by the U6 RNA polymerase III promoter can be directly transfected into cell lines of interest. (D) Purified Cas9 protein and in vitro transcribed sgRNA can be microinjected into fertilized zygotes for rapid generation of transgenic animal models. (E) For somatic genetic modification, high-titer viral vectors encoding CRISPR reagents can be transduced into tissues or cells of interest. (F) Genome-scale functional screening can be facilitated by mass synthesis and delivery of guide RNA libraries. (G) Catalytically dead Cas9 (dCas9) can be converted into a general DNA-binding domain and fused to functional effectors such as transcriptional activators or epigenetic enzymes. The modularity of targeting and flexible choice of functional domains enable rapid expansion of the Cas9 toolbox. (H) Cas9 coupled to fluorescent reporters facilitates live imaging of DNA loci for illuminating the dynamics of genome architecture. (I) Reconstituting split fragments of Cas9 via chemical or optical induction of heterodimer domains, such as the cib1/cry2 system from Arabidopsis, confers temporal control of dynamic cellular processes.

Characterization and Optimization of the CRISPR/Cas System for Applications in Genome Engineering
http://nrs.harvard.edu/urn-3:HUL.InstRepos:12407619

Two important advances in the last several decades have propelled our understanding of molecular processes far beyond descriptions of biology at macroscopic levels and fundamentally altered the way that we comprehend organisms, tissues, and cells. First, growing hand in hand with the exponential expansion of computing power, the development of genome sequencing technology, enabling high resolution mapping of DNA sequences, has allowed us to define, down to the nucleotide level, differences between multiple species, members of a species, and within an individual, between classes of cells, as well as diseased and malignant cells. At this point, our ability to make sense of this wealth of genomic information is only limited by our ability to make ever-more precise cellular and genomic alterations to which we may ascribe a phenotypic change. To achieve this, we have concurrently created tools that have allowed us to query the functions of genes and genetic variations from scales large to small by means of first random and then targeted mutagenesis, followed by increasingly refined means of manipulating either the genome directly or the activity of the genes themselves at the level of RNA or protein.

The ability to precisely manipulate the genome in a targeted manner is fundamental to driving both basic science research and development of medical therapeutics. Until recently, this has been primarily achieved through coupling of a nuclease domain with customizable protein modules that recognize DNA in a sequence-specific manner such as zinc finger or transcription activator-like effector domains. Though these approaches have allowed unprecedented precision in manipulating the genome, in practice they have been limited by the reproducibility, predictability, and specificity of targeted cleavage, all of which are partially attributable to the nature of protein-mediated DNA sequence recognition. It has been recently shown that the microbial CRISPR-Cas system can be adapted for eukaryotic genome editing. Cas9, an RNA guided DNA endonuclease, is directed by a 20-nt guide sequence via Watson-Crick base-pairing to its genomic target. Cas9 subsequently induces a double-stranded DNA break that results in targeted gene disruption through non-homologous end-joining repair or gene replacement via homologous recombination. Finally, the RNA guide and protein nuclease dual component system allows simultaneous delivery of multiple guide RNAs (sgRNA) to achieve multiplex genome editing with ease and efficiency.

The potential effects of off-target genomic modification represent a significant caveat to genome editing approaches in both research and therapeutic applications. Prior work from our lab and others has shown that Cas9 can tolerate some degree of mismatch with the guide RNA to target DNA base pairing. To increase substrate specificity, we devised a technique that uses a Cas9 nickase mutant with appropriately paired guide RNAs to efficiently inducing double-stranded breaks via simultaneous nicks on both strands of target DNA. As single-stranded nicks are repaired with high fidelity, targeted genome modification only occurs when the two opposite-strand nicks are closely spaced. This double nickase approach allows for marked reduction of off-target genome modification while maintaining robust on-target cleavage efficiency, making a significant step towards addressing one of the primary concerns regarding the use of genome editing technologies.

The ability to multiplex genome engineering by simply co-delivering multiple sgRNAs is a versatile property unique to the CRISPR-Cas system. While co-transfection of multiple guides is readily feasible in tissue culture, many in vivo and therapeutic applications would benefit from a compact, single vector system that would allow robust and reproducible multiplex editing. To achieve this, we first generated and functionally validated alternate sgRNA architectures to characterize the structure-function relationship of the Cas9 protein with the sgRNA in DNA recognition and cleavage. We then applied this knowledge towards the development and optimization of a tandem synthetic guide RNA (tsgRNA) scaffold that allows for a single promoter to drive expression of a single RNA transcript encoding two sgRNAs, which are subsequently processed into individual active sgRNAs.

A programmable genome editing tool fundamentally consists of two key elements: a DNA recognition domain conferring target specificity and a nuclease domain, ideally without any sequence specificity on its own. A key breakthrough came with the observation that the restriction enzyme FokI has molecularly distinct binding and cleavage domains, and that swapping of recognition domains could alter FokI targeting specificity. Prior to this realization, zinc fingers were discovered as a class of protein motifs in X. laevi, and found to be frequently occurring in mammalian cells as transcription factors where bind DNA in a modular, sequence specific manner. Each individual module of a Cys2-His2 zinc finger domain, the most commonly used ZF-type domain in genome engineering applications, contains approximately 30 amino acids that fold to interact with 3-bp of DNA.

With the creation of custom zinc-finger arrays capable of targeting any DNA sequence, either through stringing together of pre-defined modules with known, predicted 3bp-binding affinity or selection-based protocols with randomized ZF array libraries to account and optimize for inter-modular interactions, the pairing of the DNA-targeting ZF and FokI nuclease components created a new class of zinc finger nucleases (ZFNs) that quickly proved to be an adaptable and efficient method for targeting specific genomic loci in a variety of model organisms. While zinc finger technology can in theory target any specific genomic sequence, the difficulty of accurately predicting protein conformational folding and DNA-protein interactions prior to array assembly can make ZFN construction a somewhat tedious and costly process involving a substantial validation phase prior to practical use.

More recently, an analogous, simpler alternative was developed following the deciphering of the DNA recognition patterns of another class of proteins: the transcription activator-like effector proteins (TALEs). First observed in the rice pathogen Xanthomonas, these proteins consisted of naturally occurring modular arrays of 33-35 amino acid domains, each interacting with a single base pair. Although the single base discrimination of TALE modules compared to 3bp recognition in ZF domains provides greater ease and flexibility in designing TALE arrays to genomic targets, the inherently repetitive nature of TALE repeats posed a technical challenge that required the development of new assembly methodologies. Even so, given the modular separation of DNA recognition activity from nuclease or other effector domains, TALE-derived proteins have been able to quickly co-opt existing technology generated by the studies involving ZF proteins to similarly demonstrate effective genome editing capabilities in a wide variety of model organisms and systems.

One of the major limitations of the aforementioned genome-engineering technologies is their intrinsic dependence on protein-DNA interactions to drive specificity. As such, even after following rational design or thorough in vitro selection processes, it is necessary to perform extensive in vitro validation as protein activity and affinity may vary depending on the specific context in unpredictable ways. Practically, these factors necessitate the construction of multiple sets of TALENs or ZFNs for each locus targeted and, as a consequence, make high-throughput screening applications less tractable.

Although not directly manipulating the genome, the use of small-interfering RNAs (siRNA) to modulate gene expression represents a powerful alternative technology that is not bound by many of the short-comings of these existing genome editing technologies and revolutionized our ability to functionally interrogate the genome. The foundational observation was first made in C. elegans, that the introduction of double-stranded RNA into a cell results in potent post- transcriptional silencing of gene or genes carrying sequences complementary to the exogenous sequence. There are a number of key features that made the RNAi approach particularly tractable and drove its widespread and rapid adoption in basic science research.

  1. RNAi is an extremely efficient method of gene silencing. It is not uncommon to achieve greater than 85% gene knockdown, which, while not complete, is often more than sufficient for inducing a phenotype by which to assess gene function.
  2. siRNA targeting is mediated by predictable Watson-Crick base-pairing. This has allowed the elucidation of design parameters to both maximize on-target silencing and minimize off-target effects. Additionally, the relative ease of designing and creating siRNA constructs allows for rapid prototyping and validation of new targets.
  3. the mechanism of siRNA action takes advantage of a highly-conserved endogenous pathway for processing small RNAs, which minimizes the amount of material that needs to be delivered for adequate effect.

This has had a number of key impacts including but not limited to the possibility of multiplexed delivery to silence more than a single gene at a time or to target a single gene with multiple siRNAs to maximize knock-down, as well as the generation of large siRNA libraries allowing the development of high-throughput screening methodologies for rapid phenotyping in different contexts. The efficacy, predictability, and generalizability of RNAi technologies provided it with enough compelling qualities to become a truly disruptive technology in the field of genome engineering.

Re-purposing the bacterial CRISPR/Cas system for genome editing

The RNA-guided CRISPR (clustered regularly interspaced short palindromic repeats) endonuclease system was first observed in E. coli in 1987 by its striking eponymous genomic structure evolved as an adaptive immune system, bacteria and archaea use a set of CRISPR- associated (Cas) genes to incorporate exogenous material into the CRISPR locus, and subsequently transcribe them as RNA templates for targeted destruction of the mobile elements at either DNA or RNA level.

Three types of CRISPR systems have been identified to date, differing in their targets as well as mechanisms of action. Type I and III CRISPR systems employ an ensemble of Cas gene to carryout RNA processing, recognition of target, and cleavage33,34. By contrast, the type II CRISPRCas system makes use of a single endonuclease, Cas9, to locate and cleave target DNA. Cas9 is guided by a pair non-coding RNAs, a guide-bearing and variable crRNA and a required auxiliary transactivating crRNA (tracrRNA). The crRNA contains a 20-nt guide sequence, also known as a spacer, that determines target specificity by via Watson-Crick base-pairing with target DNA, followed by the invariant “direct repeat” portion that base-pairs with the “antirepeat” portion of the tracrRNA to form an RNA duplex. In the native bacterial system, multiple crRNAs are co-transcribed as a pre-crRNA array before being processed down to individual units for directing Cas9 against various targets. In the CRISPR-Cas system derived from Streptococcus pyogenes, the target DNA sequence always precedes a 5’-NGG protospacer adjacent motif (PAM), which can differ depending on the CRISPR system.

The S. pyogenes CRISPR-Cas system was the first to be reconstituted in mammalian cells through the heterologous expression of human codon-optimized Cas9 and the two RNA components. By altering the the 20-nt guide sequence within the sgRNA, Cas9 can be redirected toward any target bearing an appropriate PAM. Furthermore, elements from the crRNA and tracrRNA can be artificially linked to create a chimeric, single guide RNA (sgRNA), further simplifying the system for eukaryotic gene targeting.

At an overall structural level, Cas9 contains two nuclease domains, HNH and RuvC, each of which cleaves one strand of the target DNA. A mutation in either one of its catalytic domains converts Cas9 nuclease into a nickase, which has shown to induce single-stranded breaks for high-fidelity HDR applications, potentially ameliorating unwanted indel mutations from off target DSBs. Finally, a catalytically inactive or dead Cas9 (dCas9) with mutations in both DNA-cleaving catalytic residues can serve as an RNA-guided DNA-binding scaffold for localizing target effector domains that gene expression at the transcriptional level.

Engineering synthetic TALE and CRISPR-Cas9 transcription factors for regulating gene expression
Methods 2014; 69:188-197
http://dx.doi.org/10.1016/j.ymeth.2014.06.014

Fig.1. TheTAL effectorDNA-binding domain.(A) Through a DNA–protein interaction, each TALE repeatbinds one bp of DNA.TheTALE repeat is shown in blue, and the repeat variable di residue (RVD) at the 12th and 13th position are shown in green and red, respectively. (B) TALEs can be linked in tandem to recognize virtually any DNA sequence. The desired string of TALEs is then fused to an effector domain to induce a specific action at a predetermined DNA sequence. Crystal structure adapted from [60].

Fig. 2. The CRISPR/Cas9 DNA-binding domain. The Cas9 protein forms a complex with the gRNA, which recognizes a specific 20 bp DNA target sequence, known as the protospacer. A short sequence directly downstream from the protospacer, the protospacer adjacent motif (PAM),is requiredfor Cas9-mediated cleavage. ThePAM sequence is highly variable between different organisms (Table 2). With only two amino acid substitutions (D10A and H840A), Cas9 endonuclease activity can been eliminated while maintaining its RNA-guided DNA-binding activity. This deactivated Cas9 (dCas9) functions as a modular DNA-binding domain, similar to TALEs. RNA-guided transcriptional activators and repressors have been created by fusing dCas9 with different effector domains.

Fig.3. Golden gate assembly ofTALEs.Golden Gate assembly makesuse of type IIS restriction enzymes, including BsaI, BsmBI,and Esp3I, that cleave outside their recognition sequence to create unique overhangs. Therefore it is possible to digest and ligate multiple inserts into a destination plasmid with a single restriction enzyme in a single reaction. In step 1, single RVDs are excised from module plasmids and ligated into the desired array plasmid (sample overhangs are shown). This platform allows for construction ofup to 10RVDsinto each array plasmid. Importantly,the array plasmids confer spectinomycin resistance (SpecR) rather than tetracycline resistance (TetR). This ensures that only successfully assembled array plasmids are propagated. In step 2, the array plasmids and the last repeat (LR) plasmid are assembled in a second Golden Gate reaction to obtain the final desired TALE construct. Similar to step 1, in step 2 the final backbone vector confers ampicillin resistance (AmpR), rather than spectinomycin or tetracycline resistance, to ensure that only successfully assembled vectors are propagated. Replacement of the b-galactosidase expression cassette (LacZ) in the final step allows for blue-white screening of successful ligations. Figure adapted from [37].

Fig. 4. Custom gRNA cloning. The most common gRNA cloning methods make use of the BbsI type IIS restriction enzyme that cleaves outside its recognition sequence to create unique overhangs. Single stranded oligonucleotides containing each protospacer are annealed to create overhangs that are compatible with the BbsI sites in the destination vector. Upon ligation, the protospacer is inserted directly following the human U6 promoter and in front of the remainder of the chimeric gRNA sequence. The underlined G indicates the transcriptional start site.

The CRISPR/Cas9 gRNA Targeting System

The recent discovery of the CRISPR/Cas9 sysem has provided researchers an invaluable tool to target and modify any genomic sequence with high levels of efficacy and specificity. The system, consisting of a nuclease (Cas9) and a DNA-directed guide RNA (gRNA), allows for sequence-specific cleavage of target sequence containing a protospacer adaptor motif “NGG”. By changing the gRNA target sequence, virtually any gene sequence upstream of a PAM motif can be targeted by the CRISPR/Cas9 system, enabling the possibility of systematic targeting of sequences on a genomic scale. The most successful gene targeting using the CRISPR/Cas9 system is through expression of multiple gRNAs to guide the enzyme complex to several locations within the target gene to be cut or nicked.

The scalability of the Multiplex gRNA Cloning Kit allows for simultaneous cloning of two or more gRNAs at once into a single vector. This enables researchers to perform more advanced CRISPR/Cas9 techniques such as tandem double-nicking (4 gRNAs total) to remove defined genomic segments using Cas9 Nickase with significantly decreased chances for off-target effects.

The cloning of four gRNAs will require the researcher to perform three separate PCR reactions with separate primer pairs and blocks. Once the correct size amplicons are generated and gel-purified, they can be mixed at equimolar ratios (1:1:1) based on their concentrations and used as inserts in the subsequent fusion reaction with a suitable linearized destination vector.

https://www.systembio.com/downloads/Multiplex-gRNA-Cas9-system_ver5.pdf

https://www.systembio.com/images/How-quad-plex-cloning-works.jpg

https://www.addgene.org/static/data/easy-thumbnails/filer_public/cms/filer_public/7a/b2/7ab294b8-7f7a-4c30-8650-dbb520e2beb4/grna-and-cas9_1.jpg__600x277_q85_subsampling-2_upscale.png

Generation and utility of genetically humanized mouse models
Scheer N, Snaith M, Wolf CR, and Seibler J
Drug Discov Today 2013; 18(23/24):1200-1210
http://dx.doi.org/10.1016/j.drudis.2013.07.007

Applications of genetically humanized mouse models
Type of humanized mouse model Applications
Proteins involved in drug metabolismand disposition Drug–drug interaction studies
Identification and safety assessmentof human metabolites

Assessment of drug bioavailability

and clearance
PKPD modelling

Proteins of the immune and hematopoietic system Studying infectious diseases
Vaccine development and testingStudying autoimmune disorders, ..

involving the immune system

Discovery and testing of antibodies

for therapeutic use

Supported engraftment of human

cells in mice

Proteins involved in pathogeninfection Studying human infectiousdiseases
Aneuploidies or chromosomalre-arrangements Studying human hereditarydiseases
Drug targets Efficacy testing
Human regulatory elements Studying human gene expressionand regulation
Human proto-oncogenes ortumor suppressor genes Cancerogenicity testing

Components of the major pathway for drug metabolism and disposition.

Ligand-dependent activation of the xenobiotic receptors PXR, CAR, PPARa and AHR leads to a translocation to the nucleus and, together with their respective heterodimerization partners retinoic X receptor (RXR) and aryl hydrocarbon receptor nuclear translocator (ARNT), to binding of corresponding response elements and an induction of target genes.

Identifying Drug-Target Selectivity of Small-Molecule CRM1/XPO1 Inhibitors by CRISPR-Cas9 Genome Editing
JE Neggers, et al.
Chemistry & Biology , Jan 22, 2015; 22:107–116
http://dx.doi.org/10.1016/j.chembiol.2014.11.015

Figure 1. Generation of a Mutant XPO1C528S Cell Line Using CRISPR/Cas9 Genome Editing and Homologous Recombination (A) A schematic presentation of the two SINE compounds KPT-185 and KPT-330. (B) Schematic overview of the CRISPR/Cas9induced homologous recombination of human XPO1. Exons are represented by open thick arrows. The blue arrow indicates the sgRNA target site, and small arrowheads beneath the exons indicate forward and reverse PCR A or sequencing primersB.Thesiteofrecombinationis enlarged, and the location of the double strand break (scissors and arrow) is shown. Both the WT XPO1 and donor mutant template sequences are shown at the bottom (magenta, PAM motif; bold, cysteine 528 codon; red, template mutations; underlined, sgRNA sequence). (C) Sequencing chromatogram of genomic DNA of the XPO1 region around the targeted cysteine codon (in bold) from XPO1C528S cells (clone 6).See also Figure S1 and Table S1. (D) Partial protein sequence of XPO1 in WT and mutant XPO1C528S cells (clone 6). Residue 528 of XPO1 is shown in bold. (E) Sequencing chromatogram of the mRNA from XPO1C528S cells (clone 6) in the XPO1 region around the targeted cysteine codon. (F) Visualization of XPO1 protein expression in WT and mutant XPO1C528S cells (clone 6) by immunoblot with b-tubulin as loading control. (G) Relative comparison of XPO1 mRNA expression levels quantified with a probe specific to exon 2 of XPO1 (unpaired student’s t test p value, <0.0001). GAPDH and b-actin were used as internal controls. (H) Relative comparison of mean XPO1 protein expression in WT and XPO1C528S cells (clone 6) as measured by immunofluorescence staining and quantified by confocal fluorescence microscopy (unpaired student’s t test p value, <0.0001). Error bars indicate the 95% confidence interval.

Repurposing CRISPR as an RNA-Guided platform for sequence-specific control of gene expression
LS Qi. MH Larson, LA Gilbert, JA Duoda, et al.
Cell Feb 28, 2013; 152:1173–1183
http://dx.doi.org/10.1016/j.cell.2013.02.022

Figure 1. Design of the CRISPR Interference System (A)Theminimalinterferencesystemconsistsofasingleproteinandadesigned sgRNA chimera. The sgRNA chimera consists of three domains (boxed region): a 20 nt complementary region for specific DNA binding, a 42 nt hairpin for Cas9 binding (Cas9 handle), and a 40 nt transcription terminator derived from S. pyogenes. The wild-type Cas9 protein contains the nuclease activity. The dCas9 protein is defective in nuclease activity. (B) The wild-type Cas9 protein binds to the sgRNA and forms a protein-RNA complex. The complex binds to specific DNA targets by Watson-Crick base pairing between the sgRNA and the DNA target. In the case of wild-type Cas9, the DNA will be cleaved due to the nuclease activity of the Cas9 protein. We hypothesize that the dCas9 is still able to form a complex with the sgRNA and bind to specific DNA target. When the targeting occurs on the protein-coding region, it could block RNA polymerase and transcript elongation. See also Figure S1

Figure 2. CRISPRi Effectively Silences Transcription Elongation and Initiation (A) The CRISPRi system consists of an inducible Cas9 protein and a designed sgRNA chimera. The dCas9 contains mutations of the RuvC1 and HNH nuclease domains. The sgRNA chimera contains three functional domains, as described in Figure 1. (B) Sequence of designed sgRNA (NT1) and the DNA target. NT1 targets the nontemplate DNA strand of the mRFP-coding region. Only the region surrounding the base-pairing motif (20 nt) is shown. Base-pairing nucleotides are shown in orange, and the dCas9-binding hairpin is in blue. The PAM sequence is shown in red. (C) CRISPRi blocks transcription elongation in a strand-specific manner. A synthetic fluorescence-based reporter system containing an mRFP-coding gene is inserted into the E.coli MG1655 genome (then sfA locus). Six sgRNAs that bind to either the template DNA strand or the nontemplate DNA strand are coexpressed with the dCas9 protein, with their effects on the target mRFP measured by in vivo fluorescence assay. Only sgRNAs that bind to the nontemplate DNA strand showed silencing (10- to 300-fold). The control shows fluorescence of the cells with dCas9 protein but without the sgRNA. (D) CRISPRi blocks transcription initiation. Five sgRNAs are designed to bind to different regions around an E.coli promoter (J23119). The transcription start site is labeled as +1. The dotted oval shows the initial RNAP complex that covers a 75 bp region from 55 to +20. Only sgRNAs targeting regions inside of the initial RNAP complex show repression (P1–P4). Unlike transcription elongation block, silencing is independent of the targeted DNA strand. (E) CRISPRi regulation is reversible. Both dCas9 and sgRNA (NT1) are under the control of an aTc-inducible promoter. Cell culture was maintained during exponential phase. At timeT=0, 1mM of a Tc was supplemented to cells with OD=0.001. Repression of target mRFP starts within 10min.The fluorescence signal decays in a way that is consistent with cell growth, suggesting that the decay is due to cell division. In 240 min, the fluorescence reaches the fully repressed level. At T= 370 min, a T cis washed away from the growth media, and cells are diluted back to OD = 0.001. Fluorescence starts to increase after 50 min and takes about 300 min to rise to the same level as the positive control. Positive control: always without the inducer; negative control: always with 1 mM aTc inducer. Fluorescence results in (C)–(E) represent average and SEM of at least three biological replicates. See also Figures S2 and S3.

Figure 3. CRISPRi Functions by Blocking Transcription Elongation (A) FLAG-tagged RNAP molecules were immunoprecipitated, and the associated nascent mRNA transcripts were sequenced. (Top) Sequencing results of the nascent
mRFP transcript in cells without sgRNA. (Bottom) Results in cells with sgRNA. In the presence of sgRNA, a strong transcriptional pause is observed 19 bp upstream of the target site, after which the number of sequencing reads drops precipitously. (B) A proposed CRISPRi mechanism based on physical collision between RNAP and dCas9-sgRNA. The distance from the center of RNAP to its front edge is ~19 bp, which matches well with our measured distance between the transcription pause site and 30 of sgRNA base-pairing region. The paused RNAP aborts transcription elongation upon encountering the dCas9-sgRNA roadblock.

Figure 4. Targeting Specificity of the CRISPRi System (A) Genome-scale mRNA sequencing (RNA-seq) confirms that CRISPRi targeting has no off-target effects. The sgRNA NT1 that bindsto the mRFP coding region is used. The dCas9, mRFP, and sfGFP genes are highlighted. (B)Multiple sgRNAs can independently silence two fluorescent protein reporters in the same cell. Each sgRNA specifically represses its cognate gene,but not the other gene. When both sgRNAs are present, both genes are silenced. Error bars represent SEM from at least three biological replicates. (C) Microscopic images for using two sgRNAs to control two fluorescent proteins. (Top) Bright-field images of the E. coli cells; (middle) RFP channel; (bottom) GFP channel. Coexpression of one sgRNA and dCas9 only silences the cognate fluorescent protein, but not the other. The knockdown effect is strong, as almost no fluorescence is observed from cells with certain fluorescent protein silenced. Scale bar, 10 mm. Control shows cells without any fluorescent protein reporters.

In vitro and in vivo growth suppression of human papillomavirus 16-positive cervical cancer cells by CRISPR-Cas9
S Zhen, L Hua, et al.
BBRC 2014; 450:1422-1426
http://dx.doi.org/10.1016/j.bbrc.2014.07.014

Fig. 4. Suppression of in vivo growth of SiHa cells in BALB/c nude mice by CRISPR/ Cas9. (A) In vivo tumor growth curves of CRISPR/Cas9 systems-treated SiHa cells. The mean tumor volumes ± SD (bars) are shown at the times that tumor measurements were made (n = 6). (B) Tumor weight 10 weeks after inoculation. All tumors were excised and weighted.

One-Step Generation of Mice Carrying Mutations in Multiple Genes by CRISPR-Cas-mediated genome engineering
Wang H, Yang H, et al.
Cell  2013; 153:910-918
http://dx.doi.org/10.1016/j.cell.2013.04.025

Figure 2. Single- and Double-Gene Targeting In Vivo by Injection into Fertilized Eggs (A) Genotyping of Tet1 single-targeted mice. (B) Upper: genotyping of Tet2 single-targeted mice. RFLP analysis; lower: Southern blot analysis. (C) The sequence of both alleles of targeted gene in Tet1 biallelic mutant mouse 2 and Tet2 biallelic mutant mouse 4. (D) Genotyping of Tet1/Tet2 double-mutant mice. Analysis of mice 1 to 12 is shown. Upper: RFLP analysis; lower: southern blot analysis. The Tet1 locus is displayed on the left and the Tet2 locus on the right. (E) The sequence of four mutant alleles from double-mutant mouse 9 and 10. PAM sequences are labeled in red. (F) Three-week-old double-mutant mice. All RFLP and Southern digestions and probes are the same as those used in Figure 1. See also Figures S2 and S3.

The impact of CRISPR–Cas9 on target identification and validation
JD Moore
Drug Discov Develop 2015
http://dx.doi.org/10.1016/j.drudis.2014.12.016

Gene editing with Cas9. (a) Knock-out generation via Cas9 and a single synthetic guide (sg)RNA. sgRNAs form Watson–Crick base pairs with target sequences recruiting the wild-type Cas9 nuclease. Cas9 generates double stranded breaks that are typically repaired by the imprecise NHEJ mechanism resulting in small insertions or deletions, most of which generate frameshift mutations. Transient expression of sgRNA plus Cas9 leads to editing of 2–25% of alleles. Derivative clones are analysed to find examples where Gene editing with Cas9. (a) Knock-out generation via Cas9 and a single synthetic guide (sg)RNA. sgRNAs form Watson–Crick base pairs with target sequences recruiting the wild-type Cas9 nuclease. Cas9 generates double stranded breaks that are typically repaired by the imprecise NHEJ mechanism resulting in small insertions or deletions, most of which generate frameshift mutations. Transient expression of sgRNA plus Cas9 leads to editing of 2–25% of alleles. Derivative clones are analysed to find examples where both alleles have been repaired with frame shift mutations. (b) Knock-out generation via Cas9 and a pair of sgRNAs. When wild-type Cas9 is expressed with a pair of sgRNAs targeting sites in the same region of a gene, simultaneous dual double-stranded breaks will be introduced in a fraction of cells. Repair via NHEJ will tend to delete the intervening sequence. (c) Knock-in generation using sgRNAs, donor DNA and either wild-type Cas9 or the Cas9-D10A nickase mutant. Wild-type Cas9 generates double stranded breaks that can be repaired by NHEJ generating indels or by homology-directed repair (HDR) leading to knock-in of mutations present on homology templates. The Cas9-D10A nickase mutant only generates single stranded breaks, which are not a substrate for the NHEJ pathway. However, these can be processed by HDR leading to the introduction of knock-in mutations. (d) Using the Cas9D10A nickase mutant to enhance the specificity of gene editing. The sgRNA shown in red also recruits Cas9 to partially mismatched off-target sites where wild-type Cas9 can efficiently introduce double stranded breaks leading to editing of an off-target exon.  More…

Repurposing CRISPR-Cas9 for in situ functional assays
Malina A, Mills JR, …, Pelletier J.
Genes & Development 2015; 27:2602–2614
http://www.genesdev.org/cgi/doi/10.1101/gad.227132.113

Figure 1. Genome editing of a TLR locus in 293Tcells using an engineered all-in-one type II CRISPR system. (A) Schematic diagram of LeGO-based lentivirus (pLC) constructs driving expression of Cas9 and sgRNAs. (B) Predicted secondary structure (http://rna.tbi. univie.ac.at/cgi-bin/RNAfold.cgi) of sgRNA showing alignment of trigger sequence with target and PAM. The first nucleotide of the trigger sequence is forcibly a G, since the sgRNA is expressed from the murine U6 promoter. (C) Schematic of TLR with the position and nucleotide sequence of the TLR trigger, PAM, and stop codon shown. (D) A genomically integrated TLR is efficiently targeted by pLC-TLR. Quantitation of 293T TLR cells transfected with the indicated Cas9/sgRNA expression constructs and, where indicated, in combination with D20 eGFP. (E) Immunoblot showing expression and subcellular localization of Cas9 from the experiment presented in D. (C) Cytoplasmic fraction; (M) membrane fraction; (N) nuclear fraction. Blots were probed with the antibodies indicated below each panel. (F) Lentiviral-mediated NHEJ and HDR in 293T TLR cells. Cells were infected with lentivirus expressing Cas9 and the corresponding sgRNA and analyzed by flow cytometry 6 d later. The D20 eGFP donor plasmid was introduced by transfection 1 d prior to transduction with the Cas9/sgRNA lentiviral construct.

Figure 2. Cas9-mediated editing of Trp53 in Arf[1]/[1] MEFs leads to Nutlin-3a resistance. (A) Schematic diagram of the pQ-based retroviral constructs driving expression of Cas9, GFP, and sgRNAs (pQCiG). (B) Flow cytometric analysis of Arf[1]/[1] and p53[1]/[1] MEFs transduced with QCiG-Rosa, QCiG-p53, or MLP-p53.1224 retroviruses, cultured 3 d later in the presence of vehicle or 10 mM Nutlin-3a for 24 h, and then allowed to recover for 4 d. (C) Colony formation assay of infected Arf[1]/[1] and p53[1]/[1] MEFs with QCiG-Rosa, QCiGp53, or MLP-p53.1224. Five-thousand cells were seeded, exposed to 10 mM Nutlin-3a for 24 h, and allowed to recover for 12 d in the absence of drug, at which point they were stained with crystal violet. (D) SURVEYOR assay of DNA isolated from QCiG-p53- and QCiG-Rosa-infected Arf[1]/[1] MEFs exposed to 10 mM Nutlin-3a for 24 h and allowed to recover for 4 d. The arrowhead denotes the expected SURVEYOR cleavage products. (E) Immunoblot documenting Cas9 and p53 expression in QCiG- and MLP-infected MEFs. The asterisk denotes the position of a prominent p53 truncated product

Figure 3. Cas9-mediated editing of Trp53 in Arf[1]/[1]Em-myc lymphomas is positively selected for following DXR treatment in vivo. (A) Schematic diagram of in vivo fitness assay. (B) Kaplan-Meier analysis of tumor-free survival of mice injected with Rosa26 or Trp53 Cas9 targeted Arf[1]/[1]Em-myc and p53[1]/[1]Em-myc lymphomas following treatment with DXR. (C) Detection of GFP in tumors arising from QCiG-p53-infected Arf[1]/[1]Em-myc lymphomas following exposure to DXR and analyzed 3 d later. White arrows denote GFP fluorescence in lymph nodes originating from the presence of QCiG-p53 in the resulting tumors. (D) FACS analysis of the indicated Cas9 targeted Em-myc lymphomas analyzed before injection into mice (input), from tumors arising in vivo (pre-DXR), and from tumors for which the host had received DXR treatment (post-DXR). (E) SURVEYOR assay of DNA from QCiG-p53- and QCiG-Rosa-infected Arf-/-Em-myc lymphomas isolated from mice prior to DXR treatment. (F) Immunoblot showing long-term Cas9, p53, and GFP expression in QCiG-Rosa and QCiG-p53 Arf-/-Em-Myc lymphomas in vivo. Samples are from three separate tumors isolated prior to (pre-DXR) or following (post-DXR) DXR treatment. In the case of post-DXR samples for QCiG-Rosa Arf-/-Em-myc lymphomas, tumors were harvested after relapse (~10 d after post-DXR treatment). The asterisk highlights a truncated p53 protein arising in the Cas9 edited samples.

Figure 4. Analysis of indels at the Trp53 locus and at predicted off-target sites in Arf-/-MEFs and Arf-/-Em-myc tumors edited with Rosa26 and Trp53 sgRNAs. (A) Total count and location of insertions and deletions in exon 7 of Trp53 in Arf-/-Em-myc cells prior to injection, post-implantation, and post-DXR treatment, respectively. The vertical dashed line represents the predicted Cas9 cleavage site. (B) Frequency of mutant reads obtained following sequencing of Trp53 exon 7 from the indicated cells and tumors. T-1, T-2, and T-3 represent three independent tumors. (C, top panel) Sequence alignment of the trigger site in the Trp53 and Trp53 pseudogene. Differences are highlighted in green. (Bottom panel) Pie charts illustrating the proportion of mutated sequence reads at Trp53 (left) and the Trp53 pseudogene (right) relative to wild-type sequences (wt; blue). DNA was isolated from samples of Arf-/-Em-myc lymphoma cells infected with QCiG-Rosa-infected (top), QCiG-p53-infected (middle), or QCiG-p53-infected cells that were exposed to 10 mM Nutlin-3a for 3 d followed by a 10-d recovery period (bottom). (D) Prediction of genomic sequences showing sequences complementary to the first 13 perfectly matched nucleotides 59 to the PAM of the Trp53 trigger sequence with all possible combinations of PAM. The trigger sequence is shown in blue, PAM is in red, and flanking nucleotides are in black. The genomic location is shown at the right. (E) Percent mutant reads at the indicated genomic locus in Rosa26- and Trp53-modified Arf-/- MEFs. The total read count for each amplified region ranged from ;11,000 to 15,000 (sample #8), ;18,000 to 23,000 (sample #7), and ;20,000 to 53,000 (all others). Read counts for locus #2 are absent, since the barcode that had been used in the preparation of that sample could not be deciphered from the output of reads.

TALE nucleases- tailored genome engineering made easy
Mussolino C, Cathomen T
Current Opinion in Biotechnology 2012; 23:644–650
http://dx.doi.10.1016/j.copbio.2012.01.013

Generation of customized TALENs by ‘Golden Gate’ cloning. Dependent on the user-defined target sequence, the respective repeat units with desired specificities can be assembled using a two-step ‘Golden Gate’ cloning protocol. A TALEN monomer is generated by incorporating the TALE designer array in a TALEN backbone, which contains an N-terminal NLS, the ‘0 repeat’ binding to the 50-T nucleotide, the 17.5 ‘half-repeat’, and the terminal FokI cleavage domain (N).

TALEN or Cas9 – Rapid, efficient and specific choices for genome modifications
Wei C, Liu J, et al.
J Genetics and Genomics 40 (2013) 281e289
http://dx.doi.org/10.1016/j.jgg.2013.03.013

Fig. 1. Schematic principles of TALEN- and CRISPR/Cas9-mediated genomic modifications. A: a single TALEN consists of an N-terminal domain including a nuclear localization signal (NLS, blue); a central domain typically composed of tandem TALE repeats (green) for the recognition of a specific DNA sequence; and a C-terminal domain of the functional endonuclease Fok I (black). Each TALE repeat comprises of a 34-amino-acid unit that differs at the position of 12th and 13th amino acids: NG (recognizing T), NI (recognizing A), HD (recognizing C), or NN (recognizing G) (color boxes). B: double-strand breaks (DSBs) that are resulted from the cut by dimeric Fok I can be repaired either by non-homologous end joining (NHEJ) to yield indels or by homologous recombination (HR) with available homologous donor templates. The red star indicates where indels occur. C: the CRISPR/Cas9 system consists of a group of CRISPR-associated (Cas) genes (arrows with the direction to the right) and a CRISPR locus that contains an array of repeats (dark diamonds) e spacer (color boxes) sequences. All repeats are the same in sequence and all spacers are different and complementary to their target DNA sequences. The tracrRNA (trans-activating crRNA, arrow on the most left) can help to produce the crRNA (CRISPR RNA). D: the Cas9 protein (blue) binds to crRNA (orange) and tracrRNA (purple) to form a ribonucleoprotein complex. The crRNA sequence guides this complex to a complementary sequence in the target DNA (black). Then the HNH and RuvC domains of Cas9 nick the complementary and non-complementary strands, respectively, making a DSB. PAM: protospacer adjacent motif NGG (yellow box). gRNA: guiding RNA. NCC is a complementary motif of the PAM motif (NGG).

Table 1 Comparison of TALEN- and CRISPR/Cas9-mediated genomic modifications e principles and applications

TALEN CRIPR/Cas9
Target-binding principle Protein-DNA specific recognition Watson Crick complementary rule
Working mode TALE specifically recognizes the target DNA and dimeric Fok I makes the DSB, which is repaired by NHEJ or HR Guide RNA specifically recognizes the target DNA and Cas9 makes the DSB, which is repaired by NHEJ or HR
Essential components TALE-Fok I fusion protein Guide RNA and Cas9
Off-target effects Minor effects Not determined
Efficiency High but variable High but variable
Target site availability No restriction PAM (NGG) motif restriction
Work in pair/dimmer Yes No
Inheritability in animals Yes Not determined
3D structure Yes Yes
Time to construct 5-7 d 1-3 d
Origin discovery Plant pathogen E. coli

Genome-Scale CRISPR-Mediated Control of Gene Repression and Activation
Gilbert LA, et al.
Cell, Oct 23, 2014; 159: 647–661
http://dx.doi.org/10.1016/j.cell.2014.09.029

Figure 1. A Tiling sgRNA Screen Defines Rules for CRISPRi Activity at Endogenous Genes in Human Cells (A) Massively parallel determination of growth or toxin-resistance phenotypes caused by sgRNAs in mammalian cells expressing dCas9 or dCas9 fusion constructs. (B) UCSC genome browser tracks showing the genomic organization, GC content, and repetitive elements around the TSS of a representative gene, VPS54, across a 10 kb window targeted by the tiling sgRNA library. sgRNA ricin-resistance phenotypes (as Z scores, see Figure S1 and Experimental Procedures) in dCas9 and dCas9-KRAB expressing K562 cells are depicted in black on the top and bottom, respectively. See also Figure S2A for more examples. (C) Sliding-window analysis of all 49 genes targeted in a tiling sgRNA library. Green line: median sgRNA activity in a defined window for all genes. Orange region: observed average window of maximum CRISPRi activity. Data displayed as a phenotype signed Z score, excluding all guides longer than 22 bp. (D) CRISPRi activity for all 49 genes in defined windows relative to the TSS of each gene. (E) Ricin-resistance phenotypes, comparing CRISPRi sgRNAs selected by our rules to RNAi, for genes previously established to cause ricin-resistance phenotypes when knocked down by RNAi. Mean ± SD phenotype-signed Z score of 100 sets of 10 randomly subsampled sgRNAs or shRNAs. See also Figure S2F

Figure 2. CRISPRi Activity is Highly Sensitive to Mismatches Between the sgRNA and DNA sequence On- and off-target activity of dCas9, dCas9-KRAB and Cas9 for sgRNAs with a varying number and position of mismatches. Off-target activity of sgRNAs with mismatches is displayed as percent of the on-target activity for the corresponding sgRNA without mismatches. Asterisk indicates sgRNAs with three, four, or five mismatches randomly distributed across region 3 of the sgRNA sequence. Data are displayed for each mismatch position as the mean of all sgRNAs with that mismatch; see Figure S3 for individual sgRNA activities. sgRNAs were included in the analysis only if the fully matched guide was highly active (phenotype-signed Z score R 4); n = 5 for dCas9, n = 11 for dCas9-KRAB, and n = 10 for Cas9.

Figure 3. A Tiling sgRNA Screen Defines Rules for CRISPRa Activity at Endogenous Genes in Human Cells (A) A schematic of the dCas9-SunTag + scFV-VP64 + sgRNA system for CRISPRa. (B)ActivityofsgRNAsinK562cellsstablyexpressingeachcomponentofCRISPRa,asafunctionofthedistanceofthesgRNAsitetotheTSSofthetargetedgene (Phenotype-signed Z scores; therefore, negative values represent opposite results than from knockdown). Top, sgRNAs targeting VPS54; Bottom, slidingwindow analysis of all 49 genes targeted by our tiling library in green. Green line, median activity; orange, window of maximal activity. Guides longer than 22 bp were excluded. See also Figure S4. (C)CRISPRaphenotypesandCRISPRi(dCas9-KRAB)phenotypesareanticorrelated forselect genes.Foreachgene,aMann-Whitneypvalueiscalculatedusing CRISPRi/a sgRNA activity relative to a negative control distribution for 24 subsampled sgRNAs. Mean ± SD p value of 100 randomly subsampled sets is displayed. (D) CRISPRi knockdown and CRISPRa activation of the same gene can have opposing effects on ricin resistance in both primary screens and single sgRNA validation experiments (mean ± SD of 3 replicates). (E) Modulation of expression levels for 3 genes by CRISPRi and CRISPRa as quantified by qPCR plotted against the ricin-resistance phenotype (mean ± SD of 3 replicates) measured for each sgRNA.

Figure 4. Genome-Scale CRISPRi and CRISPRa Screens Reveal Genes Controlling Cell Growth (A) sgRNA phenotypes from a genome-scale CRISPRi screen for growth in human K562 cells (black). Three classes of negative control sgRNAs are color-coded: nontargeting sgRNAs (gray), sgRNAs targeting Y-chromosomal genes (green) and sgRNAs targeting olfactory genes (orange). (B) Coexpression of sgRNAs and dCas9-KRAB or dCas9-SunTag + scFV-VP64 is not toxic in K562 cell lines over 16 days. (C) Gene set enrichment analysis (GSEA) for hits from the CRISPRi screen. A histogram of gene distribution is shown under the GSEA curve. (D) CRISPRi versus CRISPRa gene phenotypes for genome-scale growth screens (black). For the 50 genes in the CRISPRa screen with the most negative growth phenotype, each gene was annotated and labeled based on evidence of activity as a tumor suppressor (orange), developmental transcription factor (green), or in regulation of the centrosome (purple). Two additional CRISPRi hit genes that are discussed in the text are labeled in red. See Table S4 for annotations and references. (E) GSEA for hits from the CRISPRa growth screen. A histogram of gene distribution is shown under the GSEA curve.

Figure 5. CRISPRi Gene Silencing Is Inducible, Reversible, and Nontoxic (A) Expression construct encoding an inducible KRAB-dCas9 fusion protein. (B) Western blot analysis of inducible KRAB-dCas9 in the absence, presence, and after washout of doxycycline. (C) Relative RAB1A expression levels (as quantified by qPCR) in inducible CRISPRi K562 cells transduced with RAB1A-targeting sgRNAs in the absence, presence, and after washout of doxycycline. Mean ± standard error of technical replicates (n = 2) normalized to control cells (assayed in the presence of doxycycline) from the day 2 time point. (D) Competitive growth assays performed with inducible CRISPRi K562 cells transduced with the indicated sgRNAs in the presence and absence of doxycycline. Data are represented as the mean ± SD of replicates (n = 3). See also Figure S5G. (E) A CRISPRi sublibrary screen for effects on cell growth was performed with inducible CRISPRi K562 cells in the presence and absence of doxycycline. (F) Cumulative growth curves from the sublibrary screen represented in (E) show no bulk changes to growth caused by induction of KRAB-dCas9. Mean ± SD of replicate infections each screened in duplicate.

Figure 6. Genome-Scale CRISPRi and CRISPRa Screens Reveal Known and New Pathways and Complexes Governing the Response to a Cholera-Diphtheria Fusion Toxin (A) Model for CTx-DTA binding, retrograde trafficking, retrotranslocation, and cellular toxicity. (B) Overview of top hit genes detected by the CTx-DTA screen. Dark red and blue circles: Top 50 sensitizing and protective hits, respectively. Light red and blue circles: further hits that fall into the same protein complexes or pathways as top 50 hits. Circle area is proportional to phenotype strength. White stars denote genes identified in a previous haploid mutagenesis screen (Guimaraes et al., 2011). See also Figure S6 for hit gene names. (C) CRISPRi and CRISPRa hits in sphingolipid metabolism. Display as in (B), except that the left and right sides of each circle represent the phenotypes in the CRISPRi and CRISPRa screens, respectively.

Figure 7. CRISPRi Strongly Represses Gene Expression of Both Protein-Coding and Noncoding Genes, Resulting in Reproducible Phenotypes (A–C) Cells expressing a negative control sgRNA or an sgRNA targeting SEL1L or B4GALNT1 were incubated with cholera toxin and fractionated to quantify cholera toxin present in the cytosolic and membrane fractions by western blot. B4GALNT1 repression blocks toxin uptake, whereas SEL1L repression prevents toxin retrotranslocation from the membrane fraction to the cytosol. (D) Validation of CTx-DTA screen phenotypes with single sgRNA retest experiments. Data are represented as the mean ± SD of replicates (n = 3). (E) CRISPRi knockdown of 13 hit genes (28 sgRNAs; sgRNAs correspond to 7D) identified in the CTx-DTA screen was quantified by qPCR. The gray shaded region denotes sgRNAs showing at least 90% knockdown for each gene. Data are normalized to a negative control sgRNA (NC). (F) CRISPRi knockdown of 6 lncRNA genes was quantified by qPCR. Two to three sgRNAs computationally predicted to target each gene were cloned and transduced into K562 cells expressing dCas9-KRAB. Data are normalized to a negative control sgRNA (NC). (G) K562 cells expressing dCas9-KRAB were transduced with either a nontargeting sgRNA or an sgRNA targeting the XIST locus (sgXIST-1). The cells were then stained with DAPI and an RNA FISH probe for the XIST transcript. Two hundred nonapoptotic interphase cells in each condition were scored for XIST RNA coating. XIST is undetectable in cells transduced with sgXIST-1. Scale bar, 5 mm

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Advances in Gene Editing Technology: New Gene Therapy Options in Personalized Medicine

Curators: Stephen J Williams, PhD and Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2015/03/16/advances-in-gene-editing-technology-new-gene-therapy-options-in-personalized-medicine/

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RNAi – On Transcription and Metabolic Control

Writer and Curator: Larry H Bernstein, MD, FCAP

 

RNAi

This is the third contribution to a series on transcription and metabolic control. It reveals the enormous complexity in this emerging research.

 

mRNA, small RNAs, long RNAs, RNAi and DicAR

Aberrant mRNA translation in cancer pathogenesis
Pier Paolo Pandolfi
Oncogene (2004) 23, 3134–3137
http://dx.doi.org:/10.1038/sj.onc.1207618

As the molecular processes that control mRNA translation and ribosome biogenesis in the eukaryotic cell are extremely complex and multilayered, their deregulation can in principle occur at multiple levels, leading to both disease and cancer pathogenesis. For a long time, it was speculated that disruption of these processes may participate in tumorigenesis, but this notion was, until recently, solely supported by correlative studies. Strong genetic support is now being accrued, while new molecular links between tumor-suppressive and oncogenic pathways and the control of protein synthetic machinery are being unraveled. The importance of aberrant protein synthesis in tumorigenesis is further underscored by the discovery that compounds such as Rapamycin, known to modulate signaling pathways regulatory of this process, are effective anticancer drugs. A number of fundamental questions remain to be addressed and a number of novel ones emerge as this exciting field evolves.

 

mRNA Translation and Energy Metabolism in Cancer
I. Topisirovic and N. Sonenberg
Cold Spring Harbor Symposia on Quantitative Biology, Volume LXXVI
http://dx.doi.org:/10.1101/sqb.2011.76.010785

A prominent feature of cancer cells is the use of aerobic glycolysis under conditions in which oxygen levels are sufficient to support energy production in the mitochondria (Jones and Thompson 2009; Cairns et al. 2010). This phenomenon, named the “Warburg effect,” after its discoverer Otto Warburg, is thought to fuel the biosynthetic requirements of the neoplastic growth (Warburg 1956; Koppenol et al. 2011) and has recently been acknowledged as one of the hallmarks of cancer (Hanahan and Weinberg 2011). mRNA translation is the most energy-demanding process in the cell (Buttgereit and Brand 1995).In mammalian cells it consumes >20% of cellular ATP, not considering the energy that is required for the biosynthesis of the components of the translational machinery (e.g., ribosome biogenesis; Buttgereit and Brand 1995). Control of mRNA translation plays a pivotal role in the regulation of gene expression (Sonenberg and Hinnebusch 2009). In fact, a recent study demonstrated that mammalian proteome is mostly governed at the mRNA translation level (Schwanhausser et al. 2011). Malfunction of mRNA translation critically contributes to human disease, including diabetes, heart disease, blood disorders, and, most notably, cancer (Fig. 1; Crozier et al. 2006; Narla and Ebert 2010; Silvera et al. 2010; Spriggs et al. 2010). The first account of changes in the translational apparatus in cancer dates back to 1896, showing enlarged and irregularly shaped nucleoli that are the site of ribosome biogenesis (Pianese 1896). Rapidly proliferating cancer cells have more ribosomes than normal cells.

Figure 1. Dysregulated mRNA translation plays a pivotal role in cancer. Malignant cells are characterized by enlarged nucleoli and a larger number of ribosomes than their normal counterparts. Mutations and/or altered expression of ribosomal proteins (e.g., RPS19, RPS 24), rRNA-modifying enzymes (e.g., dyskerin), translation initiation factors (e.g., eIF4E), or the initiator tRNA (tRNAiMet) result in malignant transformation. Signaling pathways whose dysfunction is frequent in cancer (e.g., MAPK, PI3K/AKT) affect mRNA translation. Perturbations in the translatome result in aberrant cellular growth, proliferation, and survival characteristic of tumorigenesis.

 

In stark contrast to normal cells, in cancer cells ribosomal biogenesis is uncoupled from cell proliferation (Stanners et al. 1979). Accordingly, cancer cells exhibit abnormally high rates of protein synthesis (Silvera et al. 2010). That ribosomal dysfunction plays a central role in cancer is further corroborated by the findings that genetic alterations, which encompass the components of the ribosome machinery (i.e., “ribosomopathies”), are characterized by elevated cancer risk (Narla and Ebert 2010).

mRNA translation is the most energy-consuming process in the cell and strongly correlates with cellular metabolic activity. Translation and energy metabolism play important roles in homeostatic cell growth and proliferation, and when dysregulated lead to cancer. eIF4E is a key regulator of translation, which promotes oncogenesis by selectively enhancing translation of a subset of tumor-promoting mRNAs (e.g., cyclins and c-myc). PI3K/AKT and mitogen-activated protein kinase (MAPK) pathways, which are strongly implicated in cancer etiology, exert a number of their biological effects by modulating translation. The PI3K/AKT pathway regulates eIF4E function by inactivating the inhibitory 4E-BPs via mTORC1, whereas MAPKs activate MAP kinase signal-integrating kinases 1 and 2, which phosphorylate eIF4E. In addition, AMP-activated protein kinase, which is a central sensor of the cellular energy balance, impairs translation by inhibiting mTORC1. Thus, eIF4E plays a major role in mediating the effects of PI3K/AKT, MAPK, and cellular energetics on mRNA translation.Figure 2. eIF4E is regulated by multiple mechanisms. The expression of eIF4E is regulated by several transcription factors (e.g., c-myc, hnRNPK, p53) and adenine-uracil-rich element binding proteins (i.e., HuR and AUF1). eIF4E is suppressed by 4E-BPs, which are regulated by mTORC1. MAP kinase signal integrating kinases 1 and 2 (MNKs) phosphorylate eIF4E.

 

Figure 3. Ras/MAPK and PI3K/AKT/mTORC1 regulate the activity of eIF4E. Various stimuli activate phosphoinositide-3-kinase (PI3K) through the receptor tyrosine kinases (RTKs). Upon activation, PI3K converts phosphatidylinositol 4,5-bisphosphate (PIP2) into phosphatidylinositol-3,4,5-triphosphate (PIP3). This reaction is reversed by PTEN. Phosphoinositide-dependent protein kinase 1 (PDK1) and AKT bind to PIP3 via their pleckstrin homology domains, which allows for the phosphorylation and activation of AKT by PDK1. In addition, the mammalian target of rapamycin complex 2 (mTORC2) modulates the activity of AKT by phosphorylating its hydrophobic motif. AKT phosphorylates tuberous sclerosis complex 2 (TSC2) at multiple sites, which results in its inhibition and consequent activation of Ras homolog enriched in brain (Rheb), which is a small GTPase that activates mTORC1. mTORC1 phosphorylates 4E-BPs leading to their dissociation from eIF4E. In addition to the PI3K/AKT pathway, the activity of mTORC1 is regulated by the serine/threonine kinase 11/LKB1/AMP-kinase (LKB1/AMPK) pathway, regulated in development and DNA damage response 1 (REDD1) and Rag GTPases in response to the changes in cellular energy balance, oxygen and amino acid availability, respectively. Ras and the MAPK pathways are activated by various stimuli through receptor tyrosine kinases (RTKs). In addition the MAPK pathway isactivatedthrough theGprotein–coupled receptors(GPCRs) and byproteinkinaseC (PKC;notshown).TheMAPK pathways encompass an initial GTPase-regulated kinase (MAPKKK), which activates an effector kinase (MAPK) via an intermediate kinase (MAPKK). In response to stimuli such as growth factors, hormones, and phorbol-esters, Ras GTPase stimulates Raf kinase (MAPKKK), which activates extracellular signal-regulated kinases 1 and 2 (ERK 1 and 2) via extracellular signal-regulated kinase activator kinases MEK1 and 2 (MAPKK). Cellular stresses, including osmotic shock, inflammatory cytokines, and UV light, activate p38 MAPKs via multiple mechanisms including Rac kinase (MAPKKK) and MKK3 and 6 (MAPKK). p38 MAPK and ERK activate the MAPK signal–integrating kinases 1 and 2 (MNK1/2), which phosphorylate eIF4E. Additional abbreviations are provided in the text.

 

Cancer Exosomes Perform Cell-Independent MicroRNA Biogenesis and Promote Tumorigenesis
Cancer Cell Nov, 2014; 26: 707–721.
http://dx.doi.org/10.1016/j.ccell.2014.09.005

Breast cancer cells secrete exosomes with specific capacity for cell-independent miRNA biogenesis, while normal cellderivedexosomes lack thisability. Exosomes derivedfrom cancer cellsand serum frompatients withbreast cancer contain the RISC loading complex proteins, Dicer, TRBP, and AGO2, which process pre-miRNAs into mature miRNAs. Cancer exosomes alter the transcriptome of target cells in a Dicer-dependent manner, which stimulate nontumorigenic epithelial cells to form tumors.This study identifies a mechanism whereby cancer cells impart an oncogenic field effect by manipulating the surrounding cells via exosomes. Presence of Dicer in exosomes may serve as biomarker for detection of cancer.


Dicers at RISC. The Mechanism of RNAi

Marcel Tijsterman and Ronald H.A. Plasterk
Cell, Apr 2014; 117:1–4

Figure 1. Model for RNA Silencing in Drosophila In an ordered biochemical pathway, miRNAs (left panel) and siRNAs (right panel) are processed from double-stranded precursor molecules by Dcr-1and Dcr-2, respectively, and stay attached to Dicer-containing complexes, which assemble into RISC. The degree of complementarity between the RNA silencing molecule (in red) and its cognate target determines the fate of the mRNA: blocked translation or immediate destruction.

Argonaute2 Cleaves the Anti-Guide Strand of siRNA during RISC Activation
Cell 2005; 123:621-629
http://www.cell.com/cgi/content/full/123/4/621/DC1/
Dicing and slicing- The core machinery of the RNA interference pathway
Scott C Hammond
FEBS Letters 579 (2005) 5822–5829
http://dx.doi.org:/10.1016/j.febslet.2005.08.079

Fig. 1. Domain organization of RNaseIII gene family. Three classes of RNaseIII genes are shown. The PAZ domain in Dm-Dicer-2 contains mutations in several residues required for RNA binding and may not be functional.

Fig. 2. Model for Dicer catalysis. The PAZ domain binds the 2 nt 30 overhang of a dsRNA terminus. The RNaseIII domains form a pseudo-dimer. Each domain hydrolyzes one strand of the substrate. The binding site of the dsRBD is not defined. The function of the helicase domain is not known.

Fig. 3. Biogenesis pathway of microRNAs. MicroRNA genes are transcribed by RNA polymerase II. The primary transcript is referred to as ‘‘primicroRNA’’. Drosha processing occurs in the nucleus. The resulting precursor, ‘‘pre-microRNA’’, is exported to the cytoplasm for Dicer processing. In a coordinated manner, the mature microRNA is transferred to RISC and unwound by a helicase. mRNA targets that duplex in the Slicer scissile site are cleaved and degraded, if the microRNA is loaded into an Ago2 RISC. Mismatched targets are translationally suppressed. All Ago family members are believed to function in translational suppression.

Fig. 4. Model for Slicer catalysis. The siRNA guide strand is bound at the 50 end by the PIWI domain and at the 30 end by the PAZ domain. The 50 phosphate is coordinated by conserved basic residues. mRNA targets are initially bound by the seed region of the siRNA and pairing is extended to the 30 end. The RNaseH fold hydrolyzes the target in a cation dependent manner. Slicer cleavage is measured from the 50 end of the siRNA. Product is released by an unknown mechanism and the enzyme recycles.

 

 

RNA interference (RNAi) is a biological process in which RNA molecules inhibit gene expression, typically by causing the destruction of specific mRNA molecules. Historically, it was known by other names, including co-suppression, post transcriptional gene silencing (PTGS), and quelling. Only after these apparently unrelated processes were fully understood did it become clear that they all described the RNAi phenomenon. Andrew Fire and Craig C. Mello shared the 2006 Nobel Prize in Physiology or Medicine for their work on RNA interference in the nematode worm Caenorhabditis elegans, which they published in 1998.

 

Two types of small ribonucleic acid (RNA) molecules – microRNA (miRNA) and small interfering RNA (siRNA) – are central to RNA interference. RNAs are the direct products of genes, and these small RNAs can bind to other specific messenger RNA (mRNA) molecules and either increase or decrease their activity, for example by preventing an mRNA from producing a protein. RNA interference has an important role in defending cells against parasitic nucleotide sequences – viruses and transposons. It also influences development.

 

The RNAi pathway is found in many eukaryotes, including animals, and is initiated by the enzyme Dicer, which cleaves long double-stranded RNA (dsRNA) molecules into short double stranded fragments of ~20 nucleotide siRNAs. Each siRNA is unwound into two single-stranded RNAs (ssRNAs), the passenger strand and the guide strand. The passenger strand is degraded and the guide strand is incorporated into the RNA-induced silencing complex (RISC). The most well-studied outcome is post-transcriptional gene silencing, which occurs when the guide strand pairs with a complementary sequence in a messenger RNA molecule and induces cleavage by Argonaute, the catalytic component of the RISC complex. In some organisms, this process spreads systemically, despite the initially limited molar concentrations of siRNA.
http://en.wikipedia.org/wiki/RNA_interference

 

http://upload.wikimedia.org/wikipedia/commons/thumb/e/e4/ShRNA_Lentivirus.svg/481px-ShRNA_Lentivirus.svg.png

 

http://www.frontiersin.org/files/Articles/66078/fnmol-06-00040-HTML/image_m/fnmol-06-00040-g001.jpg
http://dx.doi.org:/10.3389/fnmol.2013.00040

The enzyme dicer trims double stranded RNA, to form small interfering RNA or microRNA. These processed RNAs are incorporated into the RNA-induced silencing.
MiRNA biogenesis and function. (A) The canonical miRNA biogenesis pathway is Drosha- and Dicer-dependent. It begins with RNA Pol II-mediated transcription..

 

Dicer Promotes Transcription Termination

Dicer Promotes Transcription Termination

Dicer Promotes Transcription Termination at Sites of Replication Stress to Maintain Genome Stability
Cell Oct 2014; 159(3): 572–583
http://dx.doi.org/10.1016/j.cell.2014.09.031

http://www.cell.com/cms/attachment/2019646604/2039684570/fx1.jpg

 

18-13 miRNA- protein complex ap-chap-18-pp-42-728

18-13 miRNA- protein complex ap-chap-18-pp-42-728

18-13 miRNA- protein complex (a) Primary miRNA transcript Translation blocked Hydrogen bond (b) Generation and function of miRNAs Hairpin miRNA miRNA Dicer …

http://image.slidesharecdn.com/ap-chap-18-pp-1229097198123780-1/95/ap-chap-18-pp-42-728.jpg?cb=1229090143

 

 

Identification and characterization of small RNAs involved in RNA silencing
FEBS Letters 579 (2005) 5830–5840
http://dx.doi.org:/10.1016/j.febslet.2005.08.009

Fig. 1. Small RNA cloning procedure. Outline of the small RNA cloning procedure. RNA is dephosphorylated (step 1) for joining the 30 adapter by T4 RNA ligase 1 in the presence of ATP (step 2). The use of a chemically adenylated adapter and truncated form of T4 RNA ligase 2 (Rnl2) allows eliminating the dephosphorylation step (step 4). If the RNA was dephosphorylated, it is re-phosphorylated (step 3) prior to 50 adapter ligation with T4 RNA ligase 1 and ATP (step 5). After 50 adapter ligation, a standard reverse transcription is performed (step 6). Alternatively, after 30 adapter ligation, the RNA is used directly for reverse transcription simultaneously with 50 adaptor joining (step 7). In this case, the property of reverse transcriptase to add non-templated cytidine residues at the 50 end of synthesized DNA is used to facilitate template switch of the reverse transcriptase to the 30 guanosine residues of the 50 adapter (SMART technology, Invitrogen). Abbreviations: P and OH indicate phosphate and hydroxyl ends of the RNA; App indicates 50 chemically adenylated adapter; L, 30 blocking group; CIP, calf alkaline phosphatase and PNK, polynucleotide kinase.

 

Transcriptional regulatory functions of nuclear long noncoding RNAs
Trends in Genetics, Aug 2014; 30(8):348-356
http://dx.doi.org/10.1016/j.tig.2014.06.001

Cis-acting lncRNAEnhancer-associated lncRNAIntergenic lncRNA

lncRNA

Promoter-associated lncRNA

Proximity transfer

Trans-acting lncRNA

 

Functional interactions among microRNAs and long noncoding RNAs
Sem Cell Dev Biol 2014; 34:9-14
http://dx.doi.org/10.1016/j.semcdb.2014.05.015
Genome-wide application of RNAi to the discovery of potential drug targets
FEBS Letters 579 (2005) 5988–599
http://dx.doi.org://10.1016/j.febslet.2005.08.015

Fig. 1. Schematic representation of gene silencing by an shRNA-expression vector. The shRNA is processed by Dicer. The processed siRNA enters the RNA-induced silencing complex (RISC), where it targets mRNA for degradation.

Fig. 2. Schematic representation of a transcription system for production of siRNA

Fig. 3. (A) Schematic representation of the proposed siRNA-expression system. Three or four C to U or A to G mutations are introduced into the sense strand. (B) Schematic representation of the discovery of a novel gene using an siRNA library.

 

Imperfect centered miRNA binding sites are common and can mediate repression of target mRNAs
Martin et al. Genome Biology 2014, 15:R51 http://genomebiology.com/2014/15/3/R51

 

 

 

 

Table 1 Number of inferred targets for each miRNA tested

miRNA Probes Transcripts Genes
miR-10a 2,206 5,963 1,887
miR-10a-iso 1,648 1,468 4,211
miR-10b 1,588 3,940 1,365
miR-10b-iso 963 2,235 889
miR-17-5p 1,223 2,862 1,137
miR-17-5p-iso 1,656 3,731 1,461
miR-182 2,261 6,423 2,008
miR-182-iso 1,569 4,316 1,444
miR-23b 2,248 5,383 1,990
miR-27a 2,334 5,310 2,069

Probes: number of probes significantly enriched in pull-downs compared to controls (5% FDR). Transcripts: number of transcripts to which those probes map exactly. Genes: number of genes from which those transcripts originate

Figure 2 Biotin pull-downs identify bone fide miRNA targets. (A) Volcano plot showing the significance of the difference in expression between the miR-17-5p pull-down and the mock-transfected control, for all transcripts expressed in HEK293T cells. Both targets predicted by TargetScan or validated previously via luciferase assay were significantly enriched in the pull-down compared to the controls. (B) Results from luciferase assays on previously untested targets predicted using TargetScan and uncovered using the biotin pull-down. The plot indicates mean luciferase activity from either the empty plasmid or from pMIR containing a miRNA binding site in the 3′ UTR, relative to a negative control. Asterisks indicate a significant reduction in luciferase activity (one-sided t-test; P<0.05) and error bars the standard error of the mean over three replicates. (C-E) Targets identified through PAR-CLIP or through miRNA over-expression studies show greater enrichment in the pull-down. Cumulative distribution of log fold-change in the pull-down for transcripts identified as targets by the indicated miRNA over-expression study or not. Red, canonical transcripts found to be miR-17-5p targets in the indicated study (Table S5 in Additional file 1); black, all other canonical transcripts; p, one-sided P-value from Kolmogorov-Smirnov test for a difference in distributions. (F) To confirm that our results were dependent on RISC association, cells were transfected with either single or double-stranded synthetic miRNAs, then subjected to AGO2 immunoprecipitation. The biotin pull-down was performed in the AGO2-enriched and AGO2-depleted fractions. (G-H) Quantitative RT-PCR revealed that, with double-stranded (ds) miRNA (G), four out of five known targets were enriched relative to input mRNA (*P≤0.05, **P<0.01, ***P<0.001) in the AGO2-enriched but not in the AGO2-depleted fractions, but this enrichment was not seen for the cells transfected with a single-stranded (ss) miRNA (H). The numbers on the x-axis correspond to those in Figure 2F. Error bars represent the standard error of mean (sem).

Figure 5 IsomiRs and canonical miRNAs target many of the same transcripts.

Hammerhead ribozymes in therapeutic target discovery and validation
Drug Disc Today 2009; 14(15/16): 776-783
http://dx.doi.org/10.1016/j.drudis.2009.05.003

Figure 1. Features of hammerhead ribozymes. A generic diagram of a hammerhead ribozyme bound to its target substrate: NUH is the cleavage triplet on target sequence, stems I and III are sites of the specific interactions between ribozyme and target, stem II is the structural element connecting separate parts of the catalytic core. Arrows represent the cleavage site, numbering system according to Hertel et al. [60].

hammerhead ribozyme

hammerhead ribozyme

https://www-ssrl.slac.stanford.edu/research/highlights_archive/ribozyme_fig1.jpg

 

Figure 1  Schematic (A) and ribbon (B) diagrams depicting the crystal structure of the full-length hammerhead ribozyme. The sequence and secondary structure

 

TABLE 1 Typical examples of successful applications of hammerhead ribozymes. Most of the data are derived from [10] and [11], the others are expressly specified.

  • Growth factors, receptors, transduction elements
  • Oncogenes, protoncogenes, fusion genes
  • Apoptosis, survival factors, drug resistance
  • Transcription factors
  • Extracellular matrix, matrix modulating factors
  • Circulating factors
  • Viral genome, viral genes

Figure 2.Target–ribozyme interactions. (a) As cheme of ribozyme binding to full substrate. The calculated energy of this binding ensures the formation of a stable complex. At the denaturating temperature, Tm, will allow this complex to survive to biological conditions. Conversely, after cleavage, binding energies calculated on single, (b) and (c), ribozyme arms are very low and no longer stable. These properties will ensure both the efficient release of cleavage fragments and the prevention of binding to unrelated targets. RNAs complementary to one binding arm only will not be bound or cleaved by the hammerhead catalytic sequence.

Figure 3. ‘Chemical omics’ approach. According to this target discovery strategy: (1) a first round of ‘omic’ study (proteomic, genomic, metabolomic, …) will enable the discovery of a set of (2) putative markers. A series of hammerhead ribozymes will then be prepared in order to target each marker. (4) A second ‘omic’ study round will be performed on (3) knocked down samples obtained after ribozymes administration. (5) A new series of markers will then be produced. An expanding analytical process of this type may be further repeated. Finally, a robust bioinformatic algorithm will make it possible to connect the different markers and draw new hypothetical links and pathways.

 

miRNA

ADAR Enzyme and miRNA Story
Sara Tomaselli, Barbara Bonamassa, Anna Alisi, et al.
Int. J. Mol. Sci. 2013, 14, 22796-22816;
http://dx.doi.org:/10.3390/ijms141122796

Adenosine deaminase acting on RNA (ADAR) enzymes convert adenosine (A) to inosine (I) in double-stranded (ds) RNAs. Since Inosine is read as Guanosine, the biological consequence of ADAR enzyme activity is an A/G conversion within RNA molecules. A-to-I editing events can occur on both coding and non-coding RNAs, including microRNAs (miRNAs), which are small regulatory RNAs of ~20–23 nucleotides that regulate several cell processes by annealing to target mRNAs and inhibiting their translation. Both miRNA precursors and mature miRNAs undergo A-to-I RNA editing, affecting the miRNA maturation process and activity. ADARs can also edit 3′ UTR of mRNAs, further increasing the interplay between mRNA targets and miRNAs. In this review, we provide a general overview of the ADAR enzymes and their mechanisms of action as well as miRNA processing and function. We then review the more recent findings about the impact of ADAR-mediated activity on the miRNA pathway in terms of biogenesis, target recognition, and gene expression regulation.

Figure 1. Structure of ADAR family proteins: ADAR1, ADAR2, and ADAR3. The ADAR enzymes contain a C-terminal conserved catalytic deaminase domain (DM), two or three dsRBDs in the N-terminal portion. ADAR1 full-length protein also contains a N-terminal Zα domain with a nuclear export signal (NES) and a Zβ domain, while ADAR3 has a  R-domain. A nuclear localization signal is also indicated.

 

Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites
Doron Betel, Anjali Koppal, Phaedra Agius, Chris Sander, Christina Leslie
Genome Biology 2010, 11:R90 http://genomebiology.com/2010/11/8/R90

microRNAs are a class of small regulatory RNAs that are involved in post-transcriptional gene silencing. These small (approximately 22 nucleotide) single-strand RNAs guide a gene silencing complex to an mRNA by complementary base pairing, mostly at the 3′ untranslated region (3′ UTR). The association of the RNAinduced silencing complex (RISC) to the conjugate mRNA results in silencing the gene either by translational repression or by degradation of the mRNA. Reliable microRNA target prediction is an important and still unsolved computational challenge, hampered both by insufficient knowledge of microRNA biology as well as the limited number of experimentally validated targets.

mirSVR is a new machine learning method for ranking microRNA target sites by a down-regulation score. The algorithm trains a regression model on sequence and contextual features extracted from miRanda-predicted target sites. In a large-scale evaluation, miRanda-mirSVR is competitive with other target prediction methods in identifying target genes and predicting the extent of their downregulation at the mRNA or protein levels. Importantly, the method identifies a significant number of experimentally determined non-canonical and non-conserved sites.
Human RISC – MicroRNA Biogenesis and Posttranscriptional Gene Silencing
Cell 2005; 123:631-640
http://dx.doi.org:/10.1016/j.cell.2005.10.022
Development of microRNA therapeutics
Eva van Rooij & Sakari Kauppinen
EMBO Mol Med (2014) 6: 851–864
http://dx.doi.org:/10.15252/emmm.20110089

MicroRNAs (miRNAs) play key regulatory roles in diverse biological processes and are frequently dysregulated in human diseases. Thus, miRNAs have emerged as a class of promising targets for therapeutic intervention. Here, we describe the current strategies for therapeutic modulation of miRNAs and provide an update on the development of miRNA-based therapeutics for the treatment of cancer, cardiovascular disease and hepatitis C virus (HCV) infection.

Figure 1. miRNA biogenesis and modulation of miRNA activity by miRNA mimics and antimiR oligonucleotides. MiRNA genes are transcribed by RNA polymerase II from intergenic, intronic or polycistronic loci to long primary miRNA transcripts (pri-miRNAs) and processed in the nucleus by the Drosha–DGCR8 complex to approximately 70 nt pre-miRNA hairpin structures. The most common alternative miRNA biogenesis pathway involves short intronic hairpins, termed mirtrons, that are spliced and debranched to form pre-miRNA hairpins. Pre-miRNAs are exported into the cytoplasm and then cleaved by the Dicer–TRBP complex to imperfect miRNA: miRNA* duplexes about 22 nucleotides in length. In the cytoplasm, miRNA duplexes are incorporated into Argonaute-containing miRNA induced silencing complex (miRISC), followed by unwinding of the duplex and retention of the mature miRNA strand in miRISC, while the complementary strand is released and degraded. The mature miRNA functions as a guide molecule for miRISC by directing it to partially complementary sites in the target mRNAs, resulting in translational repression and/or mRNA degradation. Currently, two strategies are employed to modulate miRNA activity: restoring the function of a miRNA using double-stranded miRNA mimics, and inhibition of miRNA function using single-stranded anti-miR oligonucleotides.

Figure 2. Design of chemically modified miRNA modulators. (A) Structures of chemical modifications used in miRNA modulators. A number of different sugar modifications are used to increase the duplex melting temperature (Tm) of anti-miR oligonucleotides. The20-O-methyl(20-O-Me), 20-O-methoxyethyl(20-MOE )and 20-fluoro(20-F) nucleotides are modified at the 20 position of the sugar moiety, whereas locked nucleic acid (LNA) is a bicyclic RNA analogue in which the ribose is locked in a C30-endo conformation by introduction of a 20-O,40-C methylene bridge. To increase nuclease resistance and enhance the pharmacokinetic properties, most anti-miR oligonucleotides harbor phosphorothioate (PS) backbone linkages, in which sulfur replaces one of the non-bridging oxygen atoms in the phosphate group. In morpholino oligomers, a six-membered morpholine ring replaces the sugar moiety. Morpholinos are uncharged and exhibit a slight increase in binding affinity to their cognate miRNAs. PNA oligomers are uncharged oligonucleotide analogues, in which the sugar–phosphate backbone has been replaced by a peptide-like backbone consisting of N-(2-aminoethyl)-glycine units. (B) An example of a synthetic double-stranded miRNA mimic described in this review. One way to therapeutically mimic a miRNA is by using synthetic RNA duplexes that harbor chemical modifications for improved stability and cellular uptake. In such constructs, the antisense (guide) strand is identical to the miRNA of interest, while the sense (passenger) strand is modified and can be linked to a molecule, such as cholesterol, for enhanced cellular uptake. The sense strand contains chemical modifications to prevent mi-RISC loading. Several mismatches can be introduced to prevent this strand from functioning as an anti-miR, while it is further left unmodified to ensure rapid degradation.The20-F modification helps to protect the antisense strand against exonucleases, hence making the guide strand more stable, while it does not interfere with mi-RISC loading. (C) Design of chemically modified anti-miR oligonucleotides described in this review. Antagomirs are30 cholesterol-conjugated,20-O-Me oligonucleotides fully complementary to the mature miRNA sequence with several PS moieties to increase their in vivo stability. The use of unconjugated 20-F/MOE-, 20-MOE- or LNA-modified anti-miR oligonucleotides harboring a complete PS backbone represents another approach for inhibition of miRNA function in vivo. The high duplex melting temperature of LNA-modified oligonucleotides allows efficient miRNA inhibition using truncated, high-affinity 15–16-nucleotide LNA/DNA anti-miR oligonucleotides targeting the 50 region of the mature miRNA. Furthermore, the high binding affinity of fully LNA-modified 8-mer PS oligonucleotides, designated as tiny LNAs, facilitates simultaneous inhibition of entire miRNA seed families by targeting the shared seed sequence.

Human MicroRNA Targets
Bino John, Anton J. Enright, Alexei Aravin, Thomas Tuschl,.., Debora S. Mark
PLoS Biol 2004; 2(11): e363  http://www.plosbiology.org

More than ten years after the discovery of the first miRNA gene, lin-4 (Chalfie et al. 1981; Lee et al. 1993), we know that miRNA genes constitute about 1%–2% of the known genes in eukaryotes. Investigation of miRNA expression combined with genetic and molecular studies in Caenorhabditis elegans, Drosophila melanogaster, and Arabidopsis thaliana have identified the biological functions of several miRNAs (recent review, Bartel 2004). In C. elegans, lin-4 and let-7 were first discovered as key regulators of developmental timing in early larval developmental transitions (Ambros 2000; Abrahante et al. 2003; Lin et al. 2003; Vella et al. 2004). More recently lsy-6 was shown to determine the left–right asymmetry of chemoreceptor expression (Johnston and Hobert 2003). In D. melanogaster, miR-14 has a role in apoptosis and fat metabolism (Xu et al. 2003) and the bantam miRNA targets the gene hid involved in apoptosis and growth control (Brennecke et al. 2003).

MicroRNAs (miRNAs) interact with target mRNAs at specific sites to induce cleavage of the message or inhibit translation. The specific function of most mammalian miRNAs is unknown. We have predicted target sites on the 39 untranslated regions of human gene transcripts for all currently known 218 mammalian miRNAs to facilitate focused experiments. We report about 2,000 human genes with miRNA target sites conserved in mammals and about 250 human genes conserved as targets between mammals and fish. The prediction algorithm optimizes sequence complementarity using position-specific rules and relies on strict requirements of interspecies conservation. Experimental support for the validity of the method comes from known targets and from strong enrichment of predicted targets in mRNAs associated with the fragile X mental retardation protein in mammals. This is consistent with the hypothesis that miRNAs act as sequence-specific adaptors in the interaction of ribonuclear particles with translationally regulated messages. Overrepresented groups of targets include mRNAs coding for transcription factors, components of the miRNA machinery, and other proteins involved in translational regulation, as well as components of the ubiquitin machinery, representing novel feedback loops in gene regulation. Detailed information about target genes, target processes, and open-source software for target prediction (miRanda) is available at http://www.microrna.org. Our analysis suggests that miRNA genes, which are about 1% of all human genes, regulate protein production for 10% or more of all human genes.

Figure 1. Target Prediction Pipeline for miRNA Targets in Vertebrates The mammalian (human, mouse, and rat) and fish (zebra and fugu) 39 UTRs were first scanned for miRNA target sites using position specific rules of sequence complementarity. Next, aligned UTRs of orthologous genes were used to check for conservation of miRNA– target relationships (‘‘target conservation’’) between mammalian genomes and, separately, between fish genomes. The main results (bottom) are the conserved mammalian and conserved fish targets, for each miRNA,as well as a smaller set of super-conserved vertebrate targets.   http://dx.doi.org:/10.1371/journal.pbio.0020363.g00
Figure 2. Distribution of Transcripts with Cooperativity of Target Sites and Estimated Number of False Positives Each bar reflects the number of human transcripts with a given number of target sites on their UTR. Estimated rate of false positives(e.g., 39%for2 targets) is given by the number of target sites predicted using shuffled miRNAs processed in a way identical to real miRNAs, including the use of interspecies conservation filter. http://dx.doi.org:/10.1371/journal.pbio.0020363.g002

Conserved Seed Pairing, Often improved an-Flanked by Adenosines, Indicates Thousands of Human Genes are MicroRNA Targets
Cell, Jan 2005; 120: 15–20
http://dx.doi.org:/10.1016/j.cell.2004.12.035

Integrated analysis of microRNA and mRNA expression. adding biological significance to microRNA target predictions.
Maarten van Iterson, Sander Bervoets, Emile J. de Meijer, et al.
Nucleic Acids Research, 2013; 41(15), e146
http://dx.doi.org:/10.1093/nar/gkt525

Current microRNA target predictions are based on sequence information and empirically derived rules but do not make use of the expression of microRNAs and their targets. This study aimed to improve microRNA target predictions in a given biological context, using in silico predictions, microRNA and mRNA expression. We used target prediction tools to produce lists of predicted targets and used a gene set test designed to detect consistent effects of microRNAs on the joint expression of multiple targets. In a single test, association between microRNA expression and target gene set expression as well as the contribution of the individual target genes on the association are determined. The strongest negatively associated mRNAs as measured by the test were prioritized. We applied our integration method to a well-defined muscle differentiation model. Validation of our predictions in C2C12 cells confirmed predicted targets of known as well as novel muscle-related microRNAs. We further studied associations between microRNA–mRNA pairs in human prostate cancer, finding some pairs that have been recently experimentally validated by others. Using the same study, we showed the advantages of the global test over Pearson correlation and lasso. We conclude that our integrated approach successfully identifies regulated microRNAs and their targets.

Long non-coding RNA and microRNAs might act in regulating the expression of BARD1 mRNAs
Int J Biol & Cell Biol 2014; 54:356-367
http://dx.doi.org/10.1016/j.biocel.2014.06.018

 

Passenger-Strand Cleavage Facilitates Assembly of siRNA into Ago2-Containing RNAi Enzyme Complexes
Cell 2006; 123:607-620
http://dx.doi.org:/10.1016/j.cell.2006.08.044

 

RNAi- RISC Gets Loaded
Cell 2005; 123:543-553
http://dx.doi.org:/10.1016/j.cell.2005.11.006
RNAi- The Nuts and Bolts of the RISC Machine
Cell 2005; 122:17-20
http://dx.doi.org:/10.1016/j.cell.2005.06.023
Structural domains in RNAi
FEBS Letters 579 (2005) 5841–5849
http://dx.doi.org:/10.1016/j.febslet.2005.07.072

Fig. 1. A ‘‘Domain-centric’’ view of RNAi. (A) The conserved pathways of RNA silencing. The domain structure of each protein in (hypothetical) interaction with its RNA is shown. For clarity, the second column lists domains in order N- to C-terminal. Figures are not to scale. In brief, Drosha, an RNase III enzyme, and its obligate binding partner, Pasha recognize pri-mRNA loops, and cut these into 70 nt hairpin pre-miRNAs. Dicer utilizes a PAZ domain to sense the 30 2-nt overhang created, and further processes these, and dsRNAs into miRNAs and siRNAs. Argonaute binds the 50 end of guide RNAs via its PIWI domain, and the 30 end via a PAZ domain, yielding RISCs that effect RNA silencing through several mechanisms. A Viral protein, VP19 can suppress RNA silencing by sequestering siRNAs. (B) A summary of known siRNA structural biology. Listed by domain are solved structures, their protein/organism of origin, and ligands, where applicable. Also shown are PDB codes.

Fig. 2. Novel modes of RNA recognition. (A) A typical dsRBD: Xenopus binding protein A (1DI2). A RNA helix is modeled pink, and the protein is rendered in transparent electrostatic contours (blue is basic, red acidic). Note the interaction of helices along the major groove, and the position of helix 1. A second dsRBD protein is visible, in the lower right. (B) A dsRBD, Saccharomyces Rnt1P (1T4L), recognizes hairpin loops. A novel third helix (top) pushes helix one into the loop of a hairpin RNA. (C) 30-OH recognition by PAZ. Human Eif2c1 (1SI3) bound to RNA (pink) is shown. PAZ is green, with transparent electrostatic surface plot. The OB-fold (nucleotide binding fold) and the insertion domain are labeled. Note the glove-and-thumb like cleft they form, that the 30-OH is inserted into. A basic groove (blue) the RNA binds along outside the cleft is visible. (D) A close-up view of PAZ, as in C (surface not-transparent, slightly rotated). See white arrows for orientation, and location of 30-OH binding site. RNA is shown red in sticks. The terminal –OH is barely visible, buried in a cleft. It and the carbon it bonds have been colored yellow for clarity. (E) The PIWI domain (2BGG). Note the insertion of the 50P red (labeled) into the binding site. Its complimentary strand (pink) is not annealed to it, and the 30 overhang and first complimentary bases sit on the protein surface. (F) An enlarged view of (E), with protein in slate and RNA modeled as red sticks. The coordinated magnesium is a grey sphere, which is coordinated by the terminal carboxylate of the protein, protein side chains, and RNA phosphate oxygens. The 50 base stacks against a conserved Tyr. Several other sidechain contacts are shown.

Fig. 3. Argonaute/RISC. (A) P. furiosus Argonaute (PDB 1Z26). A color-guided key to the domains is presented. PAZ sits over the PIWI/N/MID bowl and active site. The liganding atoms for the catalytic metal are depicted as yellow balls for clarity. The tungstate binding site (50P surrogate) is shown as tan spheres. (B) A guide strand channel. Looking down from the PAZ domain towards the active site, Z-sections are clipped off. Colors of domains are as in the key in (A). Wrapping down along a basic cleft from the PAZ 30OH binding site (approximate position labeled), a RNA binding groove passes the active site (yellow), and runs down to the 50P binding site (tan balls). A second cleft running perpendicular to this one at its entry may accommodate target strand RNA. For more detail, and models of siRNA placed into the grooves, see [27,29].

Fig. 4. VP19 sequestration of siRNA. (A) CIRV VP19 (1RPU, RNA removed). Two monomers (blue and cyan) form an 8 strand, concave b-sheet with bracketing helices at the ends. (B) Tombus viral VP19 bound to siRNA (1 monomer shown). RNA strands are modeled as sticks, with one strand pink and one red. The bracketing helix places two tryptophans in position to stack over the terminal RNA bases. On the b-sheet surface, and Arg and a Lys interact with the phosphate backbone, and at the center of the RNA binding surface, a number of Ser and Thr mediate an extensive hydrogen bond network. Both the Trp brackets and RNA binding by an extended b-sheet are unique.

 

Small RNA asymmetry in RNAi- Function in RISC assembly and gene regulation
FEBS Letters 579 (2005) 5850–5857
http://dx.doi.org:/10.1016/j.febslet.2005.08.071

 

The role of the oncofetal IGF2 mRNA-binding protein 3 (IGF2BP3) in cancer
Seminars in Cancer Biol 2014; 29:3-12
http://dx.doi.org/10.1016/j.semcancer.2014.07.006

Table 1 – Target mRNAs of IGF2BP3.

Target cis-Element Regulation
CD44 3’ -utr Control of mRNA stability
IGF2 5’ -utr Translational control
H19 ncRNA Unknown
ACTB 3’ -utr Unknown
MYC CRD Unknown
CD164 Unknown Control of mRNA stability
MMP9 Unknown Control of mRNA stability
ABCG2 Unknown Unknown
PDPN 3’ -utr Control of mRNA stability
HMGA2 3’ -utr Protection from miR directed degradation
CCND1 3’ -utr translational control
CCND3 3’ -utr translational control
CCNG1 3’ -utr translationalcontrol

 

Targeting glucose uptake with siRNA-based nanomedicine for cancer therapy
Biomaterials 2015; 51:1-11
http://dx.doi.org/10.1016/j.biomaterials.2015.01.068
The therapeutic potential of RNA interference
FEBS Letters 579 (2005) 5996–6007
http://dx.doi.og:/10.1016/j.febslet.2005.08.004

Table 1 Companies developing RNAi therapeutics that includes cancer

Company name Primary areas of interest
Atugen AG Metabolic disease; cancer ocular disease; skin disease
Benitec Australia Limited Hepatitis C virus; HIV/AIDS; cancer; diabetes/obesity
Calando Pharmaceuticals Nanoparticle technology
Genta Incorporated Cancer
Intradigm Corporation Cancer; SARS; arthritis
Sirna Therapeutics, Inc. AMD; Hepatitis C virus; asthma; diabetes; cancer; Huntington s disease; hearing loss

 

The Noncoding RNA Revolution—Trashing Old Rules to Forge New Ones
Cell 2014; 157:77-94
http://dx.doi.org/10.1016/j.cell.2014.03.008

Figure 1. Noncoding RNAs Function in Diverse Contexts Noncoding RNAs function in all domains of life, regulating gene expression from transcription to splicing to translation and contributing to genome organization and stability. Self-splicing RNAs, ribosomes, and riboswitches function in both eukaryotes and bacteria. Archaea (not shown) also utilize ncRNA systems including ribosomes, riboswitches, snoRNPs, and CRISPR. Orange strands, ncRNA performing the action indicated; red strands, the RNA acted upon by the ncRNA. Blue strands, DNA. Triangle, small-molecule metabolite bound by a riboswitch. Ovals indicate protein components of an RNP, such as the spliceosome (white oval), ribosome (two purple subunits), or other RNPs (yellow ovals). Because of the importance of RNA structure in these ncRNAs, some structures are shown but they are not meant to be realistic.

 

miRNAs and cancer targeting

Table 1 of targets

miRNA Cancer type reference
NA GI cancer Current status of miRNA-targeting therapeutics and preclinical studies against gastroenterological carcinoma
NA Renal cell Differential expression profiling of microRNAs and their potential involvement in renal cell carcinoma pathogenesis
NA urothelial
cancer
A microRNA expression ratio defining the invasive phenotype in bladder tumors
miR-31 breast A Pleiotropically Acting MicroRNA, miR-31, inhibits breast cancer growth
miR-512-3p NSCLC Inhibition of RAC1-GEF DOCK3 by miR-512-3p contributes to suppression of metastasis in non-small cell lung cancer
miR-495 gastric Methylation-associated silencing of miR-495 inhibit the migration and invasion of human gastric cancer cells
microRNA-218 prostate microRNA-218 inhibits prostate cancer cell growth and promotes apoptosis by repressing TPD52 expression
MicroRNA-373 cervical cancer MicroRNA-373 functions as an oncogene and targets YOD1 gene in cervical cancer
miR-25 NSCLC miR-25 modulates NSCLC cell radio-sensitivity – inhibiting BTG2 expression
miR-92a cervical cancer miR-92a. upregulated in cervical cancer & promotes cell proliferation and invasion by targeting FBXW7
MiR-153 NSCLC MiR-153 inhibits migration and invasion of human non-small-cell lung cancer by targeting ADAM19
miR-203 melanoma miR-203 inhibits melanoma invasive and proliferative abilities by targeting the polycomb group gene BMI1
miR-204-5p Papillary thyroid miR-204-5p suppresses cell proliferation by inhibiting IGFBP5 in papillary thyroid carcinoma
miR-342-3p Hepato-cellular miR-342-3p affects hepatocellular carcinoma cell proliferation via regulating NF-κB pathway
miR-1271 NSCLC miR-1271 promotes non-small-cell lung cancer cell proliferation and invasion via targeting HOXA5
miR-203 pancreas Pancreatic cancer derived exosomes regulate the expression of TLR4 in dendritic cells via miR-203
miR-203 metastatic SCC Rewiring of an Epithelial Differentiation Factor, miR-203, to Inhibit Human SCC Metastasis
miR-204 RCC TRPM3 and miR-204 Establish a Regulatory Circuit that Controls Oncogenic Autophagy in Clear Cell Renal Cell Carcinoma
NA urologic MicroRNAs and cancer. Current and future perspectives in urologic oncology
NA RCC MicroRNAs and their target gene networks in renal cell carcinoma
NA osteoSA MicroRNAs in osteosarcoma
NA urologic MicroRNA in Prostate, Bladder, and Kidney Cancer
NA urologic Micro-RNA profiling in kidney and bladder cancers

 

Current status of miRNA-targeting therapeutics and preclinical studies against gastroenterological carcinoma
Shibata et al. Molecular and Cellular Therapies 2013, 1:5 http://www.molcelltherapies.com/content/1/1/5

Differential expression profiling of microRNAs and their potential involvement in renal cell carcinoma pathogenesis
Clinical Biochemistry 43 (2010) 150–158
http://dx.doi.org:/10.1016/j.clinbiochem.2009.07.020

A microRNA expression ratio defining the invasive phenotype in bladder tumors
Urologic Oncology: Seminars and Original Investigations 28 (2010) 39–48
http://dx.doi.org:/10.1016/j.urolonc.2008.06.006

A Pleiotropically Acting MicroRNA, miR-31, inhibits breast cancer growth
Cell 137, 1032–1046, June 12, 2009
http://dx.doi.org:/10.1016/j.cell.2009.03.047

Inhibition of RAC1-GEF DOCK3 by miR-512-3p contributes to suppression of metastasis in non-small cell lung cancer
Intl JBiochem & Cell Biol 2015; 61:103-114
http://dx.doi.org/10.1016/j.biocel.2015.02.005

Methylation-associated silencing of miR-495 inhibit the migration and invasion of human gastric cancer cells by directly targeting PRL-3
Biochem Biochem Res Commun 2014; 456:344-350
http://dx.doi.org/10.1016/j.bbrc.2014.11.083

microRNA-218 inhibits prostate cancer cell growth and promotes apoptosis by repressing TPD52 expression
Biochem Biophys Res Commun 2015; 456:804-809
http://dx.doi.org/10.1016/j.bbrc.2014.12.026

MicroRNA-373 functions as an oncogene and targets YOD1 gene in cervical cancer
BBRC 2015; xx:1-6
http://dx.doi.org/10.1016/j.bbrc.2015.02.138

miR-25 modulates NSCLC cell radio-sensitivity – inhibiting BTG2 expression
BBRC 2015; 457:235-241
http://dx.doi.org/10.1016/j.bbrc.2014.12.094

miR-92a. upregulated in cervical cancer & promotes cell proliferation and invasion by targeting FBXW7
BBRC 2015; 458:63-69
http://dx.doi.org/10.1016/j.bbrc.2015.01.066

MiR-153 inhibits migration and invasion of human non-small-cell lung cancer by targeting ADAM19
BBRC 2015; 456:381-385
http://dx.doi.org/10.1016/j.bbrc.2014.11.093

miR-203 inhibits melanoma invasive and proliferative abilities by targeting the polycomb group gene BMI1
BBMC 2015; 456: 361-366
http://dx.doi.org/10.1016/j.bbrc.2014.11.087

miR-204-5p suppresses cell proliferation by inhibiting IGFBP5 in papillary thyroid carcinoma
BBRC 2015; 457:621-627
http://dx.doi.org/10.1016/j.bbrc.2015.01.037

miR-342-3p affects hepatocellular carcinoma cell proliferation via regulating NF-κB pathway
BBRC 2015; 457:370-377
http://dx.doi.org/10.1016/j.bbrc.2014.12.119

miR-1271 promotes non-small-cell lung cancer cell proliferation and invasion via targeting HOXA5
BBRC 2015; 458:714-719
http://dx.doi.org/10.1016/j.bbrc.2015.02.033

Pancreatic cancer derived exosomes regulate the expression of TLR4 in dendritic cells via miR-203
Cell Immunol 2014; 292:65-69
http://dx.doi.org/10.1016/j.cellimm.2014.09.004

Rewiring of an Epithelial Differentiation Factor, miR-203, to Inhibit Human Squamous Cell Carcinoma Metastasis
Cell Reports 2014; 9:104-117
http://dx.doi.org/10.1016/j.celrep.2014.08.062

TRPM3 and miR-204 Establish a Regulatory Circuit that Controls Oncogenic Autophagy in Clear Cell Renal Cell Carcinoma
Cancer Cell Nov 10, 2014; 26: 738–753
http://dx.doi.org/10.1016/j.ccell.2014.09.015

MicroRNA in Prostate, Bladder, and Kidney Cancer
Eur Urol 2011; 59:671-681
http://dx.doi.org/10.1016/j.eururo.2011.01.044

Micro-RNA profiling in kidney and bladder cancers
Urologic Oncology: Seminars and Original Investigations 2007; 25:387–392
http://dx.doi.org:/10.1016/j.urolonc.2007.01.019

MicroRNAs and cancer. Current and future perspectives in urologic oncology
Urologic Oncology: Seminars and Original Investigations 2010; 28:4–13
http://dx.doi.org:/10.1016/j.urolonc.2008.10.021

MicroRNAs and their target gene networks in renal cell carcinoma
BBRC 2011; 405:153-156
http://dx.doi.org/10.1016/j.bbrc.2011.01.019

MicroRNAs in osteosarcoma
Clin Chim Acta 2015; 444:9-17
http://dx.doi.org/10.1016/j.cca.2015.01.025

 

Table 2. miRNA cancer therapeutics

 

 

  • miRNA and mRNA cancer signatures determined by analysis of expression levels in large cohorts of patients
    | PNAS | Nov 19, 2013; 110(47): 19160–19165
    http://www.pnas.org/cgi/doi/10.1073/pnas.1316991110The study of mRNA and microRNA (miRNA) expression profiles of cells and tissue has become a major tool for therapeutic development. The results of such experiments are expected to change the methods used in the diagnosis and prognosis of disease. We introduce surprisal analysis, an information-theoretic approach grounded in thermodynamics, to compactly transform the information acquired from microarray studies into applicable knowledge about the cancer phenotypic state. The analysis of mRNA and miRNA expression data from ovarian serous carcinoma, prostate adenocarcinoma, breast invasive carcinoma, and lung adenocarcinoma cancer patients and organ specific control patients identifies cancer-specific signatures. We experimentally examine these signatures and their respective networks as possible therapeutic targets for cancer in single cell experiments.

 

 

RNA editing is vital to provide the RNA and protein complexity to regulate the gene expression. Correct RNA editing maintains the cell function and organism development. Imbalance of the RNA editing machinery may lead to diseases and cancers. Recently,RNA editing has been recognized as a target for drug discovery although few studies targeting RNA editing for disease and cancer therapy were reported in the field of natural products. Therefore, RNA  editing may be a potential target for therapeutic natural products

 

Aberrant microRNA (miRNA) expression is implicated in tumorigenesis. The underlying mechanisms are unclear because the regulations of each miRNA on potentially hundreds of mRNAs are sample specific.

 

We describe a novel approach to infer Probabilistic Mi RNA–mRNA  Interaction Signature (‘ProMISe’) from a single pair of miRNA–mRNA expression profile. Our model considers mRNA and miRNA competition as a probabilistic function of the expressed seeds (matches). To demonstrate ProMISe, we extensively exploited The Cancer Genome Atlas data. As a target predictor, ProMISe identifies more confidence/validated targets than other methods. Importantly, ProMISe confers higher cancer diagnostic power than using expression profiles alone.

Gene set enrichment analysis on averaged ProMISe uniquely revealed respective target enrichments of oncomirs miR-21 and 145 in glioblastoma and ovarian cancers. Moreover, comparing matched breast (BRCA) and thyroid (THCA) tumor/normal samples uncovered thousands of tumor-related interactions. For example, ProMISe– BRCA network involves miR-155/183/21, which exhibits higher ProMISe coupled with coherently higher miRNA expression and lower target expression; oncomirs miR-221/222 in the ProMISe–THCA network engage with many downregulated target genes. Together, our probabilistic approach of integrating expression and sequence scores establishes a functional link between the aberrant miRNA and mRNA expression, which was previously under-appreciated due to the methodological differences.

 

 

 

 

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2.0 Genomics and Epigenetics: Genetic Errors and Methodologies – Cancer and Other Diseases

Writer and Curator: Larry H Bernstein, MD, FCAP

This is the second article in a series concerning genomic expression, The first of which was concerned with the expanded technologies in use for study of genomic expression.  This portion will also cover more of genetic errors as well as methodologies, but not all examples are in the realm of cancer.

I shall start with a New York Times editorial on July 24, 2015 by Angelina Jolie Pitt on her experience with BRCA1 gene and her family history.  It is very instructive on how she worked through her experience.

http://www.nytimes.com/2015/03/24/opinion/angelina-jolie-pitt-diary-of-a-surgery.html?

Two years ago she was found to have a positive test for BRCA1, carrying an 87 percent risk for breast cancer and a 50 percent risk for ovarian cancer.  At that time she had a preventive mastectomy.  The decision was not easy, but it also brought into consideration that her mother and grandmother both died of breast cancer.  She did not have an oophorectomy at that time because on considering the advice of medical experts, she would have been left with no estrogen support. She wanted to delay her early vegetative senescence.  She has reached the age of 39 years and on the advice of medical expert opinion, she proceeded with salpingo-oophorectomy, at age 39 years, a decade before  her  mother had developed cancer.  But her delay was to allow her to recover and adjust emotionally to her ongoing situation, with a remaining risk for ovarian cancer.

She tested negative for CA-1251-5 at this time prior to surgery. But the CA-125 test could well be negative with early onset ovarian cancer. It may be considered a better test for following treatment than for early diagnosis. Her choice was to sacrifice early menopause to the ability to live through her childrens’ childhood development.  This was a well thought out decision.  In addition, there were abnormal inflammatory markers that were not specific for cancer rsik, but were worth taking into account.  The procedure itself was simpler than the mastectomy.

23op-ed-thumbStandard

http://static01.nyt.com/images/2015/03/23/opinion/23op-ed/23op-ed-master315.jpg

2.1  CA-125 and Ovarian Cancer

2.1.1  lmmunoradiometric Assay of CA 125 in Effusions: Comparison with Carcinoembryonic Antigen

Marguerite M. Pinto, MD,‘ Larry H. Bernstein, MD,* Dennis A. Brogan, MPH, MT

and Elaine Criscuolo, CT(ASCP) CMIACS

The levels of CA 125 antigen were measured in 167 effusions from 150 patients using radioimmunoassay, and the results compared with the levels of carcinoembryonic antigen (CEA) in the fluids. The results indicate that an elevated fluid CA 125 level (>14,000 U/ml-68,000 U/ml) and a negative fluid CEA level (4 ng/ml) is suggestive of serous and endometrioid carcinoma of ovary, and adenocarcinoma of the endometrium and fallopian tube. Alternatively, an elevated fluid CEA level (14 ng/ml-600 ng/ml) and a negative CA 125 level (20-5000 U/ml) is seen in metastatic carcinomas of breast, lung, gastrointestinal tract, and mucinous ystadenocarcinoma. Lymphomas, melanomas, and benign effusions are negative for both antigens. The combined use of CEA and CA 125 antigen in fluids is useful in the differential diagnosis of adenocarcinoma of unknown primary. Cancer 59:218-222, 1987.

2.1.2 CA-125 in fine-needle aspirates of solid tumors: comparison with cytologic diagnosis and carcinoembryonic antigen (CEA) assay.

Marguerite M. Pinto, S Kotta

Diagnostic Cytopathology 03/1996; 14(2):121-5.
http://dx.doi.org:/10.1002/(SICI)1097-0339(199603)14:2<121::AID-DC4>3.0.CO;2-M

One hundred and twenty-two fine needle aspirates (FNA) from female patients were studied to determine whether CA-125 assay contributed to cytologic diagnosis and CEA assay. Cytologic examination was done on Papanicolaou-stained smears and cell blocks, CEA by EIA (Abbott Laboratory, > 5 ng/ml cutoff) and CA-125 by RIA (Abbott Laboratory, North Chicago, IL, > 66 mu/ml cutoff). Final diagnosis were correlated with histologic diagnosis when available, clinical, radiologic studies, and follow-up. Results: 29 benign, 93 malignant. Sensitivities and specificities: cytology, 91%, 100%; CEA: 59%, 86%; CA-125, 50%, 55%. CEA plus cytology sensitivity, 97%. CA-125 content was highest in endometrial/ovarian carcinoma (39,899 mu/ml) and < 5,000 mu/ml in other tumors and benign FNA in contrast to CEA which showed highest levels in carcinomas of colon, pancreas, and lung (> 280 ng/ml). While elevated CEA enhances the sensitivity of cytologic diagnosis of carcinomas of the colon, pancreas, and lung, low CEA and high CA-125 content supports an ovarian/endometrial primary.

2.1.3  Diagnostic efficiency of carcinoembryonic antigen and CA125 in the cytological evaluation of effusions.

Pinto MM, Bernstein LH, Rudolph RA, Brogan DA, Rosman M.
Arch Pathol Lab Med. 1992 Jun; 116(6):626-31.

In our previous study, the combination of the concentrations of carcinoembryonic antigen (CEA) and CA125 and the findings from cytological examination in 189 benign and malignant pleural and peritoneal effusions was useful in the diagnosis/classification of malignant effusions. Sensitivity of CEA (level, greater than 5 ng/mL) was 68%; specificity was 99% for the diagnosis of malignant effusions secondary to carcinoma of the lung, breast, gastrointestinal tract, and mucinous carcinoma of the ovary. Sensitivity of CA125 (level, greater than 5000 U/mL) was 85%; specificity was 96% for the diagnosis of malignant effusions in carcinoma of the ovary, fallopian tube, and endometrium. We now expanded the study to include 840 pleural and peritoneal effusions (benign, n = 520; malignant, n = 320) and analyzed the data by the statistical method of Rudolph and colleagues. Based on new cutoff values, ie, CEA level at 6.3 ng/mL and CA125 level at 3652 U/mL, the sensitivities for detection of malignant effusions secondary to carcinomas of the lung, breast, and gastrointestinal tract and mucinous carcinoma of the ovary varied between 75% and 100%; specificity was 98%. Sensitivity of CA125 for detection of malignant effusions from müllerian epithelial carcinoma was 71%; specificity was 99%. The elevated CEA fluid level alone helped to diagnose malignant effusions of the gastrointestinal tract in 54%, breast in 19%, and lung in 16%. The high CA125 fluid level was predictive of müllerian epithelial carcinoma. Adjunctive use of CEA and CA125 levels in fluid enhances the sensitivity of cytological diagnosis and may be predictive of the primary site in patients who present with carcinoma of an unknown primary source.

2.2 Carcinoembryonic antigen in diagnostics

2.2.1 Carcinoembryonic antigen content in fine needle aspirates of the lung. A diagnostic adjunct to cytology.

Pinto MM1, Ha DJ.
Acta Cytol. 1992 May-Jun; 36(3):277-82

Carcinoembryonic Antigen (CEA) was measured in 59 consecutive fine needle aspirates (FNAs) of the lung from 58 patients to determine if the CEA content would enhance the sensitivity of the cytologic diagnosis. Twenty-eight males and 30 females with tumors 1-40 cm in diameter were studied. Final diagnoses were correlated with the clinical history, radiologic studies, tissue (when available) and follow-up. Image-guided FNAs were performed by radiologists using a 22-gauge Chiba needle and 20-mL syringe with one to four passes per specimen. Cytologic examination included rapid assessment in the radiology suite and a final diagnosis in 24 hours. CEA was measured by enzyme immunoassay using monoclonal antibody. Nine benign aspirates and 50 malignant aspirates were diagnosed. The sensitivity of cytology was 86% and specificity, 100%. Using 5 ng/mL as the cutoff, the sensitivity of CEA for malignant aspirates was 50% and specificity, 90%. The combined sensitivity of CEA and cytology was 95%. The mean CEA in malignant aspirates was 131 ng/mL and in benign aspirates, 2.41. The highest mean CEA was seen in adenocarcinoma, 402.6 ng/mL. Lower CEA content was seen in epidermoid carcinoma (58.6 ng/mL), large cell carcinoma (8.09), oat cell carcinoma, metastatic carcinoma of the kidney and breast, thymoma and lymphoma (each less than 1 ng/mL). Elevated CEA alone was diagnostic in two aspirates of bronchioloalveolar carcinoma; carcinoma with an unknown primary source, three; and large cell carcinoma, one. The adjunctive use of CEA in FNAs of the lung enhances the sensitivity of the cytologic diagnosis.

2.2.2  Relationship between serum CA125 half life and survival in ovarian cancer

Table
Gupta and Lis Journal of Ovarian Research 2009 2:13
http://dx.doi.org:/10.1186/1757-2215-2-13

First Author, Year, Study Place Data Collection Study
Design
Sample
Size
RR/HR, (95% CI),
P-Value
Riedinger JM, 2006, France 1988 to
1996
R 553 2.04 (1.58-2.63), < 0.0001
Gadducci A, 2004, Italy 1996 to2002 R 71 3.11 (1.22-7.98), 0.0181
Munstedt K, 1997, Germany 1987 to1994 R 85 0.6184
Gadducci A, 1995, Italy 1986 to1992 R 225 2.13 (1.23-3.68), 0.0073
Rosman M, 1994, Connecticut 1985 to
1989
R 51 3.6 (1.8-7.4), < 0.001
Yedema C A, 1993, Netherlands 1984 to
1990
R 60 9.17 (1.49-56.3), 0.01
Hawkins RE, 1989, London NA P 29 3.7 (0.7-20.1), 0.001;27.8 (4.0-193), 0.001

1CA125 half-life was independent prognostic indicator for survival
2FIGO stage, tumor grade, residual disease, CA125
http://www.ovarianresearch.com/content/2/1/13/table/T6

3.3.0      DNA double strand breaks

2.3.1.  Collaboration and competition – DNA double-strand break repair pathways

Kass EM, Jasin M
FEBS Letters 2010; 584:3703-3708
http://dx.doi.org:/jfebslet.2010.07.057

DNA double-strand breaks occur in replication and exogenous sources pose risk to genome stability. There are two pathways to repair.  They are non-homologous end joining and homologous recombination. Both pathways cooperate and compete at double-strand break sites.

2.3.2 DNA Double-Strand Break Repair Inhibitors as Cancer Therapeutics

Srivastava M, Rashavan SC
Chem & Biol 2015 Jan; pp17-29
http://dx.doi.org:/10.1016/jchembiol.2014.11.013

Homologous recombination and non-homologous end joining are the two major repair pathways expressed in eukaryotes.  For double-strand breaks, and the DSB repair gene is vulnerable to chemotherapy and radiation therapy, accounting for treatment resistance. Therefore, targeting DSB repair is attractive. Blocking the residual repair using inhibitors can potentiate treatment.

2.3.3  Animation published in DNA Repair: Helleday T, Lo J, van Gent DC, Engelward BP. DNA double-strand break repair: From mechanistic understanding to cancer treatment. DNA Repair. (14 Mar 2007)
2.3.3.1 http://web.mit.edu/engelward-lab/animations/DSBR.html

2.3.3.2 https://www.youtube.com/watch?v=eg8rpYFsqCA

2.3.4 Homology-dependent double strand break repair. Oxford Academic (Oxford University Press)

https://www.youtube.com/watch?v=86JCMM5kb2A

2.4.0 Managing DNA data sets

2.4.1 Bionimbus –  a cloud for managing, analyzing and sharing large genomics datasets

The Bionimbus Protected Data Cloud (PDC) is a collaboration between the Open Science Data Cloud (OSDC) and the IGSB (IGSB,) the Center for Research Informatics (CRI), the Institute for Translational Medicine (ITM), and the University of Chicago Comprehensive Cancer Center (UCCCC). The PDC allows users authorized by NIH to compute over human genomic data from dbGaP in a secure compliant fashion. Currently, selected datasets from the The Cancer Genome Atlas (TCGA) are available in the PDC.

https://bionimbus-pdc.opensciencedatacloud.org/

2.4.1.2 Accounting for uncertainty in DNA sequencing data

O’Rawe JA, Ferson S, Lyon GJ
Trends in Genetics 2015 Feb; 31(2):61-66
http://dx.doi.org:/10.101/jtig.2014.12.002

This article reviews uncertainty in quantification in DNA sequency applications and sources of error propagation, and it proposes methods to account for errors and uncertainties.

2.5.0 Linking Traits to Mechanisms and UPR response/proteostasis

2.5.1 Stress-Independent Activation of XBP1s and/or ATF6 Reveals –Three Linking traits based on their shared molecular mechanisms

Shoulders MD, Ryno LM, Genereux JC,…Wiseman BL
Cell Reports 2013 Apr; 3, pp 1279-1292
http://dx.doi.org:/10.1016/j.celrep.2013.03.024

The unfolded protein response (UPR) maintains ER proteostasis through the transcription factors XP1s and ATF6. This study measured orthogonal small molecule-mediated activation of transcription factors nXP1s and/or ATF6 using transcriptomics and quantitative proteomics. The finding is that three ER proteostasis environmants differentially influence

  1. Folding
  2. Traffiking, and
  3. Degradation of destabilized ER client proteins

Without affecting endogenous proteome. The proteostasis network is remodeled with the potential for selective restoration of the aberrant ER proteostasis.

2.5.2 Biological and chemical approaches to diseases of proteostasis deficiency.

Powers ET, Morimoto RI, Dillin A, Kelly JW, Balch WE
Annu Rev Biochem. 2009; 78:959-91.
http://dx.doi.org:/10.1146/annurev.biochem.052308.114844

Many diseases appear to be caused by the misregulation of protein maintenance. Such diseases of protein homeostasis, or “proteostasis,” include loss-of-function diseases (cystic fibrosis) and gain-of-toxic-function diseases (Alzheimer’s, Parkinson’s, and Huntington’s disease). Proteostasis is maintained by the proteostasis network, which comprises pathways that control protein synthesis, folding, trafficking, aggregation, disaggregation, and degradation. The decreased ability of the proteostasis network to cope with inherited misfolding-prone proteins, aging, and/or metabolic/environmental stress appears to trigger or exacerbate proteostasis diseases. Herein, we review recent evidence supporting the principle that proteostasis is influenced both by an adjustable proteostasis network capacity and protein folding energetics, which together determine the balance between folding efficiency, misfolding, protein degradation, and aggregation. We review how small molecules can enhance proteostasis by binding to and stabilizing specific proteins (pharmacologic chaperones) or by increasing the proteostasis network capacity (proteostasis regulators). We propose that such therapeutic strategies, including combination therapies, represent a new approach for treating a range of diverse human maladies.

2.5.3 Extracellular Chaperones and Proteostasis

Amy R. Wyatt, Justin J. Yerbury, Heath Ecroyd, and Mark R. Wilson
Annual Review of Biochemistry 2013 Jun; 82: 295-322
http://dx.doi.org:/10.1146/annurev-biochem-072711-163904

There exists a family of currently untreatable, serious human diseases that arise from the inappropriate misfolding and aggregation of extracellular proteins. At present our understanding of mechanisms that operate to maintain proteostasis in extracellular body fluids is limited, but it has significantly advanced with the discovery of a small but growing family of constitutively secreted extracellular chaperones. The available evidence strongly suggests that these chaperones act as both sensors and disposal mediators of misfolded proteins in extracellular fluids, thereby normally protecting us from disease pathologies. It is critically important to further increase our understanding of the mechanisms that operate to effect extracellular proteostasis, as this is essential knowledge upon which to base the development of effective therapies for some of the world’s most debilitating, costly, and intractable diseases.

http://www.proteostasis.com/our-technology/proteostasis-network.html

proteostasis model

http://www.proteostasis.com/images/stories/technology/illustration1.gif

2.6.0 Transcription

2.6.1 Looping Back to Leap Forward. Transcription Enters a New Era

Levine M, Cattoglio C, Tijan R
Cell 2014 Mar; 157: 13-22.
http://dx.doi.org:/10.1016/j.cell.2014.02.009

Organism complexity is not in gene number, but lies in gene regulation. The human genbome contains hundreds of thousands of enhancers, and genes are embedded in a milieu of enhancers . Proliferation of cis-regulatory DNAs is accompanied by complexity and functional diversity of transcription machinery recognizing distal enhancers and promotors, and high-order spatial organization. This article reviews the dynamic communication of remote enhancers with target promoters.

2.6.2 Activating gene expression in mammalian cells with promoter-targeted duplex RNAs.

Janowski BA, Younger ST, Hardy DB, Ram R, Huffman KE, Corey DR.
Nat Chem Biol. 2007 Mar; 3(3):166-73
http://dx.doi.org:/10.1038/nchembio860

The ability to selectively activate or inhibit gene expression is fundamental to understanding complex cellular systems and developing therapeutics. Recent studies have demonstrated that duplex RNAs complementary to promoters within chromosomal DNA are potent gene silencing agents in mammalian cells. Here we report that chromosome-targeted RNAs also activate gene expression. We have identified multiple duplex RNAs complementary to the progesterone receptor (PR) promoter that increase expression of PR protein and RNA after transfection into cultured T47D or MCF7 human breast cancer cells. Upregulation of PR protein reduced expression of the downstream gene encoding cyclooygenase 2 but did not change concentrations of estrogen receptor, which demonstrates that activating RNAs can predictably manipulate physiologically relevant cellular pathways. Activation decreased over time and was sequence specific. Chromatin immunoprecipitation assays indicated that activation is accompanied by reduced acetylation at histones H3K9 and H3K14 and by increased di- and trimethylation at histone H3K4. These data show that, like proteins, hormones and small molecules, small duplex RNAs interact at promoters and can activate or repress gene expression.
2.6.3 Tight control of gene expression in mammalian cells by tetracycline-responsive promoters.

M Gossen and H Bujard
Proc Natl Acad Sci U S A. 1992 Jun 15; 89(12): 5547–5551.

Control elements of the tetracycline-resistance operon encoded in Tn10 of Escherichia coli have been utilized to establish a highly efficient regulatory system in mammalian cells. By fusing the tet repressor with the activating domain of virion protein 16 of herpes simplex virus, a tetracycline-controlled transactivator (tTA) was generated that is constitutively expressed in HeLa cells. This transactivator stimulates transcription from a minimal promoter sequence derived from the human cytomegalovirus promoter IE combined with tet operator sequences. Upon integration of a luciferase gene controlled by a tTA-dependent promoter into a tTA-producing HeLa cell line, high levels of luciferase expression were monitored. These activities are sensitive to tetracycline. Depending on the concentration of the antibiotic in the culture medium (0-1 microgram/ml), the luciferase activity can be regulated over up to five orders of magnitude. Thus, the system not only allows differential control of the activity of an individual gene in mammalian cells but also is suitable for creation of “on/off” situations for such genes in a reversible way.

Diagrams of two regulatable gene expression systems.

Diagrams of two regulatable gene expression systems.

http://www.intechopen.com/source/html/16788/media/image5.jpeg

schematic-representation-of-transgenic-mouse-breeding-scheme-h2b-gfp-mice-should-not-express-gfp-in-the-absence-of-a-tetracycline-regulatable-transactivator

schematic-representation-of-transgenic-mouse-breeding-scheme-h2b-gfp-mice-should-not-express-gfp-in-the-absence-of-a-tetracycline-regulatable-transactivator

http://openi.nlm.nih.gov/imgs/512/321/2408727/2408727_pone.0002357.g001.png

2.7.0 Epigenetics and Cancer

2.7.1 Epigenetics and cancer metabolism

Johnson C, Warmoes MO, Shen X, Locasale JW
Cancer Letters 2015;  356:309-314.
http://dx.doi.org:/10.1016/j.canlet.2013.09.043

Cancer is characterized by adaptive metabolic changes for proliferation and survival of the neoplastic cell, which is accompanied by dysfunctional metabolic enzyme changes in a specific nutrient supplied environment. The oncogenic change uses epigenetic level enzymes that catalyze posttranslational modifications of the DNA/histone expression with metabolites including cofactors and substrates for reactions. This interaction of epigenetics and metabolism provides new insights for anti-cancer therapy.

2.7.2 Cancer Epigenetics. From Mechanism to Therapy

Dawson MA, Konzarides T
Cell 2012 Jul; 150:12-27
http://dx.doi.org:/10.1016/j.cell.2012.06.013

Carcinogenesis requires all of the following:

  • DNA methylation
  • Histone modification
  • Nucleosome remodeling
  • RNA mediated targeting

This article reviews basic principles of epigenetic pathways that are dysregulated in carcinogenesis.

2.7.4 A subway review of cancer pathways

Hahn WC, Weinberg RA
Nature Reviews: Cancer
http://www.nature.com/nrc/poster/subpathways/index.html

Cancer arises from the stepwise accumulation of genetic changes that confer upon an incipient neoplastic cell the properties of unlimited, self-sufficient growth and resistance to normal homeostatic regulatory mechanisms. Advances in human genetics and molecular and cellular biology have identified a collection of cell phenotypes � the main destinations in the subway map below � that are required for malignant transformation1. Specific molecular pathways (subway lines) are responsible for programming these behaviours. Although the connections between cancer-cell wiring and function remain incompletely explored and specified � hence the many lines under construction � the broad outlines of the molecular circuitry of the cancer cell can now be sketched. Further advances in understanding these pathways and their interconnections will accelerate the development of molecularly targeted therapies that promise to change the practice of oncology.

cancer subway map

cancer subway map

http://www.nature.com/nrc/poster/subpathways/images/map.gif

Subway map designed by Claudia Bentley.

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The Life and Work of Allan Wilson

Curator: Larry H. Bernstein, MD, FCAP

 

Allan Charles Wilson (18 October 1934 – 21 July 1991) was a Professor of Biochemistry at the University of California, Berkeley, a pioneer in the use of molecular approaches to understand evolutionary change and reconstruct phylogenies, and a revolutionary contributor to the study of human evolution. He was one of the most controversial figures in post-war biology; his work attracted a great deal of attention both from within and outside the academic world. He is the only New Zealander to have won the MacArthur Fellowship.

He is best known for experimental demonstration of the concept of the molecular clock (with his doctoral student Vincent Sarich), which was theoretically postulated by Linus Pauling and Emile Zuckerkandl, revolutionary insights into the nature of the molecular anthropology of higher primates and human evolution, called Mitochondrial Eve hypothesis (with his doctoral students Rebecca L. Cann and Mark Stoneking).

Allan Wilson was born in Ngaruawahia, New Zealand, and raised on his family’s rural dairy farm at Helvetia, Pukekohe, about twenty miles south of Auckland. At his local Sunday School, the vicar’s wife was impressed by young Allan’s interest in evolution and encouraged Allan’s mother to enroll him at the elite King’s College secondary school in Auckland. There he excelled in mathematics, chemistry, and sports.

Wilson already had an interest in evolution and biochemistry, but intended to be the first in his family to attend university by pursuing studies in agriculture and animal science. Wilson met Professor Campbell Percy McMeekan, a New Zealand pioneer in animal science, who suggested that Wilson attend the University of Otago in southern New Zealand to further his study in biochemistry rather than veterinary science. Wilson gained a BSc from the University of Otago in 1955, majoring in both zoology and biochemistry.

The bird physiologist Donald S. Farner met Wilson as an undergraduate at Otago and invited him to Washington State University at Pullman as his graduate student. Wilson obliged and completed a master’s degree in zoology at WSU under Farner in 1957, where he worked on the effects of photoperiod on the physiology of birds.

Wilson then moved to the University of California, Berkeley, to pursue his doctoral research. At the time the family thought Allan would only be gone two years. Instead, Wilson remained in the United States, gaining his PhD at Berkeley in 1961 under the direction of biochemist Arthur Pardee for work on the regulation of flavin biosynthesis in bacteria. From 1961 to 1964, Wilson studied as a post-doc under biochemist Nathan O. Kaplan at Brandeis University in Waltham, Massachusetts. In Kaplan’s lab, working with lactate and malate dehydrogenases, Wilson was first introduced to the nascent field of molecular evolution. Nate Kaplan was one of the very earliest pioneers to address phylogenetic problems with evidence from protein molecules, an approach that Wilson later famously applied to human evolution and primate relationships. After Brandeis, Wilson returned to Berkeley where he set up his own lab in the Biochemistry department, remaining there for the rest of his life.

Wilson joined the UC Berkeley faculty of biochemistry in 1964, and was promoted to full professor in 1972. His first major scientific contribution was published as Immunological Time-Scale For Hominid Evolution in the journal Science in December 1967. With his student Vincent Sarich, he showed that evolutionary relationships of the human species with other primates, in particular the Great Apes (chimpanzees, gorillas, and orangutans), could be inferred from molecular evidence obtained from living species, rather than solely from fossils of extinct creatures.

Their microcomplement fixation method (see complement system) measured the strength of the immune reaction between an antigen (serum albumin) from one species and an antibody raised against the same antigen in another species. The strength of the antibody-antigen reaction was known to be stronger between more closely related species: their innovation was to measure it quantitatively among many species pairs as an “immunological distance”. When these distances were plotted against the divergence times of species pair with well-established evolutionary histories, the data showed that the molecular difference increased linearly with time, in what was termed a “molecular clock”. Given this calibration curve, the time of divergence between species pairs with unknown or uncertain fossil histories could be inferred. Most controversially, their data suggested that divergence times between humans, chimpanzees, and gorillas were on the order of 3~5 million years, far less than the estimates of 9~30 million years accepted by conventional paleoanthropologists from fossil hominids such as Ramapithecus. This ‘recent origin’ theory of human/ape divergence remained controversial until the discovery of the “Lucy” fossils in 1974.

Wilson and another PhD student Mary-Claire King subsequently compared several lines of genetic evidence (immunology, amino acid differences, and protein electrophoresis) on the divergence of humans and chimpanzees, and showed that all methods agreed that the two species were >99% similar.[4][19] Given the large organismal differences between the two species in the absence of large genetic differences, King and Wilson argued that it was not structural gene differences that were responsible for species differences, but gene regulation of those differences, that is, the timing and manner in which near-identical gene products are assembled during embryology and development. In combination with the “molecular clock” hypothesis, this contrasted sharply with the accepted view that larger or smaller organismal differences were due to large or smaller rates of genetic divergence.

In the early 1980s, Wilson further refined traditional anthropological thinking with his work with PhD students Rebecca Cann and Mark Stoneking on the so-called “Mitochondrial Eve” hypothesis.[20] In his efforts to identify informative genetic markers for tracking human evolutionary history, he focused on mitochondrial DNA (mtDNA) — genes that are found in mitochondria in the cytoplasm of the cell outside the nucleus. Because of its location in the cytoplasm, mtDNA is passed exclusively from mother to child, the father making no contribution, and in the absence of genetic recombination defines female lineages over evolutionary timescales. Because it also mutates rapidly, it is possible to measure the small genetic differences between individual within species by restriction endonuclease gene mapping. Wilson, Cann, and Stoneking measured differences among many individuals from different human continental groups, and found that humans from Africa showed the greatest inter-individual differences, consistent with an African origin of the human species (the so-called “Out of Africa” hypothesis). The data further indicated that all living humans shared a common maternal ancestor, who lived in Africa only a few hundreds of thousands of years ago.

This common ancestor became widely known in the media and popular culture as the Mitochondrial Eve. This had the unfortunate and erroneous implication that only a single female lived at that time, when in fact the occurrence of a coalescent ancestor is a necessary consequence of population genetic theory, and the Mitochondrial Eve would have been only one of many humans (male and female) alive at that time.[2][3] This finding was, like his earlier results, not readily accepted by anthropologists. Conventional hypothesis was that various human continental groups had evolved from diverse ancestors, over several million of years since divergence from chimpanzees. The mtDNA data, however, strongly suggested that all humans descended from a common, quite recent, African mother.

Wilson became ill with leukemia, and after a bone marrow transplant, died on Sunday, 21 July 1991, at the Fred Hutchinson Memorial Cancer Research Center in Seattle. He had been scheduled to give the keynote address at an international conference the same day. He was 56, at the height of his scientific recognition and powers.

Wilson’s success can be attributed to his strong interest and depth of knowledge in biochemistry and evolutionary biology, his insistence of quantification of evolutionary phenomena, and has early recognition of new molecular techniques that could shed light on questions of evolutionary biology. After development of quantitative immunological methods, his lab was the first to recognize restriction endonuclease mapping analysis as a quantitative evolutionary genetic method, which led to his early use of DNA sequencing, and the then-nascent technique of PCR to obtain large DNA sets for genetic analysis of populations. He trained scores of undergraduate, graduate (34 people, 17 each of men and women, received their doctoral degrees in his lab), and post-doctoral students in molecular evolutionary biology, including sabbatical visitors from six continents. His lab published more than 300 technical papers, and was recognized as a mecca for those wishing to enter the field of molecular evolution in the 1970s and 1980s.

The Allan Wilson Centre for Molecular Ecology and Evolution was established in 2002 in his honour to advance knowledge of the evolution and ecology of New Zealand and Pacific plant and animal life, and human history in the Pacific. The Centre is under the Massey University, at Palmerston North, New Zealand, and is a national collaboration involving the University of Auckland, Victoria University of Wellington, the University of Otago, University of Canterbury and the New Zealand Institute for Plant and Food Research.

A 41-minutes documentary film of his life entitled Allan Wilson, Evolutionary: Biochemist, Biologist, Giant of Molecular Biology was released by Films Media Group in 2008.

 

Allan Charles Wilson. 18 October 1934 — 21 July 1991

Rebecca L. Cann

Department of Cell and Molecular Biology, University of Hawaii at Manoa, Biomedical Sciences Building T514, 1960 East–West Rd, Honolulu, HI 96822, USA

Abstract

Allan Charles Wilson was born on 18 October 1934 at Ngaruawahia, New Zealand. He died in Seattle, Washington, on 21 July 1991 while undergoing treatment for leukemia.  Allan was known as a pioneering and highly innovative biochemist, helping to define the field of molecular evolution and establish the use of a molecular clock to measure evolutionary change between living species. The molecular clock, a method of measuring the timescale of evolutionary change between two organisms on the basis of the number of mutations that they have accumulated since last sharing a common genetic ancestor, was an idea initially championed by Émile Zuckerkandl and Linus Pauling (Zuckerkandl & Pauling 1962), on the basis of their observations that the number of changes in an amino acid sequence was roughly linear with time in the aligned hemoglobin proteins of animals. Although it is now not unusual to see the words ‘molecular evolution’ and ‘molecular phylogeny’ together, when Allan formed his own biochemistry laboratory in 1964 at the University of California, Berkeley, many scientists in the field of evolutionary biology considered these ideas complete heresy. Allan’s death at the relatively young age of 56 years left behind his wife, Leona (deceased in 2009), a daughter, Ruth (b. 1961), and a son, David (b. 1964), as well his as mother, Eunice (deceased in 2002), a younger brother, Gary Wilson, and a sister, Colleen Macmillan, along with numerous nieces, nephews and cousins in New Zealand, Australia and the USA. In this short span of time, he trained more than 55 doctoral students and helped launch the careers of numerous postdoctoral fellows.

Allan Charles Wilson, Biochemistry; Molecular Biology: Berkeley

1934-1991

Professor

The sudden death of Allan Wilson, of leukemia, on 21 July 1991, at the age of 56, and at the height of his powers, robbed the Berkeley campus and the international scientific community of one of its most active and respected leaders.

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The History of Hematology and Related Sciences

Curator: Larry H. Bernstein, MD, FCAP

 

The History of Hematology and Related Sciences: A Historical Review of Hematological Diagnosis from 1880 -1980

 

Blood Description: The Analysis of Blood Elements a Window into Diseases

Diagnosing bacterial infection (BI) remains a challenge for the attending physician. An ex vivo infection model based on human fixed polymorphonuclear neutrophils (PMNs) gives an autofluorescence signal that differs significantly between stimulated and unstimulated cells. We took advantage of this property for use in an in vivo pneumonia mouse model and in patients hospitalized with bacterial pneumonia. A 2-fold decrease was observed in autofluorescence intensity for cytospined PMNs from broncho-alveolar lavage (BAL) in the pneumonia mouse model and a 2.7-fold decrease was observed in patients with pneumonia when compared with control mice or patients without pneumonia, respectively. This optical method provided an autofluorescence mean intensity cut-off, allowing for easy diagnosis of BI. Originally set up on a confocal microscope, the assay was also effective using a standard epifluorescence microscope. Assessing the autofluorescence of PMNs provides a fast, simple, cheap and reliable method optimizing the efficiency and the time needed for early diagnosis of severe infections. Rationalized therapeutic decisions supported by the results from this method can improve the outcome of patients suspected of having an infection.

Monsel A, Le´cart S, Roquilly A, Broquet A, Jacqueline C, et al. (2014) Analysis of Autofluorescence in Polymorphonuclear Neutrophils: A New Tool for Early Infection Diagnosis. PLoS ONE 9(3): e92564.
http://dx.doi.org:/10.1371/journal.pone.0092564

This study was designed to validate or refute the reliability of total lymphocyte count (TLC) and other hematological parameters as a substitute for CD4 cell counts. Participants consisted of two groups, including 416 antiretroviral naive (G1) and 328 antiretroviral experienced (G2) patients. CD4+ T cell counts were performed using a Cyflow machine. Hematological parameters were analyzed using a hematology analyzer. The median ± SEM CD4 count (range) of participants in G1 was 199 ± 10.9 (5–1840 cells/μL) and the median ± SEM TLC (range) was 1. 61 ± 0.05 (0.07–6.63 × 103/μL). The corresponding values among G2 were 421 ± 15.8 (13–1801) and 2.13 ± 0.04 (0.06–5.58), respectively. Using a threshold value of 1.2 × 103/μL for TLC alone, the sensitivity of G1 was 88.4% (specificity (SP) 67.4%, the positive predictive value (PPV) 53.5% and negative predictive value (NPV) of 93.2% for CD4 , 200 cells/μL, the sensitivity for G2 was 83.3%, SP 85.3%, PPV 23.8%, and NPV of 93.2%. Using multiple parameters, including TLC , 1.2 × 103/μL, hemoglobin , 10 g/dL, and platelets , 150 × 103/L, the sensitivity increased to 96.0% (SP, 82.7%; PPV, 80%; NPV, 96.7%) among G1, while no change was observed in the G2 cohort. TLC , 1.2 × 103/μL alone is an insensitive predictor of CD4 count of , 200 cells/μL. Incorporating hemoglobin , 10 g/dL, and platelets , 150 × 103/L enhances the ability of TLC , 1.2 × 103/μL to predict CD4 count , 200 cells/μL among the antiretroviral-naïve cohort. We recommend the use of multiple, inexpensively measured hematological parameters in the form of an algorithm for predicting CD4 count level.

Evaluating Total Lymphocyte Counts and Other Hematological Parameters as a Substitute for CD4 Counts in the Management of HIV Patients in Northeastern Nigeria. BA Denue, AU Abja, IM Kida, AH Gabdo, AA Bukar and CB Akawu.
Retrovirology: Research and Treatment 2013:5 9–16 http://dx.doi.org:/10.4137/RRT.S11562

Sepsis is a syndrome that results in high morbidity and mortality. We investigated the delta neutrophil index (DN) as a predictive marker of early mortality in patients with gram-negative bacteremia. Retrospective study. The DN was measured at onset of bacteremia and 24 hours and 72 hours later. The DN was calculated using an automatic hematology analyzer. Factors associated with 10-day mortality were assessed using logistic regression. A total of 172 patients with gram-negative bacteremia were included in the analysis; of these, 17 patients died within 10 days of bacteremia onset. In multivariate analysis, Sequental organ failure assessment scores (odds ratio [OR]: 2.24, 95% confidence interval [CI]: 1.31 to 3.84; P = 0.003), DN-day 1 ≥ 7.6% (OR: 305.18, 95% CI: 1.73 to 53983.52; P = 0.030) and DN-day 3 ≥ DN day 1 (OR: 77.77, 95% CI: 1.90 to 3188.05; P = 0.022) were independent factors associated with early mortality in gram-negative bacteremia. Of four multivariate models developed and tested using various factors, the model using both DN-day 1 ≥ 7.6% and DN-day 3 ≥ DN-day 1 was most predictive early mortality. DN may be a useful marker of early mortality in patients with gram-negative bacteremia. We found both DN-day 1 and DN trend to be significantly associated with early mortality.

Delta Neutrophil Index as a Prognostic Marker of Early Mortality in Gram Negative Bacteremia. HW Kim, JH Yoon, SJ Jin, SB Kim, NS Ku, SJ Jeong,
et al. Infect Chemother 2014;46(2):94-102. pISSN 2093-2340·eISSN 2092-6448
http://dx.doi.org/10.3947/ic.2014.46.2.94
Various indices derived from red blood cell (RBC) parameters have been described for distinguishing thalassemia and iron deficiency. We studied the microcytic to hypochromic RBC ratio as a discriminant index in microcytic anemia and compared it to traditional indices in a learning set and confirmed our findings in a validation set. The learning set comprised samples from 371 patients with microcytic anemia mean cell volume (MCV < 80 fL), which were measured on a CELL-DYN Sapphire analyzer and various discriminant functions calculated. Optimal cutoff values were established using ROC analysis. These values were used in the validation set of 338 patients. In the learning set, a microcytic to hypochromic RBC ratio >6.4 was strongly indicative of thalassemia (area under the curve 0.948). Green-King and England-Fraser indices showed comparable area under the ROC curve. However, the microcytic to hypochromic ratio had the highest sensitivity (0.964). In the validation set, 91.1% of microcytic patients were correctly classified using the M/H ratio. Overall, the microcytic to hypochromic ratio as measured in CELL-DYN Sapphire performed equally well as the Green-King index in identifying thalassemia carriers, but with higher sensitivity, making it a quick and inexpensive screening tool.
Differential diagnosis of microcytic anemia: the role of microcytic and hypochromic erythrocytes. E. Urrechaga, J.J.M.L. Hoffmann, S. Izquierdo, J.F. Escanero. Intl Jf Lab Hematology Aug 2014. http://dx.doi.org:/10.1111/ijlh.12290

Achievement of complete response (CR) to therapy in chronic lymphocytic leukemia (CLL) has become a feasible goal, directly correlating with prolonged survival. It has been established that the classic definition of CR actually encompasses a variety of disease loads, and more sensitive multiparameter flow cytometry [and polymerase chain reaction methods] can detect the disease burden with a much higher sensitivity. Detection of malignant cells with a sensitivity of 1 tumor cell in 10,000 cells (10–4), using the above-mentioned sophisticated techniques, is the current cutoff for minimal residual disease (MRD). Tumor burdens lower than 10–4 are defined as MRD-negative. Several studies in CLL have determined the achievement of MRD negativity as an independent favorable prognostic factor, leading to prolonged disease-free and overall survival, regardless of the treatment protocol or the presence of other pre-existing prognostic indicators. Minimal residual disease evaluation using flow cytometry is a sensitive and applicable approach which is expected to become an integral part of future prospective trials in CLL designed to assess the role of MRD surveillance in treatment tailoring.

Minimal Residual Disease Surveillance in Chronic Lymphocytic Leukemia by Fluorescence-Activated Cell Sorting. S Ringelstein-Harlev, R Fineman.
Rambam Maimonides Med J. Oct 2014   5 (4)  e0027. http://dx.doi.org:/10.5041/RMMJ.10161

Natural Killer cells (CD3-CD16+CD56+) are a major players in innate immunity, both as direct cytotoxic effectors as well as regulators for other innate immunity cell types. We have shown that, using the FlowCellect™ human NK cell characterization kit, one can achieve accurate phenotyping on a variety of sample types, including whole blood samples. Using the same kit to perform an NK cell cytotoxicity test, we demonstrate that unbound K562 target cells can be clearly distinguished from those that have been engaged by CD56+ NK cells, and each of these populations can be further investigated for viability using the eFluor 660® dye.

Analysis of NK cell subpopulations in whole blood

Analysis of NK cell subpopulations in whole blood

Analysis of NK cell subpopulations in whole blood

A

Proportion of K562 target cells bound to NK cells

Proportion of K562 target cells bound to NK cells

In a 5:1 effector cell:target cell population, 8% of the K562 cells were bound to NK cells (Figure 3B). 84% of the bound K562 cells were viable (Figure 3C) stained with fixable viability dye), while 96% of the unbound K562 cells were viable (Figure 3D). (B,C,D not shown)

Characterization of Natural Killer Cells Using Flow Cytometry.
EMD Millipore is a division of Merck KGaA, Darmstadt, Germany.

Red blood cell distribution width (RDW) is increased in liver disease. Its clinical significance, however, remains largely unknown. The aim of this study was to identify whether RDW was a prognostic index for liver disease. Retrospective: 33 patients with non-cirrhotic HBV chronic hepatitis, 125 patients with liver cirrhosis after HBV infection, 81 newly diagnosed primary epatocellular carcinoma (pHCC) patients, 17 alcoholic liver cirrhosis patients and 42 patients with primary biliary cirrhosis (PBC). Sixty-six healthy individuals represented the control cohort. The relationship between RDW on admission and clinical features: The association between RDW and hospitalization outcome was estimated by receiver operating curve (ROC) analysis and a multivariable logistic regression model. Increased RDW was observed in liver disease patients. RDW was positively correlated with serum bilirubin and creatinine levels, prothrombin time, and negatively correlated with platelet counts and serum albumin concentration. A subgroup analysis, considering the different etiologies, revealed similar findings. Among the patients with liver cirrhosis, RDW increased with worsening of Child-Pugh grade. In patients with PBC, RDW positively correlated with Mayo risk score. Increased RDW was associated with worse hospital outcome, as shown by the AUC [95% confidence interval (CI)] of 0.76 (0.67 – 0.84). RDW above 15.15% was independently associated with poor hospital outcome after adjustment for serum bilirubin, platelet count, prothrombin time, albumin and age, with the odds ratio (95% CI) of 13.29 (1.67 – 105.68). RDW is a potential prognostic index for liver disease.

Red blood cell distribution width is a potential prognostic index for liver disease
Z Hua , Y Suna , Q Wanga , Z Han , Y Huang , X Liu , C Ding, et al.
Clin Chem Lab Med 2013; 51(7):1403–1408.
http://dx.doi.org:/10.1515/cclm-2012-0704

Blood Plasma and Red Blood Cells

Whole blood consists of red and white blood cells, as well as platelets suspended in a liquid referred to as blood plasma. According to the American Red Cross, plasma is 92% water and makes up 55% of blood volume. The permeability of blood plasma is equal to 1.

Red blood cells make up slightly lower blood volume than blood plasma — about 45% of whole blood. As you probably already know, these types of blood cells contain hemoglobin, which in turn consists of iron that helps transport oxygen throughout the body. The permeability of red blood cells is slightly less than 1,
(1 – 3.9e-6). Or to put it in words, red blood cell particles are diamagnetic.

Due to their magnetic properties, red blood cells may be separated from the plasma via a magnetophoretic approach. If the blood were to be in a channel subject to a magnetophoretic force, we could control where the red blood cells and the plasma go within the channels. In other words, because the red blood cells have different permeability, they can be separated from the flow channel. However, such methodology is beyond the year 1980.

Timeline of Major Hematology Landmarks

1877 Paul Ehrlich develops techniques to stain blood cells to improve microscopic visualization.

1897 The Diseases of Infancy and Childhood contains a 20-page chapter on diseases of the blood and is the first American pediatric medical textbook to provide significant hematologic information.

1821–1902 Rudolph Virchow, during a long and illustrious career, demonstrates the importance of fibrin in the blood coagulation process, coins the terms embolism and thrombosis, identifies the disease leukemia, and theorizes that leukocytes are made in response to inflammation.

1901 Karl Landsteiner and colleagues identify blood groups of A, B, AB, and O.

1907 Ludvig Hektoen suggests that the safety of transfusion might be improved by crossmatching blood between donors and patients to exclude incompatible mixtures. Reuben Ottenberg performs the first blood transfusion using blood typing and crossmatching in New York. Ottenberg also observes the Mendelian inheritance of blood groups and recognizes the “universal” utility of group O donors.

1910 The first clinical description of sickle cell published in medical literature.

1914 Sodium citrate is found to prevent blood from clotting, allowing blood to be stored between collection and transfusion.

1924 Pediatrics is the first comprehensive American publication on pediatric hematology.

1925 Alfred P. Hart performs the first exchange transfusion.

1925 Thomas Cooley describes a Mediterranean hematologic syndrome of anemia, erythroblastosis, skeletal disorders, and splenomegaly that is later called Cooley’s anemia and now thalassemia.

1936 Chicago’s Cook County Hospital establishes the first true “blood bank” in the United States.

1938 Dr. Louis Diamond (known as the “father of American pediatric hematology”) along with Dr. Kenneth Blackfan describes the anemia still known as Diamond-Blackfan anemia.

1941 The Atlas of the Blood of Children is published by Blackfan, Diamond, and Leister.

1945 Coombs, Mourant, and Race describe the use of antihuman globulin (later known as the “Coombs Test”) to identify “incomplete” antibodies.

1954 The blood product cryoprecipitate is developed to treat bleeds in people with hemophilia.

1950s The “butterfly” needle and intercath are developed, making IV access easier and safer.

1961 The role of platelet concentrates in reducing mortality from hemorrhage in cancer patients is recognized.

1962 The first antihemophilic factor concentrate to treat coagulation disorders in hemophilia patients is developed through fractionation.

1969 S. Murphy and F. Gardner demonstrate the feasibility of storing platelets at room temperature, revolutionizing platelet transfusion therapy.

1971 Hepatitis B surface antigen testing of blood begins in the United States.

1972 Apheresis is used to extract one cellular component, returning the rest of the blood to the donor.

1974 Hematology of Infancy and Childhood is published by Nathan and Oski.

As I write today my hospital celebrates its 150th anniversary. Great Ormond Street Children’s Hospital was founded on 14 February 1852 by the visionary Dr Charles West followed his belief that hospital care allied to research in children’s diseases would reduce child mortality from above 50% by the age of 15 years. It is foolish to believe that we can progress in medicine without a knowledge of the past and that much of life is based upon experience. When putting together a series of articles on the history of haematology, initially published in BJH, this was the main raison d’être, along with the belief that the practice of medicine has become increasingly serious but should also be fun and interesting and even occasionally uplifting to the spirit.

The central problem of any survey of the history of haematology is usually the question of balance. Achieving a degree of balance among themes and topics that will be satisfactory to practicing haematologists/physicians with an interest in blood diseases is essentially impossible. Our preference has been for themes of general interest rather than those of a purely scientific view into a field that has led the way in understanding the molecular basis of human disease.

  1. M. Hann, London, 2002; O. P. Smith, Dublin, 2002.

Origins of the Discipline `Neonatal Haematology’, 1925-75

In every modern neonatal intensive care unit (NICU), haematological problems are encountered daily. Many of these problems involve varieties of anaemia, neutropenia or thrombocytopenia that are unique to NICU patients. A characteristic aspect of these unique problems is that, if the neonate survives, the haematological problem will remit and will not recur later in life, nor will it evolve into a chronic illness (although the problem might occur in a future newborn sibling). This characteristic comes about because the common haematological problems of NICU patients are not genetic defects but are environmental stresses (such as infection, alloimmunization or a variety of maternal illnesses) that are imposed on a developmentally immature haematopoietic system.

In the USA, and in some parts of Europe, the unique haematological problems that occur among NICU patients are diagnosed and treated by neonatologists, not by paediatric haematologists. Although these haematological conditions were generally first described by haematologists, the conditions occur, obviously, in neonates. Thus, the neonatologist, who is familiar with intensive care management of neonates, has also become familiar with the diagnosis and management of the neonate’s common haematological disorders. A growing number of neonatologists have sought specific additional training in haematology, with the goals of discovering the mechanisms underlying the unique haematological problems of NICU patients and improving the management and outcome of the patients who have these conditions. These physicians have remained as neonatologists and they do not practice paediatric haematology, although their research contributions certainly come under the purview of haematology, or more precisely under the discipline of `neonatal haematology’. In many places in Europe, it is the haematologists rather than the neonatologists who have an academic and clinical interest in neonatal haematology.

The roots of the discipline of neonatal haematology can be traced to the early application of haematological methods to animal and human embryos and fetuses, such as found in the reports of Maximow (1924) and Wintrobe & Schumacker (1936). The clinical underpinnings of this discipline include reports of anaemia (Fikelstein, 1911) and jaundice (Blomfeld, 1901; YlppoÈ, 1913) among neonates.

Before the 1930s, very few studies and very few published clinical case reports originated from premature nurseries. Such nurseries had dubious beginnings, which were criticized by some physicians as more resembling circus exhibitions than medical care wards (Bonar, 1932). These units generally had mortality rates greatly exceeding 50% on the day of admission, with the majority of the first-day survivors having late deaths or serious long-term morbidity.

It was not until publication of the review of premature nursery care at the Children’s Hospital of Michigan, in 1932, that it was clear that some units had instituted systematic attempts to monitor and improve outcomes. A special care nursery had been established at the Children’s Hospital in 1926 and, in 1932, Drs Marsh Poole and Thomas Cooley reported their experience in that unit (Poole & Cooley, 1932). The report included  incubator design with temperature and humidity control, growth curves of patients on various feeding practices, mortality statistics and attempts to determine causes of death.

At the time premature nursery care was beginning to merit academic credentials, reports were published of haematological problems that were unique to the neonate. These papers included the seminal publication on erythroblastosis fetalis by Drs Diamond (Fig 1), Blackfan and Baty (Diamond et al, 1932), and the report of sepsis neonatorum at the Yale New Haven Hospital by Ethyl C. Dunham (Fig 2) (Dunham,

1933).

The first major textbook devoted to clinical haematology, as well as the first textbook of neonatology, contained very little information about what are today’s common NICU haematological problems. For instance, in the first edition of Clinical Hematology by Dr Maxwell M. Wintrobe (Fig 3), of the Johns Hopkins University Hospital (Wintrobe, 1942), several topics related to paediatric haematology were reviewed, but discussions of the haematological problems of neonates were limited to three – erythroblastosis fetalis, haemorrhagic disease of the newborn and the `anaemia of prematurity’. Similarly, Premature Infants: A Manual for

Physicians, the original neonatology textbook, published in 1948 by Dr Ethyl C. Dunham (Fig 2; Dunham, 1948), had only a few pages devoted to haematological problems – the same three discussed by Dr Wintrobe. Also, the classic neonatology text book, `The Physiology of the Newborn Infant’, published in 1945 by Dr Clement A. Smith, contained almost no discussion of haematological problems (Smith, 1945). hrombocytopenia, which is now diagnosed among 25-30% of NICU patients, and neutropenia, now diagnosed in 8-10% of NICU patients, were not mentioned.

The first article published in Paediatrics (1948) dealing with a neonatal haematological problem was in volume two, in which Dr Diamond detailed his technique for performing a replacement transfusion (which later became known as an `exchange’ transfusion) as a treatment for erythroblastosis fetalis (Diamond, 1949). The second paper published by Paediatrics containing aspects of neonatal haematology was 1 year later, when Sliverman & Homan (1949) described leucopenia among neonates with sepsis. Most of the 25 infants they described, who were treated at Babies Hospital in New York over an 11-year period, had `late-onset’ sepsis, beginning after 3 days of life. They reported 14 neonates with Escherichia coli sepsis and four with streptococcal or staphylococcal sepsis, and observed that leucopenia occurred occasionally among these patients but was uncommon. (Indeed, today neutropenia remains uncommon in `late-onset’ sepsis, but common in congenital or `early onset’ sepsis.)

Louis K. Diamond, MD, at Children's Hospital, Boston,

Louis K. Diamond, MD, at Children’s Hospital, Boston,

Louis K. Diamond, MD, at Children’s Hospital, Boston, MA. , date unknown (obtained with the kind assistance of Charles F. Simmons, MD, Harvard University).

Diagnosing neutropenia, anaemia or thrombocytopenia in a neonate obviously requires knowledge of the expected normal range for neutrophil concentration, haematocrit and platelet concentration in the appropriate reference population. Early contributions to neonatal haematology included the publications of these reference ranges. The landmark studies included the range of blood leucocyte and neutrophil concentrations in neonates published in 1935 by Dr Katsuji Kato from the Department of Paediatrics at the University of Chicago (Kato, 1935). He tabulated the leucocyte concentrations and differential counts of 1081 children, ranging from birth to 15 years of age. A striking finding of his report (Fig 4) was the very high neutrophil counts during the first hours and days of life. Blood neutrophil concentrations among neonates with infections were published during the early and mid-1970s by Dr Marietta Xanthou (Fig 5) at the Hammersmith Hospital in London (Xanthou, 1970, 1972), and by Drs Barbara Manroe and Charles Rosenfeld (Fig 6) at the University of Texas Southwestern Medical Center in Dallas, Texas (Manroe et al, 1977).

Normal values for haemoglobin, haematocrit, erythrocyte indices and leucocyte concentrations were refined by DeMarsh et al (1942, 1948), and in a series of publications in the early 1950s in Archives of Diseases of Children by Gairdner et al (1952a, b). These were followed by observations on human fetal haematopoiesis by Thomas and Yoffey in the British Journal of Haematology (Thomas & Yoffey, 1962, 1964), and by the work on blood volume during the 1960s (Usher et al, 1963, Usher & Lind, 1965; Yao et al, 1967, 1968). Normal ranges for blood platelet counts in ill and well preterm and term infants were published in the early 1970s (Sell et al, 1973; Corrigan, 1974).

The first publication addressing the problem of neutropenia accompanying fatal early onset bacterial sepsis was that of Tygstrup et al (1968). This was a report of a near-term male with congenital Listeria sepsis who lived for only 4 h. The platelet count was 80*109/l and the leucocyte count was 13´7*109/l, but no granulocytes were observed on the differential count, which consisted of 84% lymphocytes, 8% monocytes and 8% leucocyte precursors. A sternal marrow aspirate was taken of the infant shortly before death that revealed myeloblasts, promyelocytes and myelocytes, but no band or segmented neutrophils.

An important advance in understanding the blood neutrophil count during neonatal sepsis occurred with the back-to-back papers in Archives of Diseases of Childhood in 1972 by Dr Marietta Xanthou of Hammersmith Hospital, London (Xanthou, 1972), and Drs Gregory and Hey of Babies’ Hospital, Newcastle upon Tyne (Gregory & Hey, 1972). Both papers reported that neonates who had life threatening (or indeed fatal) infections became neutropenic prior to death. Dr Xanthou reported 35 ill preterm and term babies within their first 28 d of life. Twenty-four were ill but not infected, and these had normal blood neutrophil concentrations and morphology. However, among the 11 who were ill with a bacterial infection, neutrophilia was observed in the survivors, but neutropenia, a `left shift’, and toxic granulation were observed in the non-survivors. Consistent with this observation, Gregory and Hey reported three neonates who died with overwhelming bacterial sepsis and noted that all had profound neutropenia. Neutrophilia was common among the survivors and neutropenia, a “left shift’, and specific neutrophil morphological changes were seen among those who subsequently died.

A pivotal publication that launched the search for mechanistic information and successful treatments was that of Dr Barbara Manroe, a fellow in Neonatal Medicine, and her mentor Dr Charles Rosenfeld (Fig 6) from the University of Texas, South-western, Parkland Hospital in Dallas, Texas (Manroe et al, 1977). They evaluated 45 neonates who had culture-proven group B streptococcal infection and found that 39 had abnormal leucocyte counts: 25 neutrophilia and 14 neutropenia, and that 41 had a `left shift’. This paper was the first to quantify the `left shift’ using a method that has since become popular in neonatology – the ratio of immature neutrophils to total neutrophils on the differential cell count.

From these beginning, hundreds of studies using experimental models and clinical observations and trials were published, detailing the kinetic and molecular mechanisms accounting for this common variety of neutropenia. Marked improvements in the survival of neonates with this condition have come about through combined efforts, including early maternal screening for GBS carriage, early anti-microbial administration to ill neonates, non-specific antibody administration and a variety of measures to improve supportive care of neonates with early onset sepsis.

In the early 1930s, Dr Helen Mackay worked as a paediatrician in Mother’s Hospital, a maternity hospital located in the north-east section of London. Acting on the observation of Lichtenstein (1921) that infants of subnormal birth weight regularly became anaemic in the first months of life, she measured and reported serial heel-stick haemoglobin levels on 150 infants during their first 6 months. Thirty-nine of these infants weighed under five pounds at birth (six were under four pounds), 52 weighed five to six pounds, and 59 weighed six pounds and upwards. She showed that babies of the lightest birth weights had the most rapid fall in haemoglobin and that these fell to lower levels than those of babies of heavier birth weight (MacKay et al, 1935). Figure 7 contrasts this fall in babies weighing `3-4 lbs odd at birth’ with those weighing `5 lbs odd at birth’.

Her attempts to prevent the anaemia of prematurity failed,  but her work constituted the first clear definition of the `anaemia of prematurity’ and showed that iron administration did not prevent this condition. In the early 1950s, Douglas Gairdner, John Marks and Janet D. Roscoe, of the Department of Pathology of Cambridge Maternity Hospital, published pioneering studies in blood formation in infancy (Gairdner et al, 1952a, b). Studying 105 blood samples and 102 bone marrow samples, they concluded that `erythropoiesis ceases when the oxygen saturation just after birth increases from about 65% in the umbilical vein to .95% just after birth’. Publications by Dr Irving Schulman, in the mid- to late 1950s, defined three phases of the anaemia of prematurity and provided a mechanistic explanation for the anaemia (Schulman & Smith, 1954; Schulman, 1959). His work illustrated that the early and intermediate phases of this anaemia occur in the face of relative iron excess and are unaffected by prophylactic iron administration.

Haemoglobin levels during the first 25 weeks of life among

Haemoglobin levels during the first 25 weeks of life among

Haemoglobin levels during the first 25 weeks of life among neonates in London [by permission; Archives Diseases of Children, (MacKay, 1935)].

In 1963, Dr Sverre Halvorsen of the Department of Paediatrics at Rikshospatalet in Oslo, Norway (Fig 9), provided an underlying explanation for the observations made by MacKay, Gairdner and Schulman (Halvorson, 1963). He observed that, compared with the blood of healthy adults, umbilical cord blood of healthy neonates had a high erythropoietin concentration, but the concentration was considerably higher in the plasma of severely erythroblastotic, anaemic infants. Among the healthy infants, erythropoietin levels fell to unmeasurably low concentrations after delivery, but levels remained elevated in hypoxic and cyanotic infants. Dr Per Haavardsholm Finne, also of the Children’s Department, Paediatric Research Institute and Department of Obstetrics and Gynaecology at Rikshospitalet in Oslo, observed high oncentrations of erythropoietin in the amniotic fluid and the umbilical cord blood after fetal hypoxia (Finne, 1964, 1967).

In subsequent studies, Dr Halvorsen observed lower plasma erythropoietin concentrations in the cord blood of preterm infants at delivery than in term neonates at delivery (Halvorsen & Finne, 1968). These observations supported the concept of Gairdner et al (1952a, b) that the postnatal fall in erythropoiesis (the `physiologic anaemia’ of neonates) is as a result of an increase in oxygen delivery to tissues following birth and is mediated by a fall in circulating erythropoietin concentration. The observations gave rise to the postulate that the `anaemia of prematurity’ was an exaggeration of this physiological anaemia and involved a limitation of preterm infants to appropriately increase erythropoietin production.

Many landmark reports of haematological findings of neonates that were published between 1925 and 1975 were not detailed in this review because they were outside the restricted topics selected.

Robert D. Christensen, MD, Gainesville, FL
Brit J Haem 2001; 113: 853-860

Towards Molecular Medicine; Reminiscences of the Haemoglobin Field

When historians of medicine in the twentieth century start to piece together the complex web of events that led from a change of emphasis of medical research from studies of patients and their organs to disease at the levels of cells and molecules they will undoubtedly have their attention drawn to the haemoglobin field, particularly the years that followed Linus Pauling’s seminal paper in 1949 which described sickle-cell anaemia as a `molecular disease’. These are personal reminiscences of some of the highlights of those exciting times, and of those who made them happen.

One of my first patients serving the RAMC was a Nepalese Ghurka child who was kept alive from the first few months of life with regular blood transfusion without a diagnosis. Henry Kunkel published a paper which described how, using electrophoresis in slabs of starch, he had found a minor component of human haemoglobin (Hb), Hb A2, the proportion of which was elevated in some carriers of thalassaemia. After several weeks spent knee deep in potato starch, we found that the Ghurka child’s parents had increased Hb A2 levels and, hence, that she was likely to be homozygous for thalassaemia. I was hauled up before the Director General of Medical Services for the Far East Land Forces and told that I could be court marshalled for not getting permission from the War House (Office) to publish information about military personnel. `And, in any case’, he added, `it is bad form to tell the world that one of our pukka regiments has bad genes; don’t do it again’.

Just before the end of my National Service I arranged to go to Johns Hopkins Hospital in Baltimore to train in genetics and haematology. I was told that I was wasting my time working on haemoglobin because there was `nothing left to do’. `Start exploring red cell enzymes’, he suggested. On arriving in Baltimore in 1960 it turned out that human genetics, and the haemoglobin field in particular, were bubbling with excitement and potential. The only lessons for those contemplating careers in medical research from this chapter of academic and military gaffs are that, regardless of the working conditions, when there are sick people there are always interesting research questions to be asked.

The excitement of the haemoglobin field in 1960 reflected the chance amalgamation of several disciplines in the 1950s, particularly X-ray crystallography, protein chemistry, human genetics and haematology.

From the early 1930s the structure of proteins became one of the central problems of biochemistry. At that time, the only way of tackling this problem was by X-ray crystallography. In 1937 Felix Haurowitz suggested to Max Perutz (Fig 1) that an X-ray study of haemoglobin might be a good subject for his doctoral thesis. He was given some large crystals of horse methaemoglobin which gave excellent Xray diffraction patterns.

Max Perutz

Max Perutz

However, there was a major snag; an X-ray diffraction pattern provided only half the information required to solve the structure of a protein, that is the amplitudes of diffracted rays, while the other half, their phases, could not be determined. But in 1953, they discovered that it could be solved in two dimensions by comparison of the diffraction patterns of a crystal of native haemoglobin with that of haemoglobin reacted with mecuribenzoate, which combines with its two reactive sulphydryl groups. In short, to solve the structure in three dimensions required the comparison of the diffraction patterns of at least three crystals, one native and two with heavy atoms combined with different sites on the haemoglobin molecule. In 1959 this approach yielded the first three-dimensional model of haemoglobin, at 5´5 AÊ resolution.

Protein chemistry evolved side-by-side with X-ray crystallography during the 1950s. In 1951 Fred Sanger solved the structure of insulin, a remarkable tour de force which showed that proteins have unique chemical structures and amino acid sequences. Sanger had perfected methods for fractionation and characterization of small peptides by paper chromatography or electrophoresis. In 1956 Vernon Ingram (Fig 2), who, like Max Perutz, was a refugee from Germany, was set the task of studying the structure of haemoglobin from patients with sickle-cell anaemia. Ingram separated the peptides produced after globin had been hydrolysed with the enzyme trypsin, which cuts only at lysine and arginine residues. Although these amino acids accounted for 60 residues per mol of haemoglobin, only 30 tryptic peptides were obtained, indicating that haemoglobin consists of two identical half molecules. Re-examination of the amino-terminal sequences of haemoglobin by groups in the United States and Germany showed 2 mols of valine ± leucine and 2 mols of valine ± histidine ± leucine per mol of globin. These findings, which were in perfect agreement with the X-ray crystallographic results, suggested that haemoglobin is a tetramer composed of two pairs of unlike peptide chains, which were called α and β.

A seminal advance, and one which was to mark the beginning of molecular medicine, was the chance result of an overnight conversation on a train journey between Denver and Chicago. Linus Pauling, the protein chemist, and William Castle (Fig 3), one of the founding fathers of experimental haematology, were returning from a meeting in Denver and Castle mentioned to Pauling that he and his colleagues had noticed that when red cells from patients with sickle-cell anaemia are deoxygenated and sickle they show birefringence in polarized light.

Five generations of Boston haematology. Seated is William Castle. Standing (left to right) are Stuart Orkin, David Nathan and Alan Michelson. The picture on the left is of Dean David Edsall of Harvard Medical School who established the Thorndyke Laboratory at the Boston City Hospital. He was succeeded by Dean Peabody, who recruited both George Minot, who won the Nobel Prize for his work on pernicious anaemia, and William Castle, who should have also received it.

Pauling guessed that this might reflect a structural difference between normal and sickle-cell haemoglobin which could be detected by a change in charge. He gave this problem to one of his postdoctoral students, a young medical graduate called Harvey Itano. At that time they knew that a Swede, Arne Tiselius, had invented a machine for separating proteins according to their charge by electrophoresis. As there was no machine of this kind in Pauling’s laboratory, Itano and his colleagues set to and built one. Eventually they found that the haemoglobin of patients with sickle-cell anaemia behaves differently to that of normal people in an electric field, indicating that it must have a different amino acid composition. Even better, the haemoglobin of sickle-cell carriers was a mixture of both types of haemoglobin. This work was published in Science in 1949, under the title `Sickle-cell anaemia: a molecular disease’.

Perutz and Crick suggested to Ingram that he should apply Sanger’s techniques of peptide analysis to see if he could find any difference between normal and sickle cell haemoglobin. After digesting haemoglobin with trypsin, Ingram separated the peptides by electrophoresis and chromatography in two dimensions to produce what he later called `fingerprints’. He recalls that his first efforts looked like a watercolour that had been left out in the rain. But gradually things improved and he was able to show that the fingerprints of Hbs A and S were identical except for the position of one peptide. Using a method that had been developed a few years earlier by Pehr Edman, which allowed a peptide to be degraded one amino acid at a time in a stepwise fashion, Ingram found that this difference was due to the substitution of valine for glutamic acid at position 6 in the β chain of Hb S.

As well as demonstrating how a crippling disease can result from only a single amino acid difference in the haemoglobin molecule, this beautiful work had broader implications for molecular genetics. Although nothing was known about the nature of the genetic code at the time, the findings were compatible with the notion that the primary product of the β-globin gene is a peptide chain, a further development of the one-gene-one-enzyme concept, suggested earlier by Beadle and Tatum from their studies of Neurospora, and a prelude to the later studies of Yanofsky on Escherichia coli, which were to confirm this principle.

With the advent of simple filter paper electrophoresis, haemoglobin analysis became the province of clinical research laboratories during the 1950s and `new’ abnormal haemoglobins appeared almost by the week. Although many scientists were involved it was Hermann Lehmann (Fig 4) who became the father figure. Like Handel, Hermann was born in Halle and, also like the composer, made his home in Great Britain. He came to England as a refugee and at the beginning of the Second World War had a short period of internment as a `friendly alien’ at Huyton, close to Liverpool, an experience shared with many others, including Max Perutz. He travelled widely during his later war service in the RAMC and developed a wide international network which enabled him to discover 81 haemoglobin variants during his career.

Harvey Itano and Elizabeth Robinson showed that Hb Hopkins 2 is an a chain variant. Hence, it was now clear that there must be at least two unlinked loci involved in regulating haemoglobin production, a and b. The discovery of the λ and δ chains of Hbs F and A2, respectively, meant that there must be at least four loci involved. Subsequent family studies and analyses of unusual variants resulting from the production of δβ or λβ fusion chains led to the ordering of the non-α globin genes.

It had been known for some years that children with severe forms of thalassaemia might have persistent production of HbF and it was found later that some carriers might have elevated levels of Hb A2. The seminal observation in favour of this notion came from the study of patients who had inherited the sickle-cell gene from one parent and thalassaemia from the other. Sickle-cell thalassaemia was first described by Ezio Silvestroni and his wife Ida Bianco in 1946, although at the time they could not have known the full significance of their finding.  Phillip Sturgeon and his colleagues in the USA found that the pattern of haemoglobin production in patients with sickle-cell thalassaemia is quite different to that of heterozygotes for the sickle-cell gene; the effect of the thalassaemia gene is to reduce the amount of Hb A to below that of Hb S, i.e. exactly the  opposite to the ratio observed in sickle-cell carriers. As it was known that the sickle-cell mutation occurs in the β globin gene, it could be inferred that the action of the thalassaemia gene was to reduce the amount of β globin production from the normal allele. Indeed, from the few family studies available in 1960 there was a hint that this form of thalassaemia might be an allele of the β globin gene. Another major observation that was made in the mid-50 s was the association of unusual tetramer haemoglobins, β4 (Hb H) and λ4 (Hb Bart’s), with a thalassaemia phenotype. In 1959 Vernon Ingram and Tony Stretton proposed in a seminal article that there are two major classes, α and β, just as there are two major types of structural haemoglobin variants. They extended the ideas of Linus Pauling and Harvey Itano, who had suggested that defective globin synthesis in thalassaemia might be due to `silent’ mutations of the β globin genes, and postulated that the defects might lie outside the structural gene in the area of DNA in the connecting unit. work on the interactions of thalassaemia and haemoglobin variants in the late 1950s had moved the field to a considerably higher level of understanding than is apparent in the earlier papers of Pauling and Itano. In any case, in their paper Ingram and Stretton generously acknowledged the ideas of other workers, including Lehmann, Gerald, Neel and Ceppellini, that had allowed them to develop their conceptual framework of the general nature of thalassaemia. This interpretation of events, and the input of scientists from many different disciplines into these concepts, is supported by the published discussions of several conferences on haemoglobin held in the late 1950s.

Historical Review. Towards Molecular Medicine; Reminiscences of the Haemoglobin Field. D. J. Weatherall, Weatherall Institute of Molecular Medicine, University of Oxford. Brit J  Haem 115:729-738.

The Emerging Understanding of Sickle Cell Disease

The first indisputable case of sickle cell disease in the literature was described in a dental student studying in Chicago between 1904 and 1907 (Herrick, 1910). Coming from the north of the island of Grenada in the eastern Caribbean, he was first admitted to the Presbyterian Hospital, Chicago, in late December 1904 and a blood test showed the features characteristic of homozygous sickle cell (SS) disease. It was a happy coincidence that he was under the care of Dr James Herrick (Fig 1) and his intern Dr Ernest Irons because both had an interest in laboratory investigation and Herrick had previously presented a paper on the value of blood examination in reaching a diagnosis (Herrick, 1904-05). The resulting blood test report by Dr Irons described and contained drawings of the abnormal red cells (Fig 2) and the photomicrographs, showing irreversibly sickled cells.

People with positive sickle tests were divided into asymptomatic cases, `latent sicklers’, and those with features of the disease, `active sicklers’, and it was Dr Lemuel Diggs of Memphis who first clearly distinguished symptomatic cases called sickle cell anaemia from the latent asymptomatic cases which were termed the sickle cell trait (Diggs et al, 1933).

Prospective data collection in 29 cases of the disease showed sickling in all 42 parents tested (Neel, 1949), providing strong support for the theory of homozygous inheritance. A Colonial Medical Officer working in Northern Rhodesia (Beet, 1949) reached similar conclusions at the same time with a study of one large family (the Kapokoso-Chuni pedigree). The implication that sickle cell anaemia should occur in all communities in which the sickle cell trait was common and that its frequency would be determined by the prevalence of the trait did not appear to fit the observations from Africa. Despite a sickle cell trait prevalence of 27% in Angola, Texeira (1944) noted the active form of the disease to be `extremely rare’ and similar observations were made from East Africa. Lehmann and Raper (1949, 1956) found a positive sickling test in 45% of one community, from which homozygous inheritance would have predicted that nearly 10% of children had SS disease, yet not a single case was found. The discrepancy led to a hypothesis that some factor inherited from non-black ancestors in America might be necessary for expression of the disease (Raper, 1950).

The explanation for this apparent discrepancy gradually emerged. Working with the Jaluo tribe in Kenya, Foy et al (1951) found five cases of sickle cell anaemia among very young children and suggested that cases might be dying at an age before those sampled in surveys. A similar hypothesis was advanced by Jelliffe (1952) and was supported by data from the then Belgian Congo (Lambotte-Legrand Lambotte-Legrand, 1951, Lambotte-Legrand, 1952, Vandepitte, 1952). Although most cases were consistent with the concept of homozygous inheritance, exceptions continued to occur. Patients with a non-sickling parent of Mediterranean ancestry were later recognized to have sickle cell-β thalassaemia (Powell et al, 1950; Silvestroni & Bianco, 1952; Sturgeon et al, 1952; Neel et al, 1953a), a condition also widespread in African and Indian subjects that presents a variable syndrome depending on the molecular basis of the β thalassaemia mutation and the amount of HbA produced.

Phenotypically, there are two major groups in subjects of African origin, sickle cell-β+ thalassaemia manifesting 20-30% HbA and mutations at 229(A,G) or 288(C,T), and sickle cell-β0 thalassaemia with no HbA and mutations at IVS2-849(A,G) or IVS2-1(G,A). In Indian subjects, a more severe β thalassaemia mutation IVS1-5(G,C) results in a sickle cell-β+ thalassaemia condition with 3-5% HbA and a relatively severe clinical course.

Other double heterozygote conditions causing sickle cell disease include sickle cell-haemoglobin C (SC) disease, (Kaplan et al, 1951; Neel et al, 1953b), sickle cellhaemoglobin O Arab (Ramot et al, 1960), sickle cellhaemoglobin Lepore Boston (Stammatoyannopoulos & Fessas, 1963) and sickle cell-haemoglobin D Punjab (Cooke & Mack, 1934). The latter condition was first described in siblings in 1934, who were reinvestigated for confirmation of HbD (Itano, 1951), the clinical features reported (Sturgeon et al, 1955) and who were finally identified as HbD Punjab (Babin et al, 1964), representing a remarkable example of longitudinal observation and investigation in the same family over 30 years.

The maintenance of high frequencies of the sickle cell trait in the presence of almost obligatory losses of homozygotes in Equatorial Africa implied that there was either a very high frequency of HbS arizing by fresh mutations or that the sickle cell trait conveyed a survival advantage in the African environment. There followed a remarkable period in the 1950s when three prominent scientists were each addressing this problem in East Africa, Dr Alan Raper and Dr Hermann Lehmann in Uganda and Dr Anthony Allison in Kenya. It was quickly calculated that mutation rates were far too low to balance the loss of HbS genes from deaths of homozygotes (Allison, 1954a). An increased fertility of heterozygotes was proposed (Foy et al, 1954; Allison, 1956a) but never convincingly demonstrated. Raper (1949) was the first to suggest that the sickle cell trait might have a survival advantage against some adverse condition in the tropics and Mackey & Vivarelli (1952) suggested that this factor might be malaria. The close geographical association between the distribution of malaria and the sickle cell gene supported this concept (Allison, 1954b) and led to an exciting period in the history of research in sickle cell disease.

The first observations on malaria and the sickle cell trait were from Northern Rhodesia where Beet (1946, 1947) noted that malarial parasites were less frequent in blood films from subjects with the sickle cell trait. Allison (1954c) drew attention to this association, concluding that persons with the sickle cell trait developed malaria less frequently and less severely than those without the trait. This communication marked the beginning of a considerable controversy.Two studies failed to document differences in parasite densities between `sicklers’ and `non-sicklers’ (Moore et al, 1954; Archibald & Bruce-Chwatt, 1955) and Beutler et al (1955) were unable to reproduce the inoculation experiments of Allison (1954c). Raper (1955) speculated that some feature of Allison’s observations had accentuated a difference of lesser magnitude and postulated that the sickle cell trait might inhibit the establishment of malaria in non-immune subjects. The conflicting results in these and other studies appear to have occurred because the protective effect of the sickle cell trait was overshadowed by the role of acquired immunity. Examination of young children before the development of acquired immunity confirmed both lower parasite rates and densities in children with the sickle cell trait (Colbourne & Edington, 1956; Edington & Laing, 1957; Gilles et al, 1967) and it is now generally accepted that the sickle cell trait confers some protection against falciparum malaria during a critical period of early childhood between the loss of passively acquired immunity and the development of active immunity (Allison, 1957; Rucknagel & Neel, 1961; Motulsky, 1964). The mechanism of such an effect is still debated, although possible factors include selective sickling of parasitized red cells (Miller et al, 1956; Luzzatto et al, 1970) resulting in their more effective removal by the reticulo-endothelial system, inhibition of parasite growth by the greater potassium loss and low pH of sickled red cells (Friedman et al, 1979), and greater endothelial adherence of parasitized red cells (Kaul et al, 1994).

The occurrence of the sickle cell mutation and the survival advantage conferred by malaria together determine the primary distribution of the sickle cell gene. Equatorial Africa is highly malarial and the sickle cell mutation appears to have arisen independently on at least three and probably four separate occasions in the African continent, and the mutations were subsequently named after the areas where they were first described and designated the Senegal, Benin, Bantu and Cameroon haplotypes of the disease (Kulozik et al, 1986; Chebloune et al, 1988; Lapoumeroulie et al, 1992). The disease seen in North and South America, the Caribbean and the UK is predominantly of African origin and mostly of the Benin haplotype, although the Bantu is proportionately more frequent in Brazil (Zago et al, 1992). It is therefore easy to understand the common misconception held in these areas that the disease is of African origin.

However, the sickle cell gene is widespread around the Mediterranean, occurring in Sicily, southern Italy, northern Greece and the south coast of Turkey, although these are all of the Benin haplotype and so, ultimately, of African origin. In the Eastern province of Saudi Arabia and in central India, there is a separate independent occurrence of the HbS gene, the Asian haplotype. The Shiite population of the Eastern Province traditionally marry first cousins, tending to increase the prevalence of SS disease above that expected from the gene frequency (Al-Awamy et al, 1984). Furthermore, extensive surveys performed by the Anthropological Survey of India estimate an average sickle cell trait frequency of 15% across the states of Orissa, Madhya Pradesh and Masharastra which, with the estimated population of 300 million people, implies that there may be more cases of sickle cell disease born in India than in Africa. The Asian haplotype of sickle cell disease is generally associated with very high frequencies of alpha thalassaemia and high levels of fetal haemoglobin, both factors believed to ameliorate the severity of the disease.

The promotion of sickling by low oxygen tension and acid conditions was first recognized by Hahn & Gillespie (1927) and further investigated by others (Lange et al, 1951; Allison, 1956b; Harris et al, 1956). The morphological and some functional characteristics of irreversibly sickled cells were described (Diggs & Bibb, 1939; Shen et al, 1949), but the essential features of the polymerization of reduced HbS molecules had to await the developments of electron microscopy (Murayama, 1966; Dobler & Bertles, 1968; Bertles & Dobler, 1969; White & Heagan, 1970) and Xray diffraction (Perutz & Mitchison, 1950; Perutz et al, 1951). The early observations on the inducement of sickling by hypoxia led to the first diagnostic tests utilizing sealed chambers in which oxygen was removed by white cells (Emmel, 1917), reducing agents such as sodium metabisulphite (Daland & Castle, 1948) or bacteria such as Escherichia coli (Raper, 1969). These slide sickling tests are very reliable with careful sealing and the use of positive controls, but require a microscope and some expertise in its use. An alternative method of detecting HbS utilizes its relative insolubility in hypermolar phosphate buffers (Huntsman et al, 1970), known as the solubility test. Both the slide sickle test and the solubility test detect the presence of HbS, but fail to make the vital distinction between the sickle cell trait and forms of sickle cell disease. This requires the process of haemoglobin electrophoresis, which detects the abnormal mobility of HbS, HbC and many other abnormal haemoglobins within an electric field.

The contributions of several workers on the determinants of sickling (Daland & Castle, 1948), birefringence of deoxygenated sickled cells (Sherman, 1940) the lesser degree of sickling in very young children which implied that it was a feature of adult haemoglobin (Watson, 1948) led Pauling to perform Tiselius moving boundary electrophoresis on haemoglobin solutions from subjects with sickle cell anaemia and the sickle cell trait. The demonstration of electrophoretic and, hence, implied chemical differences between normal, sickle cell trait and sickle cell disease led to the proposal that it was a molecular disease (Pauling et al, 1949). The chance encounter between Castle and Pauling who shared a train compartment returning from a meeting in Denver in 1945, its background and implications, has passed into the folklore of medical research (Conley, 1980; Feldman & Tauber, 1997).

The nature of this difference was soon elucidated. The haem groups appeared identical, suggesting that the difference resided in the globin, but early chemical analyses revealed no distinctive differences (Schroeder et al, 1950; Huisman et al, 1955). Analyses of terminal amino acids also failed to reveal differences, although an excess of valine in HbS was noted but considered an experimental error (Havinga, 1953). The development of more sensitive methods of fingerprinting combining high voltage electrophoresis and chromatography allowed the identification of the essential difference between HbA and HbS. This method enabled the separation of constituent peptides and demonstrated that a peptide in HbS was more positively charged than in HbA (Ingram, 1956). This peptide was found to contain less glutamic acid and more valine, suggesting that valine had replaced glutamic acid (Ingram, 1957). The sequence of this peptide was shown to be Val-His-Leu-Thr-Pro-Val-Glu-Lys in HbS instead of the Val-His-Leu-Thr-Pro-Glu-Glu-Lys in HbA (Hunt & Ingram, 1958), a sequence which was subsequently identified as the amino-terminus of the b chain (Hunt & Ingram, 1959). This amino acid substitution was consistent with the genetic code and was subsequently found to be attributable to the nucleotide change from GAG to GTG (Marotta et al, 1977).

Haemolysis and anaemia. The presence of anaemia and jaundice in the first four cases suggested accelerated haemolysis, which was supported by elevated reticulocyte counts (Sydenstricker et al, 1923) and expansion of the bone marrow (Sydenstricker et al, 1923; Graham, 1924). The bone changes of medullary expansion and cortical thinning were noted in early radiological reports (Vogt & Diamond, 1930; LeWald, 1932; Grinnan, 1935). Drawing on a comparison of sickle cell disease and hereditary spherocytosis, Sydenstricker (1924) introduced the term `haemolytic crisis’ that has persisted in the literature to this day, despite the lack of evidence for such an entity in sickle cell disease. The increased requirements of folic acid and the consequence of a deficiency leading to megaloblastic change was not noted until much later (Zuelzer & Rutzky, 1953; Jonsson et al, 1959; MacIver & Went, 1960).

The haemoglobin level in SS disease of African origin is typically between 6 and 9 g/dl and is well tolerated, partly because of a marked shift in the oxygen dissociation curve (Scriver & Waugh, 1930; Seakins et al, 1973) so that HbS within the red cell behaves with a low oxygen affinity. This explains why patients at their steady state haemoglobin levels rarely show classic symptoms of anaemia and fail to benefit clinically from blood transfusions intended to improve oxygen delivery.

Graham R. Serjeant
Sickle Cell Trust, Kingston, Jamaica
Brit J Haem 2001; 112: 3-18

The Immune Haemolytic Anaemias

The growth in knowledge of the scientific basis of haemolytic anaemias, which have been a main interest of the author, has been remarkable, as have consequent advances in the practice of medicine since the mid-1930s. At that time, the cause and mechanism of important disorders such as the acquired antibody determined (immune) haemolytic anaemias, haemolytic disease of the newborn, hereditary spherocytosis and paroxysmal nocturnal haemoglobinuria were unknown or but partially understood.

According to Crosby (1952), William Hunter of London, in an article on pernicious anaemia published in 1888, was the first to use the term `haemolytic’ to denote an anaemia caused by excessive blood destruction. By the turn of the century, the term was being widely used in clinical literature. Peyton Rous, in his comprehensive review `Destruction of the red blood corpuscles in health and disease’ (Rous, 1923), concluded that the generally held view in the early 1930s was that about one-fifteenth of the erythrocyte mass was destroyed daily. Rous was aware of the pioneer work of Winifred Ashby (1919), who, by following the survival of serologically distinct but compatible transfused erythrocytes, had found that normal erythrocytes might live for up to 100 d in the recipients’ circulation. Subsequent work using radioactive chromium (51Cr) as an erythrocyte label, showed that Ashby’s data and conclusions were in fact correct, i.e. that normal erythrocytes in health circulate in the peripheral blood for approximately 110 d. Erythrocyte labelling with 51Cr also had a further advantage over the Ashby method in addition to enabling the life-span of the patients’ erythrocytes to be assessed in the circulation by surface counting, to detect and measure the accumulation of radioactivity in the spleen and liver, and thereby assess the organs’ role in haemolysis

In the first decade of the twentieth century Widal et al (1908a) and Le Gendre & Brulea (1909) reported that autohaemoagglutination was a striking finding in some cases of icteare heamolytique acquis, and also Chauffard & Trosier (1908) and Chauffard & Vincent (1909) had described the presence of haemolysins in the serum of patients suffering from intense haemolysis. The conclusion was that abnormal immune processes, i.e. the development of auto-antibodies damaging the patients’ own erythrocytes, might play a part in the genesis of some cases of acquired haemolytic anaemia. This was indeed antedated by the classic observations of Donath & Landsteiner (1904) and Eason (1906) on the mechanism of haemolysis in paroxysmal cold haemoglobinuria.

That blood might auto-agglutinate when chilled had been described by Landsteiner (1903) and that an unusual degree of the phenomenon might complicate some types of respiratory disease was reported by Clough & Richter (1918) and later by Wheeler et al (1939). A few years later Peterson et al (1943) and Horstmann & Tatlock (1943) reported that cold auto-agglutinins at high titres were frequently found in the serum of patients who had suffered from the then so called primary atypical pneumonia.

Stats & Wasserman’s (1943) review on cold haemagglutination was a valuable contribution to contemporary knowledge. They listed in a table as many as 94 references to papers published between 1890 and 1943 in which cold haemagglutination had been described. In 32 of the papers the patients referred to had suffered from increased haemolysis

Recognition that cold auto-antibodies played an important role in the pathogenesis of some cases of haemolytic anaemia led to the concept that auto-immune haemolytic anaemia (AIMA) might usefully be classified into warm antibody or cold-antibody types, according to whether the patient is forming (warm) antibodies which react (perhaps optimally) at body temperature or (cold) antibodies which react strongly at low temperatures (e.g. 48C) but progressively less well as the temperature is raised and are perhaps inactive at 37oC. The clinical syndrome suffered by the patient would depend not only on the amount of antibody produced but also on its temperature requirement. Another important advance in understanding has been the realization that both types of AIHA could develop in association with a wide range of underlying disorders (secondary AIHA) as well as `idiopathically’, i.e. for no obvious cause (primary AIHA). The author’s own experience was summarized in a review (Dacie & Worlledge, 1969): 99 out of 210 cases of warm AIHA were judged to be secondary as were 39 out of 85 cases of cold AIHA. Petz & Garratty (1980), summarized the data from six centres: 55% out of a total of 656 cases had been reported as secondary. They listed the disorders with which warm antibody AIHA had been associated as chronic lymphocytic leukaemia, Hodgkin’s disease, non-Hodgkin’s lymphomas, thymomas, multiple myeloma, Waldenstrom’s macroglobulinaemia, systemic lupus erythematosus, scleroderma, rheumatoid arthritis, infectious disease/ childhood viral disorders, hypogammaglobulinaemia, dysglobulinaemias, other immune deficiency syndromes, and ulcerative colitis.

Conley (1981), in an interesting review of warm-antibody AIHA patients seen at the Johns Hopkins Hospital, emphasized how important it was to carry out a careful enquiry into the patient’s past history and also to undertake a prolonged follow-up. He stated that a retrospective review of 33 patients whose illnesses in the past have been designated `idiopathic” had revealed an associated immunologically related disorder in 19 of them. An additional three patients had developed a lymphoma 2±10 years after they had developed AIHA. As already referred to, warm-antibody AIHA is now known to complicate a wide range of underlying diseases, particularly malignant lymphoproliferative disorders, other auto-immune disorders and immune deficiency syndromes. What proportion of patients suffering from a lymphoproliferative disorder develop AIHA is an interesting question. Duehrsen et al (1987) stated that this had occurred in 12 out of 637 patients. Early data on the incidence of a positive DAT in SLE were provided by Harvey et al (1954) – in six out of 34 patients tested the DAT had been positive. Later, Mongan et al (1967), who had studied a large number of patients suffering from a variety of connective tissue disorders, reported that the DAT had been positive in 15 out of 23 patients with SLE, none of whom, however, had suffered from overt haemolytic anaemia. It has also been realized since the 1960s that warm-antibody AIHA may develop in patients suffering from a variety of immune deficiency syndromes, both congenital and acquired.

It was in the mid-1960s that it was realized that, in a significant proportion of patients thought to have `idiopathic’ warm-antibody AIHA, the development of the causal auto-antibodies had been triggered in some way by a drug the patient was taking. The first drug implicated was the antihypertensive drug a-methyldopa (Aldomet) (Carstairs et al, 1966a,b). Following the finding that treating hypertensive patients with a-methyldopa led to the formation of anti-erythrocyte auto-antibodies in a significant percentage of patients, renewed interest was taken in the possibility that other drugs might have the same effect. Two main hypotheses have been advanced in relation to how certain drugs in some patients appear to have caused the development of anti-erythrocyte auto-antibodies. One hypothesis was that the drug or its metabolites act on the immune system so as to impair immune tolerance; the other was that the drug affects antigens at the erythrocyte surface in such a way that a normally active immune system responds by developing anti-erythrocyte antibodies. Clearly, too, the patient’s individuality must be an important factor, for only a proportion of patients receiving the same dosage of the offending drug for the same period of time develop a positive DAT and only a small percentage develop overt AIHA.

An interesting development in the history of the immune haemolytic anaemias was the realization in the mid-1950s that, rather rarely, haemolysis was brought about by the patient developing antibodies that were directed against a drug the patient had been taking and that the erythrocytes were in some way secondarily involved. The first drug to be implicated was Fuadin (stibophen), which had been used to treat a patient with schistosomiasis (Harris, 1954, 1956). The patient’s serum contained an antibody that agglutinated his own or normal erythrocytes and/or sensitized them to agglutination by antiglobulin sera; however, this occurred only in the presence of the drug.

In the late 1940s, several accounts of patients with AIHA who had persistently low platelet counts were published, e.g. Fisher (1947) and Evans & Duane (1949); and it was suggested that the patients might have been forming autoantibodies directed against platelets. This concept was further developed by Evans et al (1951). Eight out of their 18 patients with AIHA were thrombocytopenic; four had clinically obvious purpura. Evans et al (1951) suggested that there exists `a spectrum-like relationship between acquired haemolytic anaemia and thrombocytopenic purpura’; also that `on the one hand, acquired haemolytic anaemia with sensitization of the red cells is often accompanied with thrombocytopenia, while, on the other hand, primary thrombocytopenic purpura is frequently accompanied with red cell sensitization with or without haemolytic anaemia’. Many further case reports of AIHA accompanied by severe thrombocytopenia have since been published

There are two features in the blood film of a patient with an acquired haemolytic anaemia which indicate that he or she is suffering from AIHA; one is auto-agglutination, the other is erythrophagocytosis. Spherocytosis, although often present to a marked degree, is of course found in other types of haemolytic anaemia.

The pioneer French observations on auto-agglutination already referred to were generally overlooked until the late 1930s, and serological studies seem seldom to have been undertaken until the publication of Dameshek & Schwartz’s (1938b) report in which they described the presence of `haemolysins’ in cases of acute apparently acquired haemolytic anaemia. Dameshek & Schwartz (1940) summarized contemporary knowledge in an extensive review. They concluded that it was not improbable that haemolysins of various types and `dosages’ were in fact responsible for many cases of human haemolytic anaemias, including congenital haemolytic anaemia, which they suggested might be caused by the `more or less continued action of an haemolysin’.

Six years were to pass before the concept that an abnormal immune mechanism played a decisive role in some cases of acquired haemolytic anaemia was clearly demonstrated by Boorman et al (1946), who reported that the erythrocytes of five patients with acquired acholuric jaundice had been agglutinated by an antiglobulin serum, i.e. that the newly described antiglobulin reaction or Coombs test (Coombs et al, 1945) was positive, while the test had been negative in 28 patients suffering from congenital acholuric jaundice. This work aroused great interest and was soon confirmed.

Until the 1950s, the auto-antibodies responsible for AIHA were generally concluded to be `non-specific’. According to Wiener et al (1953), `Red cell auto-antibodies react not only with the individual’s own red cells but also with the erythrocytes of all other human beings. The substances on the red blood cell envelope with which the auto-antibodies combine are agglutinogens like the ABO, MN and RhHr systems, except that, in the former case, the blood factors with which the auto-antibodies react are not type specific but are shared by all human beings.’ They suggested that the auto-antibodies might be directed to the `nucleus of the RhHr substance’. Earlier work had, however, indicated that the sensitivity of normal group-compatible erythrocytes to a patient’s auto-antibody might vary considerably (Denys & van den Broucke, 1947; Kuhns & Wagley, 1949). That auto-antibodies might have a clearly defined Rh specificity, e.g. anti-e, was described by Race & Sanger (1954) in the second edition of their book. Referring to Wiener et al (1953), they wrote: `This beautifully clear investigation made the present authors realize that a curious result obtained by one of them (Ruth Sanger) in 1953 in Australia had after all been true; the serum of a man who had died of a haemolytic anaemia 3000 miles away contained anti-e; his cells were clearly CDe-cde’. A similar finding, i.e. an auto-anti-e, was described by Weiner et al (1953).

A further development in the unravelling of a complicated story was the realization that some of the antibodies which appeared to be specific were reacting with more basic antigens, although showing a preference for specific antigens, i.e. some specific auto-antibodies appeared to be less specific than their allo-antibody counterparts. Moreover, some antibodies, reacting with specific antigens, have been shown to be partially or completely absorbable by antigen negative cells.

Many apparently `non-specific’ antidl antibodies have been shown to be not strictly `nonspecific’ but to react with antigens of very high frequency, e.g. to be anti-Wrb, anti-Ena, anti-LW or anti-U. Issitt et al (1980)) listed six additional very common antigens that had been identified as targets for anti-dl auto-antibodies, i.e. Hr, Hro, Rh34, Rh29, Kpb and K13.

In relation to human acquired haemolytic anaemia, the discovery in the late 1940s and 1950s that many cases were apparently brought about by the development of damaging anti-erythrocyte antibodies led to intense interest and speculation into the why and how of auto-antibody formation. Of seminal importance at the time were the experiments and theoretical arguments of Burnet (Burnet & Fenner, 1949; Burnet, 1957, 1959, 1972) and the studies on transplantation immunity of Medawar (Billingham et al, 1953; Medawar, 1961). Of particular interest, too, was the report by Bielschowsky et al (1959) of the occurrence of AIHA in an inbred strain of mice – the NZB/BL strain. Remarkably, by the time the mice were 9-months-old the DAT was positive in almost every mouse. Burnet (1963) referred to the gift of the mice to the Walter and Eliza Hall Institute of Medical Research, Melbourne as `the finest gift the Institute has ever received’.

Exactly how is it that auto-antibodies reacting with an erythrocyte surface antigen result in the cell’s premature destruction? The possible role of auto-agglutination in bringing about haemolysis was emphasized by Castle and colleagues as the result of a series of studies carried out in the 1940s and 1950s. As summarized by Castle et al (1950), an antibody which appears to be incapable of causing `lysis in vitro might bring about the following sequence of events in vivo. (1) Red cell agglutination in the peripheral blood; (2) red cell sequestration and separation from plasma in tissue capillaries; (3) ischaemic injury of tissue cells with release of substances that increase the osmotic and mechanical fragilities of red cells locally; (4) local osmotic lysis of red cells or subsequent escape of mechanically fragile red cells into the blood stream where the traumatic motion of the circulation causes their destruction’.

We can expect, as the years pass, that more and more will be known as to the intricate mechanisms that bring about self-tolerance and the mechanisms underlying the occurrence of auto-immune disorders in general, including the role of infectious agents, drugs and genetic factors. Patients with immune haemolytic anaemias can be expected to benefit from the new knowledge; for in parallel with a better understanding as to how immune self-tolerance breaks down will hopefully be the development of more effective drugs and therapies aimed at controlling the breakdown.

The Immune Haemolytic Anaemias: A Century of Exciting Progress in Understanding.  Sir John Dacie, Emeritus Professor of Haematology.
Brit J Haem 2001; 114: 770-785.

A History of Pernicious Anaemia

This is a review of the ideas and observations that have led to our current understanding of pernicious anaemia (PA). PA is a megaloblastic anaemia (MA) due to atrophy of the mucosa of the body of the stomach which, in turn, is brought about by autoimmune factors.

A case report by Osler & Gardner (1877) in Montreal could be that of PA. This anaemic patient had numbness of the fingers, hands and forearms; the red blood cells were large; at autopsy the gastric mucosa appeared atrophic and the marrow had large numbers of erythroblasts with finely granular nuclei. The increased marrow cellularity had also been noted by Cohnheim (1876).

Ehrlich (1880) (Fig 1) distinguished between cells he termed megaloblasts present in the blood in PA from normoblasts present in anaemia as a result of blood loss. Not only were large red blood cells noted in PA, but irregular red cells, ? poikilocytes, were reported in wet blood preparations by Quincke (1877). Megaloblasts in the marrow during life were first noted by Zadek (1921). Hypersegmented neutrophils in peripheral blood in PA were described by Naegeli (1923) and came to be widely recognized after Cooke’s study (Cooke, 1927). The giant metamyelocytes in the marrow were described by Tempka & Braun (1932).

Paul Ehrlich

Paul Ehrlich

Fig 1. Paul Ehrlich (Wellcome Institute Library, London).

The association between PA and spinal cord lesions was described by Lichtheim (1887) and a full account was published by Russell et al (1900), who coined the term `subacute combined degeneration of the spinal cord’ (SCDC) although they were not convinced of its relation to PA. Arthur Hurst at Guy’s Hospital, London, confirmed the association of the neuropathy with PA and added, too, the association of loss of hydrochloric acid in the gastric juice (Hurst & Bell, 1922). Cabot (1908) found that numbness and tingling of the extremities were present in almost all of his 1200 patients and 10% had ataxia. William Hunter (1901) noted the prevalence of a sore tongue in PA, which was present in 40% of Cabot’s series.

In 1934, the Nobel Prize in medicine and physiology was awarded to Whipple, Minot and Murphy. Was there ever an award more deserved? They saved the lives of their patients and pointed the way forward for further research. What was there in liver that was lacking in patients with PA? The effect of liver in restoring the anaemia in Whipple’s iron-deficient dogs was by supplying iron which is  abundant in liver.

Liver given by mouth also provides Cbl and folic acid. But patients with PA cannot absorb Cbl, although some 1% of an oral dose can cross the intestinal mucosa by passive diffusion; this, presumably, is what happened when large amounts of liver were eaten. Beef liver contains about 110 mg of Cbl per 100 g and about 140 mg of folate per 100 g. Cbl is stable and generally resistant to heat; folate is labile unless preserved with reducing agents. The daily requirement of Cbl by man is l-2 mg. The liver diet, if consumed, had enough of these haematinics to provide a response in most MAs.

George Richard Minot

George Richard Minot

George Richard Minot (Wellcome Institute Library, London).

The availability of liver extracts brought about interest in the nature of the haematological response. An optimal response required a peak rise of reticulocytes 5±7 d after the injection of liver extract and the height of the peak was greatest in those with severe anaemia; the flood of reticulocytes was as a result of a synchronous maturation of a vast number of megaloblasts into red cells. There is a steady rise in the red cell count to reach 3 x 1012/l in the 3rd week (Minot & Castle, 1935). Many liver extracts did not have enough antianaemic factor to achieve this and some assayed by the author had only 1-2 mg of Cbl.  It took another 22 years for a pure antianaemic factor to be isolated, although, admittedly, the Second World War intervened; in 1948, an American group led by Karl Folkers and an English group led by E. Lester-Smith published, within weeks of each other, the isolation of a red crystalline substance termed vitamin B12 and subsequently renamed cobalamin.

The structure of this red crystalline compound was studied by the nature of its degradation products and by X-ray crystallography. It soon became apparent that there was a cobalt atom at the heart of the structure and this heavy atom was of great aid to the crystallographers, so much so that, with additional information from the chemists, they were the first to come up with the complete structure. To quote Dorothy Hodgkin: `To be able to write down a chemical structure very largely from purely crystallographic evidence on the arrangement of atoms in space – and the chemical structure of a quite formidably large molecule at that – is for any crystallographer, something of a dream-like situation’. As Lester-Smith (1965) pointed out, it also required some 10 million calculations. In 1964, Dorothy Hodgkin was awarded the Nobel Prize for chemistry.

Barker et al (1958) published an account of the metabolism of glutamate by a Clostridium. The glutamate underwent an isomerization and an orange-coloured co-enzyme was involved that turned out to be Cbl with a deoxyadenosyl group attached to the cobalt.

This Cbl co-enzyme, deoxyadenosylCbl, is the major form of Cbl in tissues; it is also extremely sensitive to light, being changed rapidly to hydroxoCbl. DeoxyadenosylCbl is concerned with the metabolism of methylmalonic acid in man (Flavin & Ochoa, 1957). The other functional form of Cbl is methylCbl involved in conversion of homocysteine to methionine (Sakami & Welch, 1950). Both these pathways are impaired in PA in relapse.

Cbl consists of a ring of four pyrrole units very similar to that present in haem. These, however, have the cobalt atom in the centre instead of iron and the ring is called the corrin nucleus. The cobalamins have a further structure, a base, termed benzimidazole, set at right angles to the corrin nucleus and this may have a link to the cobalt atom (base on position).

By the time Cbl had been isolated from liver it was already known that it was also present in fermentation flasks growing bacteria such as streptomyces species. Other organisms gave higher yields so that kilogram quantities of pure Cbl were obtained; these sources have replaced liver in the production of Cbl. By adding radioactive form of cobalt to the fermentation flasks instead of ordinary cobalt, labelled Cbl became available (Chaiet et al, 1950). The importance of labelled Cbl is that it made it possible to carry out Cbl absorption tests in patients, to design isotope dilution assays for serum Cbl, to design ways of assaying intrinsic factor (IF), to detect antibodies to IF and even to measure glomerular filtratration rate, as free Cbl is excreted by the glomerulus without any reabsorption by the renal tubules.

William Castle at the Thorndike Memorial Laboratory, Boston City Hospital, devised experiments to explore the relationship between gastric juice, the anti-anaemic factor that Castle assumed, correctly, was also present in beef, and the response in PA. The question Castle asked was `Was it possible that the stomach of the normal person could derive something from ordinary food that for him was equivalent to eating liver?’.

The experiment in untreated patients with PA consisted of two consecutive periods of 10 d or more during which daily reticulocyte counts were made. During the first period of 10 d, the PA patient received 200 g of lean beef muscle (steak) each day. There was no reticulocyte response. During the second period, the contents of the stomach of a healthy man were recovered 1 h after the ingestion of 300 g of steak; about 100 g could not be recovered. The gastric contents were incubated for a few hours until liquefied and then given to the PA patient through a tube. This was done daily. On day 6 there was a rise in reticulocytes reaching a peak on day 10, followed by a rise in the red cell count. The response was similar to that obtained with large amounts of oral liver.

Thus, Castle concluded that a reaction was taking place between an unknown intrinsic factor (IF) in the gastric juice and an unknown extrinsic factor in beef muscle. Whereas Minot & Murphy (1926) found that 200-300 g of liver daily was needed to get a response in PA, 10 g liver was adequate when incubated with 10-20 ml normal gastric juice (Reiman & Fritsch, 1934). Castle’s extrinsic factor is the same as the anti-anaemic factor that is Cbl, and IF is needed for its absorption. Presumably the gastric juice in PA lacks IF.

The elegant studies of Hoedemaeker et al (1964) in Holland using autoradiography of frozen sections of human stomach incubated with [57Co]-Cbl showed that IF was produced in the gastric parietal cell. The binding of Cbl to

the parietal cell was abolished by first incubating the section with a serum containing antibodies to IF. The parietal cell in man is thus the source of both hydrochloric acid and IF. The parietal cell is the only source of IF in man as a total gastrectomy is invariably followed by a MA due to Cbl deficiency. IF is a glycoprotein with a molecular weight of 45 000.

Assay of protein fractions of serum after electrophoresis showed that endogenous Cbl is in the position of α-1 globulin. Chromatography of serum after addition of [57Co]-Cbl on Sephadex G-200 showed that Cbl was attached to two proteins, one eluting before the albumin termed transcobalamin I (TCI) and the other after the albumin termed transcobalamin II (TCII). Charles Hall showed that, when labelled Cbl given by mouth is absorbed, it first appears in the position of TCII and later in the position of TCI as well (Hall and Finkler, l965). They concluded that TCII is the prime Cbl transport protein carrying Cbl from the gut into the blood and then to the liver from where it is redistributed by both new TCII as well as TCI. Congenital absence of a functional TCII causes a severe MA in the first few months of life owing to an inability to transport Cbl. Most of the Cbl in serum is on TCI because it has a relatively long half-life of 9±10 d, whereas the half-life of TCII is about 1.5 h. Thus, in assaying the serum Cbl level, it is mainly TCI-Cbl that is being assayed.

With the availability of labelled Cbl, Cbl absorption tests began to be widely used in the 1950s. The commonest method was the urinary excretion test described by Schilling (1953). Here, an oral dose of radioactive Cbl is followed by an injection of 1000 mg of cyano-Cbl. The free cyano-Cbl is largely excreted into the urine over the next 24 h and carries with it about one third of the absorbed labelled Cbl.

Parietal cell antibodies (Taylor et al, 1962) are present in serum in 76-93% of different series of PAs and in the serum of 36% of the relatives of PA patients. The antibody is present in sera from 32% of patients with myxoedema, 28% of patients with Graves’ disease, 20% of relatives of thyroid patients and 23% of patients with Addison’s disease. Parietal cell antibodies are found in between 2-16% of controls, the high 16% figure being in elderly women. There is a higher frequency of PA in women, the female to male ratio being 1.7 to 1.0. The parietal cell antibody is probably important in the production of gastric atrophy. Thyroid antibodies are present in sera from 55% of PAs, in sera from 50% of PA relatives, in 87% of sera from myxoedema patients, in 53% of sera in Graves’ disease and in 46% of relatives of patients with thyroid disease.

There is a high frequency of PA among those disorders that have antibodies against the target organ. Thus, among 286 patients with myxoedema, 9.0% also had PA (Chanarin, 1979), as compared with a frequency of PA of about 1 per 1000 (0.01%) in the general population. Of 102 consecutive patients with vitiligo,
eight also had PA.

Patients with acquired hypogammaglobulinaemia are unable to make humoral antibodies; nevertheless, one third have PA as well. This cannot be as a result of action of IF antibodies and must be because of specific cell-mediated immunity. Tai & McGuigan (1969) demonstrated lymphocyte transformation in the presence of IF in six out of 16 PA patients and Chanarin & James (1974) found 10 out of 51 tests were positive.

Twenty-five patients with PA were tested for the presence of humoral IF antibody in serum and gastric juice and for cell-mediated immunity against IF. All but one gave positive results in one or more tests. It was concluded that these findings establish the autoimmune nature of PA and that the immunity is not merely an interesting byproduct.

Patients with PA treated with steroids show a reversal of the abnormal findings characterizing the disease. If they are still megaloblastic, the anaemia will respond in the first instance (Doig et al, 1957), but in the longer term Cbl neuropathy may be precipitated. The absorption of Cbl improves and may become `normal’ (Frost & Goldwein, 1958). There is a return of IF in the gastric juice (Kristensen and Friis, 1960) and a decline in the amount of IF antibody in serum (Taylor, 1959). In some patients there is return of acid in the gastric juice. Gastric biopsy shows a return of parietal and chief cells (Ardeman & Chanarin, 1965b; Jeffries, 1965). All this is as a result of suppression of cell-mediated immunity against the parietal cell and against IF. Withdrawal of steroids leads to a slow return to the status quo.

The author has dipped freely into the two volumes by the late M. M. Wintrobe. These are: Wintrobe, M.M. (1985) Hematology, the Blossoming of a Science. Lea & Febinge

A History of Pernicious Anaemia
I. Chanarin, Richmond, Surrey
Brit J Haem 111: 407-415
History of Folic Acid

1928 Lucy Wills studied macrocytic anaemia in pregnancy in Bombay, India

1932 Janet Vaughn studied macrocytic anemia associated with coeliac disease and idiopathic steatorrhea (1932) showed a response to marmite

1941 Folic acid extracted from spinach and is a growth factor for S. Faecalis

1941 pteroylglutamic acid synthesized at Amer Cyanamide – Pteridine ring, paraminobenzoic acid, glutamine –  PGA differed from natural compound in some respects

1945 PGA resolved the macrocytic anemia, but not the neuropathy

1979 Stokstad and associates at Berkeley obtained the first purified mammalian enzymes involved in synthesis

Folate antagonists inhibit tumor growth (Hitchings and Elion)(Nobel)

  • Misincorporation of uracil instead of thymine into DNA

Sidney Farber introduced Aminopterine and also Methotrexate for treatment of childhood lymphoblastic leukemia

  • MTX inhibits DHFR enzyme (dihydrofolate reductase) necessary for THF

Wellcome introduces trimethoprim (antibacterial), and also pyramethoprime (antimalarial)

Homocysteine isolated by Du Vineaud, but it was not noticed

Finkelstein and Mudd demonstrated the importance of remethylation for tHy and worked out the transsulfuration pathway

  1. Function of methyl THF is remethylation of homocysteine
  2. Synthesized by MTHFR
Metabolism of folate

Metabolism of folate

Metabolism of folate

Allosterically regulated by S-adenosyl methionine (Stokstad)

MTHF also inhibits glycine methyl transferase controlling excess SAM – transmethylation

JD Finkelstein

JD Finkelstein

James D Finkelstein

  • Homocysteinuria – mental retardation, skeletal malformation, thromboembolic disease; deficiency of cystathionine synthase (controls trans-sulfuration)
  • NTDs – pregnancy
  • Hyperhomocysteinemia and VD

AD Hoffbrand and DG Weir
Brit J Haem 2001; 113: 579-589

The History of Haemophilia in the Royal Families of Europe Queen Victoria.

On 17 July 1998 a historic ceremony of mourning and commemoration took place in the ancestral church of the Peter and Paul Fortress in St Petersburg. President Boris Yeltsin, in a dramatic eleventh-hour change of heart, decided to represent his country when the bones of the last emperor, Tsar Nicholas II, and his family were laid to rest 80 years to the day after their assassination in Yekaterinberg (Binyon, 1998). He described it as ‘ironic that the Orthodox Church, for so long the bedrock of the people’s faith, should find it difficult to give this blessing the country had expected’. ‘I have studied the results of DNA testing carried out in England and abroad and am convinced that the remains are those of the Tsar and his family’ (The Times, 1998a). Unfortunately, politicians and the hierarchy of the Russian Orthodox Church had argued about what to do with the bones previously stored in plastic bags in a provincial city mortuary. Politics, ecclesiastical intrigue, secular ambition, and emotions had fuelled the debate. Yeltsin and the Church wanted to honour a man many consider to be a saint, but many of the older generation are opposed to the rehabilitation of a family which symbolizes the old autocracy.

Our story starts, almost inevitably, with Queen Victoria of England who had nine children by Albert, Prince of Saxe-Coburg-Gotha. Victoria was certainly an obligate carrier for haemophilia as over 20 individuals subsequently inherited the condition (Figs 1 and 2). Princess Alice (1843–78) was Victoria’s third child and second daughter. Having married the Duke of Hesse at an early age, Alice went on to have seven children, one of whom, Frederick (‘Frittie’) was a haemophiliac who died at the age of 3 following a fall from a window.

Prince Leopold with Sir William Jenner at Balmoral in 1877

Prince Leopold with Sir William Jenner at Balmoral in 1877

Prince Leopold with Sir William Jenner at Balmoral in 1877. (Hulton Deutsch Collection Ltd.)

Alexandra was the sixth child and was only 6 years old when her mother and youngest sister died. ‘Sunny’, as she became known, was a favourite of Queen Victoria, who as far as possible directed her upbringing from across the channel: Alexandra (Alix) was forced to eat her baked apples and rice pudding with the same regularity as her English cousins. Alix visited her older sister Elizabeth (Ella) on her marriage to Grand Duke Serge and met Tsarevich Nicholas for the first time: she was 12 and not impressed. Five years later they met again and Alix fell in love, but by now she had been confirmed in the Lutheran Church and religion became the solemn core of her life.

Victoria had other aspirations for Alix. She hoped that she would marry her grandson Albert Victor (The Duke of Clarence) and the eldest son of the Prince of Wales (later Edward VII). The Duke was an unimpressive young man who was somewhat deaf and had limited intellectual abilities. If this arrangement had proceeded then Alix’s haemophilia carrier status would have been introduced into the British Royal Family and the possibility of a British monarch with haemophilia might have become a reality; however, the Duke died in 1892.

Nicholas and Alexandra. Alix and Nicholas were married in 1894 one week after the death of Nicholas’s father (Alexander III). In the same way that Victoria, with her personal aspirations of a marriage between Alix and the Duke of Clarence, had not considered the possibility of haemophilia, neither did the St Petersburg hierarchy consider a marriage to Nicholas undesirable. Haemophilia was already well recognized in Victoria’s descendants. Her youngest son, Leopold, had already died, as had Frittie her grandson. The inheritance of haemophilia had been known for some time since its description by John Conrad Otto (Otto, 1803). However, it was as late as 1913 before the first royal marriage was declined because of the risk of haemophilia, when the Queen of Rumania decided against an association between her son, Crown Prince Ferdinand, and Olga, the eldest daughter of Nicholas and Alexandra. The Queen of Rumania was herself a granddaughter of Queen Victoria and therefore a potential haemophilia carrier!

Alix was received into the Russian Orthodox Church, taking the name of Alexandra Fedorova. The first duty of a Tsarina was to maintain the dynasty and produce a male heir, but between 1895 and 1901 Alix produced four princesses, Olga, Tatiana, Maria and Anastasia. Failure to produce a son made Alix increasingly neurotic and she had at least one false pregnancy. However, in early 1904 she was definitely pregnant.

For a month or so all seemed well with little Alexis, but it was then noticed that the Tsarevitch was bleeding excessively from the umbilicus (a relatively uncommon feature of haemophilia). At first the diagnosis was not admitted by the parents, but eventually the truth had to be faced although even then only by the doctors and immediate family. Alix was grief stricken: ‘she hardly knew a day’s happiness after she realized her boy’s fate’. As a newly diagnosed haemophilia carrier she dwelt morbidly on the fact that she had transmitted the disease. These feelings are well known to some haemophiliac mothers but the situation was different in Russia in the early twentieth century. The people regarded any defect as divine intervention. The Tsar, as head of the Church and leader of the people, must be free of any physical defect, so the Tsarevich’s haemophilia was concealed. The family retreated into greater isolation and were increasingly dominated by the young heir’s affliction (Fig 3).

Up to a third of haemophiliac males do not have a family history of the condition. This is usually thought to be the result of a relatively high mutation rate occurring in either affected males or female carriers. None of Queen Victoria’s ancestors, for many generations, showed any evidence of haemophilia. Victoria was therefore either a victim of a mutation, or the Duke of Kent was not her father.The mutation is unlikely to have been in her mother, Victoire, who had a son and daughter by her first marriage, and there is no sign of haemophilia in their numerous descendants.

Victoire was under considerable pressure to produce an heir. The year before Victoria was born, Princess Charlotte, the only close heir to the throne, had died and the Duke of Kent had somewhat reluctantly agreed to marry Victoire with the aim of producing an heir. The postulate that the Queen’s gardener had a limp has not been substantiated!

The Duke of Kent had no evidence of haemophilia (he was 51 when Victoria was born) but did inherit another condition from his father (George III): porphyria. While a young man in Gibralter he suffered bilious attacks which were recognized as being similar to his father’s complaint.

Had Queen Victoria carried the gene for porphyria we might expect that she would have at least as many descendants with this condition as had haemophilia. Until recently only two possible cases of porphyria have been suggested amongst Victoria’s descendants: Kaiser Wilhelm’s sister and niece (MacAlpine & Hunter, 1969), but they could have inherited it from their Hohenzollern ancestor, Frederick the Great. A recent television programme (Secret History, 1998) claims to have identified two more cases in Victoria’s descendants, Princess Victoria, the Queen’s eldest daughter, and Prince William of Gloucester, nephew of George V. If these two cases are correct then they would tend to confirm that Victoria was indeed the daughter of the Duke of Kent, but the apparent lack of more cases in Victoria’s extended family is difficult to understand. The gene for acute intermittent porphyria has been isolated on chromosome 11. There is still plenty of scope for further genetic analysis on the European Royal Families!

We can only speculate as to the impact on European events over the last 150 years if the marriages within the Royal houses had been different. What is evident is the dramatic effect of haemophilia on the Royal Princes and their families.

Empress Alexandra at the Tsarevich’s bedside during a haemophiliac crisis

Empress Alexandra at the Tsarevich’s bedside during a haemophiliac crisis

Empress Alexandra at the Tsarevich’s bedside during a haemophiliac crisis in 1912. (Radio Times Hulton Picture Library.)

Richard F. Stevens
Royal Manchester Children’s Hospital
Brit J Haem 1999, 105, 25–32

`The longer you can look back ± the further you can look forward’: Winston Churchill in an address to The Royal College of Physicians, London 1944. At the time that Churchill was speaking in 1944, leukaemia was a fatal disease that had been identified 100 years before. The disease was described as the dreaded leukaemias, sinister and poorly understood.

Thomas Hodgkin chose a career in medicine and enrolled as a pupil at Guy’s Hospital in London. Being a Quaker, however, he could not enter the English universities of Oxford and Cambridge and decided to follow the medical courses at Edinburgh. At that times, Aristotelian and Hippocratic medicine were greatly influencing British physicians. Hodgkin, still a medical student, wrote a paper `On the Uses of the Spleen’ where he reported his beliefs on the purposes of the spleen: to regulate fluid volume, clean impurities from the body, supply expandability to the portal system. The subject was a presage of the disease that bears his name.

Hodgkin interrupted his studies at Edinburgh to spend a year in Paris where he met many people who had a great influence in his life and future activities. Among them, were Laennec (Hodgkin played an important role in bringing the stethoscope to Great Britain); Baron von Humboldt who introduced Hodgkin to the field of anthropology; Baron Cuvier, a distinguished anatomist and palaeontologist; and Thomas A. Bowditch, whose expeditions to Africa had a great impact on Hodgkin’s future activities.

In 1825, Thomas Hodgkin returned to London to join the staff at Guy’s Hospital, and in 1826 he was made `Inspector of the Dead’ and `Curator of the Museum of Morbid Anatomy’. In developing the museum he had accumulated, by 1829, over 1600 specimens demonstrating the effects of disease. The correlation of clinical disease to pathological material was quite new: from analyses of pathological specimens Hodgkin was able to describe appendicitis with perforation and peritonitis, the local spread of cancer to draining lymph nodes, noting that the tumour had similar characteristics at both sides, and features of other diseases.

In his historic paper `On Some Morbid Appearances of the Absorbent Glands and Spleen’ (Hodgkin, 1832), he briefly described the clinical histories and gross postmortem findings on six patients from the experience at Guy’s Hospital and included another case sent to him in a detailed drawing by his friend Carswell (Fig 2). In the very first paragraph he wrote: `The morbid alterations of structure which I am about to describe are probably familiar to many practical morbid anatomists, since they can scarcely have failed to have fallen under their observation in the course of cadaveric inspection’. Hodgkin’s studies had convinced him that he was dealing with a primary disease of the absorbent (lymphatic) glands. `This enlargement of the glands appeared to be a primitive affection of those bodies, rather than the result of an irritation propagated to them from some ulcerated surface or other inflamed texture – Unless the word inflammation be allowed to have a more indefinite and loose eaning, this affection – can hardly be attributed to that cause’ was stated on pages 85 and 86 of his 1832 paper. Hodgkin also mentioned that the first reference that he could find to this or similar disease was in fact by Malpighi in 1666.

Wilks (1865) described the disease in detail and, made aware by Bright that the first observations were done by Hodgkin, linked his name permanently to this new entity in a paper entitled `Cases of Enlargement of the Lymphatic Glands and Spleen (or Hodgkin’s Disease) with Remarks’ (Fig 3).

In 1837 Thomas Hodgkin was the outstanding candidate for the position of Assistant Physician at Guy’s Hospital in succession to Thomas Addison who had been promoted to Physician. After 10 years spent as Inspector of the Dead, he had published a great deal, including a two-volume work entitled The Morbid Anatomy of Serous and Mucous Membrane.

Hodgkin, acting in his other capacity, had sent Benjamin Harrison a report on the terrible consequences to native Indians of monopoly trading and on the inhuman treatment they received from officials of the Hudson Bay Company, of which Harrison was the financier. when the opportunity to appoint an Assistant Physician occurred, Harrison exercised an autocratic rule over the hospital and presided at the appointment made by the General Court. Thomas Hodgkin did not get the job and the next day he resigned all his appointments at Guy’s Hospital. Social medicine, medical problems associated with poverty, antislavery, concern for underpriviledged groups such as American Indians and Africans, as well as a strong sense of responsibility defined his life after this separation.

Sternberg (1898) and Reed (1902) are generally credited with the first definitive and thorough descriptions of the histopathology of Hodgkin’s disease. Based on the findings observed in her case series, Dorothy Reed concluded `We believe then, from the descriptions in the literature and the findings in 8 cases examined, that Hodgkin’s disease has a peculiar and typical histological picture and could thus rightly be considered a histopathological disease entity’.

During the successive decades, pathologists began to describe a broader spectrum of histological features. However, it was Jackson and Parker who, in scientific papers and in their well-known book Hodgkin’s Disease and Allied Disorders (Jackson & Parker, 1947), presented the first serious effort at a histopathological classification. They assigned the name `Hodgkin’s granuloma’ to the main body of typical cases. A much more malignant variant, usually characterized by a great abundance of pleomorphic and anaplastic Reed-Sternberg cells and seen in a relativelysmall number of cases was named `Hodgkin’s sarcoma’. A third, similarly infrequent, variant characterized by an extremely slow clinical evolution, a relative paucity of Reed-Sternberg cells and a great abundance of lymphocytes was termed `Hodgkin’s paragranuloma’. It was only approximately 20 years later that Lukes & Butler (1966) reported a characteristic subtype of the heterogeneous `granuloma’ category, to which they assigned the name `nodular sclerosis’. They also proposed a new histopathological classification, still in use to date, with an appreciably greater prognostic relevance and usefulness than the

previous Jackson-Parker classification.

The first human bone marrow transfusion was given to a patient with aplastic anemia in 1939.9 This patient received daily blood transfusions, and an attempt to raise her leukocyte and platelet counts was made using intravenous injection of bone marrow. After World War II and the use of the atomic bomb, researchers tried to find ways to restore the bone marrow function in aplasia caused by radiation exposure. In the 1950s, it was proven in a mouse model that marrow aplasia secondary to radiation can be overcome by syngeneic marrow graft.10 In 1956, Barnes and colleagues published their experiment on two groups of mice with acute leukemia: both groups were irradiated as anti-leukemic therapy and both were salvaged from marrow aplasia by bone marrow transplantation.

The topics of leukemias and lymphomas will not be discussed further in  this discussion.

The related references are:

Leukaemia – A Brief Historical Review from Ancient Times to 1950
British Journal of Haematology, 2001, 112, 282-292

The Story of Chronic Myeloid Leukaemia
British Journal of Haematology, 2000, 110, 2-11

Historical Review of Lymphomas
British Journal of Haematology 2000, 109, 466-476

Historical Review of Hodgkin’s Disease
British Journal of Haematology, 2000, 110, 504-511

Multiple Myeloma: an Odyssey of Discovery
British Journal of Haematology, 2000, 111, 1035-1044

The History of Blood Transfusion
British Journal of Haematology, 2000, 110, 758-767

Hematopoietic Stem Cell Transplantation—50 Years of Evolution and Future Perspectives. Henig I, Zuckerman T.
Rambam Maimonides Med J 2014;5 (4):e0028.
http://dx.doi.org/10.5041/RMMJ.10162

Landmarks in the history of blood transfusion.

1666 Richard Lower (Oxford) conducts experiments involving transfusion of blood from one animal to another

1667 Jean Denis (Paris) transfuses blood from animals to humans

1818 James Blundell (London) is credited with being the first person to transfuse blood from one human to another

1901 Karl Landsteiner (Vienna) discovers ABO blood groups. Awarded Nobel Prize for Medicine in 1930

1908 Alexis Carrel (New York) develops a surgical technique for transfusion, involving anastomosis of vein in the recipient with artery in the donor. Awarded Nobel Prize for Medicine in 1912

1915 Richard Lewinsohn (New York) develops 0.2% sodium citrate as anticoagulant

1921 The first blood donor service in the world was established in London by Percy Oliver

1937 Blood bank established in a Chicago hospital by Bernard Fantus

1940 Landsteiner and Wiener (New York) identify Rhesus antigens in man

1940 Edwin Cohn (Boston) develops a method for fractionation of plasma proteins. The following year, albumin produced by this method was used for the first time to treat victims of the Japanese attack on Pearl Harbour

1945 Antiglobulin test devised by Coombs (Cambridge), which also facilitated identification of several other antigenic systems such as Kell (Coombs et al, 1946), Duffy (Cutbush et al, 1950) and Kidd (Cutbush et al, 1950)

1948 National Blood Transfusion Service (NBTS) established in the UK

1951 Edwin Cohn (Boston) and colleagues develop the first blood cell separator

1964 Judith Pool (Palo Alto, California) develops cryoprecipitate for the treatment of haemophilia

1966 Cyril Clarke (Liverpool) reports the use of anti-Rh antibody to prevent haemolytic disease of the newborn

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Selected Contributions to Chemistry from 1880 to 1980

Curator: Larry H. Bernstein, MD, FCAP

 

FUNDAMENTALS OF CHEMISTRY – Vol. I  The Contribution of Nobel Laureates to Chemistry

– Ferruccio Trifiro

http://www.eolss.net/sample-chapters/c06/e6-11-01-04.pdf

This chapter deals with the contribution to the development of chemistry of all the Nobel Prize winners in chemistry up to the end of the twentieth century, together with some in physics and medicine or physiology that have had particular relevance for the advances achieved in chemistry. The contributions of the various Nobel laureates cited are briefly summarized. The Nobel laureates in physics dealt with in this chapter are those who made important contributions to ard the understanding of the properties of atoms, the development of theoretical tools to treat the chemical bond, or the development of new analytical instrumentation. The Nobel laureates in medicine or physiology cited here are those whose contributions have been in the area of using chemistry to understand natural processes, such as the physiological aspects of living organisms through electron and ion exchange processes, enzymatic catalysis, and DNA-based chemistry. Eight areas of thought or thematic areas were chosen into which the contributions of the Nobel laureates to chemistry can be subdivided.

  1. The Properties of Molecules

4.1. The Discovery of Coordination and Metallorganic Compounds

4.2. The Discovery of New Organic Molecules

4.3. The Emergence of Quantum Chemistry

  1. The Dynamics of Chemical Reactions

6.1. Kinetics of Heterogeneous and Homogeneous Processes

6.2. The Identification of the Activated State

  1. The Understanding of Natural Processes

8.1. From Ferments to Enzymes

8.2. Understanding the Mechanism of Action of Enzymes

8.3. Mechanisms of Important Natural Processes

8.4. Characterization of Biologically Important Molecules

  1. The Identification of Chemical Entities

9.1. Analytical Methods

9.2. New Separation Techniques

9.3. The Development of New Instrumentation for Structure Analysis

The Nobel Prize in Chemistry: The Development of Modern Chemistry

by Bo G. Malmström and Bertil Andersson*

http://www.nobelprize.org/nobel_prizes/themes/chemistry/malmstrom/

Introduction

1.1 Chemistry at the Borders to Physics and Biology

The turn of the century 1900 was also a turning point in the history of chemistry. A survey of the Nobel Prizes in Chemistry during this century provides a view toward important trends in the development of Chemistry at the center of the sciences, bordering onto physics, which provides its theoretical foundation, on one side, and onto biology on the other. The fact that chemistry flourished during the beginning of the 20th century is intimately connected with fundamental developments in physics.

In 1897 Sir Joseph John Thomson of Cambridge announced his discovery of the electron, for which he was awarded the Nobel Prize for Physics in 1906. It took a number of years before its relevance to chemistry was seen. In 1911 Ernest Rutherford, who had worked in Thomson’s laboratory in the 1890s, formulated an atomic model, which depicted a cloud of electrons circling around the nucleus. Rutherford had received the Nobel Prize for Chemistry in 1908 for his work on radioactivity.

In Rutherford’s atomic model the stability of atoms was at variance with the laws of classical physics. Niels Bohr from Copenhagen brought clarity to this dilemma in the distinct lines observed in the spectra of atoms, the regularities of which had been discovered in 1890 by the physics professor Johannes (Janne) Rydberg at Lund University. This was the basis for Bohr’s formulation (1913) of an alternative atomic model. Only certain circular orbits of the electrons are allowed. In this model light is emitted (or absorbed), when an electron makes a transition from one orbit to another. For this, Bohr received the Nobel Prize for Physics in 1922

Gilbert Newton Lewis next suggested in 1916 that strong (covalent) bonds between atoms involve a sharing of two electrons between these atoms (electron-pair bond). Lewis also contributed fundamental work in chemical thermodynamics, and his brilliant textbook, Thermodynamics (1923), written together with Merle Randall, is counted as one of the masterworks in the chemical literature. Lewis never received a Nobel Prize.

However, important work was published in the 1890s, considered by the first Nobel Committee for Chemistry (see Section 2). Three of the Laureates during the first decade, Jacobus Henricus van’t Hoff, Svante Arrhenius and Wilhelm Ostwald, are generally regarded as the founders of a new branch of chemistry, physical chemistry. Fundamental work was also recognized in organic chemistry and in the chemistry of natural products, which is clearly reflected in the early prizes. Further, the Nobel Committee, recognized the border towards biology in 1907, with the prize to Eduard Buchner “for his biochemical researches and his discovery of cell-free fermentation”.

  1. The First Decade of Nobel Prizes for Chemistry

So much fundamental work in chemistry had been carried out during the last two decades of the 19th century that a decision for the first several prizes was not easy.  In 1901 the Academy had to consider 20 nominations, but no less than 11 of these named van’t Hoff, who was selected. van’t Hoff had already established the four valences for the carbon atom in his PhD thesis in Utrecht in 1874, foundation work for  modern organic chemistry. But the Nobel Prize was awarded for his later work on chemical kinetics and equilibria and on the osmotic pressure in solution, published in 1884 and 1886.

In his 1886 work van’t Hoff showed that most dissolved chemical compounds give an osmotic pressure equal to the gas pressure they would have exerted in the absence of the solvent. An apparent exception was aqueous solutions of electrolytes (acids, bases and their salts), but in the following year Arrhenius showed that this anomaly could be explained, if it is assumed that electrolytes in water dissociate into ions. Arrhenius had already presented the rudiments of his dissociation theory in his doctoral thesis, which was defended in Uppsala in 1884 and was not entirely well received by the faculty. It was, however, strongly supported by Ostwald in Riga, who, in fact, travelled to Uppsala to initiate a collaboration with Arrhenius. In 1886-1990 Arrhenius did work with Ostwald, first in Riga and then in Leipzig, and also with van’t Hoff in Berlin. Arrhenius was awarded the Nobel Prize for Chemistry in 1903,  and he was also nominated for the Prize for Physics (see Section 1).

The award of the Nobel Prize for Chemistry in 1909 to Ostwald was chiefly in recognition of his work on catalysis and the rates of chemical reactions. Ostwald had in his investigations, following up observations in his thesis in 1878, shown that the rate of acid-catalyzed reactions is proportional to the square of the strength of the acid, as measured by titration with base. His work offered support not only to Arrhenius’ theory of dissociation but also to van’t Hoff’s theory for osmotic pressure. Ostwald was founder and editor of Zeitschrift für Physikalische Chemie, the publication of which is generally regarded as the birth of this new branch of chemistry.

Three of the Nobel Prizes for Chemistry during the first decade were awarded for pioneering work in organic chemistry. In 1902 Emil Fischer, then in Berlin, was given the prize for “his work on sugar and purine syntheses”. Fischer’s work is an example of the growing interest biologically important substances, and was a foundation for the development of biochemistry. Another major influence from organic chemistry was the development of chemical industry, and a chief contributor here was Fischer’s teacher, Adolf von Baeyer in Munich, who was awarded the prize in 1905 “in recognition of his services in the advancement of organic chemistry and the chemical industry, … ” His contributions include, in particular, structure determination of organic

Ernest Rutherford [Lord Rutherford since 1931], professor of physics in Manchester, was awarded the Nobel Prize for Chemistry in 1908. In his studies of uranium disintegration he found two types of radiation, named α- and β-rays, and by their deviation in electric and magnetic fields he could show that α-rays consist of positively charged particles. He had received many nominations for the Nobel Prize for Physics (see Section 1).

In 1897 Eduard Buchner, at the time professor in Tübingen, published results demonstrating that the fermentation of sugar to alcohol and carbon dioxide can take place in the absence of yeast cells. Louis Pasteur had earlier maintained that alcoholic fermentation can only occur in the presence of living yeast cells. Buchner’s experiments showed unequivocally that fermentation is a catalytic process caused by the action of enzymes, as had been suggested by Berzelius for all life processes. Because of Buchner’s experiment, 1897 is generally regarded as the birth date for biochemistry proper. Buchner was awarded the Nobel Prize for Chemistry in 1907, when he was professor at the agricultural college in Berlin. This confirmed the prediction of his former teacher, Adolf von Baeyer: “This will make him famous, in spite of the fact that he lacks talent as a chemist.”

  1. The Nobel Prizes for Chemistry 1911-2000

3.1 General and Physical Chemistry

The Nobel Prize for Chemistry in 1914 was awarded to Theodore William Richards of Harvard University for “his accurate determinations of the atomic weight of a large number of chemical elements”. In 1913 Richards had discovered that the atomic weight of natural lead and of that formed in radioactive decay of uranium minerals differ. This pointed to the existence of isotopes, i.e. atoms of the same element with different atomic weights, which was accurately demonstrated by Francis William Aston at Cambridge University, with the aid of an instrument developed by him, the mass spectrograph. For his achievements Aston received the Nobel Prize for Chemistry in 1922.

One branch of physical chemistry deals with chemical events at the interface of two phases, for example, solid and liquid, and phenomena at such interfaces have important applications all the way from technical to physiological processes. Detailed studies of adsorption on surfaces, were carried out by Irving Langmuir at the research laboratory of General Electric Company, who was awarded the Nobel Prize for Chemistry in 1932, the first industrial scientist to receive this distinction.

Two of the Prizes for Chemistry in more recent decades have been given for fundamental work in the application of spectroscopic methods (Prizes for Physics in 1952, 1955 and 1961) to chemical problems. Gerhard Herzberg, a physicist at the University of Saskatchewan, received the Nobel Prize for Chemistry in 1971 for his molecular spectroscopy studies “of the electronic structure and geometry of molecules, particularly free radicals”. The most used spectroscopic method in chemistry is undoubtedly NMR (nuclear magnetic resonance), and Richard R. Ernst at ETH in Zürich was given the Nobel Prize for Chemistry in 1991 for “the development of the methodology of high resolution nuclear magnetic resonance (NMR) spectroscopy”. Ernst’s methodology has now made it possible to determine the structure in solution (in contrast to crystals; cf. Section 3.5) of large molecules, such as proteins.

3.2 Chemical Thermodynamics

The Nobel Prize for Chemistry to van’t Hoff was in part for work in chemical thermodynamics, and many later contributions in this area have also been recognized with Nobel Prizes.  Walther Hermann Nernst of Berlin received this award in 1920 for work in thermochemistry, despite a 16-year opposition to this recognition from Arrhenius. Nernst had shown that it is possible to determine the equilibrium constant for a chemical reaction from thermal data, and in so doing he formulated what he himself called the third law of thermodynamics. This states that the entropy, a thermodynamic quantity, which is a measure of the disorder in the system, approaches zero as the temperature goes towards absolute zero. van’t Hoff had derived the mass action equation in 1886, with the aid of the second law which says, that the entropy increases in all spontaneous processes [this had already been done in 1876 by J. Willard Gibbs at Yale, who certainly had deserved a Nobel Prize].  Nernst showed in 1906 that it is possible with the aid of the third law, to derive the necessary parameters from the temperature dependence of thermochemical quantities. Nernst carried out thermo-chemical measurements at very low temperatures to prove his heat theorem. G.N. Lewis (see Section 1.1) in Berkeley extended these studies in the 1920s and his new formulation of the third law was confirmed by his student, William Francis Giauque, who extended the temperature range experimentally accessible by introducing the method of adiabatic demagnetization in 1933. He managed to reach temperatures a few thousandths of a degree above absolute zero and could thereby provide extremely accurate entropy estimates. He also showed that it is possible to determine entropies from spectroscopic data. Giauque was awarded the Nobel Prize for Chemistry in 1949 for his contributions to chemical thermodynamics.

The next Nobel Prize given for work in thermodynamics went to Lars Onsager of Yale University in 1968 for contributions to the thermodynamics of irreversible processes. Classical thermodynamics deals with systems at equilibrium, in which the chemical reactions are said to be reversible, but many chemical systems, for example, the most complex of all, living organisms, are far from equilibrium and their reactions are said to be irreversible. Onsager developed his so-called reciprocal relations in 1931, describing the flow of matter and energy in such systems, but the importance of his work was not recognized until the end of the 1940s. A further step forward in the development of non-equilibrium thermodynamics was taken by Ilya Prigogine in Bruxelles, whose theory of dissipative structures was awarded the Nobel Prize for Chemistry in 1977.

3.3 Chemical Change

The chief method to get information about the mechanism of chemical reactions is chemical kinetics, i.e. measurements of the rate of the reaction as a function of reactant concentrations as well as its dependence on temperature, pressure and reaction medium. Important work in this area had been done already in the 1880s by two of the early Laureates, van’t Hoff and Arrhenius, who showed that it is not enough for molecules to collide for a reaction to take place. Only molecules with sufficient kinetic energy in the collision do, in fact, react, and Arrhenius derived an equation in 1889 allowing the calculation of this activation energy from the temperature dependence of the reaction rate. With the advent of quantum mechanics in the 1920s (see Section 3.4), Eyring developed his transition-state theory in 1935 which showed that the activation entropy is also important. Strangely, Eyring never received a Nobel Prize (see Section 1.2).

In 1956 Sir Cyril Norman Hinshelwood of Oxford and Nikolay Nikolaevich Semenov from Moscow shared the Nobel Prize for Chemistry “for their researches into the mechanism of chemical reactions”.  A limit in investigating reaction rates is set by the speed with which the reaction can be initiated. If this is done by rapid mixing of the reactants, the time limit is about one thousandth of a second (millisecond). In the 1950s Manfred Eigen from Göttingen developed chemical relaxation methods that allow measurements in times as short as a thousandth or a millionth of a millisecond (microseconds or nanoseconds). The methods involve disturbing an equilibrium by rapid changes in temperature or pressure and then follow the passage to a new equilibrium. Another way to initiate some reactions rapidly is flash photolysis, i.e. by short light flashes, a method developed by Ronald G.W. Norrish at Cambridge and George Porter (Lord Porter since 1990) in London. Eigen received one-half and Norrish and Porter shared the other half of the Nobel Prize for Chemistry in 1967. The milli- to picosecond time scales gave important information on chemical reactions. However, it was not until it was possible to generate femtosecond laser pulses (10-15 s) that it became possible to reveal when chemical bonds are broken and formed. Ahmed Zewail (born 1946 in Egypt) at California Institute of Technology received the Nobel Prize for Chemistry in 1999 for his development of “femtochemistry” and in particular for being the first to experimentally demonstrate a transition state during a chemical reaction. His experiments relate back to 1889 when Arrhenius (Nobel Prize, 1903) made the important prediction that there must exist intermediates (transition states) in the transformation from reactants to products.

Henry Taube of Stanford University was awarded the Nobel Prize for Chemistry in 1983 “for his work on the mechanism of electron transfer reactions, especially in metal complexes”. Even if Taube’s work was on inorganic reactions, electron transfer is important in many catalytic processes used in industry and also in biological systems, for example, in respiration and photosynthesis.

3.4 Theoretical Chemistry and Chemical Bonding

Quantum mechanics, developed in the 1920s, offered a tool towards a more basic understanding of chemical bonds. In 1927 Walter Heitler and Fritz London showed that it is possible to solve exactly the relevant equations for the hydrogen molecule ion, i.e. two hydrogen nuclei sharing a single electron, and thereby calculate the attractive force between the nuclei. A pioneer in developing such methods was Linus Pauling at California Institute of Technology, who was awarded the Nobel Prize for Chemistry in 1954 “for his research into the nature of the chemical bond …” Pauling’s valence-bond (VB) method is rigorously described in his 1935 book Introduction to Quantum Mechanics (written together with E. Bright Wilson, Jr., at Harvard). A few years later (1939) he published an extensive non-mathematical treatment in The Nature of the Chemical Bond, a book which is one of the most read and influential in the entire history of chemistry. Pauling was not only a theoretician, but he also carried out extensive investigations of chemical structure by X-ray diffraction (see Section 3.5). On the basis of results with small peptides, which are building blocks of proteins, he suggested the α-helix as an important structural element. Pauling was awarded the Nobel Peace Prize for 1962, and he is the only person to date to have won two unshared Nobel Prizes.

α-helix   Pauling’s α-helix

α-carbon atoms are black, other carbon atoms grey, nitrogen atoms blue, oxygen atoms red and hydrogen atoms white; R designates amino-acid side chains. The dotted red lines are hydrogen bonds between amide and carbonyl groups in the peptide bonds.

Pauling’s VB method cannot give an adequate description of chemical bonding in many complicated molecules, and a more comprehensive treatment, the molecular-orbital (MO) method, was introduced already in 1927 by Robert S. Mulliken from Chicago and later developed further. MO theory considers, in quantum-mechanical terms, the interaction between all atomic nuclei and electrons in a molecule. Mulliken also showed that a combination of MO calculations with experimental (spectroscopic) results provides a powerful tool for describing bonding in large molecules. Mulliken received the Nobel Prize for Chemistry in 1966.

Theoretical chemistry has also contributed significantly to our understanding of chemical reaction mechanisms. In 1981 the Nobel Prize for Chemistry was shared between Kenichi Fukui in Kyoto and Roald Hoffmann of Cornell University “for their theories, developed independently, concerning the course of chemical reactions”. Fukui introduced in 1952 the frontier-orbital theory, according to which the occupied MO with the highest energy and the unoccupied one with the lowest energy have a dominant influence on the reactivity of a molecule. Hoffmann formulated in 1965, together with Robert B. Woodward (see Section 3.8), rules based on the conservation of orbital symmetry, for the reactivity and stereochemistry in chemical reactions.
3.5 Chemical Structure

The most commonly used method to determine the structure of molecules in three dimensions is X-ray crystallography. The diffraction of X-rays was discovered by Max von Laue in 1912, and this gave him the Nobel Prize for Physics in 1914. Its use for the determination of crystal structure was developed by Sir William Bragg and his son, Sir Lawrence Bragg, and they shared the Nobel Prize for Physics in 1915. The first Nobel Prize for Chemistry for the use of X-ray diffraction went to Petrus (Peter) Debye, then of Berlin, in 1936. Debye did not study crystals, however, but gases, which give less distinct diffraction patterns.

Many Nobel Prizes have been awarded for the determination of the structure of biological macromolecules (proteins and nucleic acids). Proteins are long chains of amino-acids, as shown by Emil Fischer (see Section 2), and the first step in the determination of their structure is to determine the order (sequence) of these building blocks. An ingenious method for this tedious task was developed by Frederick Sanger of Cambridge, and he reported the amino-acid sequence for a protein, insulin, in 1955. For this achievement he was awarded the Nobel Prize for Chemistry in 1958. Sanger later received part of a second Nobel Prize for Chemistry for a method to determine the nucleotide sequence in nucleic acids (see Section 3.12), and he is the only scientist so far who has won two Nobel Prizes for Chemistry.

The first protein crystal structures were reported by Max Perutz and Sir John Kendrew in 1960, and these two investigators shared the Nobel Prize for Chemistry in 1962. Perutz had started studying the oxygen-carrying blood pigment, hemoglobin, with Sir Lawrence Bragg in Cambridge already in 1937, and ten years later he was joined by Kendrew, who looked at crystals of the related muscle pigment, myoglobin. These proteins are both rich in Pauling’s α-helix (see Section 3.4), and this made it possible to discern the main features of the structures at the relatively low resolution first used. The same year that Perutz and Kendrew won their prize, the Nobel Prize for Physiology or Medicine went to Francis Crick, James Watson and Maurice Wilkins “for their discoveries concerning the molecular structure of nucleic acids … .” Two years later (1964) Dorothy Crowfoot Hodgkin received the Nobel Prize for Chemistry for determining the crystal structures of penicillin and vitamin B12.

Crystallographic electron microscopy was developed by Sir Aaron Klug in Cambridge, who was awarded the Nobel Prize for Chemistry in 1982. Attempts to prepare crystals of membrane proteins for structural studies were unsuccessful, but in 1982 Hartmut Michel managed to crystallize a photosynthetic reaction center after a painstaking series of experiments. He then proceeded to determine the three-dimensional structure of this protein complex in collaboration with Johann Deisenhofer and Robert Huber, and this was published in 1985. Deisenhofer, Huber and Michel shared the Nobel Prize for Chemistry in 1988. Michel has later also crystallized and determined the structure of the terminal enzyme in respiration, and his two structures have allowed detailed studies of electron transfer (cf. Sections 3.3 and 3.4) and its coupling to proton pumping, key features of the chemiosmotic mechanism for which Peter Mitchell had already received the Nobel Prize for Chemistry in 1978 (see Section 3.12). Functional and structural studies on the enzyme ATP synthase, connected to this proton pumping mechanism, was awarded one-half of the Nobel Prize for Chemistry in 1997, shared between Paul D. Boyer and John Walker (see Section 3.12).

3.6 Inorganic and Nuclear Chemistry

Much of the progress in inorganic chemistry during the 20th century has been associated with investigations of coordination compounds, i.e., a central metal ion surrounded by a number of coordinating groups, called ligands. In 1893 Alfred Werner in Zürich presented his coordination theory, and in 1905 he summarized his investigations in this new field in a book (Neuere Anschauungen auf dem Gebiete der anorganischen Chemie), which appeared in no less than five editions from 1905-1923. . Werner showed that a structure for compounds in which a metal ion binds several other molecules (ligands), all the ligand molecules are bound directly to the metal ion. Werner was awarded the Nobel Prize for Chemistry in 1913. Taube’s investigations of electron transfer, awarded in 1983 (see Section 3.3), were mainly carried out with coordination compounds, and vitamin B12 as well as the proteins hemoglobin and myoglobin, investigated by the Laureates Hodgkin, Perutz and Kendrew (see Section 3.5), also belong to this category.

Much inorganic chemistry in the early 1900s was a consequence of the discovery of radioactivity in 1896, for which Henri Becquerel from Paris was awarded the Nobel Prize for Physics in 1903, together with Pierre and Marie Curie. In 1911 Marie Curie received the Nobel Prize for Chemistry for her discovery of the elements radium and polonium and for the isolation of radium and studies of its compounds, and this made her the first investigator to be awarded two Nobel Prizes. The prize in 1921 went to Frederick Soddy of Oxford for his work on the chemistry of radioactive substances and on the origin of isotopes. In 1934 Frédéric Joliot and his wife Irène Joliot-Curie, the daughter of the Curies, discovered artificial radioactivity, i.e., new radioactive elements produced by the bombardment of non-radioactive elements with a-particles or neutrons. They were awarded the Nobel Prize for Chemistry in 1935 for “their synthesis of new radioactive elements”.

Many elements are mixtures of non-radioactive isotopes (see Section 3.1), and in 1934 Harold Urey of Columbia University had been given the Nobel Prize for Chemistry for his isolation of heavy hydrogen (deuterium). Urey had also separated uranium isotopes, and his work was an important basis for the investigations by Otto Hahn from Berlin. In attempts to make transuranium elements, i.e., elements with a higher atomic number than 92 (uranium), by radiating uranium atoms with neutrons, Hahn discovered that one of the products was barium, a lighter element. Lise Meitner, at the time a refugee from Nazism in Sweden, who had earlier worked with Hahn and taken the initiative for the uranium bombardment experiments, provided the explanation, namely, that the uranium atom was cleaved and that barium was one of the products. Hahn was awarded the Nobel Prize for Chemistry in 1944 “for his discovery of the fission of heavy nuclei”, and it can be wondered why Meitner was not included. Hahn’s original intention with his experiments was later achieved by Edwin M. McMillan and Glenn T. Seaborg of Berkeley, who were given the Nobel Prize for Chemistry in 1951 for “discoveries in the chemistry of transuranium elements”.

The use of stable as well as radioactive isotopes have important applications, not only in chemistry, but also in fields as far apart as biology, geology and archeology. In 1943 George de Hevesy from Stockholm received the Nobel Prize for Chemistry for his work on the use of isotopes as tracers, involving studies in inorganic chemistry and geochemistry as well as on the metabolism in living organisms. The prize in 1960 was given to Willard F. Libby of the University of California, Los Angeles (UCLA), for his method to determine the age of various objects (of geological or archeological origin) by measurements of the radioactive isotope carbon-14.

3.7 General Organic Chemistry

Contributions in organic chemistry have led to more Nobel Prizes for Chemistry than work in any other of the traditional branches of chemistry. Like the first prize in this area, that to Emil Fischer in 1902 (see Section 2), most of them have, however, been awarded for advances in the chemistry of natural products and will be treated separately (Section 3.9). Another large group, preparative organic chemistry, has also been given its own section (Section 3.8), and here only the prizes for more general contributions to organic chemistry will be discussed.

In 1969 the Nobel Prize for Chemistry went to Sir Derek H. R. Barton from London, and Odd Hassel from Oslo for developing the concept of conformation, i.e. the spatial arrangement of atoms in molecules, which differ only by the orientation of chemical groups by rotation around a single bond. This stereochemical concept rests on the original suggestion by van’t Hoff of the tetrahedral arrangement of the four valences of the carbon atom (see Section 2), and most organic molecules exist in two or more stable conformations.

The Nobel Prize for Chemistry in 1975 to Sir John Warcup Cornforth of the University of Sussex and Vladimir Prelog of ETH in Zürich was also based on research in stereochemistry. Not only can a compound have more than one geometric form, but chemical reactions can also have specificity in their stereochemistry, thereby forming a product with a particular three-dimensional arrangement of the atoms. This is especially true of reactions in living organisms, and Cornforth has mainly studied enzyme-catalyzed reactions, so his work borders onto biochemistry (Section 3.12). One of Prelog’s main contributions concerns chiral molecules, i.e. molecules that have two forms differing from one another as the right hand does from the left. Stereochemically specific reactions have great practical importance, as many drugs, for example, are active only in one particular geometric form.

Organometallic compounds constitute a group of organic molecules containing one or more carbon-metal bond, and they are thus the organic counterpart to Werner’s inorganic coordination. In 1952 Ernst Otto Fischer and Sir Geoffrey Wilkinson independently described a completely new group of organometallic molecules, called sandwich compounds in which compounds a metal ion is bound not to a single carbon atom but is “sandwiched” between two aromatic organic molecules. Fischer and Wilkinson shared the Nobel Prize for Chemistry in 1973.

3.8 Preparative Organic Chemistry

One of the chief goals of the organic chemist is to be able to synthesize increasingly complex compounds of carbon in combination with various other elements. The first Nobel Prize for Chemistry recognizing pioneering work in preparative organic chemistry was that to Victor Grignard from Nancy and Paul Sabatier from Toulouse in 1912. Grignard had discovered that organic halides can form compounds with magnesium. Sabatier was given the prize for developing a method to hydrogenate organic compounds in the presence of metallic catalysts. The prize in 1950 was presented to Otto Diels from Kiel and Kurt Alder from Cologne “for their discovery and development of the diene synthesis”, developed in 1928, by which organic compounds containing two double bonds (“dienes”) can effect the syntheses of many cyclic organic substances.

The German organic chemist Hans Fischer from Munich had already done significant work on the structure of hemin, the organic pigment in hemoglobin, when he synthesized it from simpler organic molecules in 1928. He also contributed much to the elucidation of the structure of chlorophyll, and for these important achievements he was awarded the Nobel Prize for Chemistry in 1930 (cf. Section 3.5). He finished his determination of the structure of chlorophyll in 1935, and by the time of his death he had almost completed its synthesis as well.

Robert Burns Woodward from Harvard is rightly considered the founder of the most advanced, modern art of organic synthesis. He designed methods for the total synthesis of a large number of complicated natural products, for example, cholesterol, chlorophyll and vitamin B12. He received the Nobel Prize for Chemistry in 1965, and he would probably have received a second chemistry prize in 1981 for his part in the formulation of the Woodward-Hoffmann rules (see Section 3.4), had it not been for his early death.

The Nobel Prize for Chemistry in 1984 was given to Robert Bruce Merrifield of Rockefeller University “for his development of methodology for chemical synthesis on a solid matrix”. Specifically, the synthesis of large peptides and small proteins.

3.9 Chemistry of Natural Product

The synthesis of complex organic molecules must be based on detailed knowledge of their structure. Early work on plant pigments was carried out by Richard Willstätter, a student of Adolf von Baeyer from Munich (see Section 2). Willstätter showed a structural relatedness between chlorophyll and hemin, and he demonstrated that chlorophyll contains magnesium as an integral component. He also carried out pioneering investigations on other plant pigments, such as the carotenoids, and he was awarded the Nobel Prize for Chemistry in 1915 for these achievements. Willstätter’s work laid the ground for the synthetic accomplishments of Hans Fischer (see Section 3.8). In addition, Willstätter contributed to the understanding of enzyme reactions.

The prizes for 1927 and 1928 were both presented to Heinrich Otto Wieland from Munich and Adolf Windaus from Göttingen, respectively, at the Nobel ceremony in 1928. These two chemists had done closely related work on the structure of steroids. The award to Wieland was primarily for his investigations of bile acids, whereas Windaus was recognized mainly for his work on cholesterol and his demonstration of the steroid nature of vitamin D. Wieland had already in 1912, before his prize-winning work, formulated a theory for biological oxidation, according to which removal of hydrogen (dehydrogenation) rather than reaction with oxygen is the dominating process.

Investigations on vitamins were recognized in 1937 and 1938 with the prizes to Sir Norman Haworth from Birmingham and Paul Karrer from Zürich and to Richard Kuhn from Heidelberg. Haworth did outstanding work in carbohydrate chemistry, establishing the ring structure of glucose. He was the first chemist to synthesize vitamin C, and this is the basis for the present large-scale production of this nutrient. Haworth shared the prize with Karrer, who determined the structure of carotene and of vitamin A. Kuhn also worked on carotenoids, and he published the structure of vitamin B2 at the same time as Karrer. He also isolated vitamin B6. In 1939 the Nobel Prize for Chemistry was shared between Adolf Butenandt from Berlin and Leopold Ruzicka (1887-1976) of ETH, Zurich. Butenandt was recognized “for his work on sex hormones”, having isolated estrone, progesterone and androsterone. Ruzicka synthesized androsterone and also testosterone.

The awards for outstanding work in natural-product chemistry continued after World War II. In 1947 Sir Robert Robinson from Oxford received the prize for his studies on plant substances, particularly alkaloids, such as morphine. Robinson also synthesized steroid hormones, and he elucidated the structure of penicillin. Many hormones are of a polypeptide nature, and in 1955 Vincent du Vigneaud of Cornell University was given the prize for his synthesis of two such hormones, vasopressin and oxytocin. Finally, in this area, Alexander R. Todd (Lord Todd since 1962) was recognized in 1957 “for his work on nucleotides and nucleotide co-enzymes”. Todd had synthesized ATP (adenosine triphosphate) and ADP (adenosine diphosphate), the main energy carriers in living cells, and he determined the structure of vitamin B12 (cf. Section 3.5) and of FAD (flavin-adenine dinucleotide).

3.10 Analytical Chemistry and Separation Science

A prize in analytical chemistry was given to Jaroslav Heyrovsky from Prague in 1959 for his development of polarographic methods of analysis. In these a dropping mercury electrode is employed to determine current-voltage curves for electrolytes. A given ion reacts at a specific voltage, and the current is a measure of the concentration of this ion.

The analysis of macromolecular constituents in living organisms requires specialized methods of separation. Ultracentrifugation wad developed by The Svedberg from Uppsala a few years before he was awarded the Nobel Prize for Chemistry in 1926 “for his work on disperse systems” (see Section 3.11). Svedberg’s student, Arne Tiselius, studied the migration of protein molecules in an electric field, and with this method, named electrophoresis, he demonstrated the complex nature of blood proteins. Tiselius also refined adsorption analysis, a method first used by the Russian botanist, Michail Tswett, for the separation of plant pigments and named chromatography by him. In 1948 Tiselius was given the prize for these achievements. A few years later (1952) Archer J.P. Martin from London and Richard L.M. Synge from Bucksburn (Scotland) shared the prize “for their invention of partition chromatography”, and this method was a major tool in many biochemical investigations later awarded with Nobel Prizes (see Section 3.12).

3.11 Polymers and Colloids

The Svedberg who received the Nobel Prize for Chemistry in 1926, also investigated gold sols. He used Zsigmond’s ultramicroscope to study the Brownian movement of colloidal particles, so named after the Scottish botanist Robert Brown, and confirmed a theory developed by Albert Einstein in 1905 and, independently, by M. Smoluchowski. His greatest achievement was, however, the construction of the ultracentrifuge, with which he studied not only the particle size distribution in gold sols but also determined the molecular weight of proteins, for example, hemoglobin. In the same year as Svedberg got the prize the Nobel Prize for Physics was awarded to Jean Baptiste Perrin of Sorbonne for developing equilibrium sedimentation in colloidal solutions, a method which Svedberg later perfected in his ultracentrifuge. Svedberg’s investigations with the ultracentrifuge and Tiselius’s electrophoresis studies (see Section 3.10) were instrumental in establishing that protein molecules have a unique size and structure, and this was a prerequisite for Sanger’s determination of their amino-acid sequence and the crystallographic work of Kendrew and Perutz (see Section 3.5).

3.12 Biochemistry

The second Nobel Prize for discoveries in biochemistry came in 1929, when Sir Arthur Harden from London and Hans von Euler-Chelpin from Stockholm shared the prize for investigations of sugar fermentation, which formed a direct continuation of Buchner’s work awarded in 1907. With his young co-worker, William John Young, Harden had shown in 1906 that fermentation requires a dialysable substance, called co-zymase, which is not destroyed by heat. Harden and Young also demonstrated that the process stops before all sugar (glucose) has been used up, but it starts again on addition of inorganic phosphate, and they suggested that hexose phosphates are formed in the early steps of fermentation. von Euler had done important work on the structure of co-zymase, shown to be nicotinamide adenine dinucleotide (NAD, earlier called DPN). As the number of Laureates can be three, it may seem appropriate for Young to have been included in the award, but Euler’s discovery was published together with Karl Myrbäck, and the number of Laureates is limited to three.

The next biochemical Nobel Prize was given in 1946 for work in the protein field. James B. Sumner of Cornell University received half the prize “for his discovery that enzymes can be crystallized” and John H. Northrop together with Wendell M. Stanley, both of the Rockefeller Institute, shared the other half “for their preparation of enzymes and virus proteins in a pure form”. Sumner had in 1926 crystalized an enzyme, urease, from jack beans and suggested that the crystals were the pure protein. His claim was, however, greeted with great scepticism, and the crystals were suggested to be inorganic salts with the enzyme adsorbed or occluded. Just a few years after Sumner’s discovery Northrop, however, managed to crystalize three digestive enzymes, pepsin, trypsin and chymotrypsin, and by painstaking experiments shown them to be pure proteins. Stanley started his attempt to purify virus proteins in the 1930s, but not until 1945 did he get virus crystals, and this then made it possible to show that viruses are complexes of protein and nucleic acid. The pioneering studies of these three investigators form the basis for the enormous number of new crystal structures of biological macromolecules, which have been published in the second half of the 20th century (cf. Section 3.5).

Several Nobel Prizes for Chemistry have been awarded for work in photosynthesis and respiration, the two main processes in the energy metabolism of living organisms (cf. Section 3.5). In 1961 Melvin Calvin of Berkeley received the prize for elucidating the carbon dioxide assimilation in plants. With the aid of carbon-14 (cf. Section 3.6) Calvin had shown that carbon dioxide is fixed in a cyclic process involving several enzymes. Peter Mitchell of the Glynn Research Laboratories in England was awarded in 1978 for his formulation of the chemiosmotic theory. According to this theory, electron transfer (cf. Sections 3.3 and 3.4) in the membrane-bound enzyme complexes in both respiration and photosynthesis, is coupled to proton translocation across the membranes, and the electrochemical gradient thus created is used to drive the synthesis of ATP (adenosine triphosphate), the energy storage molecule in all living cells. Paul D. Boyer of UCLA and John C. Walker of the MRC Laboratory in Cambridge shared one-half of the 1997 prize for their elucidation of the mechanism of ATP synthesis; the other half of the prize went to Jens C. Skou in Aarhus for the first discovery of an ion-transporting enzyme. Walker had determined the crystal structure of ATP synthase, and this structure confirmed a mechanism earlier proposed by Boyer, mainly on the basis of isotopic studies.

Luis F. Leloir from Buenos Aires was awarded in 1970 “for the discovery of sugar nucleotides and their role in the biosynthesis of carbohydrates”. In particular, Leloir had elucidated the biosynthesis of glycogen, the chief sugar reserve in animals and many microorganisms. Two years later the prize went with one half to Christian B. Anfinsen of NIH and the other half shared by Stanford Moore and William H. Stein, both from Rockefeller University, for fundamental work in protein chemistry. Anfinsen had shown, with the enzyme ribonuclease, that the information for a protein assuming a specific three-dimensional structure is inherent in its amino-acid sequence, and this discovery was the starting point for studies of the mechanism of protein folding, one of the major areas of present-day biochemical research. Moore and Stein had determined the amino-acid sequence of ribonuclease, but they received the prize for discovering anomalous properties of functional groups in the enzyme’s active site, which is a result of the protein fold.

Naturally a number of Nobel Prizes for Chemistry have been given for work in the nucleic acid field. In 1980 Paul Berg of Stanford received one half of the prize for studies of recombinant DNA, i.e. a molecule containing parts of DNA from different species, and the other half was shared by Walter Gilbert from Harvard and Frederick Sanger (see Section 3.5) for developing methods for the determination of the base sequences of nucleic acids. Berg’s work provides the basis of genetic engineering, which has led to the large biotechnology industry. Base sequence determinations are essential steps in recombinant-DNA technology, which is the rationale for Gilbert and Sanger sharing the prize with Berg.

Sidney Altman of Yale and Thomas R. Cech of the University of Colorado shared the prize in 1989 “for their discovery of the catalytic properties of RNA”. The central dogma of molecular biology is: DNA –> RNA –> enzyme. The discovery that not only enzymes but also RNA possesses catalytic properties have led to new ideas about the origin of life. The 1993 prize was shared by Kary B. Mullis from La Jolla and Michael Smith from Vancouver, who both have given important contributions to DNA technology. Mullis developed the PCR (“polymerase chain reaction”) technique, which makes it possible to replicate millions of times a specific DNA segment in a complicated genetic material. Smith’s work forms the basis for site-directed mutagenesis, a technique by which it is possible to change a specific amino-acid in a protein and thereby illuminate its functional role.

  1. Concluding Remarks

The first eighty years of Nobel Prizes for Chemistry outlines the development of modern chemistry. The prizes cover a broad spectrum of the basic chemical sciences, from theoretical chemistry to biochemistry, and also a number of contributions to applied chemistry. Organic chemistry dominates with no less than 25 awards. This is not surprising, since the special valence properties of carbon result in an almost infinite variation in the structure of organic compounds. Also, a large number of the prizes in organic chemistry were given for investigations of the chemistry of natural products of increasing complexity, and have lead to pharmaceutical development .

As many as 11 prizes have been awarded for biochemical discoveries. The first biochemical prize was already given in 1907 (Buchner), but only three awards in this area came in the first half of the century, illustrating the explosive growth of biochemistry in recent decades (8 prizes in 1970-1997). At the other end of the chemical spectrum, physical chemistry, including chemical thermodynamics and kinetics, dominates with 14 prizes, but there have also been 6 prizes in theoretical chemistry. Chemical structure is a large area with 8 prizes, including awards for methodological developments as well as for the determination of the structure of large biological molecules or molecular complexes. Industrial chemistry was first recognized in 1931 (Bergius, Bosch), but many more recent prizes for basic contributions lie close to industrial applications.

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Summary and Perspectives: Impairments in Pathological States: Endocrine Disorders, Stress Hypermetabolism and Cancer

Summary and Perspectives: Impairments in Pathological States: Endocrine Disorders, Stress Hypermetabolism and Cancer

Author and Curator: Larry H. Bernstein, MD, FCAP

Article ID #160: Summary and Perspectives: Impairments in Pathological States: Endocrine Disorders, Stress Hypermetabolism and Cancer. Published on 11/9/2014

WordCloud Image Produced by Adam Tubman

This summary is the last of a series on the impact of transcriptomics, proteomics, and metabolomics on disease investigation, and the sorting and integration of genomic signatures and metabolic signatures to explain phenotypic relationships in variability and individuality of response to disease expression and how this leads to  pharmaceutical discovery and personalized medicine.  We have unquestionably better tools at our disposal than has ever existed in the history of mankind, and an enormous knowledge-base that has to be accessed.  I shall conclude here these discussions with the powerful contribution to and current knowledge pertaining to biochemistry, metabolism, protein-interactions, signaling, and the application of the -OMICS to diseases and drug discovery at this time.

The Ever-Transcendent Cell

Deriving physiologic first principles By John S. Torday | The Scientist Nov 1, 2014
http://www.the-scientist.com/?articles.view/articleNo/41282/title/The-Ever-Transcendent-Cell/

Both the developmental and phylogenetic histories of an organism describe the evolution of physiology—the complex of metabolic pathways that govern the function of an organism as a whole. The necessity of establishing and maintaining homeostatic mechanisms began at the cellular level, with the very first cells, and homeostasis provides the underlying selection pressure fueling evolution.

While the events leading to the formation of the first functioning cell are debatable, a critical one was certainly the formation of simple lipid-enclosed vesicles, which provided a protected space for the evolution of metabolic pathways. Protocells evolved from a common ancestor that experienced environmental stresses early in the history of cellular development, such as acidic ocean conditions and low atmospheric oxygen levels, which shaped the evolution of metabolism.

The reduction of evolution to cell biology may answer the perennially unresolved question of why organisms return to their unicellular origins during the life cycle.

As primitive protocells evolved to form prokaryotes and, much later, eukaryotes, changes to the cell membrane occurred that were critical to the maintenance of chemiosmosis, the generation of bioenergy through the partitioning of ions. The incorporation of cholesterol into the plasma membrane surrounding primitive eukaryotic cells marked the beginning of their differentiation from prokaryotes. Cholesterol imparted more fluidity to eukaryotic cell membranes, enhancing functionality by increasing motility and endocytosis. Membrane deformability also allowed for increased gas exchange.

Acidification of the oceans by atmospheric carbon dioxide generated high intracellular calcium ion concentrations in primitive aquatic eukaryotes, which had to be lowered to prevent toxic effects, namely the aggregation of nucleotides, proteins, and lipids. The early cells achieved this by the evolution of calcium channels composed of cholesterol embedded within the cell’s plasma membrane, and of internal membranes, such as that of the endoplasmic reticulum, peroxisomes, and other cytoplasmic organelles, which hosted intracellular chemiosmosis and helped regulate calcium.

As eukaryotes thrived, they experienced increasingly competitive pressure for metabolic efficiency. Engulfed bacteria, assimilated as mitochondria, provided more bioenergy. As the evolution of eukaryotic organisms progressed, metabolic cooperation evolved, perhaps to enable competition with biofilm-forming, quorum-sensing prokaryotes. The subsequent appearance of multicellular eukaryotes expressing cellular growth factors and their respective receptors facilitated cell-cell signaling, forming the basis for an explosion of multicellular eukaryote evolution, culminating in the metazoans.

Casting a cellular perspective on evolution highlights the integration of genotype and phenotype. Starting from the protocell membrane, the functional homolog for all complex metazoan organs, it offers a way of experimentally determining the role of genes that fostered evolution based on the ontogeny and phylogeny of cellular processes that can be traced back, in some cases, to our last universal common ancestor.  ….

As eukaryotes thrived, they experienced increasingly competitive pressure for metabolic efficiency. Engulfed bacteria, assimilated as mitochondria, provided more bioenergy. As the evolution of eukaryotic organisms progressed, metabolic cooperation evolved, perhaps to enable competition with biofilm-forming, quorum-sensing prokaryotes. The subsequent appearance of multicellular eukaryotes expressing cellular growth factors and their respective receptors facilitated cell-cell signaling, forming the basis for an explosion of multicellular eukaryote evolution, culminating in the metazoans.

Casting a cellular perspective on evolution highlights the integration of genotype and phenotype. Starting from the protocell membrane, the functional homolog for all complex metazoan organs, it offers a way of experimentally determining the role of genes that fostered evolution based on the ontogeny and phylogeny of cellular processes that can be traced back, in some cases, to our last universal common ancestor.

Given that the unicellular toolkit is complete with all the traits necessary for forming multicellular organisms (Science, 301:361-63, 2003), it is distinctly possible that metazoans are merely permutations of the unicellular body plan. That scenario would clarify a lot of puzzling biology: molecular commonalities between the skin, lung, gut, and brain that affect physiology and pathophysiology exist because the cell membranes of unicellular organisms perform the equivalents of these tissue functions, and the existence of pleiotropy—one gene affecting many phenotypes—may be a consequence of the common unicellular source for all complex biologic traits.  …

The cell-molecular homeostatic model for evolution and stability addresses how the external environment generates homeostasis developmentally at the cellular level. It also determines homeostatic set points in adaptation to the environment through specific effectors, such as growth factors and their receptors, second messengers, inflammatory mediators, crossover mutations, and gene duplications. This is a highly mechanistic, heritable, plastic process that lends itself to understanding evolution at the cellular, tissue, organ, system, and population levels, mediated by physiologically linked mechanisms throughout, without having to invoke random, chance mechanisms to bridge different scales of evolutionary change. In other words, it is an integrated mechanism that can often be traced all the way back to its unicellular origins.

The switch from swim bladder to lung as vertebrates moved from water to land is proof of principle that stress-induced evolution in metazoans can be understood from changes at the cellular level.

http://www.the-scientist.com/Nov2014/TE_21.jpg

A MECHANISTIC BASIS FOR LUNG DEVELOPMENT: Stress from periodic atmospheric hypoxia (1) during vertebrate adaptation to land enhances positive selection of the stretch-regulated parathyroid hormone-related protein (PTHrP) in the pituitary and adrenal glands. In the pituitary (2), PTHrP signaling upregulates the release of adrenocorticotropic hormone (ACTH) (3), which stimulates the release of glucocorticoids (GC) by the adrenal gland (4). In the adrenal gland, PTHrP signaling also stimulates glucocorticoid production of adrenaline (5), which in turn affects the secretion of lung surfactant, the distension of alveoli, and the perfusion of alveolar capillaries (6). PTHrP signaling integrates the inflation and deflation of the alveoli with surfactant production and capillary perfusion.  THE SCIENTIST STAFF

From a cell-cell signaling perspective, two critical duplications in genes coding for cell-surface receptors occurred during this period of water-to-land transition—in the stretch-regulated parathyroid hormone-related protein (PTHrP) receptor gene and the β adrenergic (βA) receptor gene. These gene duplications can be disassembled by following their effects on vertebrate physiology backwards over phylogeny. PTHrP signaling is necessary for traits specifically relevant to land adaptation: calcification of bone, skin barrier formation, and the inflation and distention of lung alveoli. Microvascular shear stress in PTHrP-expressing organs such as bone, skin, kidney, and lung would have favored duplication of the PTHrP receptor, since sheer stress generates radical oxygen species (ROS) known to have this effect and PTHrP is a potent vasodilator, acting as an epistatic balancing selection for this constraint.

Positive selection for PTHrP signaling also evolved in the pituitary and adrenal cortex (see figure on this page), stimulating the secretion of ACTH and corticoids, respectively, in response to the stress of land adaptation. This cascade amplified adrenaline production by the adrenal medulla, since corticoids passing through it enzymatically stimulate adrenaline synthesis. Positive selection for this functional trait may have resulted from hypoxic stress that arose during global episodes of atmospheric hypoxia over geologic time. Since hypoxia is the most potent physiologic stressor, such transient oxygen deficiencies would have been acutely alleviated by increasing adrenaline levels, which would have stimulated alveolar surfactant production, increasing gas exchange by facilitating the distension of the alveoli. Over time, increased alveolar distension would have generated more alveoli by stimulating PTHrP secretion, impelling evolution of the alveolar bed of the lung.

This scenario similarly explains βA receptor gene duplication, since increased density of the βA receptor within the alveolar walls was necessary for relieving another constraint during the evolution of the lung in adaptation to land: the bottleneck created by the existence of a common mechanism for blood pressure control in both the lung alveoli and the systemic blood pressure. The pulmonary vasculature was constrained by its ability to withstand the swings in pressure caused by the systemic perfusion necessary to sustain all the other vital organs. PTHrP is a potent vasodilator, subserving the blood pressure constraint, but eventually the βA receptors evolved to coordinate blood pressure in both the lung and the periphery.

Gut Microbiome Heritability

Analyzing data from a large twin study, researchers have homed in on how host genetics can shape the gut microbiome.
By Tracy Vence | The Scientist Nov 6, 2014

Previous research suggested host genetic variation can influence microbial phenotype, but an analysis of data from a large twin study published in Cell today (November 6) solidifies the connection between human genotype and the composition of the gut microbiome. Studying more than 1,000 fecal samples from 416 monozygotic and dizygotic twin pairs, Cornell University’s Ruth Ley and her colleagues have homed in on one bacterial taxon, the family Christensenellaceae, as the most highly heritable group of microbes in the human gut. The researchers also found that Christensenellaceae—which was first described just two years ago—is central to a network of co-occurring heritable microbes that is associated with lean body mass index (BMI).  …

Of particular interest was the family Christensenellaceae, which was the most heritable taxon among those identified in the team’s analysis of fecal samples obtained from the TwinsUK study population.

While microbiologists had previously detected 16S rRNA sequences belonging to Christensenellaceae in the human microbiome, the family wasn’t named until 2012. “People hadn’t looked into it, partly because it didn’t have a name . . . it sort of flew under the radar,” said Ley.

Ley and her colleagues discovered that Christensenellaceae appears to be the hub in a network of co-occurring heritable taxa, which—among TwinsUK participants—was associated with low BMI. The researchers also found that Christensenellaceae had been found at greater abundance in low-BMI twins in older studies.

To interrogate the effects of Christensenellaceae on host metabolic phenotype, the Ley’s team introduced lean and obese human fecal samples into germ-free mice. They found animals that received lean fecal samples containing more Christensenellaceae showed reduced weight gain compared with their counterparts. And treatment of mice that had obesity-associated microbiomes with one member of the Christensenellaceae family, Christensenella minuta, led to reduced weight gain.   …

Ley and her colleagues are now focusing on the host alleles underlying the heritability of the gut microbiome. “We’re running a genome-wide association analysis to try to find genes—particular variants of genes—that might associate with higher levels of these highly heritable microbiota.  . . . Hopefully that will point us to possible reasons they’re heritable,” she said. “The genes will guide us toward understanding how these relationships are maintained between host genotype and microbiome composition.”

J.K. Goodrich et al., “Human genetics shape the gut microbiome,” Cell,  http://dx.doi.org:/10.1016/j.cell.2014.09.053, 2014.

Light-Operated Drugs

Scientists create a photosensitive pharmaceutical to target a glutamate receptor.
By Ruth Williams | The Scentist Nov 1, 2014
http://www.the-scientist.com/?articles.view/articleNo/41279/title/Light-Operated-Drugs/

light operated drugs MO1

light operated drugs MO1

http://www.the-scientist.com/Nov2014/MO1.jpg

The desire for temporal and spatial control of medications to minimize side effects and maximize benefits has inspired the development of light-controllable drugs, or optopharmacology. Early versions of such drugs have manipulated ion channels or protein-protein interactions, “but never, to my knowledge, G protein–coupled receptors [GPCRs], which are one of the most important pharmacological targets,” says Pau Gorostiza of the Institute for Bioengineering of Catalonia, in Barcelona.

Gorostiza has taken the first step toward filling that gap, creating a photosensitive inhibitor of the metabotropic glutamate 5 (mGlu5) receptor—a GPCR expressed in neurons and implicated in a number of neurological and psychiatric disorders. The new mGlu5 inhibitor—called alloswitch-1—is based on a known mGlu receptor inhibitor, but the simple addition of a light-responsive appendage, as had been done for other photosensitive drugs, wasn’t an option. The binding site on mGlu5 is “extremely tight,” explains Gorostiza, and would not accommodate a differently shaped molecule. Instead, alloswitch-1 has an intrinsic light-responsive element.

In a human cell line, the drug was active under dim light conditions, switched off by exposure to violet light, and switched back on by green light. When Gorostiza’s team administered alloswitch-1 to tadpoles, switching between violet and green light made the animals stop and start swimming, respectively.

The fact that alloswitch-1 is constitutively active and switched off by light is not ideal, says Gorostiza. “If you are thinking of therapy, then in principle you would prefer the opposite,” an “on” switch. Indeed, tweaks are required before alloswitch-1 could be a useful drug or research tool, says Stefan Herlitze, who studies ion channels at Ruhr-Universität Bochum in Germany. But, he adds, “as a proof of principle it is great.” (Nat Chem Biol, http://dx.doi.org:/10.1038/nchembio.1612, 2014)

Enhanced Enhancers

The recent discovery of super-enhancers may offer new drug targets for a range of diseases.
By Eric Olson | The Scientist Nov 1, 2014
http://www.the-scientist.com/?articles.view/articleNo/41281/title/Enhanced-Enhancers/

To understand disease processes, scientists often focus on unraveling how gene expression in disease-associated cells is altered. Increases or decreases in transcription—as dictated by a regulatory stretch of DNA called an enhancer, which serves as a binding site for transcription factors and associated proteins—can produce an aberrant composition of proteins, metabolites, and signaling molecules that drives pathologic states. Identifying the root causes of these changes may lead to new therapeutic approaches for many different diseases.

Although few therapies for human diseases aim to alter gene expression, the outstanding examples—including antiestrogens for hormone-positive breast cancer, antiandrogens for prostate cancer, and PPAR-γ agonists for type 2 diabetes—demonstrate the benefits that can be achieved through targeting gene-control mechanisms.  Now, thanks to recent papers from laboratories at MIT, Harvard, and the National Institutes of Health, researchers have a new, much bigger transcriptional target: large DNA regions known as super-enhancers or stretch-enhancers. Already, work on super-enhancers is providing insights into how gene-expression programs are established and maintained, and how they may go awry in disease.  Such research promises to open new avenues for discovering medicines for diseases where novel approaches are sorely needed.

Super-enhancers cover stretches of DNA that are 10- to 100-fold longer and about 10-fold less abundant in the genome than typical enhancer regions (Cell, 153:307-19, 2013). They also appear to bind a large percentage of the transcriptional machinery compared to typical enhancers, allowing them to better establish and enforce cell-type specific transcriptional programs (Cell, 153:320-34, 2013).

Super-enhancers are closely associated with genes that dictate cell identity, including those for cell-type–specific master regulatory transcription factors. This observation led to the intriguing hypothesis that cells with a pathologic identity, such as cancer cells, have an altered gene expression program driven by the loss, gain, or altered function of super-enhancers.

Sure enough, by mapping the genome-wide location of super-enhancers in several cancer cell lines and from patients’ tumor cells, we and others have demonstrated that genes located near super-enhancers are involved in processes that underlie tumorigenesis, such as cell proliferation, signaling, and apoptosis.

Super-enhancers cover stretches of DNA that are 10- to 100-fold longer and about 10-fold less abundant in the genome than typical enhancer regions.

Genome-wide association studies (GWAS) have found that disease- and trait-associated genetic variants often occur in greater numbers in super-enhancers (compared to typical enhancers) in cell types involved in the disease or trait of interest (Cell, 155:934-47, 2013). For example, an enrichment of fasting glucose–associated single nucleotide polymorphisms (SNPs) was found in the stretch-enhancers of pancreatic islet cells (PNAS, 110:17921-26, 2013). Given that some 90 percent of reported disease-associated SNPs are located in noncoding regions, super-enhancer maps may be extremely valuable in assigning functional significance to GWAS variants and identifying target pathways.

Because only 1 to 2 percent of active genes are physically linked to a super-enhancer, mapping the locations of super-enhancers can be used to pinpoint the small number of genes that may drive the biology of that cell. Differential super-enhancer maps that compare normal cells to diseased cells can be used to unravel the gene-control circuitry and identify new molecular targets, in much the same way that somatic mutations in tumor cells can point to oncogenic drivers in cancer. This approach is especially attractive in diseases for which an incomplete understanding of the pathogenic mechanisms has been a barrier to discovering effective new therapies.

Another therapeutic approach could be to disrupt the formation or function of super-enhancers by interfering with their associated protein components. This strategy could make it possible to downregulate multiple disease-associated genes through a single molecular intervention. A group of Boston-area researchers recently published support for this concept when they described inhibited expression of cancer-specific genes, leading to a decrease in cancer cell growth, by using a small molecule inhibitor to knock down a super-enhancer component called BRD4 (Cancer Cell, 24:777-90, 2013).  More recently, another group showed that expression of the RUNX1 transcription factor, involved in a form of T-cell leukemia, can be diminished by treating cells with an inhibitor of a transcriptional kinase that is present at the RUNX1 super-enhancer (Nature, 511:616-20, 2014).

Fungal effector Ecp6 outcompetes host immune receptor for chitin binding through intrachain LysM dimerization 
Andrea Sánchez-Vallet, et al.   eLife 2013;2:e00790 http://elifesciences.org/content/2/e00790#sthash.LnqVMJ9p.dpuf

LysM effector

LysM effector

http://img.scoop.it/ZniCRKQSvJOG18fHbb4p0Tl72eJkfbmt4t8yenImKBVvK0kTmF0xjctABnaLJIm9

While host immune receptors

  • detect pathogen-associated molecular patterns to activate immunity,
  • pathogens attempt to deregulate host immunity through secreted effectors.

Fungi employ LysM effectors to prevent

  • recognition of cell wall-derived chitin by host immune receptors

Structural analysis of the LysM effector Ecp6 of

  • the fungal tomato pathogen Cladosporium fulvum reveals
  • a novel mechanism for chitin binding,
  • mediated by intrachain LysM dimerization,

leading to a chitin-binding groove that is deeply buried in the effector protein.

This composite binding site involves

  • two of the three LysMs of Ecp6 and
  • mediates chitin binding with ultra-high (pM) affinity.

The remaining singular LysM domain of Ecp6 binds chitin with

  • low micromolar affinity but can nevertheless still perturb chitin-triggered immunity.

Conceivably, the perturbation by this LysM domain is not established through chitin sequestration but possibly through interference with the host immune receptor complex.

Mutated Genes in Schizophrenia Map to Brain Networks
From www.nih.gov –  Sep 3, 2013

Previous studies have shown that many people with schizophrenia have de novo, or new, genetic mutations. These misspellings in a gene’s DNA sequence

  • occur spontaneously and so aren’t shared by their close relatives.

Dr. Mary-Claire King of the University of Washington in Seattle and colleagues set out to

  • identify spontaneous genetic mutations in people with schizophrenia and
  • to assess where and when in the brain these misspelled genes are turned on, or expressed.

The study was funded in part by NIH’s National Institute of Mental Health (NIMH). The results were published in the August 1, 2013, issue of Cell.

The researchers sequenced the exomes (protein-coding DNA regions) of 399 people—105 with schizophrenia plus their unaffected parents and siblings. Gene variations
that were found in a person with schizophrenia but not in either parent were considered spontaneous.

The likelihood of having a spontaneous mutation was associated with

  • the age of the father in both affected and unaffected siblings.

Significantly more mutations were found in people

  • whose fathers were 33-45 years at the time of conception compared to 19-28 years.

Among people with schizophrenia, the scientists identified

  • 54 genes with spontaneous mutations
  • predicted to cause damage to the function of the protein they encode.

The researchers used newly available database resources that show

  • where in the brain and when during development genes are expressed.

The genes form an interconnected expression network with many more connections than

  • that of the genes with spontaneous damaging mutations in unaffected siblings.

The spontaneously mutated genes in people with schizophrenia

  • were expressed in the prefrontal cortex, a region in the front of the brain.

The genes are known to be involved in important pathways in brain development. Fifty of these genes were active

  • mainly during the period of fetal development.

“Processes critical for the brain’s development can be revealed by the mutations that disrupt them,” King says. “Mutations can lead to loss of integrity of a whole pathway,
not just of a single gene.”

These findings support the concept that schizophrenia may result, in part, from

  • disruptions in development in the prefrontal cortex during fetal development.

James E. Darnell’s “Reflections”

A brief history of the discovery of RNA and its role in transcription — peppered with career advice
By Joseph P. Tiano

James Darnell begins his Journal of Biological Chemistry “Reflections” article by saying, “graduate students these days

  • have to swim in a sea virtually turgid with the daily avalanche of new information and
  • may be momentarily too overwhelmed to listen to the aging.

I firmly believe how we learned what we know can provide useful guidance for how and what a newcomer will learn.” Considering his remarkable discoveries in

  • RNA processing and eukaryotic transcriptional regulation

spanning 60 years of research, Darnell’s advice should be cherished. In his second year at medical school at Washington University School of Medicine in St. Louis, while
studying streptococcal disease in Robert J. Glaser’s laboratory, Darnell realized he “loved doing the experiments” and had his first “career advancement event.”
He and technician Barbara Pesch discovered that in vivo penicillin treatment killed streptococci only in the exponential growth phase and not in the stationary phase. These
results were published in the Journal of Clinical Investigation and earned Darnell an interview with Harry Eagle at the National Institutes of Health.

Darnell arrived at the NIH in 1956, shortly after Eagle  shifted his research interest to developing his minimal essential cell culture medium, still used. Eagle, then studying cell metabolism, suggested that Darnell take up a side project on poliovirus replication in mammalian cells in collaboration with Robert I. DeMars. DeMars’ Ph.D.
adviser was also James  Watson’s mentor, so Darnell met Watson, who invited him to give a talk at Harvard University, which led to an assistant professor position
at the MIT under Salvador Luria. A take-home message is to embrace side projects, because you never know where they may lead: this project helped to shape
his career.

Darnell arrived in Boston in 1961. Following the discovery of DNA’s structure in 1953, the world of molecular biology was turning to RNA in an effort to understand how
proteins are made. Darnell’s background in virology (it was discovered in 1960 that viruses used RNA to replicate) was ideal for the aim of his first independent lab:
exploring mRNA in animal cells grown in culture. While at MIT, he developed a new technique for purifying RNA along with making other observations

  • suggesting that nonribosomal cytoplasmic RNA may be involved in protein synthesis.

When Darnell moved to Albert Einstein College of Medicine for full professorship in 1964,  it was hypothesized that heterogenous nuclear RNA was a precursor to mRNA.
At Einstein, Darnell discovered RNA processing of pre-tRNAs and demonstrated for the first time

  • that a specific nuclear RNA could represent a possible specific mRNA precursor.

In 1967 Darnell took a position at Columbia University, and it was there that he discovered (simultaneously with two other labs) that

  • mRNA contained a polyadenosine tail.

The three groups all published their results together in the Proceedings of the National Academy of Sciences in 1971. Shortly afterward, Darnell made his final career move
four short miles down the street to Rockefeller University in 1974.

Over the next 35-plus years at Rockefeller, Darnell never strayed from his original research question: How do mammalian cells make and control the making of different
mRNAs? His work was instrumental in the collaborative discovery of

  • splicing in the late 1970s and
  • in identifying and cloning many transcriptional activators.

Perhaps his greatest contribution during this time, with the help of Ernest Knight, was

  • the discovery and cloning of the signal transducers and activators of transcription (STAT) proteins.

And with George Stark, Andy Wilks and John Krowlewski, he described

  • cytokine signaling via the JAK-STAT pathway.

Darnell closes his “Reflections” with perhaps his best advice: Do not get too wrapped up in your own work, because “we are all needed and we are all in this together.”

Darnell Reflections - James_Darnell

Darnell Reflections – James_Darnell

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Recent findings on presenilins and signal peptide peptidase

By Dinu-Valantin Bălănescu

γ-secretase and SPP

γ-secretase and SPP

Fig. 1 from the minireview shows a schematic depiction of γ-secretase and SPP

http://www.asbmb.org/assets/0/366/418/428/85528/85529/85530/c2de032a-daad-41e5-ba19-87a17bd26362.png

GxGD proteases are a family of intramembranous enzymes capable of hydrolyzing

  • the transmembrane domain of some integral membrane proteins.

The GxGD family is one of the three families of

  • intramembrane-cleaving proteases discovered so far (along with the rhomboid and site-2 protease) and
  • includes the γ-secretase and the signal peptide peptidase.

Although only recently discovered, a number of functions in human pathology and in numerous other biological processes

  • have been attributed to γ-secretase and SPP.

Taisuke Tomita and Takeshi Iwatsubo of the University of Tokyo highlighted the latest findings on the structure and function of γ-secretase and SPP
in a recent minireview in The Journal of Biological Chemistry.

  • γ-secretase is involved in cleaving the amyloid-β precursor protein, thus producing amyloid-β peptide,

the main component of senile plaques in Alzheimer’s disease patients’ brains. The complete structure of mammalian γ-secretase is not yet known; however,
Tomita and Iwatsubo note that biochemical analyses have revealed it to be a multisubunit protein complex.

  • Its catalytic subunit is presenilin, an aspartyl protease.

In vitro and in vivo functional and chemical biology analyses have revealed that

  • presenilin is a modulator and mandatory component of the γ-secretase–mediated cleavage of APP.

Genetic studies have identified three other components required for γ-secretase activity:

  1. nicastrin,
  2. anterior pharynx defective 1 and
  3. presenilin enhancer 2.

By coexpression of presenilin with the other three components, the authors managed to

  • reconstitute γ-secretase activity.

Tomita and Iwatsubo determined using the substituted cysteine accessibility method and by topological analyses, that

  • the catalytic aspartates are located at the center of the nine transmembrane domains of presenilin,
  • by revealing the exact location of the enzyme’s catalytic site.

The minireview also describes in detail the formerly enigmatic mechanism of γ-secretase mediated cleavage.

SPP, an enzyme that cleaves remnant signal peptides in the membrane

  • during the biogenesis of membrane proteins and
  • signal peptides from major histocompatibility complex type I,
  • also is involved in the maturation of proteins of the hepatitis C virus and GB virus B.

Bioinformatics methods have revealed in fruit flies and mammals four SPP-like proteins,

  • two of which are involved in immunological processes.

By using γ-secretase inhibitors and modulators, it has been confirmed

  • that SPP shares a similar GxGD active site and proteolytic activity with γ-secretase.

Upon purification of the human SPP protein with the baculovirus/Sf9 cell system,

  • single-particle analysis revealed further structural and functional details.

HLA targeting efficiency correlates with human T-cell response magnitude and with mortality from influenza A infection

From www.pnas.org –  Sep 3, 2013 4:24 PM

Experimental and computational evidence suggests that

  • HLAs preferentially bind conserved regions of viral proteins, a concept we term “targeting efficiency,” and that
  • this preference may provide improved clearance of infection in several viral systems.

To test this hypothesis, T-cell responses to A/H1N1 (2009) were measured from peripheral blood mononuclear cells obtained from a household cohort study
performed during the 2009–2010 influenza season. We found that HLA targeting efficiency scores significantly correlated with

  • IFN-γ enzyme-linked immunosorbent spot responses (P = 0.042, multiple regression).

A further population-based analysis found that the carriage frequencies of the alleles with the lowest targeting efficiencies, A*24,

  • were associated with pH1N1 mortality (r = 0.37, P = 0.031) and
  • are common in certain indigenous populations in which increased pH1N1 morbidity has been reported.

HLA efficiency scores and HLA use are associated with CD8 T-cell magnitude in humans after influenza infection.
The computational tools used in this study may be useful predictors of potential morbidity and

  • identify immunologic differences of new variant influenza strains
  • more accurately than evolutionary sequence comparisons.

Population-based studies of the relative frequency of these alleles in severe vs. mild influenza cases

  • might advance clinical practices for severe H1N1 infections among genetically susceptible populations.

Metabolomics in drug target discovery

J D Rabinowitz et al.

Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ.
Cold Spring Harbor Symposia on Quantitative Biology 11/2011; 76:235-46.
http://dx.doi.org:/10.1101/sqb.2011.76.010694 

Most diseases result in metabolic changes. In many cases, these changes play a causative role in disease progression. By identifying pathological metabolic changes,

  • metabolomics can point to potential new sites for therapeutic intervention.

Particularly promising enzymatic targets are those that

  • carry increased flux in the disease state.

Definitive assessment of flux requires the use of isotope tracers. Here we present techniques for

  • finding new drug targets using metabolomics and isotope tracers.

The utility of these methods is exemplified in the study of three different viral pathogens. For influenza A and herpes simplex virus,

  • metabolomic analysis of infected versus mock-infected cells revealed
  • dramatic concentration changes around the current antiviral target enzymes.

Similar analysis of human-cytomegalovirus-infected cells, however, found the greatest changes

  • in a region of metabolism unrelated to the current antiviral target.

Instead, it pointed to the tricarboxylic acid (TCA) cycle and

  • its efflux to feed fatty acid biosynthesis as a potential preferred target.

Isotope tracer studies revealed that cytomegalovirus greatly increases flux through

  • the key fatty acid metabolic enzyme acetyl-coenzyme A carboxylase.
  • Inhibition of this enzyme blocks human cytomegalovirus replication.

Examples where metabolomics has contributed to identification of anticancer drug targets are also discussed. Eventual proof of the value of

  • metabolomics as a drug target discovery strategy will be
  • successful clinical development of therapeutics hitting these new targets.

 Related References

Use of metabolic pathway flux information in targeted cancer drug design. Drug Discovery Today: Therapeutic Strategies 1:435-443, 2004.

Detection of resistance to imatinib by metabolic profiling: clinical and drug development implications. Am J Pharmacogenomics. 2005;5(5):293-302. Review. PMID: 16196499

Medicinal chemistry, metabolic profiling and drug target discovery: a role for metabolic profiling in reverse pharmacology and chemical genetics.
Mini Rev Med Chem.  2005 Jan;5(1):13-20. Review. PMID: 15638788 [PubMed – indexed for MEDLINE] Related citations

Development of Tracer-Based Metabolomics and its Implications for the Pharmaceutical Industry. Int J Pharm Med 2007; 21 (3): 217-224.

Use of metabolic pathway flux information in anticancer drug design. Ernst Schering Found Symp Proc. 2007;(4):189-203. Review. PMID: 18811058

Pharmacological targeting of glucagon and glucagon-like peptide 1 receptors has different effects on energy state and glucose homeostasis in diet-induced obese mice. J Pharmacol Exp Ther. 2011 Jul;338(1):70-81. http://dx.doi.org:/10.1124/jpet.111.179986. PMID: 21471191

Single valproic acid treatment inhibits glycogen and RNA ribose turnover while disrupting glucose-derived cholesterol synthesis in liver as revealed by the
[U-C(6)]-d-glucose tracer in mice. Metabolomics. 2009 Sep;5(3):336-345. PMID: 19718458

Metabolic Pathways as Targets for Drug Screening, Metabolomics, Dr Ute Roessner (Ed.), ISBN: 978-953-51-0046-1, InTech, Available from: http://www.intechopen.com/books/metabolomics/metabolic-pathways-as-targets-for-drug-screening

Iron regulates glucose homeostasis in liver and muscle via AMP-activated protein kinase in mice. FASEB J. 2013 Jul;27(7):2845-54.
http://dx.doi.org:/10.1096/fj.12-216929. PMID: 23515442

Metabolomics and systems pharmacology: why and how to model the human metabolic network for drug discovery

Drug Discov. Today 19 (2014), 171–182     http://dx.doi.org:/10.1016/j.drudis.2013.07.014

Highlights

  • We now have metabolic network models; the metabolome is represented by their nodes.
  • Metabolite levels are sensitive to changes in enzyme activities.
  • Drugs hitchhike on metabolite transporters to get into and out of cells.
  • The consensus network Recon2 represents the present state of the art, and has predictive power.
  • Constraint-based modelling relates network structure to metabolic fluxes.

Metabolism represents the ‘sharp end’ of systems biology, because changes in metabolite concentrations are

  • necessarily amplified relative to changes in the transcriptome, proteome and enzyme activities, which can be modulated by drugs.

To understand such behaviour, we therefore need (and increasingly have) reliable consensus (community) models of

  • the human metabolic network that include the important transporters.

Small molecule ‘drug’ transporters are in fact metabolite transporters, because

  • drugs bear structural similarities to metabolites known from the network reconstructions and
  • from measurements of the metabolome.

Recon2 represents the present state-of-the-art human metabolic network reconstruction; it can predict inter alia:

(i) the effects of inborn errors of metabolism;

(ii) which metabolites are exometabolites, and

(iii) how metabolism varies between tissues and cellular compartments.

However, even these qualitative network models are not yet complete. As our understanding improves

  • so do we recognise more clearly the need for a systems (poly)pharmacology.

Introduction – a systems biology approach to drug discovery

It is clearly not news that the productivity of the pharmaceutical industry has declined significantly during recent years

  • following an ‘inverse Moore’s Law’, Eroom’s Law, or
  • that many commentators, consider that the main cause of this is
  • because of an excessive focus on individual molecular target discovery rather than a more sensible strategy
  • based on a systems-level approach (Fig. 1).
drug discovery science

drug discovery science

Figure 1.

The change in drug discovery strategy from ‘classical’ function-first approaches (in which the assay of drug function was at the tissue or organism level),
with mechanistic studies potentially coming later, to more-recent target-based approaches where initial assays usually involve assessing the interactions
of drugs with specified (and often cloned, recombinant) proteins in vitro. In the latter cases, effects in vivo are assessed later, with concomitantly high levels of attrition.

Arguably the two chief hallmarks of the systems biology approach are:

(i) that we seek to make mathematical models of our systems iteratively or in parallel with well-designed ‘wet’ experiments, and
(ii) that we do not necessarily start with a hypothesis but measure as many things as possible (the ’omes) and

  • let the data tell us the hypothesis that best fits and describes them.

Although metabolism was once seen as something of a Cinderella subject,

  • there are fundamental reasons to do with the organisation of biochemical networks as
  • to why the metabol(om)ic level – now in fact seen as the ‘apogee’ of the ’omics trilogy –
  •  is indeed likely to be far more discriminating than are
  • changes in the transcriptome or proteome.

The next two subsections deal with these points and Fig. 2 summarises the paper in the form of a Mind Map.

metabolomics and systems pharmacology

metabolomics and systems pharmacology

http://ars.els-cdn.com/content/image/1-s2.0-S1359644613002481-gr2.jpg

Metabolic Disease Drug Discovery— “Hitting the Target” Is Easier Said Than Done

David E. Moller, et al.   http://dx.doi.org:/10.1016/j.cmet.2011.10.012

Despite the advent of new drug classes, the global epidemic of cardiometabolic disease has not abated. Continuing

  • unmet medical needs remain a major driver for new research.

Drug discovery approaches in this field have mirrored industry trends, leading to a recent

  • increase in the number of molecules entering development.

However, worrisome trends and newer hurdles are also apparent. The history of two newer drug classes—

  1. glucagon-like peptide-1 receptor agonists and
  2. dipeptidyl peptidase-4 inhibitors—

illustrates both progress and challenges. Future success requires that researchers learn from these experiences and

  • continue to explore and apply new technology platforms and research paradigms.

The global epidemic of obesity and diabetes continues to progress relentlessly. The International Diabetes Federation predicts an even greater diabetes burden (>430 million people afflicted) by 2030, which will disproportionately affect developing nations (International Diabetes Federation, 2011). Yet

  • existing drug classes for diabetes, obesity, and comorbid cardiovascular (CV) conditions have substantial limitations.

Currently available prescription drugs for treatment of hyperglycemia in patients with type 2 diabetes (Table 1) have notable shortcomings. In general,

Therefore, clinicians must often use combination therapy, adding additional agents over time. Ultimately many patients will need to use insulin—a therapeutic class first introduced in 1922. Most existing agents also have

  • issues around safety and tolerability as well as dosing convenience (which can impact patient compliance).

Pharmacometabolomics, also known as pharmacometabonomics, is a field which stems from metabolomics,

  • the quantification and analysis of metabolites produced by the body.

It refers to the direct measurement of metabolites in an individual’s bodily fluids, in order to

  • predict or evaluate the metabolism of pharmaceutical compounds, and
  • to better understand the pharmacokinetic profile of a drug.

Alternatively, pharmacometabolomics can be applied to measure metabolite levels

  • following the administration of a pharmaceutical compound, in order to
  • monitor the effects of the compound on certain metabolic pathways(pharmacodynamics).

This provides detailed mapping of drug effects on metabolism and

  • the pathways that are implicated in mechanism of variation of response to treatment.

In addition, the metabolic profile of an individual at baseline (metabotype) provides information about

  • how individuals respond to treatment and highlights heterogeneity within a disease state.

All three approaches require the quantification of metabolites found

relationship between -OMICS

relationship between -OMICS

http://upload.wikimedia.org/wikipedia/commons/thumb/e/eb/OMICS.png/350px-OMICS.png

Pharmacometabolomics is thought to provide information that

Looking at the characteristics of an individual down through these different levels of detail, there is an

  • increasingly more accurate prediction of a person’s ability to respond to a pharmaceutical compound.
  1. the genome, made up of 25 000 genes, can indicate possible errors in drug metabolism;
  2. the transcriptome, made up of 85,000 transcripts, can provide information about which genes important in metabolism are being actively transcribed;
  3. and the proteome, >10,000,000 members, depicts which proteins are active in the body to carry out these functions.

Pharmacometabolomics complements the omics with

  • direct measurement of the products of all of these reactions, but with perhaps a relatively
  • smaller number of members: that was initially projected to be approximately 2200 metabolites,

but could be a larger number when gut derived metabolites and xenobiotics are added to the list. Overall, the goal of pharmacometabolomics is

  • to more closely predict or assess the response of an individual to a pharmaceutical compound,
  • permitting continued treatment with the right drug or dosage
  • depending on the variations in their metabolism and ability to respond to treatment.

Pharmacometabolomic analyses, through the use of a metabolomics approach,

  • can provide a comprehensive and detailed metabolic profile or “metabolic fingerprint” for an individual patient.

Such metabolic profiles can provide a complete overview of individual metabolite or pathway alterations,

This approach can then be applied to the prediction of response to a pharmaceutical compound

  • by patients with a particular metabolic profile.

Pharmacometabolomic analyses of drug response are

Pharmacogenetics focuses on the identification of genetic variations (e.g. single-nucleotide polymorphisms)

  • within patients that may contribute to altered drug responses and overall outcome of a certain treatment.

The results of pharmacometabolomics analyses can act to “inform” or “direct”

  • pharmacogenetic analyses by correlating aberrant metabolite concentrations or metabolic pathways to potential alterations at the genetic level.

This concept has been established with two seminal publications from studies of antidepressants serotonin reuptake inhibitors

  • where metabolic signatures were able to define a pathway implicated in response to the antidepressant and
  • that lead to identification of genetic variants within a key gene
  • within the highlighted pathway as being implicated in variation in response.

These genetic variants were not identified through genetic analysis alone and hence

  • illustrated how metabolomics can guide and inform genetic data.

en.wikipedia.org/wiki/Pharmacometabolomics

Benznidazole Biotransformation and Multiple Targets in Trypanosoma cruzi Revealed by Metabolomics

Andrea Trochine, Darren J. Creek, Paula Faral-Tello, Michael P. Barrett, Carlos Robello
Published: May 22, 2014   http://dx.doi.org:/10.1371/journal.pntd.0002844

The first line treatment for Chagas disease, a neglected tropical disease caused by the protozoan parasite Trypanosoma cruzi,

  • involves administration of benznidazole (Bzn).

Bzn is a 2-nitroimidazole pro-drug which requires nitroreduction to become active. We used a

  • non-targeted MS-based metabolomics approach to study the metabolic response of T. cruzi to Bzn.

Parasites treated with Bzn were minimally altered compared to untreated trypanosomes, although the redox active thiols

  1. trypanothione,
  2. homotrypanothione and
  3. cysteine

were significantly diminished in abundance post-treatment. In addition, multiple Bzn-derived metabolites were detected after treatment.

These metabolites included reduction products, fragments and covalent adducts of reduced Bzn

  • linked to each of the major low molecular weight thiols:
  1. trypanothione,
  2. glutathione,
  3. g-glutamylcysteine,
  4. glutathionylspermidine,
  5. cysteine and
  6. ovothiol A.

Bzn products known to be generated in vitro by the unusual trypanosomal nitroreductase, TcNTRI,

  • were found within the parasites,
  • but low molecular weight adducts of glyoxal, a proposed toxic end-product of NTRI Bzn metabolism, were not detected.

Our data is indicative of a major role of the

  • thiol binding capacity of Bzn reduction products
  • in the mechanism of Bzn toxicity against T. cruzi.

 

 

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Summary to Metabolomics

Summary to Metabolomics

Author and Curator: Larry H. Bernstein, MD, FCAP 

This concludes a long step-by-step journey into rediscovering biological processes from the genome as a framework to the remodeled and reconstituted cell through a number of posttranscription and posttranslation processes that modify the proteome and determine the metabolome.  The remodeling process continues over a lifetime. The process requires a balance between nutrient intake, energy utilization for work in the lean body mass, energy reserves, endocrine, paracrine and autocrine mechanisms, and autophagy.  It is true when we look at this in its full scope – What a creature is man?

http://masspec.scripps.edu/metabo_science/recommended_readings.php
 Recommended Readings and Historical Perspectives

Metabolomics is the scientific study of chemical processes involving metabolites. Specifically, metabolomics is the “systematic study of the unique chemical fingerprints that specific cellular processes leave behind”, the study of their small-molecule metabolite profiles.[1] The metabolome represents the collection of all metabolites in a biological cell, tissue, organ or organism, which are the end products of cellular processes.[2] mRNA gene expression data and proteomic analyses reveal the set of gene products being produced in the cell, data that represents one aspect of cellular function. Conversely, metabolic profiling can give an instantaneous snapshot of the physiology of that cell. One of the challenges of systems biology and functional genomics is to integrate proteomic, transcriptomic, and metabolomic information to provide a better understanding of cellular biology.

The term “metabolic profile” was introduced by Horning, et al. in 1971 after they demonstrated that gas chromatography-mass spectrometry (GC-MS) could be used to measure compounds present in human urine and tissue extracts. The Horning group, along with that of Linus Pauling and Arthur B. Robinson led the development of GC-MS methods to monitor the metabolites present in urine through the 1970s.

Concurrently, NMR spectroscopy, which was discovered in the 1940s, was also undergoing rapid advances. In 1974, Seeley et al. demonstrated the utility of using NMR to detect metabolites in unmodified biological samples.This first study on muscle highlighted the value of NMR in that it was determined that 90% of cellular ATP is complexed with magnesium. As sensitivity has improved with the evolution of higher magnetic field strengths and magic angle spinning, NMR continues to be a leading analytical tool to investigate metabolism. Efforts to utilize NMR for metabolomics have been influenced by the laboratory of Dr. Jeremy Nicholson at Birkbeck College, University of London and later at Imperial College London. In 1984, Nicholson showed 1H NMR spectroscopy could potentially be used to diagnose diabetes mellitus, and later pioneered the application of pattern recognition methods to NMR spectroscopic data.

In 2005, the first metabolomics web database, METLIN, for characterizing human metabolites was developed in the Siuzdak laboratory at The Scripps Research Institute and contained over 10,000 metabolites and tandem mass spectral data. As of September 2012, METLIN contains over 60,000 metabolites as well as the largest repository of tandem mass spectrometry data in metabolomics.

On 23 January 2007, the Human Metabolome Project, led by Dr. David Wishart of the University of Alberta, Canada, completed the first draft of the human metabolome, consisting of a database of approximately 2500 metabolites, 1200 drugs and 3500 food components. Similar projects have been underway in several plant species, most notably Medicago truncatula and Arabidopsis thaliana for several years.

As late as mid-2010, metabolomics was still considered an “emerging field”. Further, it was noted that further progress in the field depended in large part, through addressing otherwise “irresolvable technical challenges”, by technical evolution of mass spectrometry instrumentation.

Metabolome refers to the complete set of small-molecule metabolites (such as metabolic intermediates, hormones and other signaling molecules, and secondary metabolites) to be found within a biological sample, such as a single organism. The word was coined in analogy with transcriptomics and proteomics; like the transcriptome and the proteome, the metabolome is dynamic, changing from second to second. Although the metabolome can be defined readily enough, it is not currently possible to analyse the entire range of metabolites by a single analytical method. The first metabolite database(called METLIN) for searching m/z values from mass spectrometry data was developed by scientists at The Scripps Research Institute in 2005. In January 2007, scientists at the University of Alberta and the University of Calgary completed the first draft of the human metabolome. They catalogued approximately 2500 metabolites, 1200 drugs and 3500 food components that can be found in the human body, as reported in the literature. This information, available at the Human Metabolome Database (www.hmdb.ca) and based on analysis of information available in the current scientific literature, is far from complete.

Each type of cell and tissue has a unique metabolic ‘fingerprint’ that can elucidate organ or tissue-specific information, while the study of biofluids can give more generalized though less specialized information. Commonly used biofluids are urine and plasma, as they can be obtained non-invasively or relatively non-invasively, respectively. The ease of collection facilitates high temporal resolution, and because they are always at dynamic equilibrium with the body, they can describe the host as a whole.

Metabolites are the intermediates and products of metabolism. Within the context of metabolomics, a metabolite is usually defined as any molecule less than 1 kDa in size.
A primary metabolite is directly involved in the normal growth, development, and reproduction. A secondary metabolite is not directly involved in those processes.  By contrast, in human-based metabolomics, it is more common to describe metabolites as being either endogenous (produced by the host organism) or exogenous. Metabolites of foreign substances such as drugs are termed xenometabolites. The metabolome forms a large network of metabolic reactions, where outputs from one enzymatic chemical reaction are inputs to other chemical reactions.

Metabonomics is defined as “the quantitative measurement of the dynamic multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification”. The word origin is from the Greek μεταβολή meaning change and nomos meaning a rule set or set of laws. This approach was pioneered by Jeremy Nicholson at Imperial College London and has been used in toxicology, disease diagnosis and a number of other fields. Historically, the metabonomics approach was one of the first methods to apply the scope of systems biology to studies of metabolism.

There is a growing consensus that ‘metabolomics’ places a greater emphasis on metabolic profiling at a cellular or organ level and is primarily concerned with normal endogenous metabolism. ‘Metabonomics’ extends metabolic profiling to include information about perturbations of metabolism caused by environmental factors (including diet and toxins), disease processes, and the involvement of extragenomic influences, such as gut microflora. This is not a trivial difference; metabolomic studies should, by definition, exclude metabolic contributions from extragenomic sources, because these are external to the system being studied.

Toxicity assessment/toxicology. Metabolic profiling (especially of urine or blood plasma samples) detects the physiological changes caused by toxic insult of a chemical (or mixture of chemicals).

Functional genomics. Metabolomics can be an excellent tool for determining the phenotype caused by a genetic manipulation, such as gene deletion or insertion. Sometimes this can be a sufficient goal in itself—for instance, to detect any phenotypic changes in a genetically-modified plant intended for human or animal consumption. More exciting is the prospect of predicting the function of unknown genes by comparison with the metabolic perturbations caused by deletion/insertion of known genes.

Nutrigenomics is a generalised term which links genomics, transcriptomics, proteomics and metabolomics to human nutrition. In general a metabolome in a given body fluid is influenced by endogenous factors such as age, sex, body composition and genetics as well as underlying pathologies. The large bowel microflora are also a very significant potential confounder of metabolic profiles and could be classified as either an endogenous or exogenous factor. The main exogenous factors are diet and drugs. Diet can then be broken down to nutrients and non- nutrients.

http://en.wikipedia.org/wiki/Metabolomics

Jose Eduardo des Salles Roselino

The problem with genomics was it was set as explanation for everything. In fact, when something is genetic in nature the genomic reasoning works fine. However, this means whenever an inborn error is found and only in this case the genomic knowledge afterwards may indicate what is wrong and not the completely way to put biology upside down by reading everything in the DNA genetic as well as non-genetic problems.

Coordination of the transcriptome and metabolome by the circadian clock PNAS 2012

Coordination of the transcriptome and metabolome by the circadian clock PNAS 2012

analysis of metabolomic data and differential metabolic regulation for fetal lungs, and maternal blood plasma

conformational changes leading to substrate efflux.img

conformational changes leading to substrate efflux.img

The cellular response is defined by a network of chemogenomic response signatures.

The cellular response is defined by a network of chemogenomic response signatures.

Dynamic Construct of the –Omics

Dynamic Construct of the –Omics

 genome cartoon

genome cartoon

central dogma phenotype

central dogma phenotype

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