Feeds:
Posts
Comments

Posts Tagged ‘glutamate’


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?
https://pharmaceuticalintelligence.com/2014/06/21/is-the-warburg-effect-the-cause-or-the-effect-of-cancer-a-21st-century-view-2/

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

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

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

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

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

Metabolomics Summary and Perspective
https://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.

 

 

 

 

 

 

 

 

Read Full Post »


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.

  1. Warburg O. On the origin of cancer cells. Science. 1956;123(3191):309–314. 2. Dang CV, Semenza GL. Oncogenic alterations of metabolism. Trends Biochem Sci. 1999; 24(2):68–72.
    3. Fan TW, et al. Rhabdomyosarcoma cells show an energy producing anabolic metabolic phenotype compared with primary myocytes. Mol Cancer. 2008;7:79.
    4. Vander Heiden MG, Cantley LC, Thompson CB. Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science. 2009;324(5930):1029–1033.
    10. Le A, et al. Glucose-independent glutamine metabolism via TCA cycling for proliferation and survival in B cells. Cell Metab. 2012;15(1):110–121
    20. Cheng T, et al. Pyruvate carboxylase is required for glutamine-independent growth of tumor cells. Proc Natl Acad Sci U S A. 2011;108(21):8674–8679.
    21. Fan TW, et al. Altered regulation of metabolic pathways in human lung cancer discerned by (13) C stable isotope-resolved metabolomics (SIRM). Mol Cancer. 2009;8:41.
    22. Marin-Valencia I, et al. Analysis of tumor metabolism reveals mitochondrial glucose oxidation in genetically diverse human glioblastomas in the mouse brain in vivo. Cell Metab. 2012;15(6):827–837.
    25. Warburg O. Versuche an überlebendem Carcinomgewebe (Methoden). Biochem Zeitschr. 1923;142:317–333.
    45. Lorkiewicz P, Higashi RM, Lane AN, Fan TW. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2012;8(5):930–939.

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.

Read Full Post »


Endocrine Action on Midbrain

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

 
  • Brain’s Role in Browning White Fat
  • Insulin and leptin act on specialized neurons in the mouse hypothalamus to promote conversion of white to beige fat.

By Anna Azvolinsky | January 15, 2015

JUSTIN HEWLETT, MNHS MULTIMEDIA, MONASH UNIVERSITY

Ever since energy-storing white fat has been shown to convert to metabolically active beige fat, through a process called browning, scientists have been trying to understand how this switch occurs. The immune system has been shown to contribute to activation of brown fat cells. Now, researchers from Monash University in Australia and their colleagues have shown that insulin and leptin—two hormones that regulate glucose metabolism and satiety and hunger cues—activate “satiety” neurons in the mouse hypothalamus to promote the conversion of white fat to beige. The results are published today (January 15) in Cell.

Hypothalamic appetite-suppressing proopiomelanocortin (POMC) neurons are known to relay the satiety signals in the bloodstream to other parts of the brain and other tissues to promote energy balance. “What is new here is that one way that these neurons promote calorie-burning is to stimulate the browning of white fat,” said Xiaoyong Yang, who studies the molecular mechanisms of metabolism at the Yale University School of Medicine, but was not involved in the work. “The study identifies how the brain communicates to fat tissue to promote energy dissipation.”

“The authors show that [insulin and leptin] directly interact in the brain to produce nervous-system signaling both to white and brown adipose tissue,” said Jan Nedergaard, a professor of physiology at Stockholm University who also was not involved in the study. “This is a nice demonstration of how the acute and chronic energy status talks to the thermogenic tissues.”

Although the differences between beige and brown fat are still being defined, the former is currently considered a metabolically active fat—which converts the energy of triglycerides into heat—nestled within white fat tissue. Because of their energy-burning properties, brown and beige fat are considered superior to white fat, so understanding how white fat can be browned is a key research question. Exposure to cold can promote the browning of white fat, but the ability of insulin and leptin to act in synergy to signal to the brain to promote browning was not known before this study, according the author Tony Tiganis, a biochemist at Monash.

White fat cells steadily produce leptin, while insulin is produced by cells of the pancreas in response to a surge of glucose into the blood. Both hormones are known to signal to the brain to regulate satiety and body weight. To explore the connection between this energy expenditure control system and fat tissue, Garron Dodd, a postdoctoral fellow in Tiganis’s laboratory, and his colleagues deleted one or both of two phosphatase enzymes in murine POMC neurons. These phosphatase enzymes were previously known to act in the hypothalamus to regulate both glucose metabolism and body weight, each regulating either leptin or insulin signaling. When both phosphatases were deleted, mice had less white fat tissue and increased insulin and leptin signaling.

“These [phosphatase enzymes] work in POMC neurons by acting as ‘dimmer switches,’ controlling the sensitivity of leptin and insulin receptors to their endogenous ligands,” Dodd told The Scientist in an e-mail. The double knockout mice also had an increase in beige fat and more active heat-generating brown fat. When fed a high-fat diet, unlike either the single knockout or wild-type mice, the double knockout mice did not gain weight, suggesting that leptin and insulin signaling to POMC neurons is important for controlling body weight and fat metabolism.

The researchers also infused leptin and insulin directly into the hypothalami of wild-type mice, which promoted the browning of white fat. But when these hormones were infused but the neuronal connections between the white fat and the brain were physically severed, browning was prevented. Moreover, hormone infusion and cutting the neuronal connection to only a single fat pad resulted in browning only in the fat pad that maintained signaling ties to the brain. “This really told us that direct innervation from the brain is necessary and that these hormones are acting together to regulate energy expenditure,” said Tiganis.

These results are “really exciting as, perhaps, resistance to the actions of leptin and insulin in POMC neurons is a key feature underlying obesity in people,” said Dodd.

Another set of neurons in the hypothalamus, the agouti-related protein expressing (AgRP) or “hunger” neurons, are activated by hunger signals and promote energy storage. Along with Tamas Horvath, Yale’s Yang recently showed that fasting activates AgRP neurons that then suppress the browning of white fat. “These two stories are complimentary, providing a bigger picture: that the hunger and satiety neurons control browning of fat depending on the body’s energy state,” said Yang. Activation of POMC neurons during caloric intake protects against diet-induced obesity while activation of AgRP neurons tells the body to store energy during fasting.

Whether these results hold up in humans has yet to be explored. Expression of the two phosphatases in the hypothalamus is known to be higher in obese people, but it is not clear whether this suppresses the browning of white fat.

“One of the next big questions is whether this increased expression and prevention of insulin plus leptin signaling, and conversion of white to brown fat perturbs energy balance and promotes obesity,” said Tiganis. Another, said Dodd, is whether other parts of the brain are involved in signaling to and from adipose tissue.

  1. Dodd et al., “Leptin and insulin act on POMC neurons to promote the browning of white fat,”

Cell, 2015.    http://dx.doi.org:/10.1016/j.cell.2014.12.022   http://medicine.yale.edu/lab/horvath/index.aspx

Our main interest is the neuroendocrine regulation of homeostasis with particular emphasis on metabolic disorders, such as obesity and diabetes, and the effect of metabolic signals on higher brain functions and neurodegeneration. We have active research programs to pursue the role of synaptic plasticity in the mediation of peripheral hormones’ effects on the central nervous system.

We also study the role of mitochondrial membrane potential in normal and pathological brain functions with particular emphasis on the acute effect of mitochondria in neuronal transmission and neuroprotection. We combine classical neurobiological approaches, including electrophysiology and neuroanatomy, with endocrine and genetic techniques to better understand biological events at the level of the organism.

Leptin and Insulin Act on POMC Neurons to Promote the Browning of White Fat

Garron T. Dodd, Stephanie Decherf, Kim Loh, Stephanie E. Simonds, Florian Wiede, Eglantine Balland, Troy L. Merry, et al.

http://dx.doi.org/10.1016/j.cell.2014.12.022

Highlights

  • Insulin and leptin act synergistically on POMC neurons to promote WAT browning
  • Increased POMC-mediated WAT browning prevents diet-induced obesity
  • PTP1B and TCPTP attenuate leptin and insulin signaling in POMC neurons
  • Combined PTP1B and TCPTP deficiency in POMC neurons promotes white fat browning

The primary task of white adipose tissue (WAT) is the storage of lipids. However, “beige” adipocytes also exist in WAT. Beige adipocytes burn fat and dissipate the energy as heat, but their abundance is diminished in obesity. Stimulating beige adipocyte development, or WAT browning, increases energy expenditure and holds potential for combating metabolic disease and obesity. Here, we report that insulin and leptin act together on hypothalamic neurons to promote WAT browning and weight loss. Deletion of the phosphatases PTP1B and TCPTP enhanced insulin and leptin signaling in proopiomelanocortin neurons and prevented diet-induced obesity by increasing WAT browning and energy expenditure. The coinfusion of insulin plus leptin into the CNS or the activation of proopiomelanocortin neurons also increased WAT browning and decreased adiposity. Our findings identify a homeostatic mechanism for coordinating the status of energy stores, as relayed by insulin and leptin, with the central control of WAT browning.  http://www.cell.com/cms/attachment/2023992410/2043906325/fx1.jpg

Light on the Brain

Researchers find that photoreceptors expressed in zebrafish hypothalamus contribute to light-dependent behavior.

By Sabrina Richards | September 20, 2012

A 21 day old zebrafish. Their optical clarity and relatively easy maintenance make them a favorite for geneticists and developmental biologists. In this fish, the muscles can be seen as chevron shapes in the tail, the swim bladder as a “bubble” just behind the head, and the food that the fish has been eating as a brown patch just below the swim bladder.

Juvenile zebrafish. Shawn Burgess, NHGRI

Zebrafish larvae without eyes or pineal glands can still respond to light using photopigments located deep within their brains.  Published today (September 20) in Current Biology, the findings are the first to link opsins, photoreceptors in the hypothalamus and other brain areas, to increased swimming in response to darkness, a behavior researchers hypothesize may help the fish move toward better-lit environments.

“[It’s a] strong demonstration that opsin-dependent photoreceptors in deep brain areas affect behaviors,” said Samer Hattar, who studies light reception in mammals at Johns Hopkins University but did not participate in the research.

Photoreceptors in eyes enable vision, and photoreceptors in the pineal gland, a small endocrine gland located in the center of the vertebrate brain, regulate circadian rhythms. But photoreceptors are also found in other brain areas of both invertebrates and vertebrate lineages. The function of these extraocular photoreceptors has been best studied in birds, where they regulate seasonal reproduction, explained Harold Burgess, a behavioral neurogeneticist at the Eunice Kennedy Shriver National Institute for Child Health and Human Development. Many opsins have been reported in the brains of tiny and transparent larval zebrafish, raising the possibility that light could be stimulating the photoreceptors even deep in the brain. To test for behaviors that may be regulated by deep brain photoreceptors, Burgess and his colleagues in Wolfgang Driever’s lab at the University of Freiburg removed the eyes of zebrafish larvae, and compared their behavior to larvae that retained their eyes. Although most light-dependent behavior required eyes, the eyeless larvae did respond when the lights were turned off, increasing their activity for a several minutes, though to a somewhat lesser extent than control larvae. But the fact that they responded at all suggests that non-retinal photoreceptors contributed to the behavior.

To confirm the role of the deep brain photoreceptors, the researchers also tested eyeless larvae that had been genetically modified to block expression of photoreceptors in the pineal gland. This fish still showed this jump in activity for several minutes after entering darkness.

Two different types of opsins—melanopsin and multiple tissue opsin—are expressed in the same type of neuron in zebrafish hypothalamus. Burgess and his colleagues looked at zebrafish missing the transcription factor Orthopedia, which is unique to these neurons, and found that the darkness-induced activity boost is nearly absent in these fish. To further narrow the search for the responsible photoreceptors, the researchers overexpressed melanopsin in hypothalamus neurons that co-express Orthopedia and melanopsin, and found that it increased the sensitivity of eyeless zebrafish to reductions in light. The results point to both melanopsin and Orthopedia as key players in modulating this behavior and pinpoint the location to neurons that coexpress these factors in the zebrafish hypothalamus.

Interestingly, the hypothalamus is one of the oldest parts of the vertebrate brain, said Detlev Arendt, a developmental biologist at the European Molecular Biology Laboratory in Heidelberg. “It’s very possible that this is one of the oldest functions”—one that evolved in “non-visual organisms” that had no eyes but still needed to sense light.

Although not as directed and efficient as eye-dependent behaviors that help fish swim toward light, Burgess speculates that deep brain opsins can still benefit zebrafish larvae. “You could imagine situation where it can’t see light, if a leaf falls on it and it doesn’t know where to swim. I think this behavior puts it in a hyperactive state where it swims wildly for several minutes until it reaches enough light for eyes to take over,” he explained, noting that such behavior is common in invertebrates.

It remains to be seen whether these deep brain opsins regulate other behaviors, perhaps in similar fashion to seasonal hormonal regulation in birds, but Hattar believes it is likely. “It’s beyond reasonable doubt there are many functions for these deep brain photoreceptors.”

Fernandes et al., “Deep brain photoreceptors control light-seeking behavior in zebrafish larvae,” Current Biology, 22:1-6, 2012.

Neuroendocrine basis of sexuality, mood, anxiety, social consciousness

Physiology, signaling, and pharmacology of galanin peptides and receptors: Three decades of emerging diversity

Lang, R., Gundlach, A.L., Holmes, F.E., (…), Hökfelt, T., Kofler, B.
Pharmacological Reviews 2015: 67 (1), pp. 118-175
http://dx.doi.org:/10.1124/pr.112.006536

Galanin was first identified 30 years ago as a “classic neuropeptide,” with actions primarily as a modulator of neurotransmission in the brain and peripheral nervous system. Other structurally-related peptides—galanin-like peptide and alarin—with diverse biologic actions in brain and other tissues have since been identified, although, unlike galanin, their cognate receptors are currently unknown. Over the last two decades, in addition to many neuronal actions, a number of nonneuronal actions of galanin and other galanin family peptides have been described. These include actions associated with neural stem cells, nonneuronal cells in the brain such as glia, endocrine functions, effects on metabolism, energy homeostasis, and paracrine effects in bone. Substantial new data also indicate an emerging role for galanin in innate immunity, inflammation, and cancer. Galanin has been shown to regulate its numerous physiologic and pathophysiological processes through interactions with three G protein–coupled receptors, GAL1, GAL2, and GAL3, and signaling via multiple transduction pathways, including inhibition of cAMP/PKA (GAL1, GAL3) and stimulation of phospholipase C (GAL2). In this review, we emphasize the importance of novel galanin receptor–specific agonists and antagonists. Also, other approaches, including new transgenic mouse lines (such as a recently characterized GAL3 knockout mouse) represent, in combination with viral-based techniques, critical tools required to better evaluate galanin system physiology. These in turn will help identify potential targets of the galanin/galanin-receptor systems in a diverse range of human diseases, including pain, mood disorders, epilepsy, neurodegenerative conditions, diabetes, and cancer.

Estradiol regulates responsiveness of the dorsal premammillary nucleus of the hypothalamus and affects fear- and anxiety-like behaviors in female rats

Litvin, Y., Cataldo, G., Pfaff, D.W., Kow, L.-M.
European Journal of Neuroscience 2014; 40 (2), pp. 2344-2351
10.1111/ejn.12608

Research suggests a causal link between estrogens and mood. Here, we began by examining the effects of estradiol (E2) on rat innate and conditioned defensive behaviors in response to cat odor. Second, we utilized whole-cell patch clamp electrophysiological techniques to assess noradrenergic effects on neurons within the dorsal premammillary nucleus of the hypothalamus (PMd), a nucleus implicated in fear reactivity, and their regulation by E2. Our results show that E2 increased general arousal and modified innate defensive reactivity to cat odor. When ovariectomized females treated with E2 as opposed to oil were exposed to cat odor, they showed elevations in risk assessment and reductions in freezing, indicating a shift from passive to active coping. In addition, animals previously exposed to cat odor showed clear cue + context conditioning 24 h later. However, although E2 persisted in its effects on general arousal in the conditioning task, its effects on fear disappeared. In the patch clamp experiments noradrenergic compounds that typically induce fear clearly excited PMd neurons, producing depolarizations and action potentials. E2 treatment shifted some excitatory effects of noradrenergic agonists to inhibitory, possibly by differentially affecting α- and β-adrenoreceptors. In summary, our results implicate E2 in general arousal and fear reactivity, and suggest these may be governed by changes in noradrenergic responsivity in the PMd. These effects of E2 may have ethological relevance, serving to promote mate seeking even in contexts of ambiguous threat and shed light on the involvement of estrogen in mood and its associated disorders.

Endogenous opiates and behavior: 2013

Richard J. Bodnar
Peptides 62 (2014) 67–136
http://dx.doi.org/10.1016/j.peptides.2014.09.013

This paper is the thirty-sixth consecutive installment of the annual review of research concerning the endogenous opioid system. It summarizes papers published during 2013 that studied the behavioral effects of molecular, pharmacological and genetic manipulation of opioid peptides, opioid receptors, opioid agonists and opioid antagonists. The particular topics that continue to be covered include the molecular-biochemical effects and neurochemical localization studies of endogenous opioids and their receptors related to behavior, and the roles of these opioid peptides and receptors in pain and analgesia; stress and social status; tolerance and dependence; learning and memory; eating and drinking; alcohol and drugs of abuse; sexual activity and hormones, pregnancy, development and endocrinology; mental illness and mood; seizures and neurologic disorders; electrical-related activity and neurophysiology; general activity and locomotion; gastrointestinal, renal and hepatic functions; cardiovascular responses; respiration and thermoregulation; and immunological responses.

Brain aromatase (cyp19a1b) and gonadotropin releasing hormone (gnrh2 and gnrh3) expression during reproductive development and sex change in black sea bass (Centropristis striata)

Timothy S Breton, Matthew A DiMaggio, Stacia A Sowe, David L Berlinsky, et al.
Comparative Biochemistry and Physiology, Part A 181 (2015) 45–53
http://dx.doi.org/10.1016/j.cbpa.2014.11.020

Teleost fish exhibit diverse reproductive strategies, and some species are capable of changing sex. The influence of many endocrine factors, such as gonadal steroids and neuropeptides, has been studied in relation to sex change, but comparatively less research has focused on gene expression changes within the brain in temperate grouper species with non-haremic social structures. The purpose of the present study was to investigate gonadotropin releasing hormone (GnRH) and brain aromatase (cyp19a1b) gene expression patterns during reproductive development and sex change in protogynous (female to male) black sea bass (Centropristis striata). Partial cDNA fragments for cyp19a1b and eef1a (a reference gene) were identified, and included with known gnrh2 and gnrh3 sequences in real time quantitative PCR. Elevated cyp19a1b expression was evident in the olfactory bulbs, telencephalon, optic tectum, and hypothalamus/
midbrain region during vitellogenic growth, which may indicate changes in the brain related to neurogenesis or sexual behavior. In contrast, gnrh2 and gnrh3 expression levels were largely similar among gonadal states, and all three genes exhibited stable expression during sex change. Although sex change in black sea bass is not associated with dramatic changes in GnRH or cyp19a1b gene expression among brain regions, these genes may mediate processes at other levels, such as within individual hypothalamic nuclei, or through changes in neuron size, that warrant further research.

Evaluation for roles of neurosteroids in modulating forebrain mechanisms controlling vasopressin secretion and related phenomena in conscious rats

Ken’ichi Yamaguchi
Neuroscience Research xxx (2015) xxx–xxx
http://dx.doi.org/10.1016/j.neures.2015.01.002

Anteroventral third ventricular region (AV3V) regulates autonomic functions through a GABAergic mechanism that possesses neuroactive steroid (NS)-synthesizing ability. Although NS can exert effects by acting on a certain type of GABAA-receptor (R), it is not clear whether NS may operate to modulateAV3V GABAergic activity for controlling autonomic functions. This study aimed to investigate the issue.AV3V infusion with a GABAA antagonist bicuculline increased plasma vasopressin (AVP), glucose, blood pressure (BP), and heart rate in rats. These events were abolished by preinjecting its agonist muscimol, whereas the infusion with allopregnanolone, a NS capable of potentiating GABAA-R function, affectednone of the variables in the absence or presence of such bicuculline actions. Similarly, AV3V infusion with pregnanolone sulfate, a NS capable of antagonizing GABAA-R, produced no effect on those variables.AV3V infusion with muscimol was effective in inhibiting the responses of plasma AVP or glucose, orBP to an osmotic loading or bleeding. However, AV3V infusion with aminoglutethimide, a NS synthesis inhibitor, did not affect any of the variables in the absence or presence of those stimuli. These results suggest that NS may not cause acute effects on the AV3V GABAergic mechanism involved in regulating AVP release and other autonomic function.

Novel receptor targets for production and action of allopregnanolone in the central nervous system: a focus on pregnane xenobiotic receptor

Cheryl A. Frye, Carolyn J. Koonce, and Alicia A. Walf
Front in Cell Neurosci Apr 2014; 8(106)
http://dx.doi.org:/10.3389/fncel.2014.00106

Neurosteroids are cholesterol-based hormones that can be produced in the brain, independent of secretion from peripheral endocrine glands, such as the gonads and adrenals. A focus in our laboratory for over 25 years has been how production of the pregnane neurosteroid, allopregnanolone, is regulated and the novel (i.e., non steroid receptor) targets for steroid action for behavior. One endpoint of interest has been lordosis, the mating posture of female rodents. Allopregnanolone is necessary and sufficient for lordosis, and the brain circuitry underlying it, such as actions in the midbrain ventral tegmental area (VTA), has been well-characterized. Published and recent findings supporting a dynamic role of allopregnanolone are included in this review. First, contributions of ovarian and adrenal sources of precursors of allopregnanolone, and the requisite enzymatic actions for de novo production in the central nervous system will be discussed.
Second, how allopregnanolone produced in the brain has actions on behavioral processes that are independent of binding to steroid receptors, but instead involve rapid modulatory actions via neurotransmitter targets (e.g., g-amino butyric acid-GABA, Nmethyl-D-aspartate- NMDA) will be reviewed.
Third, a recent focus on characterizing the role of a promiscuous nuclear receptor, pregnane xenobiotic receptor (PXR), involved in cholesterol metabolism and expressed in the VTA, as a target for allopregnanolone and how this relates to both actions and production of allopregnanolone will be addressed. For example, allopregnanolone can bind PXR and knocking down expression of PXR in the midbrain VTA attenuates actions of allopregnanolone via NMDA and/or GABAA for lordosis. Our understanding of allopregnanolone’s actions in the VTA for lordosis has been extended to reveal the role of allopregnanolone for broader, clinically-relevant questions, such as neurodevelopmental processes, neuropsychiatric disorders, epilepsy, and aging.

Long-term dysregulation of brain corticotrophin and glucocorticoid receptors and stress reactivity by single early-life pain experience in male and female rats

Nicole C. Victoria, Kiyoshi Inoue, Larry J. Young, Anne Z. Murphy
Psychoneuroendocrinology (2013) 38, 3015—3028
http://dx.doi.org/10.1016/j.psyneuen.2013.08.013

Inflammatory pain experienced on the day of birth (postnatal day 0: PD0) significantly dampens behavioral responses to stress- and anxiety-provoking stimuli in adult rats. However, to date, the mechanisms by which early life pain permanently alters adult stress responses remain unknown. The present studies examined the impact of inflammatory pain, experienced on the day of birth, on adult expression of receptors or proteins implicated in the activation and termination of the stress response, including corticotrophin releasing factor receptors (CRFR1 and CRFR2) and glucocorticoid receptor (GR). Using competitive receptor autoradiography, we show that Sprague Dawley male and female rat pups administered 1% carrageenan into the intraplantar surface of the hindpaw on the day of birth have significantly decreased CRFR1 binding in the basolateral amygdala and midbrain periaqueductal gray in adulthood. In contrast, CRFR2 binding, which is associated with stress termination, was significantly increased in the lateral septum and cortical amygdala. GR expression, measured with in situ hybridization and immunohistochemistry, was significantly increased in the paraventricular nucleus of the hypothalamus and significantly decreased in the hippocampus of neonatally injured adults. In parallel, acute stress-induced corticosterone release was significantly attenuated and returned to baseline more rapidly in adults injured on PD0 in comparison to controls. Collectively, these data show that early life pain alters neural circuits that regulate responses to and neuroendocrine recovery from stress, and suggest that pain experienced by infants in the Neonatal Intensive Care Unit may permanently alter future responses to anxiety- and stress provoking stimuli.

Dysruption of Corticotropin Releasing Factor in hypocampal region

Stress and trauma: BDNF control of dendritic-spine formation and regression

M.R. Bennett, J. Lagopoulos
Progress in Neurobiology 112 (2014) 80–99
http://dx.doi.org/10.1016/j.pneurobio.2013.10.005

Chronic restraint stress leads to increases in brain derived neurotrophic factor (BDNF) mRNA and protein in some regions of the brain, e.g. the basal lateral amygdala (BLA) but decreases in other regions such as the CA3 region of the hippocampus and dendritic spine density increases or decreases in line with these changes in BDNF. Given the powerful influence that BDNF has on dendritic spine growth, these observations suggest that the fundamental reason for the direction and extent of changes in dendritic spine density in a particular region of the brain under stress is due to the changes in BDNF there.
The most likely cause of these changes is provided by the stress initiated release of steroids, which readily enter neurons and alter gene expression, for example that of BDNF. Of particular interest is how glucocorticoids and mineralocorticoids tend to have opposite effects on BDNF gene expression offering the possibility that differences in the distribution of their receptors and of their downstream effects might provide a basis for the differential transcription of the BDNF genes. Alternatively, differences in the extent of methylation and acetylation in the epigenetic control of BDNF transcription are possible in different parts of the brain following stress.
Although present evidence points to changes in BDNF transcription being the major causal agent for the changes in spine density in different parts of the brain following stress, steroids have significant effects on downstream pathways from the TrkB receptor once it is acted upon by BDNF, including those that modulate the density of dendritic spines.
Finally, although glucocorticoids play a canonical role in determining BDNF modulation of dendritic spines, recent studies have shown a role for corticotrophin releasing factor (CRF) in this regard. There is considerable improvement in the extent of changes in spine size and density in rodents with forebrain specific knockout of CRF receptor 1 (CRFR1) even when the glucocorticoid pathways are left intact. It seems then that CRF does have a role to play in determining BDNF control of dendritic spines.

Central CRF system perturbation in an Alzheimer’s disease knockin mouse model

Qinxi Guo, Hui Zheng, Nicholas John Justice
Neurobiology of Aging 33 (2012) 2678–2691
http://dx.doi.org:/10.1016/j.neurobiolaging.2012.01.002

Alzheimer’s disease (AD) is often accompanied by changes in mood as well as increases in circulating cortisol levels, suggesting that regulation of the stress responsive hypothalamic-pituitary-adrenal (HPA) axis is disturbed. Here, we show that amyloid precursor protein (APP) is endogenously expressed in important limbic, hypothalamic, and midbrain nuclei that regulate hypothalamic-pituitary-adrenal axis activity. Furthermore, in a knockin mouse model of AD that expresses familial AD (FAD) mutations of both APP with humanized amyloid beta (hA), and presenilin 1 (PS1), in their endogenous patterns (APP/hA/PS1 animals), corticotropin releasing factor (CRF) levels are increased in key stress-related nuclei, resting corticosteroid levels are elevated, and animals display increased anxiety-related behavior. Endocrine and behavioral phenotypes can be normalized by loss of 1 copy of CRF receptor type-1 (Crfr1), consistent with a perturbation of central CRF signaling in APP/hA/PS1 animals. However, reductions in anxiety and corticosteroid levels conferred by heterozygosity of CRF receptor type-1 do not improve a deficit in working memory observed in APP/hA/PS1 mice, suggesting that perturbations of the CRF system are not the primary cause of decreased cognitive performance.

Alzheimer’s disease-like neuropathology of gene-targeted APP-SLxPS1mut mice expressing the amyloid precursor protein at endogenous levels

Christoph Kohler, Ulrich Ebert, Karlheinz Baumann, and Hannsjorg Schroeder
Neurobiology of Disease 20 (2005) 528 – 540
http://dx.doi.org:/10.1016/j.nbd.2005.04.009

Most transgenic mice used for preclinical evaluation of potential disease-modifying treatments of Alzheimer’s disease develop major histopathological features of this disease by several-fold overexpression of the human amyloid precursor protein. We studied the phenotype of three different strains of gene-targeted mice which express the amyloid precursor protein at endogenous levels. Only further crossing with transgenic mice overexpressing mutant human presenilin1 led to the deposition of extracellular amyloid, accompanied by the deposition of apolipoprotein E, an astrocyte and microglia reaction, and the occurrence of dilated cholinergic terminals in the cortex. Features of neurodegeneration, however, were absent. The pattern of plaque development and deposition in these mice was similar to that of amyloid precursor protein overproducing strains if crossed to presenilin1-transgenics. However, plaque development started much later and developed slowly until the age of 18 months but then increased more rapidly.

Central Cholinergic Functions In Human Amyloid Precursor Protein Knock-In/Presenilin-1 Transgenic Mice

Hartmann, C. Erb, U. Ebert, K. H. Baumann, A. Popp, G. Koenig, J. Klein
Neuroscience 125 (2004) 1009–1017
http://dx.doi.org:/10.1016/j.neuroscience.2004.02.038

Alzheimer’s disease is characterized by amyloid peptide formation and deposition, neurofibrillary tangles, central cholinergic dysfunction, and dementia; however, the relationship between these parameters is not well understood. We studied the effect of amyloid peptide formation and deposition on central cholinergic function in knock-in mice carrying the human amyloid precursor protein (APP) gene with the Swedish/London double mutation (APP-SL mice) which were crossbred with transgenic mice overexpressing normal (PS1wt) or mutated (M146L; PS1mut) human presenilin-1. APP-SLxPS1mut mice had increased levels of Aβ peptides at 10 months of age and amyloid plaques at 14 months of age while APP-SLPS1wt mice did not have increased peptide levels and did not develop amyloid plaques. We used microdialysis in 15–27 months old mice to compare hippocampal acetylcholine (ACh) levels in the two mouse lines and found that extracellular ACh levels were slightly but significantly reduced in the APP-SLPS1mut mice (-26%; P=0.044). Exploratory activity in the open field increased hippocampal ACh release by two-fold in both mouse lines; total and relative increases were not significantly different for the two strains under study. Similarly, infusion of scopolamine (1 µM) increased hippocampal ACh release to a similar extent (3–5-fold) in both groups. High-affinity choline uptake, a measure of the ACh turnover rate, was identical in both mouse lines. Neurons expressing choline acetyltransferase were increased in the septum of APP-SLPS1mut mice (26%; P =0.046). We conclude that amyloid peptide production causes a small decrease of extracellular ACh levels. The deposition of amyloid plaques, however, does not impair stimulated ACh release and proceeds without major changes of central cholinergic function.

Glutamate Neurotoxicity

Glutamate Neurotoxicity and Diseases of the Nervous System

Dennis W. Choi
Neuron. Oct, 1988; 1: 623-634

A growing number of studies now suggest that the cellular mechanisms which normally participate in signaling in the central nervous system (CNS) can be transformed by disease into instruments of neuronal cell destruction. Excitatory synaptic transmission in the mammalian CNS is principally mediated by L-glutamate. In fact, glutamate excites virtually all central neurons and is present in nerve terminals at millimolar levels (Curtis and Johnston, 1974). Normally, the extracellular levels of glutamate rise to high levels only in the brief and spatially localized fashion appropriate to synaptic transmission. This is fortunate, because as Lucas and Newhouse first showed in 1957, sustained exposure to glutamate can destroy retinal neurons. In a subsequent set of pioneering experiments, Olney (Olney and Sharpe, 1969; Olney et al., 1971) established that this toxicity, which he later called excitotoxicity, was not unique to glutamate or to retinal neurons, but was a feature common to the actions of all excitatory amino acids on central neurons. He postulated therefore that glutamate, or related compounds, might be the cause of the neuronal cell loss found in certain neurological diseases. In recent years, this hypothesis has gathered considerable support, fueled by new insights into glutamate receptor function and the development of effective glutamate antagonist drugs. The evidence is most convincing in diseases involving an acute insult to the brain, as occurs in a stroke, with abrupt deprivation of blood supply. But neurotoxicity due to excitatory amino acids may also be involved in slowly progressive degenerative diseases such as Huntington’s disease. Although the detailed molecular basis of glutamate neurotoxicity is not known, it appears that Ca2+ influx may play a critical role.
Glutamate interacts with at least three classes of membrane receptors, each commonly referred to by preferred pharmacological agonists: N-methyl-o-aspartate (NMDA), quisqualate, and kainate (Watkins and Olverman, 1987) (Figure I). These three classes are linked to membrane cation channels. A second type of quisqualate receptor has been additionally linked to a second messenger system (see below). It has been suggested that all three classes might actually be substates of a single molecular complex, but binding studies and newer physiological studies favor separate structures.

Quisqualate                         NMDA                       Kainate

Three Classes of Glutamate Receptors

Three Classes of Glutamate Receptors

Three Classes of Glutamate Receptors

One type of quisqualate receptor stimulates the formation of inositol 1,4,5-trisphosphate UPS) and diacylglycerol (DAG) from phosphatidylinositol-4,5-biphosphate (PIP,); the other is linked directly to a Na+ ionophore. Activation of the quisqualate receptor-ionophore complex can be potentiated by Zn2+. The NMDA receptor opens a channel permeable to Ca2+ as well as Na+; this receptor-channel complex has several modulatory sites discussed in the text. The kainate receptor opens an ionophore permeable to Na+.

Best defined is the NMDA receptor. This receptor opens a distinctive membrane channel characterized by high conductance (main state about 50 pS), voltage dependent Mgz+ blockade and permeability to both Ca2+ and Na+. The NMDA receptor can be selectively activated by several endogenous compounds, including L-aspartate, homocysteate, and quinolinate. Activation requires the coavailability of glycine in near micromolar concentrations. The action of glutamate at the NMDA receptor can be selectively antagonized: competitively by 2-amino-5-phosphonovalerate (APV) and 2-amino-5-phosphonoheptanoate (APH), or noncompetitively by drugs that bind to the phencyclidine site within the open channel (such as phencyclidine, MK-801, dextrorphan, or ketamine. The NMDA receptor-activated channel can also be blocked noncompetitively by Znz+, most likely at a site different from that which binds Mg2.
Although glutamate has high affinity for all three classes of postsynaptic receptors, it is not easy to demonstrate its neurotoxicity in vivo. Even when directly injected into brain, bypassing the blood-brain barrier, extremely high doses of glutamate are required to create lesions.  Mangano & Schwartz found that they could infuse 0.5 crl/hr of a 300 mM glutamate solution into the hippocampus of a rat for 2 weeks without producing neuronal injury. This apparent low in vivo neurotoxic potency of glutamate may represent one reason why Olney’s “glutamate hypothesis” of neurological disease did not initially achieve a more widespread following. However, in fact, glutamate is a potent and rapidly acting neurotoxin; its neurotoxicity in vivo is likely masked by the efficiency of normal cellular uptake mechanisms in removing glutamate from the extracellular space. Glutamate neurotoxicity can be most directly studied in cell culture where bath exposure is not limited by cellular uptake.
The toxic changes produced by glutamate or related excitatory amino acids in vivo are of two sorts:

  1. acute swelling of neuronal dendrites and cell bodies and a
  2. more slowly evolving neuronal degeneration (Olney, 1986).

Axons and glia are relatively spared, although high levels of excitatory amino acids can produce some swelling of glia. A hallmark of excitatory amino acid neurotoxicity is its cellular selectivity, with distinctive patterns of neuronal loss produced by different excitatory amino acids and different routes of administration. For example, Nadler and co-workers (1978) found that intraventricular kainate preferentially destroys hippocampal CA3 neurons but spares dentate granule neurons. Different neuronal subpopulations
may differ in their intrinsic vulnerability to damage.

Possible Mechanisms Involved in Glutamate Neurotoxicity

How Ca*+ may mediate glutamate-induced neuronal degeneration. Glutamate acts on NMDA, non-NMDA, and “metabotropic” receptors (the quisqualate receptor linked to a second messenger system) to produce an increase in cytosolic free Ca*+. This cytosolic Ca *+, in concert with diacylglycerol liberated by the quisqualate-triggered second messenger system, activates protein kinase C, which acts via a number of mechanisms (primarily by altering membrane ion channels) to increase neuronal excitability and further increase cytosolic Ca*+. Elevated cytosolic Ca2+ then activates several enzymes capable of either directly or indirectly (through free radical formation) destroying cellular structure. Glutamate released from synaptic terminals or leaking nonspecifically from ruptured neurons contributes to additional injury propagation.

Glutamate Neurotoxicity in Perspective

The hypothesis that excitatory amino acids may specifically mediate pathological neuronal injury gives new form to this age-old enemy and raises the tantalizing possibility that current molecular and cellular insights into excitatory amino acid transmitter systems might be harnessed to develop an efficacious clinical therapy. Some points of attack are already apparent; others will likely be defined as the biology of excitatory amino acids continues to be unraveled. An intriguing area for investigation is the relationship between excitatory amino acid neurotoxicity and normal neuronal processes such as maturation, neurite outgrowth, and synaptic plasticity.

Glutamate Toxicity in a Neuronal Cell line Involves Inhibition of Cystine Transport Leading to Oxidative Stress

Timothy H. Murphy, M Miyamoto, A Sastre, R Schnaar and JT Coyle
Neuron 1989: 2: 1547-88.

Glutamate binds to both excitatory neurotransmitter binding sites and a W-dependent, quisqualate- and cystine-inhibited transport site on brain neurons. The neuroblastoma-primary retina hybrid cells (NWRE-105) are susceptible to glutamate-induced cytotoxicity. The Cl–dependent transport site to which glutamate and quisqualate (but not kainate or NMDA) bind has a higher affinity for cystine than for glutamate. Towering cystine concentrations in the cell culture medium results in cytotoxicity similar to that induced by glutamate addition in its morphology, kinetics, and CaZ+ dependence. Glutamate-induced cytotoxicity is directly proportional to its ability to inhibit cystine uptake. Exposure to glutamate (or lowered cystine) causes a decrease in glutathione levels and an accumulation of intracellular peroxides. Like NW-RE-105 cells, primary rat hippocampal neurons (but not glia) in culture degenerate in medium with lowered cystine concentration. Thus, glutamate-induced cytotoxicity in N18-RE-105 cells is due to inhibition of cystine uptake, resulting in lowered glutathione levels leading to oxidative stress and cell death.

Mechanism of glutamate-induced neurotoxicity in HT22 mouse hippocampal cells

Masayuki Fukui, Ji-Hoon Song, Jinyoung Choi, Hye Joung Choi, Bao Ting Zhu
European Journal of Pharmacology 617 (2009) 1–11
http://dx.doi.org:/10.1016/j.ejphar.2009.06.059

Glutamate is an endogenous excitatory neurotransmitter. At high concentrations, it is neurotoxic and contributes to the development of certain neurodegenerative diseases. There is considerable controversy in the literature with regard to whether glutamate-induced cell death in cultured HT22 cells (an immortalized mouse hippocampal cell line) is apoptosis, necrosis, or a new form of cell death. The present study focused on investigating the mechanism of glutamate-induced cell death. We found that glutamate induced, in a time dependent manner, both necrosis and apoptosis in HT22 cells. At relatively early time points (8–12 h), glutamate induced mostly necrosis, whereas at late time points (16–24 h), it induced mainly apoptosis. Glutamate-induced mitochondrial oxidative stress and dysfunction were crucial early events required for the induction of apoptosis through the release of the mitochondrial apoptosis-inducing factor (AIF), which catalyzed DNA fragmentation (an ATP-independent process). Glutamate-induced cell death proceeded independently of the Bcl-2 family proteins and caspase activation. The lack of caspase activation likely resulted from the lack of intracellular ATP when the mitochondrial functions were rapidly disrupted by the mitochondrial oxidative stress. In addition, it was observed that activation of JNK, p38, and ERK signaling molecules was also involved in the induction of apoptosis by glutamate. In conclusion, glutamate-induced apoptosis is AIF-dependent but caspase-independent, and is accompanied by DNA ladder formation but not chromatin condensation.

Understanding Low Reliability of Memories for Neutral Information Encoded under Stress: Alterations in Memory-Related Activation in the Hippocampus and Midbrain

Shaozheng Qin, EJ Hermans, HJF van Marle, and G Fernandez, et al.
The Journal of Neuroscience, Mar 21, 2012; 32(12): 4032–4041
http://dx.doi.org:/10.1523/JNEUROSCI.3101-11.2012

Exposure to an acute stressor can lead to unreliable remembrance of intrinsically neutral information, as exemplified by low reliability of eyewitness memories, which stands in contrast with enhanced memory for the stressful incident itself. Stress-sensitive neuromodulators (e.g., catecholamines) are believed to cause this low reliability by altering neurocognitive processes underlying memory formation. Using event-related functional magnetic resonance imaging, we investigated neural activity during memory formation in 44 young, healthy human participants while incidentally encoding emotionally neutral, complex scenes embedded in either a stressful or neutral context.
We recorded event-related pupil dilation responses as an indirect index of phasic noradrenergic activity. Autonomic, endocrine, and psychological measures were acquired to validate stress manipulation. Acute stress during encoding led to a more liberal response bias (more hits and false alarms) when testing memory for the scenes 24 h later. The strength of this bias correlated negatively with pupil dilation responses and positively with stress-induced heart rate increases at encoding. Acute stress, moreover, reduced subsequent memory effects (SMEs; items later remembered vs forgotten) in hippocampus and midbrain, and in pupil dilation responses.
The diminished SMEs indicate reduced selectivity and specificity in mnemonic processing during memory formation. This is in line with a model in which stress-induced catecholaminergic hyperactivation alters phasic neuromodulatory signaling in memory-related circuits, resulting in generalized (gist-based) processing at the cost of specificity. Thus, one may speculate that loss of specificity may yield less discrete memory representations at time of encoding, thereby causing a more liberal response bias when probing these memories.

Neuroendocrinology – Signaling, neuron plasticity and memory

Leptin Signaling Modulates the Activity of Urocortin 1 Neurons in the Mouse Nonpreganglionic Edinger-Westphal Nucleus

Lu Xu, Wim J. J. M. Scheenen, Rebecca L. Leshan, Christa M. Patterson, et al.
Endocrinology 152(3): 979–988, 2011
http://dx.doi.org:/10.1210/en.2010-1143

A recent study systematically characterized the distribution of the long form of the leptin receptor (LepRb) in the mouse brain and showed substantial LepRb mRNA expression in the nonpreganglionic Edinger-Westphal nucleus (npEW) in the rostroventral part of the midbrain. This nucleus hosts the majority of urocortin 1 (Ucn1) neurons in the rodent brain, and because Ucn1 is a potent satiety hormone and electrical lesioning of the npEW strongly decreases food intake, we have hypothesized a role of npEW-Ucn1 neurons in leptin-controlled food intake. Here, we show by immunohistochemistry that npEW-Ucn1 neurons in the mouse contain LepRb and respond to leptin administration with induction of the Janus kinase 2-signal transducer and activator of transcription 3 pathway, both in vivo and in vitro. Furthermore, systemic leptin administration increases the Ucn1 content of then pEW significantly, whereas in mice that lack LepRb (db/db mice), then pEW contains considerably reduced amount of Ucn1. Finally, we reveal by patch clamping of midbrain Ucn1 neurons that leptin administration reduces the electrical firing activity of the Ucn1 neurons. In conclusion, we provide ample evidence for leptin actions that go beyond leptin’s well-known targets in the hypothalamus and propose that leptin can directly influence the activity of the midbrain Ucn1 neurons.

Leptin regulation of hippocampal synaptic function in health and disease

Andrew J. Irving and Jenni Harvey
Trans. R. Soc. B 369: 20130155 http://dx.doi.org/10.1098/rstb.2013.0155

The endocrine hormone leptin plays a key role in regulating food intake and body weight via its actions in the hypothalamus. However, leptin receptors are highly expressed in many extra-hypothalamic brain regions and evidence is growing that leptin influences many central processes including cognition. Indeed, recent studies indicate that leptin is a potential cognitive enhancer as it markedly facilitates the cellular events underlying hippocampal-dependent learning and memory, including effects on glutamate receptor trafficking, neuronal morphology and activity-dependent synaptic plasticity. However, the ability of leptin to regulate hippocampal synaptic function markedly declines with age and aberrant leptin function has been linked to neurodegenerative disorders such as Alzheimer’s disease (AD). Here, we review the evidence supporting a cognitive enhancing role for the hormone leptin and discuss the therapeutic potential of using leptin-based agents to treat AD.

The Y2 receptor agonist PYY3–36 increases the behavioral response to novelty and acute dopaminergic drug challenge in mice

Ulrike Stadlbauer, Elisabeth Weber, Wolfgang Langhans and Urs Meyer
International Journal of Neuropsychopharmacology (2014), 17, 407–419
http://dx.doi.org:/10.1017/S1461145713001223

The gastrointestinal hormone PYY3–36 is a preferential Y2 neuropeptide Y (NPY) receptor agonist. Recent evidence indicates that PYY3–36 acts on central dopaminergic pathways, but its influence on dopamine-dependent behaviors remains largely unknown. We therefore explored the effects of peripheral PYY3–36 treatment on the behavioral responses to novelty and to dopamine-activating drugs in mice. In addition, we examined whether PYY3–36 administration may activate distinct dopamine and γ-aminobutyric acid (GABA) cell populations in the mesoaccumbal and nigrostriatal pathways. We found that i.p. PYY3–36 injection led to a dose-dependent increase in novel object exploration. The effective dose of PYY3–36 (1 μg/100 g body weight) also potentiated the locomotor reaction to the indirect dopamine receptor agonist amphetamine and increased stereotyped climbing/leaning responses following administration of the direct dopamine receptor agonist apomorphine. PYY3–36 administration did not affect activity of midbrain dopaminergic cells as evaluated by double immuno-enzyme staining of the neuronal early gene product c-Fos with tyrosine hydroxylase. PYY3–36 did, however, lead to a marked increase in the number of cells co-expressing c-Fos with glutamic acid decarboxylase in the nucleus accumbens and caudate putamen, indicating activation of GABAergic cells in dorsal and ventral striatal areas. Our results support the hypothesis that acute administration of the preferential Y2 receptor agonist PYY3–36 modulates dopamine-dependent behaviours. These effects do not seem to involve direct activation of midbrain dopamine cells but instead are associated with neuronal activation in the major input areas of the mesoaccumbal and nigrostriatal pathways.

Somatostatin and nociceptin inhibit neurons in the central nucleus of amygdala that project to the periaqueductal grey

Billy Chieng, MacDonald J. Christie
Neuropharmacology 59 (2010) 425e430
http://dx.doi.org:/10.1016/j.neuropharm.2010.06.001

The central nucleus of amygdala (CeA) plays an important role in modulation of the descending antinociceptive pathways. Using whole-cell patch clamp recordings from brain slices, we found that CeA neurons responded to the endogenous ligands somatostatin (SST) and nociceptin/orphanin FQ (OFQ) via an increased K-conductance. Co-application with selective antagonists suggested that SST and OFQ act on SSTR2 and ORL1 receptors, respectively. Taking account of anatomical localisation of recorded neurons, the present study showed that many responsive neurons were located within the medial subdivision of CeA and all CeA projection neurons to the midbrain periaqueductal grey invariably responded to these peptides. Randomly selected agonist-responsive neurons in CeA predominantly classified physiologically as low-threshold spiking neurons. The similarity of SST, OFQ and, as previously reported, opioid responsiveness in a sub-population of CeA neurons suggests converging roles of these peptides to inhibit the activity of projections from CeA to vlPAG, and potentially similar antinociceptive actions in this pathway.

In vitro identification and electrophysiological characterization of dopamine neurons in the ventral tegmental area

Tao A. Zhang, Andon N. Placzek, John A. Dani
Neuropharmacology 59 (2010) 431e436
http://dx.doi.org:/10.1016/j.neuropharm.2010.06.004

Dopamine (DA) neurons in the ventral tegmental area (VTA) have been implicated in brain mechanisms related to motivation, reward, and drug addiction. Successful identification of these neurons in vitro has historically depended upon the expression of a hyperpolarization-activated current (Ih) and immunohistochemical demonstration of the presence of tyrosine hydroxylase (TH), the rate-limiting enzyme for DA synthesis. Recent findings suggest that electrophysiological criteria may be insufficient for distinguishing DA neurons from non-DA neurons in the VTA. In this study, we sought to determine factors that could potentially account for the apparent discrepancies in the literature regarding DA neuron identification in the rodent brain slice preparation. We found that confirmed DA neurons from the lateral VTA generally displayed a larger amplitude Ih relative to DA neurons located in the medial VTA. Measurement of a large amplitude Ih (>100 pA) consistently indicated a dopaminergic phenotype, but non-dopamine neurons also can have Ih current. The data also showed that immunohistochemical TH labeling of DA neurons can render false negative results after relatively long duration (>15 min) wholecell patch clamp recordings. We conclude that whole-cell patch clamp recording in combination with immunohistochemical detection of TH expression can guarantee positive but not negative DA identification in the VTA.

Dopamine Enables In Vivo Synaptic Plasticity Associated with the Addictive Drug Nicotine

Jianrong Tang and John A. Dani
Neuron, Sept 10, 2009; 63, 673–682
http://dx.doi.org:/10.1016/j.neuron.2009.07.025

Addictive drugs induce a dopamine signal that contributes to the initiation of addiction, and the dopamine signal influences drug-associated memories that perpetuate drug use. The addiction process shares many commonalities with the synaptic plasticity mechanisms normally attributed to learning and memory. Environmental stimuli repeatedly linked to addictive drugs become learned associations, and those stimuli come to elicit memories or sensations that motivate continued drug use. Applying in vivo recording techniques to freely moving mice, we show that physiologically relevant concentrations of the addictive drug nicotine directly cause in vivo hippocampal synaptic potentiation of the kind that underlies learning and memory. The drug-induced long-term synaptic plasticity required a local hippocampal dopamine signal. Disrupting general dopamine signaling prevented the nicotine-induced synaptic plasticity and conditioned place preference. These results suggest that dopaminergic signaling serves as a functional label of salient events by enabling and scaling synaptic plasticity that underlies drug-induced associative memory.

NCS-1 in the Dentate Gyrus Promotes Exploration, Synaptic Plasticity, and Rapid Acquisition of Spatial Memory

Bechara J. Saab, John Georgiou, Arup Nath, Frank J.S. Lee, et al.
Neuron, Sept 10, 2009; 63, 643–656
http://dx.doi.org:/10.1016/j.neuron.2009.08.014

The molecular underpinnings of exploration and its link to learning and memory remain poorly understood. Here we show that inducible, modest overexpression of neuronal calcium sensor 1 (Ncs1) selectively in the adult murine dentate gyrus (DG) promotes a specific form of exploratory behavior. The mice also display a selective facilitation of longterm potentiation (LTP) in the medial perforant path and a selective enhancement in rapid-acquisition spatial memory, phenotypes that are reversed by direct application of a cell-permeant peptide (DNIP) designed to interfere with NCS-1 binding to the dopamine type-2 receptor (D2R). Moreover, the DNIP and the D2R-selective antagonist L-741,626 attenuated exploratory behavior, DG LTP, and spatial memory in control mice. These data demonstrate a role for NCS-1 and D2R in DG plasticity and provide insight for understanding how the DG contributes to the origin of exploration and spatial memory acquisition.

Neuroligin 2 Drives Postsynaptic Assembly at Perisomatic Inhibitory Synapses through Gephyrin and Collybistin

Alexandros Poulopoulos, Gayane Aramuni, Guido Meyer, Tolga Soykan, et al.
Neuron 63, 628–642, Sept 10, 2009
http://dx.doi.org:/10.1016/j.neuron.2009.08.023

In the mammalian CNS, each neuron typically receives thousands of synaptic inputs from diverse classes of neurons. Synaptic transmission to the postsynaptic neuron relies on localized and transmitter-specific differentiation of the plasma membrane with postsynaptic receptor, scaffolding, and adhesion proteins accumulating in precise apposition to presynaptic sites of transmitter release. We identified protein interactions of the synaptic adhesion molecule neuroligin 2 that drive postsynaptic differentiation at inhibitory synapses. Neuroligin 2 binds the scaffolding protein gephyrin through a conserved cytoplasmic motif and functions as a specific activator of collybistin, thus guiding membrane tethering of the inhibitory postsynaptic scaffold. Complexes of neuroligin 2, gephyrin and collybistin are sufficient for cell-autonomous clustering of inhibitory neurotransmitter receptors. Deletion of neuroligin 2 in mice perturbs GABAergic and glycinergic synaptic transmission and leads to a loss of postsynaptic specializations specifically at perisomatic inhibitory synapses.

A Subset of Ventral Tegmental Area Neurons is Inhibited by Dopamine, 5-Hydroxytryptamine and Opioids

L. Cameron, M. W. Wessendorf and J. T. Williams
Neuroscience 1997; 77(1), pp. 155–166 PII: S0306-4522(96)00444-7

Neurons originating in the ventral tegmental area are thought to play a key role in the formation of addictive behaviors, particularly in response to drugs such as cocaine and opioids. In this study we identified different populations of ventral tegmental area neurons by the pharmacology of their evoked synaptic potentials and their response to dopamine, 5-hydroxytryptamine and opioids. Intracellular recordings were made from ventral tegmental area neurons in horizontal slices of guinea-pig brain and electrical stimulation was used to evoke synaptic potentials. The majority of cells (61.3%) hyperpolarized in response to dopamine, depolarized to 5-hydroxytryptamine, failed to respond to [Met]5enkephalin and exhibited a slow GABAB-mediated inhibitory postsynaptic potential. A smaller proportion of cells (11.3%) hyperpolarized in response to [Met]5enkephalin, depolarized to 5-hydroxytryptamine, failed to respond to dopamine and did not exhibit a slow inhibitory postsynaptic potential. These two groups of cells corresponded to previously described ‘‘principal’’ and ‘‘secondary’’ cells, respectively. A further group of cells (27.4%) was identified that, like the principal cells, hyperpolarized to dopamine.

However, these ‘‘tertiary cells’’ also hyperpolarized to both 5-hydroxytryptamine and [Met]5enkephalin and exhibited a slow, cocaine-sensitive 5-hydroxytryptamine1A-mediated inhibitory postsynaptic potential. When principal and tertiary cells were investigated immuno-histochemically, 82% of the principal cells were positive for tyrosine hydroxylase compared
with only 29% of the tertiary cells. The 5-hydroxytryptamine innervation of both these cell types was investigated and a similar density of putative contacts was observed near the somata and dendrites in both groups. This latter finding suggests that the existence of a 5-hydroxytryptamine-mediated inhibitory postsynaptic potential in the tertiary cells may be determined by the selective expression of 5-hydroxytryptamine receptors, rather than the distribution or density of the 5-hydroxytryptamine innervation.
We conclude that tertiary cells are a distinct subset of ventral tegmental area neurons where cocaine and μ-opioids both mediate inhibition.

Dopamine reward circuitry: Two projection systems from the ventral midbrain to the nucleus accumbens–olfactory tubercle complex

Satoshi Ikemoto
Brain Research Reviews 56 (2007) 27–78
http://:dx.doi.org:/10.1016/j.brainresrev.2007.05.004

Anatomical and functional refinements of the meso-limbic dopamine system
of the rat are discussed. Present experiments suggest that dopaminergic neurons localized in the posteromedial ventral tegmental area (VTA) and central linear nucleus raphe selectively project to the ventromedial striatum (medial olfactory tubercle and medial nucleus accumbens shell), whereas
the anteromedial VTA has few if any projections to the ventral striatum,
and the lateral VTA largely projects to the ventrolateral striatum (accumbens
core, lateral shell and lateral tubercle). These findings complement the recent behavioral findings that cocaine and amphetamine are more rewarding when administered into the ventromedial striatum than into the ventrolateral striatum. Drugs such as nicotine and opiates are more rewarding when administered into the posterior VTA or the central linear nucleus than into
the anterior VTA. A review of the literature suggests that
(1) the midbrain has corresponding zones for the accumbens core and medial shell;
(2) the striatal portion of the olfactory tubercle is a ventral extension of the nucleus accumbens shell; and
(3) a model of two dopamine projection systems from the ventral midbrain to the ventral striatum is useful for understanding reward function.
The medial projection system is important in the regulation of arousal characterized by affect and drive and plays a different role in goal directed learning than the lateral projection system, as described in the variation–selection hypothesis of striatal functional organization.

Metabolic hormones, dopamine circuits, and feeding

Nandakumar S. Narayanan, Douglas J. Guarnieri, Ralph J. DiLeone
Frontiers in Neuroendocrinology 31 (2010) 104–112
http://dx.doi.org:/10.1016/j.yfrne.2009.10.004

Recent evidence has emerged demonstrating that metabolic hormones such as ghrelin and leptin can act on ventral tegmental area (VTA) midbrain dopamine neurons to influence feeding. The VTA is the origin of mesolimbic dopamine neurons that project to the nucleus accumbens (NAc) to influence behavior. While blockade of dopamine via systemic antagonists or targeted gene delete can impair food intake, local NAc dopamine manipulations have little effect on food intake. Notably, non-dopaminergic manipulations in the VTA and NAc produce more consistent effects on feeding and food choice. More recent genetic evidence supports a role for the substantia nigra-striatal dopamine pathways in food intake, while the VTA–NAc circuit is more likely involved in higher-order aspects of food acquisition, such as motivation and cue associations. This rich and complex literature should be considered in models of how peripheral hormones influence feeding behavior via action on the midbrain circuits.

Control of brain development and homeostasis by local and systemic insulin signaling

Liu, P. Speder & A. H. Brand
Diabetes, Obesity and Metabolism 16 (Suppl. 1): 16–20, 2014

Insulin and insulin-like growth factors (IGFs) are important regulators of growth and metabolism. In both vertebrates and invertebrates, insulin/IGFs are made available to various organs, including the brain, through two routes: the circulating systemic insulin/IGFs act on distant organs via endocrine signaling, whereas insulin/IGF ligands released by local tissues act in a paracrine or autocrine fashion. Although the mechanisms governing the secretion and action of systemic insulin/IGF have been the focus of extensive investigation, the significance of locally derived insulin/IGF has only more recently come to the fore. Local insulin/IGF signaling is particularly important for the development and homeostasis of the central nervous system, which is insulated from the systemic environment by the blood–brain barrier. Local insulin/IGF signaling from glial cells, the blood–brain barrier and the cerebrospinal fluid has emerged as a potent regulator of neurogenesis. This review will address the main sources of local insulin/IGF and how they affect neurogenesis during development. In addition, we describe how local insulin/IGF signaling couples neural stem cell proliferation with systemic energy state in Drosophila and in mammals.

Pharmacology, Physiology, and Mechanisms of Action of Dipeptidyl Peptidase-4 Inhibitors

Erin E. Mulvihill and Daniel J. Drucker
Endocrine Reviews 35: 992–1019, 2014
http://dx.doi.org/10.1210/er.2014-1035

Dipeptidyl peptidase-4 (DPP4) is a widely expressed enzyme transducing actions through an anchored transmembrane molecule and a soluble circulating protein. Both membrane-associated and soluble DPP4 exert
catalytic activity, cleaving proteins containing a position 2 alanine or proline. DPP4-mediated enzymatic cleavage alternatively inactivates peptides or generates new bioactive moieties that may exert competing or novel activities. The widespread use of selective DPP4 inhibitors for the treatment of type 2 diabetes has heightened interest in the molecular mechanisms through which DPP4 inhibitors exert their pleiotropic actions. Here we review the biology ofDPP4with a focus on:
1) identification of pharmacological vs physiological DPP4 substrates; and
2) elucidation of mechanisms of actions of DPP4 in studies employing genetic elimination or chemical reduction of DPP4 activity.
We review data identifying the roles of key DPP4 substrates in transducing the glucoregulatory, anti-inflammatory, and cardiometabolic actions of DPP4  inhibitors in both preclinical and clinical studies. Finally, we highlight experimental pitfalls and technical challenges encountered in studies designed to understand the mechanisms of action and downstream targets activated by inhibition of DPP4.
Dipeptidyl peptidase-4 (DPP4) is a multifunctional protein that exerts biological activity through pleiotropic actions including:

  • protease activity (1),
  • association with adenosine deaminase (ADA) (2),
  • interaction with the extracellular matrix (3),
  • cell surface coreceptor activity mediating viral entry (4), and
  • regulation of intracellular signal transduction coupled to control of cell migration and proliferation (5).

The complexity of DPP4 action is amplified by the panoply of bioactive DPP4 substrates, which in turn act as elegant biochemical messengers in multiple tissues, including the immune and neuroendocrine systems.

DPP4 transmits signals across cell membranes and interacts with other membrane proteins (Figure). Remarkably, most of the protein is extracellular, including the C-terminal catalytic domain, a cysteine-rich area, and a large glycosylated region linked by a flexible stalk to the transmembrane segment. Only six N-terminal amino acids are predicted to extend into the cytoplasm. The active site, Ser 630, is flanked by the classic serine peptidase motif Gly-Trp-Ser630-Tyr-Gly-Gly-Tyr-Val.

Membrane-bound DPP4

Membrane-bound DPP4

Membrane-bound DPP4 contains residues 1–766, whereas sDPP4 contains residues 39–766. sDPP4 is lacking the cytoplasmic domain [residues 1–6], transmembrane domain [residues 7–28], and the flexible stalk [residues 29–39]. Both membrane-bound and circulating sDPP4 share many domains including the glycosylated region [residues 101–535, specific residues 85,92, 150], ADA binding domain [340–343], fibronectin binding domain [468–479], cysteine-rich domain [351–506, disulfide bonds are formed from 385–394, 444–472, and 649–762], and the catalytic domain [507–766 including residues composing the catalytic active site 630, 708, and 740].

DPP4 activity is subject to regulation at many levels, including control of gene and protein expression, interaction with binding partners, and modulation of enzyme activity. The DPP4 gene does not contain conventional TATAA or CCAAT promoter sequences but is characterized by a cytosine/guanine-rich promoter region.
DPP4 contains eight to 11 potential N-glycosylation sites, which can contribute to its folding and stability. Although glycosylation may contribute approximately 18–25% of the total molecular weight, mutational analysis has determined that the glycosylation sites are not required for dimerization, catalytic activity, or ADA binding. However, N-terminal sialylation facilitates trafficking of DPP4 to the apical membrane. Interestingly, molecular analysis of DPP4 isoforms isolated from the rat kidney brush border membrane reveals extensive heterogeneity in the oligosaccharides of DPP4.DPP4 was first investigated for its role in hydrolysis of dietary prolyl peptides (58); subsequent studies using DPP4 isolated using immunoaffinity chromatography and ADA binding identified DPP4 as the primary enzyme responsible for the generation of Gly-Prop-nitroanilide substrates in human serum. It is now known that DPP4 can cleave dozens of peptides, including chemokines, neuropeptides, and regulatory peptides, most containing a proline or alanine residue at position 2 of the amino-terminal region. Despite the preference for a position 2 proline, alternate residues (hydroxyproline, dehydroproline > alanine >,  glycine, threonine, valine, or leucine) at the penultimate position are also cleaved by DPP4, suggesting a required stereochemistry. The DPP4 cleavage at postproline peptide bonds inactivates peptides and/or generates new bioactive peptides (see Figure), thereby regulating diverse biological processes.

DPP4 cleavage regulates substrate-receptor interactions

DPP4 cleavage regulates substrate-receptor interactions

DPP4 cleavage regulates substrate/receptor interactions. A, DPP4 cleaves NPY [1–36] and PYY [1–36]. The intact forms of these peptides signal through Y1R-Y5R. After DPP4 cleavage, NPY [3–36] and PYY [3–36] are generated and preferentially signal through the Y2R and Y5R. B, DPP4 cleaves SP [1–11], which signals through the NK1R receptor to generate SP [5–11], which can signal through (NK1R, -2R, -3R).

GHRH and IGF-1

GHRH [1–44] and [1–40] are produced in the arcuate nucleus of the hypothalamus and bind its receptor on the anterior pituitary to stimulate the release of GH, and in turn, GH stimulates hepatic IGF-1 release. GHRH was among the first peptides to be identified as a DPP4 substrate; it is rapidly degraded in rodent and human plasma to GHRH [3–44]/GHRH [3–40], and this cleavage was blocked upon incubation of human plasma with the DPP4 inhibitor, diprotin A (99).GHRH[1–44] or [1–40] exhibits a very short half-life (6 min) andDPP4 cleavage was initially perceived to be a critical regulator of GHRH bioactivity and, in turn, the GH-IGF-1 axis. IGF-1, the downstream effector of GHRH and GH, is a 105-amino acid protein produced mainly by the liver.
IGF-1 was identified as a pharmacological DPP4 substrate by matrix-assisted laser desorption/ionization-time of flight analysis of molecular forms of IGF-1 generated after incubation with DPP4 purified from baculovirus-infected insect cells. However, studies in pigs treated with sitagliptin at doses inhibiting 90% of DPP4 activity failed to demonstrate an increase in active intact IGF-1.
Clinically, treatment of healthy human male subjects with sitagliptin (25–600 mg) for 10 days did not produce increased concentrations of serum IGF-1 or IGF-binding protein 3 as measured by ELISA. Furthermore, Dpp4/ mice or rats do not exhibit increased organ growth or body size. Hence, the available data suggest that although DPP4 cleaves and inactivates both GHRH and IGF-1, enzymatic inactivation by DPP4 is not the major mechanism regulating the bioactivity of the GHRH-IGF-1 axis.

The role of acute cortisol and DHEAS in predicting acute and chronic PTSD symptoms

Joanne Mouthaan, Marit Sijbrandij, Jan S.K. Luitse
Psychoneuroendocrinology (2014) 45, 179—186
http://dx.doi.org/10.1016/j.psyneuen.2014.04.001

Background: Decreased activation of the hypothalamus—pituitary—adrenal (HPA) axis in response to stress is suspected to be a vulnerability factor for posttraumatic stress disorder (PTSD). Previous studies showed inconsistent findings regarding the role of cortisol in predicting PTSD. In addition, no prospective studies have examined the role of dehydroepiandrosterone (DHEA), or its sulfate form DHEAS, and the cortisol-to-DHEA(S) ratio in predicting PTSD. In this study, we tested whether acute plasma cortisol, DHEAS and the cortisol-to-DHEAS ratio predicted PTSD symptoms at 6 weeks and 6 months post-trauma. Methods: Blood samples of 397 adult level-1 trauma center patients, taken at the trauma resuscitation room within hours after the injury, were analyzed for cortisol and DHEAS levels. PTSD symptoms were assessed at 6 weeks and 6 months post-trauma with the Clinician Administered PTSD Scale. Results: Multivariate linear regression analyses showed that lower cortisol predicted PTSD symptoms at both 6 weeks and 6 months, controlling for age, gender, time of blood sampling, injury, trauma history, and admission to intensive care. Higher DHEAS and a smaller cortisol-to-DHEAS ratio predicted PTSD symptoms at 6 weeks, but not after controlling for the same variables, and not at 6 months. Conclusions: Our study provides important new evidence on the crucial role of the HPA-axis in response to trauma by showing that acute cortisol and DHEAS levels predict PTSD symptoms in survivors of recent trauma.
Neurobiology of DHEA and effects on sexuality, mood and cognition

  1. Pluchino, P.Drakopoulos, F.Bianchi-Demicheli, J.M.Wenger
    J Steroid Biochem & Molec Biol 145 (2015) 273–280
    http://dx.doi.org/10.1016/j.jsbmb.2014.04.012

Dehydroepiandrosterone (DHEA) and its sulfate ester, DHEAS, are the most abundant steroid hormones in the humans. However, their physiological significance, their mechanisms of action and their possible roles as treatment are not fully clarified. Biological actions of DHEA(S) in the brain involve neuroprotection, neurite growth, neurogenesis and neuronal survival, apoptosis, catecholamine synthesis and secretion, as well as anti-oxidant, anti- inflammatory and antiglucocorticoid effects. In addition, DHEA affects neurosteroidogen is and endorphin synthesis/release. We also demonstrated in a model of ovariectomized rats that DHEA therapy increases proceptive behaviors, already after 1 week of treatment, affecting central function of sexual drive. In women, the analyses of clinical outcomes are far from being conclusive and many issues should still be addressed. Although DHEA preparations have been available in the market since the 1990s, there are very few definitive reports on the biological functions of this steroid. We demonstrate that 1 year DHEA administration at the dose of 10mg provided a significant improvement in comparison with vitamin D in sexual function
and in frequency of sexual intercourse in early postmenopausal women. Among symptomatic women, the spectrum of symptoms responding to DHEA requires further investigation, to define the type of sexual symptoms (e.g. decreased sexual function or hypoactive sexual desire disorder) and the degree of mood/cognitive symptoms that could be responsive to hormonal treatment.
In this regard, our findings are promising, although they need further exploration with a larger and more representative sample size.
Although adrenal cortex is considered to be the primary source of DHEAS in the brain, it was reported that DHEAS did not dis- appear or decrease in the brain 15 days neither after orchiectomy, adrenalectomy, or both, nor after the inhibition of adrenal secretion by dexamethasone. DHEA and DHEAS were among the first neurosteroids identified in rat brains. Cytochrome P450c17 was found in a subset of neurons of embryonic rodent brains. While P450c17 protein was readily detected in the brain, the abundance of P450c17 mRNA transcripts in the embryonic mouse brain or hippocampus of adult male rats was low, and was approximated to be 1/200th of the expression in testis.
DHEAS may be synthesized in the brain from DHEA. Sulfation of DHEA has been observed in the brains of rhesus monkeys in vivo and in human fetal brain slices in vitro. DHEA sulfotransferase (HSTor SULT2A1) is an enzyme that sulfonates DHEA (in addition to pregnenolone).Western blotting and immune-histochemistry showed protein expression of an HST in adult Wistar rat brain. In addition SULT2A1 mRNA expression has been shown in rat brains. DHEAS is predominately transported out of the brain across the blood–brain barrier and DHEAS found in the brain is most likely due to local synthesis . DHEA(S) may mediate some of its actions through conversion into more potent sex steroids and activation of androgen or estrogen receptors in tissue.
According to existing assumption of the biology of depression, DHEA(S) ability to modulate many neurobiological actions could underlie relationships between endogenous and/or exogenously- supplemented DHEA(S) concentrations and depression. There is evidence that DHEAS concentrations are negatively correlated with ratings of depressed mood. However, the remaining literature examining plasma and serum DHEA(S) concentrations in depression is still inconsistent and other plasma indexes were studied in order to more accurately discriminate depressed from nondepressed individuals. Hypothalamic–pituitary–adrenal axis (HPA) hyperactivity has
been demonstrated in chronic diseases affecting nervous system disorders like depression. The end products of HPA axis, glucocorticoids (GCs), regulate many physiological functions and play an important role in affective regulation and dysregulation. Despite DHEAS levels which markedly decrease throughout adulthood, an increase in circulating cortisol with advanced age has been observed in human and nonhuman primates.
The most relevant aspect meriting attention is certainly the controversial finding among the studies that investigate the correlation of the endogenous DHEA sulfate (DHEAS) level, the aging process or organ illness with the results coming from studies focusing on the effects of exogenous DHEAS administration on brain function, sexuality, cardiovascular health and metabolic syndrome. Indeed, the marked age-related decline in serum DHEA and DHEAS has suggested that a deficiency of these steroids may be causally related to the development of a series of diseases that are generally associ- ated with aging. The postulated consequences of low DHEA levels include insulin resistance, obesity, cardiovascular disease, cancer, reduction of the immune defense system as well as psychosocial problems such as depression and a general deterioration in the sensation of well-being and cognitive function, DHEA replacement may seem an attractive treatment opportunity. Nevertheless, the analyses of clinical outcomes are far from being conclusive.

Dehydroepiandrosterone, its metabolites and ion channels

Hill, M. Dusková, L. Stárka
J Steroid Biochem & Molec Biology 145(2015)293–314
http://dx.doi.org/10.1016/j.jsbmb.2014.05.006

This review is focused on the physiological and pathophysiological relevance of steroids influencing the activities of the central and peripheral nervous systems with regard to their concentrations in body fluids and tissues in various stages of human life like the fetal development or pregnancy. The data summarized in this review shows that DHEA and its unconjugated and sulfated metabolites are physiologically and pathophysiologically relevant in modulating numerous ion channels and participate in vital functions of the human organism. DHEA and its unconjugated and sulfated metabolites including 5 _/ _-reduced androstane steroids participate in various physiological and pathophysiological processes like the management of GnRH cyclic release, regulation of glandular and neurotransmitter secretions, maintenance of glucose homeostasis on one hand and insulin insensitivity on the other hand, control of skeletalmuscle and smooth muscle activities including vasoregulation, promotion of tolerance to ischemia and other neuroprotective effects. In respect of prevalence of steroid sulfates over unconjugated steroids in the periphery and the opposite situation in the CNS, the sulfated androgens and androgen metabolites reach relevance in peripheral organs. The unconjugated androgens and estrogens are relevant in periphery and so much the more in the CNS due to higher concentrations of most unconjugated steroids in the CNS tissues than in circulation and peripheral organs.

Neurotrophins are proteins found within a broad range of cell types in the brain and periphery that facilitate neuronal growth, survival, and plasticity. The neurotrophin ‘‘superfamily’’ includes nerve growth factor (NGF), brain-derived neurotrophic factor (BDNF), neurotrophin-3 (NT3), neurotrophin-4/5 (NT4/5), and neurotrophin-6. Target tissues are hypothesized to regulate neuron survival by making neurotrophins available in limited amounts, resulting in selection of neurons with the best connectivity to the target tissue. NGF, in particular, is released by the target tissue and taken up in responsive neurons by receptor-mediated endocytosis. It is then transported retrogradedly into the cell where it exerts trophic effects. Lu et al. proposed a ‘‘Yin and Yang model,’’ whereby neurotrophic action is mediated by two principal classes of transmembrane receptor systems: the tyrosine kinase (Trk) receptors (including TrkA [selective for NGF], TrkB [selective for BDNF and NT4/5], and TrkC [selective for NT3]) and the neurotrophin receptor p75NTR. Each receptor type binds mature neurotrophins and/or neurotrophin precursors (proneurotrophins), creating a complex ‘‘balance’’ that then causes neuronal survival or death.
DHEA has been shown to evoke NGF mRNA expression in target cells. In a study of pregnant women, Schulte-Herbrüggen et al. showed no relationships between serum DHEAS and NGF. In contrast, we showed that DHEAS independently associated with salivary NGF (sNGF) in military men under baseline conditions, while DHEA did not. We now know that both DHEA(S) and NGF respond affirmatively to stressful insult, yet the association between these analytes during stress exposure is not understood. Characterization of this relationship has implications for prevention and treatment of traumatic stress and injury, degenerative disease management, and nerve repair. In this report, we extended our prior study of neuroprotective properties of DHEAS in men under baseline conditions to a prospective paradigm involving intense stress exposure in both men and women. We hypothesized that

(a) robust associations would prevail between total output of DHEAS and sNGF across the stress trajectory and at each time point,
(b) changes in DHEAS would predict corresponding changes in sNGF, and
(c) baseline DHEAS would positively predict total sNGF output across the stress trajectory.
We also explored the roles of testosterone and cortisol. In light of less definitive prior literature, directional hypotheses were not stated regarding these analytes.

In the first regression model, total hormone output (AUCG) of the independent variables (DHEAS, testosterone, and cortisol) combined to explain 63.7% of variance in sNGF output (F = 65.4, p < 0.001). Standardized beta coefficients revealed that testosterone exerted an independent effect (b = 0.80, p < 0.001), while the other predictors were not significant. In light of this unexpected finding, we then used regression-based causal steps modeling to evaluate whether testosterone mediated a hypothesized direct effect of DHEAS on sNGF. Following this approach, DHEAS predicted sNGF in an initial regression model (b = 0.45, p < 0.001). When testosterone was added, the direct effect of DHEAS (path c0) on sNGF was nearly eradicated and no longer significant (b = .04, p = .57), thus suggesting a mediated effect. An alternate statistical test (Sobel Test; 34) evaluating the hypothesized difference between the total effect (path c) and the direct effect (path c0) of DHEAS on sNGF produced a similar result (test statistic = 4.0, p < 0.001). Fig. 1 depicts positive association of DHEAS to sNGF, while Fig. 2 depicts Positive association of testosterone to sNGF.

Positive association of DHEAS total output and sNGF total output

Positive association of DHEAS total output and sNGF total output

Positive association of DHEAS total output and sNGF total output

Positive association of testosterone total output and sNGF total output

Positive association of testosterone total output and sNGF total output

Positive association of testosterone total output and sNGF total output.
The models were then decomposed at each time point. At baseline, the independent variables (DHEAS, testosterone, and cortisol) combined to account for 10.2% of variance in sNGF (F = 5.3, p < 0.01). Standardized beta coefficients showed that DHEAS exerted an independent effect on sNGF (b = 0.39, p < 0.001), while the other predictors were not significant. During stress exposure, the independent variables combined to account for 28.0% of variance in NGF (F = 15.8, p < 0.001). Again, DHEAS exerted an independent effect (b = 0.56, p < 0.001) while the other predictors were not significant. During recovery, the predictor set accounted for 18.0% of variance in sNGF (F = 9.2, p < 0.001), and DHEAS exerted an independent effect (b = 0.47, p < 0.001) while the other predictors did not.
The models were then decomposed relative to each change index. In terms of reactivity, the independent variables (DHEAS, testosterone, and cortisol reactivity) and covariate (sex) combined to account for 20.3% of variance in sNGF reactivity (F = 8.2, p < 0.001). Standardized beta coefficients revealed that DHEAS reactivity exerted an independent effect (b = 0.39, p < 0.001), while the other predictors were not significant. In terms of recovery, the predictors combined to account for 28.2% of variance in sNGF recovery (F = 15.5, p < 0.001); DHEAS recovery exerted an independent effect (b = 0.52, p < 0.001), as did testosterone recovery (b = [1]0.27, p < 0.01). In terms of residual elevation/depression, the independent variables explained 12.4% of variance in sNGF residual elevation (F = 6.2, p < 0.001). DHEAS residual elevation exerted an independent effect (b = 0.35, p < 0.001), while the other predictors did not.

Endocrine-Disrupting Chemicals and Human Growth and Maturation: A Focus on Early Critical Windows of Exposure

Julie Fudvoye, Jean-Pierre Bourguignon, Anne-Simone Parent
Vitamins and Hormones, 2014; 94: Chapt 1. 1-25.
http://dx.doi.org/10.1016/B978-0-12-800095-3.00001-8

Endocrine-disrupting chemicals (EDCs) are exogenous substances that interfere with hormone synthesis, metabolism, or action. In addition, some of them could cause epigenetic alterations of DNA that can be transmitted to the following generations. Because the developing organism is highly dependent on sex steroids and thyroid hormones for its maturation, the fetus and the child are very sensitive to any alteration of their hormonal environment. An additional concern about that early period of life comes from the shaping of the homeostatic mechanisms that takes place also at that time with involvement of epigenetic mechanisms along with the concept of fetal origin of health and disease. In this chapter, we will review the studies reporting effects of EDCs on human development. Using a translational approach, we will review animal studies that can shed light on some mechanisms of action of EDCs on the developing organism. We will focus on the major hormone-dependent stages of development: fetal growth, sexual differentiation, puberty, brain development, and energy balance. We will also discuss the possible epigenetic effects of EDCs on human development.

Several studies have reported that prenatal or early postnatal exposure to some EDCs is associated with alterations of cognitive or motor functions in children. Knowing the fundamental role played by thyroid hormones and sex steroids in cortex development, one can hypothesize that disruption of those hormones could cause alteration of the development of the cerebral cortex and of its functions later in life. We will review here the human data suggesting a causal effect for endocrine disrupters on impairment of cortical functions and approach some EDC mechanisms of action using animal models.

Thyroid hormones are known to be essential for brain development. They regulate progenitor proliferation and differentiation, neuron migration, and dendrite outgrowth (Parent, Naveau, Gerard, Bourguignon, & Westbrook, 2011). Even mild thyroid hormone insufficiency in humans can produce measurable deficits in cognitive functions (Zoeller & Rovet, 2004). Thyroid hormone action is mediated by two classes of nuclear receptors (Forrest & Vennstro¨m, 2000) that exhibit differential spatial and temporal expressions in the brain, suggesting that thyroid hormones have variable functions during brain development. This differential expression of thyroid hormone receptors explains the critical period of thyroid hormone action on brain development as suggested by models of maternal hypothyroidism or congenital hypothyroidism.

Depending on the timing of onset of hypothyroidism, the offspring will display problems of visual attention, gross or fine motor skills, or language and memory skills. Similarly, one can hypothesize that disruption of thyroid function by EDCs will have different effects based on the timing of exposure. However, few studies focused on that aspect. Polychlorinated biphenyls (PCBs) form a group of widespread environmental contaminants composed of 209 different congeners used in a wide variety of applications. Their production was banned in the 1970s but PCBs are still present in the environment due to their high stability. PCBs were among the first EDCs identified as responsible for alterations of cognitive functions. Indeed, impaired memory and altered learning abilities have been associated with prenatal exposure to EDCs in humans and In animal models, perinatal exposure to PCBs has been consistently associated with a decrease of thyroid hormone concentration in maternal serum as well as pup serum. Some but not all epidemiological studies in human have found an association between PCB body burden and thyroid hormone levels. This disruption of thyroid function could explain some of the effects of PCBs on the developing brain. Indeed, animal models have shown that the ototoxic effects of PCBs could be partially ameliorated by thyroxin replacement and PCBs seem to alter some of the developmental processes in the cortex and the cerebellum that are dependent on thyroid hormones. However, recent publications raise important issues.

As it is the case for other EDCs, some windows of susceptibility have been identified during pre- and postnatal brain development. Recent studies have shown that exposure to PBDEs causes alteration of thyroid hormone levels in pregnant women and infants as it is the case in rodents. Only very few studies, however, have focused on the molecular or cellular effects of perinatal exposure to PBDEs in vivo. Viberg et al. have reported a decrease of cholinergic nicotinic receptors in the hippocampus after exposure to BDE-99 and BDE-153. However, the link between such a decrease and the behavioral effects of PBDEs is still unclear. Other teams have reported that exposure to PBDEs reduced hippocampal long term potentiation and decreased brain-derived neurotrophic factor expression in the brain. While several studies have reported negative effect of PBDEs on brain development and cognitive function in animals, there is relatively little information about adverse health effects of PBDEs in humans. Some very recent studies have identified a correlation between prenatal exposure to PBDEs and alteration of cognitive functions.

Endocrine-Disrupting Chemicals: Elucidating Our Understanding of Their Role in Sex and Gender-Relevant End Points

Cheryl A. Frye
Vitamins and Hormones, 2014; 94: 41-98
http://dx.doi.org/10.1016/B978-0-12-800095-3.00003-1

Endocrine-disrupting chemicals (EDCs) are diverse and pervasive and may have significant consequence for health, including reproductive development and expression of sex-/gender-sensitive parameters. This review chapter discusses what is known about common EDCs and their effects on reproductively relevant end points. It is proposed that one way that EDCs may exert such effects is by altering steroid levels (androgens or 17-estradiol, E2) and/or intracellular E2 receptors (ERs) in the hypothalamus and/or hippocampus. Basic research findings that demonstrate developmentally sensitive end points to androgens and E2 are provided. Furthermore, an approach is suggested to examine differences in EDCs that diverge in their actions at ERs to elucidate their role in sex-/gender-sensitive parameters.

Reproductive dysfunction among adults and emotional, attentional, and behavioral disorders among children are on the rise. Sperm counts and fertility have declined in the last 50 years . Incidence of attention-deficit hyperactivity disorder (ADHD) and autism has increased in the last 30 years. These increases in reproductive dysfunction and developmental disorders may be due to increased exposure to environmental contaminants, although there is controversy about the relationship between exposure and these effects.
Many contaminants in the environment, including polychlorinated biphenyls (PCBs), dioxins, and metals, accumulate in exposed individuals and may have adverse consequences due to effects as endocrine-disrupting chemicals (EDCs). EDCs may have effects by altering steroid levels (androgens or 17β-estradiol, E2) and/or intracellular E2 receptors (ERs) in the hypothalamus and/or hippocampus.
Steroid hormones, during critical periods of development, organize sexual dimorphisms in brain and behavior and give rise to sex differences in later responses to steroid hormones. EDCs can profoundly disrupt reproductive responses following adult exposure and result in pervasive effects that extend throughout the life of their offspring. Many nonreproductive behaviors, such
as spatial performance, activity, and arousal, are also sexually dimorphic and organized and activated by steroid hormones. Thus, EDCs may affect reproductive and the aforementioned nonreproductive parameters by altering E2 levels and/or ER binding in the hypothalamus and/or hippocampus.
Results from the literature and preliminary data will be presented that demonstrate our use of a whole-animal model to begin to investigate effects of exposure (in adulthood and/or development) to EDCs on steroid levels (androgens and E2), actions at ERs (in hypothalamus and hippocampus), and reproductive-sensitive measures (anogenital distance, accessory structure weight, onset of puberty and sexual maturity, and reproductive behavior) and nonreproductive behaviors (spatial performance, play behavior, and arousal) throughout development.

A common feature of many environmental contaminants is their estrogenic effects. Some contaminants can alter production of E2 and/or androgens or act as agonists or antagonists for intracellular or membrane ERs. Thus, the term “endocrine-disrupting chemicals” (EDCs) in this chapter is used to refer to contaminants with these effects. An important question considered here is the extent to which EDCs’ actions to alter E2 levels and/or ER binding in the hypothalamus or hippocampus mitigates effects on reproductive or nonreproductive processes. There are potential pervasive, negative effects of endocrine disrupters on steroid sensitive tissues, which may confer risk to disease states, such as cancer, heart disease, and neurodegenerative disorders. The following discussion provides evidence that exposure to EDCs during development may result in permanent, lifelong differences in sexual function and reproductive ability, as well as cognitive function and/or emotional reactivity/arousal. Gonad development, sex determination, and reproductive success of offspring are highly dependent on sex hormone systems. The developing organism is exquisitely sensitive to alterations in hormone function. In the early embryonic state, the gonads of human males and females are morphologically identical. Sexual differentiation begins under hormonal influence during the fifth and sixth weeks of fetal development, and thus, alterations in hormones during this highly sensitive period can have profound consequences. Disruption of the sex steroid system during fetal stages of life results in profound adverse developmental reproductive effects, as is well known from the effects of DES. The balance of estrogens and androgens is critical for normal development, growth, and functioning of the reproductive system. Although especially important during development, this balance is important throughout life for the preservation of normal feminine or masculine traits, as well as the expression of some sexually dimorphic behaviors (sex, spatial performance, and arousal).

Proposed negative effects of exposure to endocrine disrupters during development in people and in animals. The focus here is on vulnerability to sexually dimorphic processes that are estrogen-sensitive, such as reproductive, cognitive, and emotional development and associated behavioral processes

The existing data clearly indicate that developmental exposure to EDCs can adversely affect sexual development of people and animals; however, there are different effects depending upon the EDCs and when in development exposure occurs. Therefore, we consider the next effects of EDCs exposure at different point in development and the consequences for reproductive development and behavior, as well as E2 levels and hypothalamic ER binding.
Steroid hormones also play a critical role in neurodevelopment that influences not only reproductive but also nonreproductive behaviors that show sex differences. Specific behavioral differences in nonreproductive behaviors between males and females include differences in spatial learning, play, exploration, activity levels, novelty-seeking behavior, and emotional reactivity. These sex dimorphisms are thought to reflect adaptive differences for behavioral strategies in coping as a result of sexual selection. Moreover, these sexually dimorphic behaviors may be relevant for concerns regarding increased developmental, cognitive, or emotional disabilities over the past 30 years. Also, behaviors are particularly sensitive measures of effects of EDCs.
EDCs can alter cognitive development. Some, but not all, studies have shown a predictive relationship between prenatal PCB exposure and cognitive development in infancy through preschool years. EDCs have direct effects on nervous system function. Long-term potentiation (LTP), a form of synaptic plasticity used as a model system for study of cognitive potential, is altered by PCBs and lead. The protein kinase C (PKC)-signaling pathway is involved in the modulation of learning, memory, and motor behavior and may be a target of E2’s actions. PCBs also alter PKC signaling. Although findings provide evidence that EDCs can alter cognitive performance, these measures of cognition are neither sexually dimorphic nor E2- or ER-dependent.
There are sex-specific effects of perinatal PCB and dioxin exposure on spatial learning. Yu-Cheng boys that were prenatally exposed to high levels of PCBs and PCDFs when their mothers were accidentally exposed to these contaminants in rice oil show more disrupted cognitive development, mainly spatial function, than did exposed girls. In animal studies, spatial learning that favors males is mediated by perinatal exposure to androgens. Gestational and lactational exposure to ortho-substituted PCBs produces spatial deficits at adolescence in male mice or adulthood in male rats. The sparse data suggest that developmental exposure to EDCs disrupts spatial memory. Furthermore, Exposure during adulthood to EDCs can also have activational effects on spatial memory. Females exposed to a phytoestrogen-rich diet exhibit “masculinized” spatial performance in a radial arm maze, while males fed with a phytoestrogen-free diet show “feminized” performance.
An important question is what are the mechanisms by which developmental and/or adult exposure to EDCs alters spatial performance? There is evidence for sex differences in spatial performance and activational effects of E2 in adulthood to alter spatial performance of rats. Systemic or intrahippocampal administration of E2 improves spatial performance of female rats. Further, E2’s actions at intracellular ERs in the hippocampus of adults do not seem to be required to mediate these effects on spatial performance.
EDCs may have effects on E2 metabolism in a number of ways. First, some EDCs can alter serum lipid concentrations. Cholesterol is the precursor for the production of E2 and other steroid hormones (see Fig. 3.3). Second, there is also evidence that some EDCs can alter metabolism enzymes that are necessary for converting cholesterol to steroid hormones. Induction of CYP occurs when EDCs, such as TCDD, bind the aromatic hydrocarbon receptor (AhR). There is a firm link between PCBs, enzyme induction, and AhR. The binding of EDCs with AhR can result in antiestrogenic activity through increased metabolism and depletion of endogenous E2. Elevated levels of CYP enzymes, primarily expressed not only in the liver but also in the brain and other tissues, result in increased E2 metabolism and excretion. Alternatively, compounds that are metabolized by P450s may result in a net estrogenic effect if they inhibit endogenous estrogens from being metabolized.
Steroid hormones are lipid molecules with limited solubility in plasma and are accordingly carried through the plasma compartment to target cells by specific plasma transporter proteins. Each transporter protein has a specific ligand-binding domain for its associated hormone. It is generally accepted that the “free” formof the steroid hormone, and not the conjugate of the hormone with its plasma transport protein, enters target cells and binds with the appropriate receptor. Receptors for the steroid hormones are proteins located primarily in the cell nucleus or partitioned between the cytoplasm and the nucleus. The unoccupied steroid receptors may reside in the cell as heterodimeric complexes with the 90 kDa heat-shock protein, which prevents the receptor from binding with the DNA until the receptor has first bound with its steroid hormone. Once the hormone binds to the receptor, the hormone receptor complexes with the heterodimeric heat-shock protein and undergoes a conformational change and is activated. The activated receptor binds with DNA at a specific site, initiating gene transcription.

Traditional effects of steroid hormones at their cognate steroid receptors

Traditional effects of steroid hormones at their cognate steroid receptors

Traditional effects of steroid hormones at their cognate steroid receptors, which act as transcription factors. In this example, effects of steroid hormones, such as estradiol, to bind estrogen receptor (ER) subtypes, referred to as ERa and ERb, are shown.

Beyond traditional actions solely through intracellular cognate estrogen receptors (ERs; ERa and ERb), steroids, such as estradiol, and estradiol-mimetics (endocrine disrupters) may have novel actions involving membrane bound ERs, other neurotransmitter systems (e.g., NMDA receptor), and signal transduction cascades (e.g., growth factors, MAPK).

To date, there has been little investigation in a whole-animal model of the effects of EDCs on E2 levels and/or activity at intracellular ERs in the brain. Thus, changes in E2 levels and ER activity in the hypothalamus and hippocampus, concomitant with alterations in endocrine parameters and reproductive behavior and nonreproductive behavior, respectively, are
needed to elucidate tissue specificity of EDCs’ functions and mechanisms.

Low-Dose Effects of Hormones and Endocrine Disruptors

Laura N. Vandenberg
Vitamins and Hormones, 2014; 94: 129-165
http://dx.doi.org/10.1016/B978-0-12-800095-3.00005-5

Endogenous hormones have effects on tissue morphology, cell physiology, and behaviors at low doses. In fact, hormones are known to circulate in the part-per-trillion and part-per-billion concentrations, making them highly effective and potent signaling molecules.

Many endocrine-disrupting chemicals (EDCs) mimic hormones, yet there is strong debate over whether these chemicals can also have effects at low doses. In the 1990s, scientists proposed the “low-dose hypothesis,” which postulated that EDCs affect humans and animals at environmentally relevant doses. This chapter focuses on data that support and refute the low-dose hypothesis. A case study examining the highly controversial example of bisphenol A and its low-dose effects on the prostate is examined through the lens of endocrinology. Finally, the chapter concludes with a discussion of factors that can influence the ability of a study to detect and interpret low-dose effects appropriately.

Since EDCs began to be studied in depth in the 1990s, there has been intense debate over whether the public should be concerned about low level exposures to these chemicals. The low-dose hypothesis, proposed at that time, has steadily accumulated evidence that EDCs have actions at low doses, and these effects are not necessarily predicted from high-dose toxicology testing. In 2002, the NTP expert panel reported evidence for low-dose effects for a small number of EDCs and estradiol. In 2012, an updated approach identified several dozen additional EDCs with evidence for low-dose effects. Further, epidemiology studies continue to find relationships between EDC exposure levels and diseases in the general public, which has raised concerns because the general public is exposed to a large number of environmental chemicals at low doses. For decades, hormones have been known to produce striking changes in tissue morphology, physiology, and behaviors at exceedingly low doses.

A relatively large body of evidence suggests that EDCs, and in particular those environmental chemicals that mimic endogenous hormones, have similar effects at low doses. Although there is still no consensus about the universality of “low-dose effects” in the toxicology community, the Endocrine Society (Diamanti-Kandarakis et al., 2009; Zoeller et al., 2012) believes not only that there is sufficient evidence in support of this phenomenon but also that it is time for public health agencies to make changes to risk assessment paradigms and give greater consideration to studies that specifically identify low-dose effects when considering risks from chemical exposures.

Bisphenol A interferes with synaptic remodeling

Tibor Hajszan, Csaba Leranth
Frontiers in Neuroendocrinology 31 (2010) 519–530
http://dx.doi.org:/10.1016/j.yfrne.2010.06.004

The potential adverse effects of Bisphenol A (BPA), a synthetic xenoestrogen, have long been debated. Although standard toxicology tests have revealed no harmful effects, recent research highlighted what was missed so far: BPA-induced alterations in the nervous system. Since 2004, our laboratory has been investigating one of the central effects of BPA, which is interference with gonadal steroid-induced synaptogenesis and the resulting loss of spine synapses. We have shown in both rats and nonhuman primates that BPA completely negates the ~70–100% increase in the number of hippocampal and prefrontal spine synapses induced by both estrogens and androgens. Synaptic loss of this magnitude may have significant consequences, potentially causing cognitive decline, depression, and schizophrenia, to mention those that our laboratory has shown to be associated with synaptic loss. Finally, we discuss why children may particularly be vulnerable to BPA, which represents future direction of research in our laboratory.

Bisphenol-A rapidly promotes dynamic changes in hippocampal dendritic morphology through estrogen receptor-mediated pathway by concomitant phosphorylation of NMDA receptor subunit NR2B

Xiaohong Xu ⁎, Yinping Ye, Tao Li, Lei Chen, Dong Tian, Qingqing Luo, Mei Lu
Toxicology and Applied Pharmacology 249 (2010) 188–196
http://dx.doi.org:/10.1016/j.taap.2010.09.007

Bisphenol-A (BPA) is known to be a potent endocrine disrupter. Evidence is emerging that estrogen exerts a rapid influence on hippocampal synaptic plasticity and the dendritic spine density, which requires activation of NMDA receptors. In the present study, we investigated the effects of BPA (ranging from 1 to 1000 nM), focusing on the rapid dynamic changes in dendritic filopodia and the expressions of estrogen receptor (ER) β and NMDA receptor, as well as the phosphorylation of NMDA receptor subunit NR2B in the cultured hippocampal neurons. A specific ER antagonist ICI 182,780 was used to examine the potential involvement of ERs. The results demonstrated that exposure to BPA (ranging from 10 to 1000 nM) for 30 min rapidly enhanced the motility and the density of dendritic filopodia in the cultured hippocampal neurons, as well as the phosphorylation of NR2B (pNR2B), though the expressions of NMDA receptor subunits NR1, NR2B, and ERβ were not changed. The antagonist of ERs completely inhibited the BPA-induced increases in the filopodial motility and the number of filopodia extending from dendrites. The increased pNR2B induced by BPA (100 nM) was also completely eliminated. Furthermore, BPA attenuated the effects of 17β-estradiol (17β-E2) on the dendritic filopodia outgrowth and the expression of pNR2B when BPA was co-treated with 17β-E2. The present results suggest that BPA, like 17β-E2, rapidly results in the enhanced motility and density of dendritic filopodia in the cultured hippocampal neurons with the concomitant activation of NMDA receptor subunit NR2B via an ER-mediated signaling pathway. Meanwhile, BPA suppressed the enhancement effects of 17β-E2 when it coexists with 17β-E2. These results provided important evidence suggesting the neurotoxicity of the low levels of BPA during the early postnatal development of the brain.

Bisphenol-A rapidly enhanced passive avoidance memory and phosphorylation of NMDA receptor subunits in hippocampus of young rats

Xiaohong Xu⁎, Tao Li, Qingqing Luo, Xing Hong, Lingdan Xie, Dong Tian
Toxicology and Applied Pharmacology 255 (2011) 221–228
http://dx.doi.org:/10.1016/j.taap.2011.06.022

Bisphenol-A (BPA), an endocrine disruptor, is found to influence development of brain and behaviors in rodents. The previous study indicated that perinatal exposure to BPA impaired learning-memory and inhibited N-methyl-D-aspartate receptor (NMDAR) subunits expressions in hippocampus during the postnatal development in rats; and in cultured hippocampal neurons, BPA rapidly promotes dynamic changes in dendritic morphology through estrogen receptor-mediated pathway by concomitant phosphorylation of NMDAR subunit NR2B. In the present study, we examined the rapid effect of BPA on passive avoidance memory and NMDAR in the developing hippocampus of Sprague–Dawley rats at the age of postnatal day 18. The results showed that BPA or estradiol benzoate (EB) rapidly extended the latency to step down from the platform 1 h after foot shock and increased the phosphorylation levels of NR1, NR2B, and mitogen-activated extracellular signal-regulated kinase (ERK) in hippocampus within 1 h. While 24 h after BPA or EB treatment, the improved memory and the increased phosphorylation levels of NR1, NR2B, ERK disappeared. Furthermore, pre-treatment with an estrogen receptors (ERs) antagonist, ICI182, 780, or an ERK-activating kinase inhibitor, U0126, significantly attenuated EB- or BPA-induced phosphorylations of NR1, NR2B, and ERK within 1 h. These data suggest that BPA rapidly enhanced short-term passive avoidance memory in the developing rats. A non-genomic effect via ERs may mediate the modulation of the phosphorylation of NMDAR subunits NR1 and NR2B through ERK signaling pathway.

Bisphenol A promotes dendritic morphogenesis of hippocampal neurons through estrogen receptor-mediated ERK1/2 signal pathway

Xiaohong Xu, Yang Lu, Guangxia Zhang, Lei Chen, Dong Tian, et al.
Chemosphere 96 (2014) 129–137
http://dx.doi.org/10.1016/j.chemosphere.2013.09.063

Bisphenol A (BPA), an environmental endocrine disruptor, has attracted increasing attention to its adverse effects on brain developmental process. The previous study indicated that BPA rapidly increased motility and density of dendritic filopodia and enhanced the phosphorylation of N-methyl-D-aspartate (NMDA) receptor subunit NR2B in cultured hippocampal neurons within 30 min. The purpose of the present study was further to investigate the effects of BPA for 24 h on dendritic morphogenesis and the underlying mechanisms. After cultured for 5 d in vitro, the hippocampal neurons from 24 h-old rat were infected by AdV-EGFP to indicate time-lapse imaging of living neurons. The results demonstrated that the exposure of the cultured hippocampal neurons to BPA (10, 100 nM) or 17β-estradiol (17β-E2, 10 nM) for 24 h significantly promoted dendritic development, as evidenced by the increased total length of dendrite and the enhanced motility and density of dendritic filopodia. However, these changes were suppressed by an ERs antagonist, ICI182,780, a non-competitive NMDA receptor antagonist, MK-801, and a mitogen activated ERK1/2-activating kinase (MEK1/2) inhibitor, U0126. Meanwhile, the increased F-actin (filamentous actin) induced by BPA (100 nM) was also completely eliminated by these blockers. Furthermore, the result of western blot analyses showed that, the exposure of the cultures to BPA or 17β-E2 for 24 h promoted the expression of Rac1/Cdc42 but inhibited that of RhoA, suggesting Rac1 (Ras related C3 botulinum toxinsubstrate 1)/Cdc42 (cell divisioncycle 42) and RhoA (Ras homologous A), the Rho family of small GTPases, were involved in BPA- or 17β-E2-induced changes in the dendritic morphogenesis of neurons. These BPA- or 17b-E2-induced effects were completely blocked by ICI182,780, and were partially suppressed by U0126. These results reveal that, similar to 17β-E2, BPA exerts its effects on dendritic morphogenesis by eliciting both nuclear actions and extranuclear-initiated actions that are integrated to influence the development of dendrite in hippocampal neurons.

Tyreoliberin (Trh) – The Regulatory Neuropeptide Of Cns Homeostasis
Danuta Jantas
Advances In Cell Biology 2;(4)/2010 (139–154)
http://dx.doi.org:/10.2478/v10052-010-0008-4

The physiological role of thyreoliberin (TRH) is the preservation of homeostasis within four systems
(i) the hypothalamic-hypophsysiotropic neuroendocrine system,
(ii) the brain stem/midbrain/spinal cord system,
(iii) the limbic/cortical system, and
(iv) the chronobiological system.

Thus TRH, via various cellular mechanisms, regulates a wide range of biological processes (arousal, sleep, learning, locomotive activity, mood) and possesses the potential for unique and widespread applications for treatment of human illnesses. Since the therapeutic potential of TRH is limited by its pharmacological profile (enzymatic instability, short half-life, undesirable effects), several synthetic analogues of TRH were constructed and studied in mono- or adjunct therapy of central nervous system (CNS) disturbances. The present article summarizes the current state of understanding of the physiological role of TRH and describes its putative role in clinical indications in CNS maladies with a focus on the action of TRH analogues.

Breakthrough in neuroendocrinology by discovering novel neuropeptides and neurosteroids: 2. Discovery of neurosteroids and pineal neurosteroids

Kazuyoshi Tsutsui, Shogo Haraguchi
General and Comparative Endocrinology 205 (2014) 11–22
http://dx.doi.org/10.1016/j.ygcen.2014.03.008

Bargmann–Scharrer’s discovery of ‘‘neurosecretion’’ in the first half of the 20th century has since matured into the scientific discipline of neuroendocrinology. Identification of novel neurohormones, such as neuropeptides and neurosteroids, is essential for the progress of neuroendocrinology. Our studies over the past two decades have significantly broadened the horizons of this field of research by identifying novel neuropeptides and neurosteroids in vertebrates that have opened new lines of scientific investigation in neuroendocrinology. We have established de novo synthesis and functions of neurosteroids in the brain of various vertebrates. Recently, we discovered 7α-hydroxypregnenolone (7α-OH PREG), a novel bioactive neurosteroid that acts as a key regulator for inducing locomotor behavior by means of the dopaminergic system. We further discovered that the pineal gland, an endocrine organ located close to the brain, is an important site of production of neurosteroids de novo from cholesterol (CHOL). The pineal gland secretes 7α-OH PREG and 3α,5α-tetrahydroprogesterone (3α,5α-THP; allopregnanolone) that are involved in locomotor rhythms and neuronal survival, respectively. Subsequently, we have demonstrated their mode of action and functional significance. This review summarizes the discovery of these novel neurosteroids and its contribution to the progress of neuroendocrinology.

Mechanisms of crosstalk between endocrine systems: Regulation of sex steroid hormone synthesis and action by thyroid hormones

Paula Duarte-Guterman, Laia Navarro-Martín, Vance L. Trudeau
General and Comparative Endocrinology 203 (2014) 69–85
http://dx.doi.org/10.1016/j.ygcen.2014.03.015

Thyroid hormones (THs) are well-known regulators of development and metabolism in vertebrates. There is increasing evidence that THs are also involved in gonadal differentiation and reproductive function. Changes in TH status affect sex ratios in developing fish and frogs and reproduction (e.g., fertility), hormone levels, and gonad morphology in adults of species of different vertebrates. In this review, we have summarized and compared the evidence for cross-talk between the steroid hormone and thyroid axes and present a comparative model. We gave special attention to TH regulation of sex steroid synthesis and action in both the brain and gonad, since these are important for gonad development and brain sexual differentiation and have been studied in many species. We also reviewed research showing that there is a TH system, including receptors and enzymes, in the brains and gonads in developing and adult vertebrates. Our analysis shows that THs influences sex steroid hormone synthesis in vertebrates, ranging from fish to pigs. This concept of crosstalk and conserved hormone interaction has implications for our understanding of the role of THs in reproduction, and how these processes may be dysregulated by environmental endocrine disruptors.

Insights into the structure of class B GPCRs

Kaspar Hollenstein, Chris de Graaf, Andrea Bortolato, Ming-Wei Wang, et al.
Trends in Pharmacological Sciences, Jan 2014; 35(1)
http://dx.doi.org/10.1016/j.tips.2013.11.001

The secretin-like (class B) family of G protein-coupled receptors (GPCRs) are key players in hormonal homeostasis and are interesting drug targets for the treatment of several metabolic disorders (such as type 2 diabetes, osteoporosis, and obesity) and nervous system diseases (such as migraine, anxiety, and depression). The recently solved crystal structures of the transmembrane domains of the human glucagon receptor and human corticotropin-releasing factor receptor 1 have opened up new opportunities to study the structure and function of class B GPCRs. The current review shows how these structures offer more detailed explanations to previous biochemical and pharmacological studies of class B GPCRs, and provides new insights into their interactions with ligands.

Class B G protein-coupled receptors (GPCRs), also referred to as the secretin family of GPCRs, include receptors for 15 peptide hormones, which can be grouped into five subfamilies based on their physiological role (see Table 1 for an overview) [1]. These receptors are important drug targets in many human diseases, including diabetes, osteoporosis, obesity, cancer, neurodegeneration, cardiovascular disease, headache, and psychiatric disorders. However, the identification of small-molecule oral drugs for this family has proved extremely challenging.

(A,B) Crystal structures of the class B G protein-coupled receptors corticotropin-releasing factor receptor 1 (CRF1) [Protein Data Bank (PDB) identifier: 4K5Y] and glucagon receptor (PDB identifier: 4L6R) are shown in blue and orange ribbons, respectively, in two different views from within the membrane. Transmembrane (TM) helices and helix 8 are labelled. The disulfide bond tethering extracellular loop 2 (ECL2) to the tip of TM3 is shown as purple sticks. In CRF1 the small-molecule antagonist CP-376395 is shown in stick representation with carbon, nitrogen, and oxygen atoms colored magenta, blue, and red, respectively, and as skeletal formula in an inset. (C) Superposition of the two structures, with insets highlighting regions of particular interest. To highlight the structural differences in the extracellular halves of CRF1 and glucagon receptor, the distance of approximately 11 A° between the Ca-atoms of residues 7.33b at the N-terminal end of TM7 is indicated with a red arrow. The small molecule binding pocket is shown as a superposition of the two receptors around CP-376395, illustrating the antagonist binding mode and the substantial structural differences observed for TM6 of the two receptors.

  • Overview of NMR and crystal structures of class B G protein-coupled

receptor (GPCR) extracellular domains (ECDs; magenta) and their complexes with peptide ligands (different colors). A complete overview of corresponding Protein Data Bank identifiers is presented in Table 1 (not shown). (B) Structure-based sequence alignment of representative peptide ligands of class B GPCR, adopted from Parthier et al. [6]. The residues of the peptide ligands solved in ECD–ligand complex crystal structures are marked using the same colour as in Figure 2A. The residues that are boxed black are found in an α-helical conformation in the complex. Peptide ligand residues that covalently bind receptors in photo-crosslinking or cysteine-trapping studies are colored and boxed green, whereas peptide ligand residues that have been mutated and studied in combination with receptor mutants are colored and boxed red. Note that the first residue of glucagon-like peptide-1 (GLP-1) is His7. A complete overview of all ECD structures and important peptide ligands for all class B GPCRs is presented in Table 1. Putative helix-capping residues [6] are coloured blue and cysteines involved in a disulfide-bridge (calcitonin) are coloured orange. D-phenylalanine (f), and norleucine (m) residues are indicated in stressin and astressin. The last 41 and 99 residues of parathyroid hormone (PTH) and PTH-related protein.  (PTHrP), respectively, are not displayed. Abbreviations: CGRP, calcitonin gene-related peptide; CLR, calcitonin receptor-like receptor; CRF, corticotropin-releasing factor; CT, calcitonin; Ext-4, exendin-4; GHRHR, growth hormone releasing hormone receptor; GIP, glucose-dependent insulinotropic peptide; PAC, pituitary adenylate cyclase; PACAP, pituitary adenylate cyclase activating polypeptide; RAMP, receptor-activity modifying proteins; SCTR, secretin receptor; Ucn, urocortin; VPAC, vasoactive pituitary adenylate cyclase.

Figure 3. (not shown) (A) The spatial correspondence between residues in transmembrane (TM) helices of class A and class B G protein-coupled receptors (GPCRs) makes it possible to align the most conserved residues in class A (designated X.50, Ballesteros–Weinstein numbering) and class B (designated X.50b, Wootten numbering) for comparisons between GPCR classes (Box 1). (B) Structural alignment of corticotropin-releasing factor receptor 1 (CRF1; blue) and glucagon receptor (GCGR; orange) to two representative class A GPCRs, histamine H1 receptor (H1R; Protein Data Bank identifier: 3RZE) and CXC-chemokine receptor 4 (CXCR4; Protein Data Bank identifier: 3ODU/3OE0) (in grey). Helices are depicted as cylinders, and the ligands glucagon (for GCGR), CP-376395 (for CRF1), doxepin (for H1R), and IT1t and CVX15 (for CXCR4) are shown as sticks. The

location of the Ca-atoms of the most conserved residues of TM1–3 and TM5 among class A and class B GPCRs (Box 1) are indicated by spheres (TM4 is not depicted for clarity).

The GCGR and CRF1 crystal structures show distinct structural features and different binding pockets compared to class A GPCRs, and give new insights into the molecular details of peptide and small-molecule binding to class B GPCRs. The first two crystal structures of the TM domains of class B GPCRs provide a structural framework that will enable the design of biochemical and biophysical experiments detailing the complex structure of this class of receptors, and facilitate the design of stabilized constructs that might lead to the solution of full-length class B GPCR–ligand complexes. The structures furthermore present more reliable structural templates for the design of specific and potent small molecules for the treatment of type 2 diabetes (GCGR) and depression (CRF1) in particular, and open new avenues for structure-based small-molecule drug discovery for class B GPCRs as a whole.

Novel receptor targets for production and action of allopregnanolone in the central nervous system: a focus on pregnane xenobiotic receptor

Cheryl A. Frye, Carolyn J. Koonce and Alicia A. Walf
Front in Cell Neurosci  Apr 2014; 8(106): 1-13.
http://dx.doi.org:/10.3389/fncel.2014.00106

Neurosteroids are cholesterol-based hormones that can be produced in the brain,

independent of secretion from peripheral endocrine glands, such as the gonads and

adrenals. A focus in our laboratory for over 25 years has been how production of the

pregnane neurosteroid, allopregnanolone, is regulated and the novel (i.e., non steroid

receptor) targets for steroid action for behavior. One endpoint of interest has been lordosis, the mating posture of female rodents. Allopregnanolone is necessary and sufficient for lordosis, and the brain circuitry underlying it, such as actions in the midbrain ventral tegmental area (VTA), has been well-characterized. Published and recent findings supporting a dynamic role of allopregnanolone are included in this review.
First, contributions of ovarian and adrenal sources of precursors of allopregnanolone, and the requisite enzymatic actions for de novo production in the central nervous system will be discussed.
Second, how allopregnanolone produced in the brain has actions on behavioral processes that are independent of binding to steroid receptors, but instead involve rapid modulatory actions via neurotransmitter targets (e.g., g-amino butyric acid-GABA, N methyl-D-aspartate- NMDA) will be reviewed.
Third, a recent focus on characterizing the role of a promiscuous nuclear receptor, pregnane xenobiotic receptor (PXR), involved in cholesterol metabolism and expressed in the VTA, as a target for allopregnanolone and how this relates to both actions and production of allopregnanolone will be addressed. For example, allopregnanolone can bind PXR and knocking down expression of PXR in the midbrain VTA attenuates actions of allopregnanolone via NMDA and/or GABAA for lordosis. Our understanding of allopregnanolone’s actions in the VTA for lordosis has been extended to reveal the role of allopregnanolone for broader, clinically-relevant questions, such as neurodevelopmental processes, neuropsychiatric disorders, epilepsy, and aging.

Genetically Encoded Chemical Probes in Cells Reveal the Binding Path of Urocortin-I to CRF Class B GPCR

Irene Coin, Vsevolod Katritch, Tingting Sun, Zheng Xiang, Fai Yiu Siu
Cell  Dec 2013; 155, 1258–1269
http://dx.doi.org/10.1016/j.cell.2013.11.008

Molecular determinants regulating the activation of class B G-protein-coupled receptors (GPCRs) by native peptide agonists are largely unknown. We have investigated here the interaction between the corticotropin releasing factor receptor type 1 (CRF1R) and its native 40-mer peptide ligand Urocortin- I directly in mammalian cells. By incorporating unnatural amino acid photochemical and new click chemical probes into the intact receptor expressed in the native membrane of live cells, 44 intermolecular spatial constraints have been derived for the ligand-receptor interaction. The data were analyzed in the context of the recently resolved crystal structure of
CRF1R transmembrane domain and existing extracellular domain structures, yielding a complete conformational model for the peptide-receptor complex. Structural features of the receptor-ligand complex yield molecular insights
on the mechanism of receptor activation and the basis for discrimination between agonist and antagonist function.

Investigation of GPCR-Ligand Interactions under Native Conditions Using Genetically Encoded Chemical Probes GPCRs are integral membrane proteins containing multiple domains and various posttranslational modifications. To understand GPCR-ligand interactions by crystallography, receptors have to be extracted from the cell membrane and modified with a series of expedients such as deglycosylation, therm-stabilizing mutations, fusions with soluble proteins, or complexes with stabilizing nanobodies. We present here a method to investigate GPCR-ligand interactions at the intact fully posttranslationally modified receptor bound to its WT ligand on the membrane of the live cell, which mimics the native conditions for GPCR function. We first genetically incorporated into the receptor the photocrosslinking Uaa Azi, which served as
a proximity probe to provide an overall map of the ligand binding sites on the receptor. We then determined the relative position of the ligand in the binding pocket using a residue-specific chemical crosslinking reaction between Ffact genetically incorporated into the receptor and Cys introduced into the ligand. The derived intermolecular spatial constraints served eventually to build a detailed conformational model for the receptor-ligand complex.

Glutamate Neurons within the Midbrain Dopamine Regions

  1. Morales and D. H. Root
    Neuroscience 282 (2014) 60–68
    http://dx.doi.org/10.1016/j.neuroscience.2014.05.032

Midbrain dopamine (DA) neurons are hypothesized to play roles in reward-based behavior and addiction, reward prediction and learning by error detection, effort-based decision making, flexible reward-directed behaviors,

incentive salience, stimulus salience (e.g., prediction of rewarding and aversive events), aversion, depression, and fear. The extensive, divergent behavioral roles of midbrain dopamine neurons, predominantly from the ventral tegmental area (VTA), indicate that this system is highly heterogeneous.
This heterogeneity may be reflected in part by the diverse phenotypic characteristics among DAergic neurons and their interactive brain structures.

Midbrain dopamine systems play important roles in Parkinson’s disease, schizophrenia, addiction, and depression. The participation of midbrain dopamine systems in diverse clinical contexts suggests these systems are highly complex. Midbrain dopamine regions contain at least three neuronal phenotypes: dopaminergic, GABAergic, and glutamatergic. Here, we review the locations, subtypes, and functions of glutamatergic neurons within midbrain dopamine regions. Vesicular glutamate transporter 2 (VGluT2) mRNA-expressing neurons are observed within each midbrain dopamine system. Within rat retrorubral field (RRF), large populations of VGluT2 neurons are observed throughout its anteroposterior extent. Within rat substantia nigra pars compacta (SNC), VGluT2 neurons are observed centrally and caudally, and are most dense within the laterodorsal subdivision. RRF and SNC rat VGluT2 neurons lack tyrosine hydroxylase (TH), making them an entirely distinct population of neurons from dopaminergic neurons. The rat ventral tegmental area (VTA) contains the most heterogeneous populations of VGluT2 neurons. VGluT2 neurons are found in each VTA subnucleus but are most dense within the anterior midline subnuclei. Some subpopulations of rat VGluT2 neurons co-express TH or glutamic acid decarboxylase (GAD), but most of the VGluT2 neurons lack TH or GAD. Different subsets of rat VGluT2-TH neurons exist based on the presence or absence of vesicular monoamine transporter 2, dopamine transporter, or D2 dopamine receptor. Thus, the capacity by which VGluT2-TH neurons may release dopamine will differ based on their capacity to accumulate vesicular dopamine, uptake extracellular dopamine, or be autoregulated by dopamine. Rat VTA VGluT2 neurons exhibit intrinsic VTA projections and extrinsic projections to the accumbens and to the prefrontal cortex. Mouse VTA VGluT2 neurons project to accumbens shell, prefrontal cortex, ventral pallidum, amygdala, and lateral habenula. Given their molecular diversity and participation in circuits involved in addiction, we hypothesize that individual VGluT2 subpopulations of neurons play unique roles in addiction and other disorders. This article is part of a Special Issue entitled: Ventral Tegmentum & Dopamine. Published by Elsevier Ltd. On behalf of IBRO.

Read Full Post »


Metabolomic analysis of two leukemia cell lines. II.

Larry H. Bernstein, MD, FCAP, Reviewer and Curator

Leaders in Pharmaceutical Intelligence

 

In Part I of metabolomics of two leukemia cell lines, we have established a major premise for the study, an insight into the use of an experimental model, and some insight into questions raised.

I here return to examine these before pursuing more detail in the study.

Q1. What strong metabolic pathways come into focus in this study?

Answer – The aerobic and anaerobic glycolytic pathways, with a difference measured in the extent of participation of mitochondrial oxidative phosphorylation.

Q2. Would we expect to also gain insight into the effect, on balance, played by a suppressed ubiquitin pathway?

Answer – lets look into this in Part II.

Q3. Would the synthesis of phospholipid and the maintenance of membrane structures requires availability of NADPH, which would be a reversal of the TCA cycle at the cost of delta G in catabolic energy, be consistent with increased dependence of anaerobic glycolysis  with unchecked replication?

Answer: Part II might show this, as the direction and the difference between the cell lines is consistent with a Warburg (Pasteur) effect.

Recall the observation that the model is based on experimental results from  lymphocytic leukemia cell lines in cell culture.  The internal metabolic state is inferred from measurement of external metabolites.

The classification of the lymphocytic leukemias in humans is based on T-cell and B-cell lineages, but actually uses cell differentiation (CD) markers on the cytoskeleton for recognition.  It is only a conjecture that if the cells line were highly anaplastic, they might not be sustainable in cell culture in perpetuity.
The analogue of these cells to what I would expect to see in humans is the SLL having the characteristic marking: CD5, see http://www.pathologyoutlines.com/topic/lymphomaSLL.html

Micro description
=======================================================

● Effacement of nodal architecture by pale staining pseudofollicles or proliferation centers with ill-defined borders, containing small round mature lymphocytes, prolymphocytes (larger than small lymphocytes, abundant basophilic cytoplasm, prominent nucleoli), paraimmunoblasts (larger cells with distinct nucleoli) and many smudge cells
● Pseudofollicular centers are highlighted by decreasing light through the condenser at low power; cells have pale cytoplasm but resemble soccer balls or smudge cells on peripheral smear (cytoplasm is bubbly in mantle cell lymphoma); may have plasmacytoid features
● May have marginal zone, perifollicular or interfollicular patterns, but these cases also have proliferation centers (Mod Pathol 2000;13:1161)
● Interfollicular pattern: large, reactive germinal centers; resembles follicular lymphoma but germinal centers are bcl2 negative and tumor cells resemble SLL by morphology and immunostains
(Am J Clin Path 2000;114:41)
● Paraimmunoblastic variant: diffuse proliferation of paraimmunoblasts (normally just in pseudoproliferation centers); rare, <30 reported cases; usually multiple lymphadenopathies and rapid disease progression; case report in 69 year old man (Hum Pathol 2002;33:1145); consider as mantile cell lymphoma if t(11;14)(q13;q32) is present; may also represent CD5+ diffuse large B cell lymphoma
Bone marrow: small focal aggregates of variable size with irregular, poorly circumscribed outlines; lymphocytes are well differentiated, small, round with minimal atypia; may have foci of transformation; rarely has granulomas (J Clin Pathol 2005;58:815)
● Marrow infiltrative patterns are also described as diffuse (unmutated IgH genes, ZAP-70+, more aggressive), nodular (associated with IgH hypermutation, ZAP-70 negative) or mixed (variable mutation of IgH, variable ZAP-70, Hum Pathol 2006;37:1153)

 

Positive stains
=======================================================

● CD5, CD19, CD20 (dim), CD23, surface Ig light chain, surface IgM (dim)
● Also CD43, CD79a, CD79b (dim in 20%, Arch Pathol Lab Med 2003;127:561), bcl2
● Variable CD11c, FMC7 (42%)
Negative stains
=======================================================

● CD10, cyclin D1
Molecular
=======================================================

● Trisomy 12 (30%, associated with atypical CLL and CD79b), deletion 13q14 (25-50%),
deletion of 11q23 (worse prognosis, 10-20%)

 

Results

We set up a pipeline that could be used to

  • infer intracellular metabolic states from semi-quantitative data
  • regarding metabolites exchanged between cells and their environment.

Our pipeline combined the following four steps:

  1. data acquisition,
  2. data analysis,
  3. metabolic modeling and
  4.  experimental validation of
  • the model predictions (Fig. 1A).

We demonstrated the pipeline and the predictive potential

  • to predict metabolic alternations in diseases such as cancer
  • based on two lymphoblastic leukemia cell lines.

The resulting Molt-4 and CCRF-CEM condition-specific cell line models were able

  • to explain metabolite uptake and secretion
  •  by predicting the distinct utilization of central metabolic pathways by the two cell lines.

Whereas the CCRF-CEM model

  • resembled more a glycolytic, commonly referred to as ‘Warburg’ phenotype,
  • our predictions suggested  a more respiratory phenotype for the Molt-4  model.

We found these predictions to be in agreement with measured gene expression differences

  • at key regulatory steps in the central metabolic pathways, and
  • they were also consistent with  data regarding the energy and redox states of the cells.

After a brief discussion of the data generation and analysis steps, the results

  • derived from model generation and analysis will be described in detail.

 

2.1 Pipeline for generation of condition-specific metabolic cell line models

2.1.1 Generation of experimental data

We monitored the growth and viability of lymphoblastic leukemia cell lines in
serum- free medium (File S2, Fig. S1). Multiple omics  data sets  were derived  from these cells.

Extracellular metabolomics (exo-metabolomic) data,

  • comprising measurements of the metabolites in the spent medium of the cell cultures
    (Paglia et al. 2012a),
  • were collected along with transcriptomic data, and
  • these data sets were used to construct the models.

 

2.1.4 Condition-specific models for CCRF-CEM and Molt-4 cells

To determine whether we had obtained two distinct models,

  • we evaluated the reactions, metabolites, and genes of the two models.

Both the Molt-4 and CCRF-CEM models contained approximately

  • half of the reactions and metabolites present in the global model (Fig. 1C).

They were very similar to each other in terms of their

  • reactions,
  • metabolites, and
  • genes (File S1, Table S5A–C).

The Molt– 4 model contained

  • seven reactions that were not present in the CCRF-CEM model
    (Co-A biosynthesis pathway and exchange reactions).

In contrast, the CCRF-CEM  contained

31 unique reactions

  • arginine and proline metabolism,
  • vitamin B6  metabolism,
  • fatty acid activation,
  • transport, and exchange reaction.
  • There  were 2 and 15 unique metabolites in the Molt-4 and CCRF-CEM models,  respectively
    (File S1, Table S5B).
    Approximately three quarters of the global  model  genesremained in the condition-specific cell line models  (Fig. 1C).

The Molt-4 model contained

  • 15 unique genes, and

the CCRF-CEM model had

  • 4 unique genes (File S1, Table S5C).

Both models lacked NADH dehydrogenase
(complex I of the electron transport chain—ETC),

  •  determined by  the  absence of expression of a mandatory subunit
    (NDUFB3, Entrez gene ID 4709).

The ETC was fueled by FADH2 originating from

  1. succinate dehydrogenase and
  2. from fatty acid oxidation, which
  • through flavoprotein electron transfer
  • could contribute to the same ubiquinone pool as
  • complex I and complex II (succinate dehydrogenase).

Despite their different in vitro growth rates
(which differed by 11 %, see File S2, Fig. S1) and

  • differences in exo-metabolomic data (Fig. 1B) and
  • transcriptomic data,
  • the internal networks were largely conserved
  • in the two condition-specific cell line models.

 

2.1.5 Condition-specific cell line models predict distinct metabolic strategies

Despite the overall similarity of the metabolic models,

  • differences in their cellular uptake and secretion patterns suggested
  • distinct metabolic states in the two cell lines
    (Fig. 1B and see “Materials and methods” section for more detail).

To interrogate the metabolic differences, we sampled the solution space

  • of each model  using an Artificial Centering Hit-and-Run (ACHR) sampler (Thiele et al. 2005).

For this  analysis, additional constraints were applied, emphasizing

  • the  quantitative differences in commonly uptaken and secreted metabolites.

The  maximum possible uptake and maximum possible secretion flux rates were

  • reduced according to the measured relative differences between the cell lines
    (Fig. 1D, see “Materials and methods” section).

We plotted the number of sample points containing a particular flux rate for each reaction. The resulting

  • binned histograms can be understood as representing the probability that
  • a particular reaction can have a certain flux value.

A comparison of the sample points obtained for the Molt-4 and CCRF-CEM models revealed

  • a  considerable shift in the distributions, suggesting
  • a higher utilization of  glycolysis by the CCRF-CEM model (File S2, Fig. S2).

This result  was further  supported by differences

  • in medians calculated from sampling points (File S1,  Table S6).

The shift persisted throughout all reactions of the pathway and

  • was  induced by the higher glucose uptake (35 %) from
  • the extracellular medium in CCRF-CEM cells.

The sampling median for glucose uptake was 34 % higher

  • in the  CCRF-CEM model than in Molt-4 model (File S2, Fig. S2).

The usage of the  TCA cycle was also distinct in the two condition-specific cell-line models (Fig. 2).

  • the models used succinate dehydrogenase differently (Figs. 23).

The Molt-4 model utilized an associated reaction to generate FADH2, whereas

  • in  the CCRF-CEM model, the histogram was shifted in the opposite direction,
  • toward  the generation of succinate.

Additionally, there was a higher efflux of  citrate toward

  • amino acid and lipid metabolism in the CCRF-CEM model (Fig. 2).

There was higher flux through anaplerotic and cataplerotic reactions

  • in the CCRF-CEM model than in the Molt-4 model (Fig. 2);
  • these reactions include the efflux  of citrate through

 

  1. ATP-citrate lyase,
  2. uptake of glutamine,
  3. generation of  glutamate from glutamine,
  4. transamination of pyruvate and
  5.  glutamate to alanine  and to 2-oxoglutarate,
  6. secretion of nitrogen, and
  7. secretion of alanine.

The Molt-4 model showed higher utilization of oxidative phosphorylation (Fig. 3),

  • supported by elevated median flux through ATP synthase (36 %) and other  enzymes,
  • which contributed to higher oxidative metabolism.

The sampling  analysis therefore revealed different usage of

  • central metabolic pathways by the condition-specific models.

 

Fig. 2

Differences in the use of the TCA cycle by the CCRF-CEM

Differences in the use of the TCA cycle by the CCRF-CEM

Differences in the use of the TCA cycle by the CCRF-CEM model (red) and the Molt-4 model (blue).
The table provides the median values of the sampling results. Negative values in histograms and Table

  • describe reversible  reactions with flux in the reverse direction.

There are multiple reversible  reactions for the transformation of

  1. isocitrate and α-ketoglutarate,
  2. malate and  fumarate, and
  3. succinyl-CoA and succinate.

These reactions are  unbounded,  and therefore histograms are not shown.
The details of participating cofactors  have been removed.

Atp ATP, cit citrate, adp ADP, pi phosphate, oaa oxaloacetate, accoa acetyl-CoAcoa coenzyme-A,
icit isocitrate, αkg α-ketoglutarate, succcoa succinyl-CoAsucc succinate, fumfumarate, mal malate,
oxa oxaloacetate,  pyr pyruvate, lac lactate, ala alanine, gln glutamine, ETC electron transport  chain.

 

Electronic supplementary material The online version of this article
http://dx.doi.org:/10.1007/s11306-014-0721-3 
contains supplementary material,  which  is available to authorized users.

  1.  K. Aurich _ G. Paglia _ O ´ . Rolfsson _ S. Hrafnsdo´ ttir _
  2. Magnu´sdo´ ttir _ B. Ø. Palsson _ R. M. T. Fleming _ I. Thiele. Center for Systems Biology,
    University of Iceland, Reykjavik, Iceland
  3.  K. Aurich _ R. M. T. Fleming _ I. Thiele (&). Luxembourg Centre for Systems Biomedicine,
    University of Luxembourg, Campus Belval, Esch-Sur-Alzette, Luxembourg
    e-mail: ines.thiele@uni.lu
  4. M. Stefaniak. School of Health Science, Faculty of Food Science and Nutrition,
    University of Iceland, Reykjavik, Iceland
  5. Ø. Palsson. Department of Bioengineering, University of California San Diego, La Jolla, CA, USA

http://link.springer.com/static-content/images/404/art%253A10.1007%252
Fs11306-014-0721-3/MediaObjects/11306_2014_721_Fig3_HTML.gif

 

Fig. 3

Fatty acid oxidation and ETC _Fig3

Fatty acid oxidation and ETC _Fig3

 

Sampling reveals different utilization of oxidative phosphorylation by the

  • generated models.

Different distributions are observed for the CCRF-CEM model (red) and the Molt-4 model (blue).

  • Molt-4 has higher  median  flux through ETC reactions II–IV.

The table provides the median values  of the sampling results. Negative values in the histograms and in the table describe

  • reversible reactions with flux in the reverse direction.

Both models lack Complex I of the ETC because of constraints

  • arising from the mapping of transcriptomic data.

Electron transfer flavoprotein and

  • electron transfer flavoprotein–ubiquinone oxidoreductase
  •  both also carry higher flux in the Molt-4 model

 

2.1.6 Experimental validation of energy and redox status of CCRF-CEM and Molt-4 cells

Cancer cells have to balance their needs

  •  for energy and biosynthetic precursors, and they have
  • to maintain redox homeostasis to proliferate (Cairns et al. 2011).

We conducted enzymatic assays of cell lysates to measure levels and/or ratios of

  • ATP,
  • NADPH + NADP,
  • NADH + NAD, and
  • glutathione.

These measurements were used to provide support for

  • the in silico predicted metabolic differences (Fig. 4).

Additionally, an Oxygen Radical Absorbance Capacity (ORAC) assay was used

  • to evaluate the cellular antioxidant status (Fig. 4B).

Total concentrations of NADH + NAD, GSH + GSSG, NADPH + NADP and ATP, were higher in Molt-4 cells  (Fig. 4A).

The higher ATP concentration in Molt-4 cells could either result from

  • high production rates, or intracellular  accumulation connected to high or
  • low reactions fluxes (Fig. 4A).

Our simplified view that oxidative Molt-4 produces less ATP and was contradicted by

  • the higher ATP concentrations measured (Fig. 4L).

Yet we want to emphasize that concentrations

  • cannot be compared to flux values,
  • since we are modeling at steady-state.

NADH/NAD+ ratios for both cell lines were shifted toward NADH (Fig. 4D, E), but

  • the shift toward NADH was more pronounced in CCRF-CEM (Fig. 4E),
  • which matched  our expectation based on the higher utilization of
  • glycolysis and 2-oxoglutarate  dehydrogenase in the CCRF-CEM model (Fig. 4L).

 

Fig. 4 (not shown)

A–K  Experimentally determined ATP, NADH + NAD, NADPH + NADP, and GSH + GSSG concentrations, and ROS detoxification in the CCRF-CEM and Molt-4 cells.

L Expectations for cellular energy and redox states. Expectations are based on predicted metabolic differences of the Molt-4 and CCRF-CEM models

2.1.7 Comparison of network utilization and alteration in gene expression

With the assumption that

  • differential expression of particular genes would cause reaction flux changes,

we determined how the differences in gene expression (between CCRF-CEM and Molt-4)

  • compared to the flux differences observed in the  models.

Specifically, we checked whether the reactions associated with genes upregulated
(significantly more expressed in CCRF-CEM cells compared to Molt-4  cells)

  • were indeed more utilized by the CCRF-CEM model,

and we  checked  whether downregulated genes

  • were associated with reactions more utilized by the Molt-4 model.

The set of downregulated genes was associated with 15 reactions, and

  • the set of 49 upregulated genes was associated with 113 reactions in the models.

Reactions were defined as differently utilized

  • if the difference in flux exceeded 10 % (considering only non-loop reactions).

Of the reactions associated with upregulated genes,

  • 72.57 % were more utilized by the CCRF-CEM model, and
  • 2.65 % were more utilized by the Molt-4 model (File S1, Table S7).

In contrast, all 15 reactions associated with the 12 downregulated genes

  • were more utilized in the CCRF-CEM model (File S1, Table S8).

After this initial analysis, we approached the question from a different angle, asking

  • whether the majority of the reactions associated with each individual gene
  • upregulated in CCRF-CEM were more utilized by the CCRF-CEM model.
  •  this was the case for 77.55 % of the upregulated genes.

The majority of reactions associated with two (16.67 %) downregulated genes

  • were more utilized by the Molt-4 model.

Taken together, our comparisons of the

  • direction of gene expression with the fluxes of the two cancer cell-line models
  • confirmed that reactions associated with upregulated genes in the CCRF-CEM
    cells were generally more utilized by the CCRF-CEM model.

2.1.8 Accumulation of DEGs and AS genes at key metabolic steps

After we confirmed that most reactions associated with upregulated genes

  • were more utilized by the CCRF-CEM model,

we checked the locations of DEGs within the network. In this analysis, we paid special attention to

  • the central metabolic pathways that we had found
  • to be distinctively utilized by the two models.

Several DEGs and AS events were associated with

  • glycolysis,
  • the ETC,
  • pyruvate metabolism, and
  • the PPP (Table 1).

 

Table 1

DEGs and AS events of central metabolic and cancer-related pathways

Full lists of DEGs and AS are provided in the supplementary material.

Upregulated significantly more expressed in CCRF-CEM compared to Molt-4 cells

PPP pentose phosphate pathway, OxPhos oxidative phosphorylation, Glycolysis/gluconglycolysis/gluconeogenesis, Pyruvate met. pyruvate metabolism

Moreover, in glycolysis, the DEGs and/or AS genes

  • were associated with all three rate-limiting steps, i.e., the steps mediated by
  1. hexokinase,
  2. pyruvate kinase, and
  3. phosphofructokinase.

Of these key enzymes,

  • hexokinase 1 (Entrez Gene ID: 3098) was alternatively spliced,
  • pyruvate kinase (PKM, Entrez gene ID: 5315) was significantly more
    expressed in the CCRF-CEM cells (Table 1),

in agreement with the higher in silico predicted flux.

However, in contrast to the observed

  • higher utilization of glycolysis in the CCRF-CEM model,
  • the gene associated with the rate-limiting glycolysis step, phosphofructokinase (Entrez Gene ID: 5213),
  • was significantly upregulated in Molt-4 cells relative to CCRF-CEM cells.

This higher expression was detected for only a single isozyme, however. Two of
the three genes associated with phosphofructokinase were also subject to
alternative splicing (Table 1). In addition to the key enzymes, fructose
bisphosphate aldolase (Entrez Gene ID: 230) was also significantly

  • upregulated in Molt-4 cells relative to CCRF-CEM cells,
  • in contrast to the predicted higher utilization of glycolysis in the CCRF-CEM model.

Additionally, glucose-6P-dehydrogenase (G6PD), which catalyzes

  • the first reaction and committed step of the PPP,
  • was an AS gene (Table 1).

A second AS gene associated with

  •  the PPP reaction of the deoxyribokinase
  • was RBKS (Entrez Gene ID: 64080).

This gene is also associated with ribokinase, but ribokinase was removed

  • because of the lack of ribose uptake or secretion.

Single AS genes were associated with different complexes of the ETC (Table 1).

Literature query revealed that at least 13 genes associated with alternative

  • splicing events were mentioned previously in connection with both alternative
    splicing and cancer (File S1, Table S14), and
  • 37 genes were associated with cancer, e.g., upregulated, downregulated at the
    level of mRNA or protein, or otherwise
  • connected to cancer metabolism and signaling.

One general observation was that there was a surprising

  • accumulation of metabolite transporters among the AS.

Overall, the high incidence of

  • differential gene expression events at metabolic control points
  • increases the plausibility of the in silico predictions.

 

2.1.9 Single gene deletion

Analyses of essential genes in metabolic models have been used

  • to predict candidate drug targets for cancer cells (Folger et al. 2011).

Here, we conducted an in silico gene deletion study for all model genes to identify

  • a unique set of knock-out (KO) genes
  • for each condition-specific cell line model.

The analysis yielded 63 shared lethal KO genes and

  • distinct sets of KO genes for the CCRF-CEM model (11 genes) and the Molt-4 model (3 genes).

For three of the unique CCRF-CEM KO genes,

  • the genes were only present in the CCRF-CEM model (File S1, Table S9).

 

The essential genes for both models were then

  • related to the cell-line-specific differences in metabolite uptake and secretion (Fig. 1B).

The CCRF-CEM model

  1. needed to generate putrescine from ornithine
    (ORNDC, Entrez Gene ID: 4953)
  2. to subsequently produce 5-methylthioadenosine for secretion (Fig. 1B).
  3. S-adenosylmethioninamine produced by adenosylmethionine decarboxylase
    (arginine and proline metabolism, associated with Entrez Gene ID: 262)
  • is a substrate required for generation of 5-methylthioadenosine.

Another example of a KO gene connected to an enforced exchange reaction was

  • glutamic-oxaloacetic transaminase 1 (GOT1, Entrez Gene ID: 2805).

Without GOT1, the CCRF-CEM model was forced to secrete

  • 4-hydroxyphenylpyruvate (Fig. 1B),
  • the second product of tyrosine transaminase,
  • which is produced only by that enzyme.

 

One KO gene in the Molt-4 model (Entrez Gene ID: 26227) was associated with

  • phosphoglycerate dehydrogenase (PGDH),
  • which catalyzes the conversion of 3-phospho-d-glycerate to 3-phosphohydroxypyruvate
  • while generating NADH from NAD+.

This KO gene is particularly interesting, given

  • the involvement of this reaction in a novel pathway for ATP generation in rapidly proliferating cells
    (Locasale et al. 2011; Vander Heiden 2011; Vazquez et al. 2011).

Reactions associated with unique KO genes were in many cases utilized more by the model, in which

  • the gene KO was lethal,
  • underlining the potential importance of these reactions for the models.

Thus, single gene deletion provided unique sets of lethal genes that could be

  • specifically targeted to kill these cells.

 

3 Discussion

In the current study, we explored the possibility of

  • semi-quantitatively integrating metabolomic data with
  • the human genome-scale reconstruction to facilitate analysis.

By constructing condition-specific cell line models

  • to provide a structured framework,
  • we derived insights that could not have been obtained from data analysis alone.

We derived condition-specific cell line models

  • for CCRF-CEM and
  • Molt-4 cells

that were able to explain the observed exo-metabolomic differences (Fig. 1B).

Despite the overall similarities between the models, the analysis revealed

  • distinct usage of central metabolic pathways (Figs. 234),
  • which we validated based on experimental data and
  • differential gene expression.

The additional data sufficiently supported

  • metabolic differences in the cell lines,
  • providing confidence in the generated models and the model-based predictions.

We used the validated models

  • to predict unique sets of lethal genes
  • to identify weak links in each model.

These weak links may represent potential drug targets.

Integrating omics data with the human genome-scale reconstruction

  • provides a structured framework (i.e., pathways)
  • that is based on careful consideration of the available biochemical literature
    (Thiele and Palsson2010).

This network context can simplify omics data analysis, and

  • it allows even non-biochemical experts
  • to gain fast and comprehensive insights
  • into the metabolic aspects of omics data sets.

Compared to transcriptomic data,

  • methods for the integration and analysis of metabolomic data
  • in the context of metabolic models are less well established,

although it is an active field of research (Li et al. 2013; Paglia et al. 2012b).
In contrast to other studies, our approach emphasizes

  • the representation of experimental conditions rather than
  • the reconstruction of a generic, cell-line-specific network,
  • which would require the combination of data sets from
  • many experimental conditions and extensive manual curation.

Rather, our way of model construction allowed us to efficiently

  • assess the metabolic characteristics of cells.

Despite the fact, that only a limited number of exchanged metabolites can be

  • measured by available metabolomics platforms and
  • at reasonable time-scale,

and that pathways of measured metabolites might still be unknown to date
(File S1, Tables S2–S3), our methods have the potential

  • to reveal metabolic characteristics of cells
  • which could be useful for biomedicine and personalized health.

The reasons why some cancers respond to certain treatments and not others
remain unclear, and choosing a treatment for a specific patient is often difficult
(Vander Heiden 2011). One potential application of our approach could be the
characterization of cancer phenotypes to explore how cancer cells or other cell
types

  • with particular metabolic characteristics respond to drugs.

The generation of our condition-specific cell line models involved

  • only limited manual curation,
  • making this approach a fast way to place metabolomic data
  • into a network context.

Model building mainly involves

  • the rigid reduction of metabolite exchanges
  • to match the observed metabolite exchange pattern
  • with as few additional metabolite exchanges as possible.

It should be noted that this reduction determines,

  • which pathways can be utilized by the model.

Our approach mostly conserved the internal network redundancy. However, a

  • more significant reduction may be achieved using different data.

Generally, a trade-off exists between the reduction of the internal network and

  • the increasing number of network gaps that need to be curated
  • by using additional omics data, such as transcriptomics and proteomics.

One way to prevent the emergence of network gaps would be

  • to use mapping algorithms that conserve network functionality,
    such as GIMME (Becker and Palsson 2008).

However, several additional methods exist for the integration of
transcriptomic data (Blazier and Papin 2012), and

  • which model-building method is best depends on the available data.

Interestingly, the lack of a significant contribution of our

  • gene expression data to the reduction of network size
  • suggests that the use of transcriptomic data is not necessary
  • to identify distinct metabolic strategies;
  • rather, the integration of exo-metabolomic data alone
    may provide sufficient insight.

However, sampling of the cell line models constrained

  • according to the exo-metabolomic profiles only, or
  • increasing the cutoff for the generation of absent and present calls (p < 0.01),
  • did not yield the same insights as presented herein (File S1, Table S18).

Only recently Gene Inactivation Moderated by Metabolism, Metabolomics and
Expression (GIM(3)E) became available, which

  • enforces minimum turnover of detected metabolites
  • based on intracellular metabolomics data as well as
  • gene expression microarray data (Schmidt et al. 2013).

In contrast to this approach, we emphasized our analysis on the

  • relative differences in the exo-metabolomic data of two cell lines.

GIM(3)E constitutes another integration method when the analysis should be

  • emphasized on intracellular metabolomics data (Schmidt et al. 2013).

The metabolic differences predicted by the models are generally plausible.
Cancers are known to be heterogeneous (Cairns et al. 2011), and

  • the contribution of oxidative phosphorylation to cellular ATP production
    may vary (Zu and Guppy 2004).

Moreover, leukemia cell lines have been shown

  • to depend on glucose, glutamine, and fatty acids to varying extents
  • to support proliferation.

Such dependence may cause the cells to adapt their metabolism

  • to the environmental conditions (Suganuma et al. 2010).

In addition to identifying supporting data in the literature, we performed

  • several analyses to validate the models and model predictions.

Our expectations regarding the levels and ratios of metabolites

  • relevant to energy and redox state were largely met (Fig. 4L).

The more pronounced shift of the NADH/NAD+ ratio

  • toward NADH in the CCRF-CEM cells
  • was in agreement with the predicted Warburg phenotype (Fig. 4),
  • and the higher lactate secretion in the CCRF-CEM cells (File S2, Fig. S2)
  • implies an increase in NADH relative to NAD+
    (Chiarugi et al. 2012; Nikiforov et al. 2011), again
  • matching the known Warburg phenotype.

ROS production is enhanced in certain types of cancer (Droge 2002; Ha et al. 2000), and

  • the generation of ROS is thought to contribute to
  1. mutagenesis,
  2. tumor promotion, and
  3. tumor progression (Dreher and Junod1996; Ha et al. 2000).

However, decreased mitochondrial glucose oxidation and

  • a transition to aerobic glycolysis
  • protect cells against ROS damage during biosynthesis and cell division
    (Brand and Hermfisse1997).

The higher ROS detoxification capability in Molt-4 cells, in combination with

  • higher spermidine dismutase utilization by the Molt-4 model (Fig. 4),
  • provided a consistent picture of the predicted respiratory phenotype (Fig. 4L).

Control of NADPH maintains the redox potential through GSH and

  • protects against oxidative stress, yet
  • changes in the NADPH ratio in response to oxidative damage
  • are not well understood (Ogasawara et al.2009).

Under stress conditions, as assumed for Molt-4 cells,

  • the NADPH/NADP+ ratio is expected to decrease because of
  • the continuous reduction of GSSG (Fig. 4L), and
  • this was confirmed in the Molt-4 cells (Fig. 4).

The higher amounts of GSH found in Molt-4 cells in vitro may demonstrate

  • an additional need for ROS scavengers because of
  • a greater reliance on oxidative metabolism.

Cancer is related to metabolic reprogramming, which results from

  • alterations of gene expression and
  • the expression of specific isoforms or
  • splice forms to support proliferation
    (Cortes-Cros et al. 2013; Marin-Hernandez et al. 2009).

The gene expression differences detected between the two cell lines in this study
supported the existence of

  • metabolic differences in these cell lines, particularly because
  • key steps of the metabolic pathways central to cancer metabolism
  • seemed to be differentially regulated (Table 1).

The detailed analysis of the respective

  • differences on the pathway fluxes exceeds the scope of this study, which was to
  • demonstrate the potential of the integration of exo-metabolomic data into the network context.

We found discrepancies between differential gene regulation and

  • the flux differences between the two models as well as
  • the utilization AS gene-associated reaction.

This is not surprising, since analysis of the detailed system is required

  • to make any further assumptions on the impact that
  • the differential regulation or splicing might have on the reaction flux,
  • given that for many of the concerned enzymes isozymes exist, or
  • only one of multiple subunits of a protein complex was concerned.

Additionally, reaction fluxes are regulated by numerous post-translational factors, e.g.,

  • protein modification,
  • inhibition through proteins or metabolites,
  • alter reaction fluxes (Lenzen 2014),

which are out of the scope of constraint-based steady-state modeling.

Rather, the results of the presented  approach

  • demonstrate how the models can be used to generate
  • informed hypothesis that can guide experimental work.

The combination of our tailored metabolic models and

  • differential gene expression analysis seems well-suited
  • to determine the potential drivers
  • involved in metabolic differences between cells.

Such information could be valuable for drug discovery, especially when more

  • peripheral metabolic pathways are considered.

Statistical comparisons of gene expression data with sampling-derived flux data

  • could be useful in future studies (Mardinoglu et al. 2013).

A single-gene-deletion analysis revealed that PGDH was

  • a lethal KO gene for the Molt-4 model only.

Differences in PGDH protein levels

  • correspond to the amount of glycolytic carbon
  • diverted into glycine biosynthesis.

Rapidly proliferating cells may use an

  • alternative glycolytic pathway for ATP generation,
  • which may provide an advantage in the case of
  • extensive oxidative phosphorylation and proliferation
    (Locasale et al.2011; Vander Heiden 2011; Vazquez et al. 2011).

For breast cancer cell lines, variable dependency on

  • the expression of PGDH has already been demonstrated
    (Locasale et al. 2011).

This example of a unique KO gene demonstrates how

  • in silico gene deletion in metabolomics-driven models
  • can identify the metabolic pathways used by cancer cells.

This approach can provide valuable information for drug discovery.

In conclusion, our contextualization method produced

  • metabolic models that agreed in many ways with the validation data sets.

The analyses described in this study have great potential to reveal

  • the mechanisms of metabolic reprogramming,
  • not only in cancer cells but also in other cells affected by diseases, and
  • for drug discovery in general.

 

4.3 Analysis of the extracellular metabolome

Mass spectrometry analysis of the exo-metabolome was performed by
Metabolon®, Inc. (Durham, NC, USA) using a standardized analytical platform.
In total, 75 extracellular metabolites were detected in the initial data set for at
least 1 of the 2 cell lines (Paglia et al. 2012a). Of these metabolites, 15 were not
part of our global model and were discarded. Apart from being absent in our
global model, an independent search in HMDB (Wishart et al. 2013) revealed no
pathway information was available for most of these metabolites (File S1, Tables S2–S3).
It should be noted that metabolites e.g.,

  • N-acetylisoleucine,
  • N-acetyl-methionine or pseudouridine,

constitute protein and RNA degradation products, which were out of the scope
of the metabolic network.

Thiamin (Vitamin B1) was part of the minimal medium of essential compounds
supplied to both models.Riboflavin (Vitamin B2) and Trehalose were excluded
since these compounds cannot be produced by human cells. Erythrose and
fructose were also excluded. In contrast 46 metabolites that were part of the
global model. The data set included two different time points, which allowed us
to treat the increase/decrease of a metabolite signal between time points as

  • evidence for uptake or secretion when the change was greater than 5 %
    from what was observed in the control (File S1, Tables S2–S3).

We found 12 metabolites that were taken up by both cell lines and
10 metabolites that were commonly secreted by both cell lines over
the course of the experiment.

Molt-4 cells took up three metabolites not taken up by CCRF-CEM cells, and
secreted one metabolite not secreted by CCRF-CEM cells. Two of the three
uniquely uptaken metabolites were essential amino acids:

  1. valine and
  2. methionine.

It is unlikely that these metabolites were not taken up by the CCRF-CEM cells,
and the CCRF-CEM model was allowed to take up this metabolite. Therefore,
no quantitative constraints were applied for the sampling analysis either.
CCRF-CEM cells had

  • four unique uptaken
  • and seven unique secreted metabolites
    (exchange not detected in Molt-4 cells).

 

4.4 Network refinement based on exo-metabolic data

Despite its comprehensiveness, the human metabolic reconstruction is

  • not complete with respect to extracellular metabolite transporters
    (Sahoo et al. 2014; Thiele et al. 2013).

Accordingly, we identified metabolite transport systems

  • from the literature for metabolites that were already part of the global model,
  • but whose extracellular transport was not yet accounted for.

Diffusion reactions were included whenever a respective transporter could not be identified.

In total, 34 reactions [11 exchange reactions, 16 transport reactions and 7 demand reactions
(File S1, Table S11)] were added to Recon 2 (Thiele et al. 2013), and 2 additional reactions
were added to the global model (File S1, Table S10).

4.5 Expression profiling

Molt-4 and CCRF-CEM cells were grown in advanced RPMI 1640 and 2 mM
GlutaMax, and the cells were resuspended in medium containing DMSO
(0.67 %) at a concentration of 5 × 105 cells/mL. The cell suspension (2 mL)
was seeded in 12-well plates in triplicate. After 48 h of growth, the cells
were collected by centrifugation at 201×g for 5 min. Cell pellets were snap-frozen
in liquid N2 and kept frozen until RNA extraction and analysis by Aros
(Aarhus, Denmark).

4.6 Analysis of transcriptomic data

We used the Affymetrix GeneChip Human Exon 1.0 ST Array to measure whole
genome exon expression. We generated detection above background (DABG) calls
using ROOT (version 22) and the XPS package for R (version 11.1), with Robust
Multi-array Analysis summarization. Calls for data mapping were assigned based
on p < 0.05 as the cutoff probability to distinguish presence versus absence for
the 1,278 model genes (File S1, Table S12).

Differential gene expression and alternative splicing analyses were performed by
using AltAnalyse software (v2.02beta) with default options on the raw data files
(CEL files). The Homo sapiens Ensemble 65 database was used, probe set filtering
was kept as DABG p < 0.05, and non-log expression < 70 was used for
constitutive probe sets to determine gene expression levels. For the comparison,
CCRF-CEM was the experimental group and Molt-4 was the baseline group. The
set of DEGs between cell lines was identified based on a p < 0.05 FDR cutoff
(File S1, Table S13A–B). Alternative splicing analysis was performed on core probe sets
with a minimum alternative exon score of 2 and a maximum absolute gene
expression change of 3 because alternative splicing is a less critical factor among
highly DEGs (File S1, Table S14). Gene expression data, complete lists of DABG p-values,
DEGs and alternative splicing events have been deposited in the Gene
Expression Omnibus
 (GEO) database (Accession number: GSE53123).

 

4.7 Deriving cell-type-specific subnetworks

Transcriptomic data were mapped to the model in a manual fashion (COBRA
function: deleteModelGenes). Specifically, reactions dependent on gene products
that were called as “absent” were constrained to zero, such that fluxes through
these reactions were disabled. Submodels were extracted based on the set of
reactions carrying flux (network pruning) by running fastFVA
(Gudmundsson and Thiele 2010) after mapping the metabolomic and
transcriptomic data using the COBRA toolbox (Schellenberger et al. 2011).

 

…..

 

Electronic supplementary material

Below is the link to the electronic supplementary material.

File S1. Supplementary material 1 (XLSX 915 kb)

File S2. Supplementary material 2 (DOCX 448 kb)

References

Antonucci, R., Pilloni, M. D., Atzori, L., & Fanos, V. (2012). Pharmaceutical research and metabolomics in the newborn. Journal of Maternal-Fetal and Neonatal Medicine, 25, 22–26.PubMedCrossRef

Barrett, T., Troup, D. B., Wilhite, S. E., Ledoux, P., Evangelista, C., Kim, I. F., et al. (2011). NCBI GEO: archive for functional genomics data sets—10 years on. Nucleic Acids Research, 39, D1005–D1010.PubMedCentralPubMedCrossRef

Beck, M., Schmidt, A., Malmstroem, J., Claassen, M., Ori, A., Szymborska, A., et al. (2011). The quantitative proteome of a human cell line.Molecular Systems Biology, 7, 549.PubMedCentralPubMedCrossRef

Becker, S. A., & Palsson, B. O. (2008). Context-specific metabolic networks are consistent with experiments. PLoS Computational Biology, 4, e1000082.PubMedCentralPubMedCrossRef

Blazier, A. S., & Papin, J. A. (2012). Integration of expression data in genome-scale metabolic network reconstructions. Frontiers in Physiology, 3, 299.PubMedCentralPubMedCrossRef

Bordbar, A., Lewis, N. E., Schellenberger, J., Palsson, B. O., & Jamshidi, N. (2010). Insight into human alveolar macrophage and M. tuberculosisinteractions via metabolic reconstructions. Molecular Systems Biology, 6, 422.PubMedCentralPubMedCrossRef

Bordbar, A., & Palsson, B. O. (2012). Using the reconstructed genome-scale human metabolic network to study physiology and pathology. Journal of Internal Medicine, 271, 131–141.PubMedCentralPubMedCrossRef

Brand, K. A., & Hermfisse, U. (1997). Aerobic glycolysis by proliferating cells: a protective strategy against reactive oxygen species. FASEB Journal, 11, 388–395.PubMed

Cairns, R. A., Harris, I. S., & Mak, T. W. (2011). Regulation of cancer cell metabolism. Nature Reviews Cancer, 11, 85–95.PubMedCrossRef

Chance, B., Sies, H., & Boveris, A. (1979). Hydroperoxide metabolism in mammalian organs. Physiological Reviews, 59, 527–605.PubMed

Chapman, E. H., Kurec, A. S., & Davey, F. R. (1981). Cell volumes of normal and malignant mononuclear cells. Journal of Clinical Pathology, 34, 1083–1090.PubMedCentralPubMedCrossRef

Chiarugi, A., Dolle, C., Felici, R., & Ziegler, M. (2012). The NAD metabolome—a key determinant of cancer cell biology. Nature Reviews Cancer, 12, 741–752.PubMedCrossRef

Cortes-Cros, M., Hemmerlin, C., Ferretti, S., Zhang, J., Gounarides, J. S., Yin, H., et al. (2013). M2 isoform of pyruvate kinase is dispensable for tumor maintenance and growth. Proceedings of the National Academy of Sciences of the United States of America, 110, 489–494.PubMedCentralPubMedCrossRef

Dreher, D., & Junod, A. F. (1996). Role of oxygen free radicals in cancer development. European Journal of Cancer, 32a, 30–38.PubMedCrossRef

Droge, W. (2002). Free radicals in the physiological control of cell function. Physiological Reviews, 82, 47–95.PubMed

Duarte, N. C., Becker, S. A., Jamshidi, N., Thiele, I., Mo, M. L., Vo, T. D., et al. (2007). Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proceedings of the National Academy of Sciences of the United States of America, 104, 1777–1782.PubMedCentralPubMedCrossRef

Durot, M., Bourguignon, P. Y., & Schachter, V. (2009). Genome-scale models of bacterial metabolism: Reconstruction and applications. FEMS Microbiology Reviews, 33, 164–190.PubMedCentralPubMedCrossRef

Fleming, R. M., Thiele, I., & Nasheuer, H. P. (2009). Quantitative assignment of reaction directionality in constraint-based models of metabolism: Application to Escherichia coliBiophysical Chemistry, 145, 47–56.PubMedCentralPubMedCrossRef

Folger, O., Jerby, L., Frezza, C., Gottlieb, E., Ruppin, E., & Shlomi, T. (2011). Predicting selective drug targets in cancer through metabolic networks. Molecular Systems Biology, 7, 501.PubMedCentralPubMedCrossRef

Frezza, C., Zheng, L., Folger, O., Rajagopalan, K. N., MacKenzie, E. D., Jerby, L., et al. (2011). Haem oxygenase is synthetically lethal with the tumour suppressor fumarate hydratase. Nature, 477, 225–228.PubMedCrossRef

Ganske, F., & Dell, E. J. (2006). ORAC assay on the FLUOstar OPTIMA to determine antioxidant capacity. BMG LABTECH.

Gudmundsson, S., & Thiele, I. (2010). Computationally efficient flux variability analysis. BMC Bioinformatics, 11, 489.PubMedCentralPubMedCrossRef

Ha, H. C., Thiagalingam, A., Nelkin, B. D., & Casero, R. A, Jr. (2000). Reactive oxygen species are critical for the growth and differentiation of medullary thyroid carcinoma cells. Clinical Cancer Research, 6, 3783–3787.PubMed

Hyduke, D. R., Lewis, N. E., & Palsson, B. O. (2013). Analysis of omics data with genome-scale models of metabolism. Molecular BioSystems, 9, 167–174.PubMedCentralPubMedCrossRef

Jerby, L., & Ruppin, E. (2012). Predicting drug targets and biomarkers of cancer via genome-scale metabolic modeling. Clinical Cancer Research,18, 5572–5584.PubMedCrossRef

Jerby, L., Shlomi, T., & Ruppin, E. (2010). Computational reconstruction of tissue-specific metabolic models: Application to human liver metabolism.Molecular Systems Biology, 6, 401.PubMedCentralPubMedCrossRef

Jerby, L., Wolf, L., Denkert, C., Stein, G. Y., Hilvo, M., Oresic, M., et al. (2012). Metabolic associations of reduced proliferation and oxidative stress in advanced breast cancer. Cancer Research, 72, 5712–5720.PubMedCrossRef

Lenzen, S. (2014). A fresh view of glycolysis and glucokinase regulation: History and current status. Journal of Biological Chemistry, 289, 12189–12194.PubMedCrossRef

Lewis, N. E., Nagarajan, H., & Palsson, B. O. (2012). Constraining the metabolic genotype–phenotype relationship using a phylogeny of in silico methods. Nature Reviews Microbiology, 10, 291–305.PubMedCentralPubMed

Lewis, N. E., Schramm, G., Bordbar, A., Schellenberger, J., Andersen, M. P., Cheng, J. K., et al. (2010). Large-scale in silico modeling of metabolic interactions between cell types in the human brain. Nature Biotechnology, 28, 1279–1285.PubMedCentralPubMedCrossRef

Li, S., Park, Y., Duraisingham, S., Strobel, F. H., Khan, N., Soltow, Q. A., et al. (2013). Predicting network activity from high throughput metabolomics. PLoS Computational Biology, 9, e1003123.PubMedCentralPubMedCrossRef

Locasale, J. W., Grassian, A. R., Melman, T., Lyssiotis, C. A., Mattaini, K. R., Bass, A. J., et al. (2011). Phosphoglycerate dehydrogenase diverts glycolytic flux and contributes to oncogenesis. Nature Genetics, 43, 869–874.PubMedCentralPubMedCrossRef

Mardinoglu, A., Agren, R., Kampf, C., Asplund, A., Nookaew, I., Jacobson, P., et al. (2013). Integration of clinical data with a genome-scale metabolic model of the human adipocyte. Molecular Systems Biology, 9, 649.PubMedCentralPubMedCrossRef

Marin-Hernandez, A., Gallardo-Perez, J. C., Ralph, S. J., Rodriguez-Enriquez, S., & Moreno-Sanchez, R. (2009). HIF-1alpha modulates energy metabolism in cancer cells by inducing over-expression of specific glycolytic isoforms. Mini Reviews in Medicinal Chemistry, 9, 1084–1101.PubMedCrossRef

Mir, M., Wang, Z., Shen, Z., Bednarz, M., Bashir, R., Golding, I., et al. (2011). Optical measurement of cycle-dependent cell growth. Proceedings of the National Academy of Sciences of the United States of America, 108, 13124–13129.PubMedCentralPubMedCrossRef

Mo, M. L., Palsson, B. O., & Herrgard, M. J. (2009). Connecting extracellular metabolomic measurements to intracellular flux states in yeast. BMC Systems Biology, 3, 37.PubMedCentralPubMedCrossRef

Nikiforov, A., Dolle, C., Niere, M., & Ziegler, M. (2011). Pathways and subcellular compartmentation of NAD biosynthesis in human cells: From entry of extracellular precursors to mitochondrial NAD generation. The Journal of biological chemistry, 286, 21767–21778.PubMedCentralPubMedCrossRef

Ogasawara, Y., Funakoshi, M., & Ishii, K. (2009). Determination of reduced nicotinamide adenine dinucleotide phosphate concentration using high-performance liquid chromatography with fluorescence detection: Ratio of the reduced form as a biomarker of oxidative stress. Biological & Pharmaceutical Bulletin, 32, 1819–1823.CrossRef

Paglia, G., Hrafnsdottir, S., Magnusdottir, M., Fleming, R. M., Thorlacius, S., Palsson, B. O., et al. (2012a). Monitoring metabolites consumption and secretion in cultured cells using ultra-performance liquid chromatography quadrupole-time of flight mass spectrometry (UPLC-Q-ToF-MS).Analytical and Bioanalytical Chemistry, 402, 1183–1198.PubMedCrossRef

Paglia, G., Palsson, B. O., & Sigurjonsson, O. E. (2012b). Systems biology of stored blood cells: Can it help to extend the expiration date? Journal of Proteomics, 76, 163–167.PubMedCrossRef

Price, N. D., Schellenberger, J., & Palsson, B. O. (2004). Uniform sampling of steady-state flux spaces: Means to design experiments and to interpret enzymopathies. Biophysical Journal, 87, 2172–2186.PubMedCentralPubMedCrossRef

Reed, J. L., Famili, I., Thiele, I., & Palsson, B. O. (2006). Towards multidimensional genome annotation. Nature Reviews Genetics, 7, 130–141.PubMedCrossRef

Sahoo, S., Aurich, M. K., Jonsson, J. J., & Thiele, I. (2014). Membrane transporters in a human genome-scale metabolic knowledgebase and their implications for disease. Frontiers in Physiology, 5, 91.PubMedCentralPubMedCrossRef

Sahoo, S., & Thiele, I. (2013). Predicting the impact of diet and enzymopathies on human small intestinal epithelial cells. Human Molecular Genetics, 22, 2705–2722.PubMedCentralPubMedCrossRef

Schellenberger, J., & Palsson, B. O. (2009). Use of randomized sampling for analysis of metabolic networks. The Journal of biological chemistry,284, 5457–5461.PubMedCrossRef

Schellenberger, J., Que, R., Fleming, R. M., Thiele, I., Orth, J. D., Feist, A. M., et al. (2011). Quantitative prediction of cellular metabolism with constraint-based models: The COBRA Toolbox v2.0. Nature Protocols, 6, 1290–1307.PubMedCentralPubMedCrossRef

Schmidt, B. J., Ebrahim, A., Metz, T. O., Adkins, J. N., Palsson, B. O., & Hyduke, D. R. (2013). GIM3E: Condition-specific models of cellular metabolism developed from metabolomics and expression data. Bioinformatics (Oxford, England), 29, 2900–2908.CrossRef

Suganuma, K., Miwa, H., Imai, N., Shikami, M., Gotou, M., Goto, M., et al. (2010). Energy metabolism of leukemia cells: Glycolysis versus oxidative phosphorylation. Leukemia & Lymphoma, 51, 2112–2119.CrossRef

Thiele, I., & Palsson, B. O. (2010). A protocol for generating a high-quality genome-scale metabolic reconstruction. Nature Protocols, 5, 93–121.PubMedCentralPubMedCrossRef

Thiele, I., Price, N. D., Vo, T. D., & Palsson, B. O. (2005). Candidate metabolic network states in human mitochondria. Impact of diabetes, ischemia, and diet. The Journal of biological chemistry, 280, 11683–11695.PubMedCrossRef

Thiele, I., Swainston, N., Fleming, R. M., Hoppe, A., Sahoo, S., Aurich, M. K., et al. (2013). A community-driven global reconstruction of human metabolism. Nature Biotechnology, 31, 419–425.PubMedCrossRef

Uhlen, M., Oksvold, P., Fagerberg, L., Lundberg, E., Jonasson, K., Forsberg, M., et al. (2010). Towards a knowledge-based human protein Atlas.Nature Biotechnology, 28, 1248–1250.PubMedCrossRef

Vander Heiden, M. G. (2011). Targeting cancer metabolism: A therapeutic window opens. Nature Reviews Drug Discovery, 10, 671–684.PubMedCrossRef

Vazquez, A., Markert, E. K., & Oltvai, Z. N. (2011). Serine biosynthesis with one carbon catabolism and the glycine cleavage system represents a novel pathway for ATP generation. PLoS ONE, 6, e25881.PubMedCentralPubMedCrossRef

Wishart, D. S., Jewison, T., Guo, A. C., Wilson, M., Knox, C., Liu, Y., et al. (2013). HMDB 3.0—The human metabolome database in 2013. Nucleic Acids Research, 41, D801–D807.PubMedCentralPubMedCrossRef

Zu, X. L., & Guppy, M. (2004). Cancer metabolism: Facts, fantasy, and fiction. Biochemical and Biophysical Research Communications, 313, 459–465.PubMedCrossRef

 

Read Full Post »