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Posts Tagged ‘aerobic glycolysis’


Therapeutic Implications for Targeted Therapy from the Resurgence of Warburg ‘Hypothesis’

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

(Note that each portion of the discussion is followed by a reference)

It is now a time to pause after almost a century of a biological scientific discoveries that have transformed the practice of medicine and impacted the lives of several generations of young minds determined to probe the limits of our knowledge.  In the century that we have entered into the scientific framework of medicine has brought together a difficult to grasp evolution of the emergence of human existence from wars, famine, droughts, storms, infectious diseases, and insect born pestilence with betterment of human lives, only unevenly divided among societal classes that have existed since time immemorial. In this short time span there have emerged several generations of physicians who have benefited from a far better medical education that their forebears could have known. In this expansive volume on cancer, we follow an incomplete and continuing challenge to understand cancer, a disease that has become associated with longer life spans in developed nations.

While there are significant improvements in the diagnosis and treatment of cancers, there is still a personal as well as locality factor in the occurrence of this group of diseases, which has been viewed incorrectly as a “dedifferentiation” of mature tissue types and the emergence of a cell phenotype that is dependent on glucose, reverts to a cancer “stem cell type” (loss of stemness), loses cell to cell adhesion, loses orderly maturation, and metastasizes to distant sites. At the same time, physician and nurses are stressed in the care of patients by balancing their daily lives and maintaining a perspective.

The conceptual challenge of cancer diagnosis and management has seemed insurmountable, but owes much to the post World War I activities of Otto Heinrich Warburg. It was Warburg who made the observation that cancer cells metabolize glucose by fermentation in much the way Pasteur 60 years earlier observed fermentation of yeast cells. This metabolic phenomenon occurs even in the presence of an oxygen supply, which would provide a huge deficit in ATP production compared with respiration. The cancer cell is “addicted to glucose” and produced lactic acid. Warburg was awarded the Nobel Prize in Medicine for this work in 1931.

In the last 15 years there has been a resurgence of work on the Warburg effect that sheds much new light on the process that was not previously possible, with significant therapeutic implications.  In the first place, the metabolic mechanism for the Warburg effect was incomplete even at the beginning of the 21st century.  This has been partly rectified with the enlightening elucidation of genome modifications, cellular metabolic regulation, and signaling pathways.

The following developments have become central to furthering our understanding of malignant transformation.

  1. There is usually an identifiable risk factor, such as, H. pylori, or of a chronic inflammatory state, as in the case of Barrett’s esophagus.
  2. There are certain changes in glucose metabolism that have been unquestionably been found in the evolution of this disease. The changes are associated with major changes in metabolic pathways, miRN signaling, and the metabolism geared to synthesis of cells with an impairment of the cell death cycle. In these changes, mitochondrial function is central to both the impaired respiration and the autophagy geared to the synthesis of cancer cells.

The emergence of this cell prototype is characterized by the following, again related to the Warburg effect:

  1. Cancer cells oxidize a decreased fraction of the pyruvate generated from glycolysis
  2. The mitochondrial pyruvate carrier (MPC), composed of the products of the MPC1 and MPC2 genes, modulates fractional pyruvate oxidation. MPC1 is deleted or underexpressed in multiple cancers and correlates with poor prognosis.
  3. Cancer cells tend to express a partially inhibited splice variant of pyruvate kinase (PK-M2), leading to decreased pyruvate production.
  4. The two proteins that mediate pyruvate conversion to lactate and its export, M-type lactate dehydrogenase and the monocarboxylate transporter MCT-4, are commonly upregulated in cancer cells leading to decreased pyruvate oxidation.
  5. The enzymatic step following mitochondrial entry is the conversion of pyruvate to acetyl-CoA by the pyruvate dehydrogenase (PDH) complex. Cancer cells frequently exhibit increased expression of the PDH kinase PDK1, which phosphorylates and inactivates PDH. This PDH regulatory mechanism is required for oncogene induced transformation and reversed in oncogene-induced senescence.
  6. The PDK inhibitor dichloroacetate has shown some clinical efficacy, which correlates with increased pyruvate oxidation. One of the simplest mechanisms to explain decreased mitochondrial pyruvate oxidation in cancer cells, a loss of mitochondrial pyruvate import, has been observed repeatedly over the past 40 years. This process has been impossible to study at a molecular level until recently, however, as the identities of the protein(s) that mediate mitochondrial pyruvate uptake were unknown.
  7. The mitochondrial pyruvate carrier (MPC) as a multimeric complex that is necessary for efficient mitochondrial pyruvate uptake. The MPC contains two distinct proteins, MPC1 and MPC2; the absence of either leads to a loss of mitochondrial pyruvate uptake and utilization in yeast, flies, and mammalian cells.

A Role for the Mitochondrial Pyruvate Carrier as a Repressor of the Warburg Effect and Colon Cancer Cell Growth

John C. Schell, Kristofor A. Olson, Lei Jiang, Amy J. Hawkins, et al.
Molecular Cell Nov 6, 2014; 56: 400–413.
http://dx.doi.org/10.1016/j.molcel.2014.09.026

In addition to the above, the following study has therapeutic importance:

Glycolysis has become a target of anticancer strategies. Glucose deprivation is sufficient to induce growth inhibition and cell death in cancer cells. The increased glucose transport in cancer cells has been attributed primarily to the upregulation of glucose transporter 1 (Glut1),  1 of the more than 10 glucose transporters that are responsible for basal glucose transport in almost all cell types. Glut1 has not been targeted until very recently due to the lack of potent and selective inhibitors.

First, Glut1 antibodies were shown to inhibit cancer cell growth. Other Glut1 inhibitors and glucose transport inhibitors, such as fasentin and phloretin, were also shown to be effective in reducing cancer cell growth. A group of inhibitors of glucose transporters has been recently identified with IC50 values lower than 20mmol/L for inhibiting cancer cell growth. However, no animal or detailed mechanism studies have been reported with these inhibitors.

Recently, a small molecule named STF-31 was identified that selectively targets the von Hippel-Lindau (VHL) deficient kidney cancer cells. STF-31 inhibits VHL deficient cancer cells by inhibiting Glut1. It was further shown that daily intraperitoneal injection of a soluble analogue of STF-31 effectively reduced the growth of tumors of VHL-deficient cancer cells grafted on nude mice. On the other hand, STF-31 appears to be an inhibitor with a narrow cell target spectrum.

These investigators recently reported the identification of a group of novel small compounds that inhibit basal glucose transport and reduce cancer cell growth by a glucose deprivation–like mechanism. These compounds target Glut1 and are efficacious in vivo as anticancer agents. A novel representative compound WZB117 not only inhibited cell growth in cancer cell lines but also inhibited cancer growth in a nude mouse model. Daily intraperitoneal injection of WZB117 resulted in a more than 70% reduction in the size of human lung cancer of A549 cell origin. Mechanism studies showed that WZB117 inhibited glucose transport in human red blood cells (RBC), which express Glut1 as their sole glucose transporter. Cancer cell treatment with WZB117 led to decreases in levels of Glut1 protein, intracellular ATP, and glycolytic enzymes. All these changes were followed by increase in ATP sensing enzyme AMP-activated protein kinase (AMPK) and declines in cyclin E2 as well as phosphorylated retinoblastoma, resulting in cell-cycle arrest, senescence, and necrosis. Addition of extracellular ATP rescued compound-treated cancer cells, suggesting that the reduction of intracellular ATP plays an important role in the anticancer mechanism of the molecule.

A Small-Molecule Inhibitor of Glucose Transporter 1 Downregulates Glycolysis, Induces Cell-Cycle Arrest, and Inhibits Cancer Cell Growth In Vitro and In Vivo

Yi Liu, Yanyan Cao, Weihe Zhang, Stephen Bergmeier, et al.
Mol Cancer Ther Aug 2012; 11(8): 1672–82
http://dx.doi.org://10.1158/1535-7163.MCT-12-0131

Alterations in cellular metabolism are among the most consistent hallmarks of cancer. These investigators have studied the relationship between increased aerobic lactate production and mitochondrial physiology in tumor cells. To diminish the ability of malignant cells to metabolize pyruvate to lactate, M-type lactate dehydrogenase levels were knocked down by means of LDH-A short hairpin RNAs. Reduction in LDH-A activity resulted in stimulation of mitochondrial respiration and decrease of mitochondrial membrane potential. It also compromised the ability of these tumor cells to proliferate under hypoxia. The tumorigenicity of the LDH-A-deficient cells was severely diminished, and this phenotype was reversed by complementation with the human ortholog LDH-A protein. These results demonstrate that LDH-A plays a key role in tumor maintenance.

The results are consistent with a functional connection between alterations in glucose metabolism and mitochondrial physiology in cancer. The data also reflect that the dependency of tumor cells on glucose metabolism is a liability for these cells under limited-oxygen conditions. Interfering with LDH-A activity as a means of blocking pyruvate to lactate conversion could be exploited therapeutically. Because individuals with complete deficiency of LDH-A do not show any symptoms under ordinary circumstances, the genetic data suggest that inhibition of LDH-A activity may represent a relatively nontoxic approach to interfere with tumor growth.

Attenuation of LDH-A expression uncovers a link between glycolysis, mitochondrial physiology, and tumor maintenance

Valeria R. Fantin Julie St-Pierre and Philip Leder
Cancer Cell Jun 2006; 9: 425–434.
http://dx.doi.org:/10.1016/j.ccr.2006.04.02

The widespread clinical use of positron-emission tomography (PET) for the detection of aerobic glycolysis in tumors and recent findings have rekindled interest in Warburg’s theory. Studies on the physiological changes in malignant conversion provided a metabolic signature for the different stages of tumorigenesis; during tumorigenesis, an increase in glucose uptake and lactate production have been detected. The fully transformed state is most dependent on aerobic glycolysis and least dependent on the mitochondrial machinery for ATP synthesis.

Tumors ferment glucose to lactate even in the presence of oxygen (aerobic glycolysis; Warburg effect). The pentose phosphate pathway (PPP) allows glucose conversion to ribose for nucleic acid synthesis and glucose degradation to lactate. The nonoxidative part of the PPP is controlled by transketolase enzyme reactions. We have detected upregulation of a mutated transketolase transcript (TKTL1) in human malignancies, whereas transketolase (TKT) and transketolase-like-2 (TKTL2) transcripts were not upregulated. Strong TKTL1 protein expression was correlated to invasive colon and urothelial tumors and to poor patients outcome. TKTL1 encodes a transketolase with unusual enzymatic properties, which are likely to be caused by the internal deletion of conserved residues. We propose that TKTL1 upregulation in tumors leads to enhanced, oxygen-independent glucose usage and a lactate based matrix degradation. As inhibition of transketolase enzyme reactions suppresses tumor growth and metastasis, TKTL1 could be the relevant target for novel anti-transketolase cancer therapies. We suggest an individualized cancer therapy based on the determination of metabolic changes in tumors that might enable the targeted inhibition of invasion and metastasis.

Other important links between cancer-causing genes and glucose metabolism have been already identified. Activation of the oncogenic kinase Akt has been shown to stimulate glucose uptake and metabolism in cancer cells and renders these cells susceptible to death in response to glucose withdrawal. Such tumor cells have been shown to be dependent on glucose because the ability to induce fatty acid oxidation in response to glucose deprivation is impaired by activated Akt. In addition, AMP-activated protein kinase (AMPK) has been identified as a link between glucose metabolism and the cell cycle, thereby implicating p53 as an essential component of metabolic cell-cycle control.

Expression of transketolase TKTL1 predicts colon and urothelial cancer patient survival: Warburg effect reinterpreted

S Langbein, M Zerilli, A zur Hausen, W Staiger, et al.
British Journal of Cancer (2006) 94, 578–585.
http://dx.doi.org:/10.1038/sj.bjc.6602962

The unique metabolic profile of cancer (aerobic glycolysis) might confer apoptosis resistance and be therapeutically targeted. Compared to normal cells, several human cancers have high mitochondrial membrane potential (DJm) and low expression of the K+ channel Kv1.5, both contributing toapoptosis resistance. Dichloroacetate (DCA) inhibits mitochondrial pyruvate dehydrogenase kinase (PDK), shifts metabolism from glycolysis to glucose oxidation, decreases DJm, increases mitochondrial H2O2, and activates Kv channels in all cancer, but not normal, cells; DCA upregulates Kv1.5 by an NFAT1-dependent mechanism. DCA induces apoptosis, decreases proliferation, and inhibits tumor growth, without apparent toxicity. Molecular inhibition of PDK2 by siRNA mimics DCA. The mitochondria-NFAT-Kv axis and PDK are important therapeutic targets in cancer; the orally available DCA is a promising selective anticancer agent.

Cancer progression and its resistance to treatment depend, at least in part, on suppression of apoptosis. Although mitochondria are recognized as regulators of apoptosis, their importance as targets for cancer therapy has not been adequately explored or clinically exploited. In 1930, Warburg suggested that mitochondrial dysfunction in cancer results in a characteristic metabolic phenotype, that is, aerobic glycolysis (Warburg, 1930). Positron emission tomography (PET) imaging has now confirmed that most malignant tumors have increased glucose uptake and metabolism. This bioenergetic feature is a good marker of cancer but has not been therapeutically pursued..

The small molecule DCA is a metabolic modulator that has been used in humans for decades in the treatment of lactic acidosis and inherited mitochondrial diseases. Without affecting normal cells, DCA reverses the metabolic electrical remodeling that we describe in several cancer lines (hyperpolarized mitochondria, activated NFAT1, downregulated Kv1.5), inducing apoptosis and decreasing tumor growth. DCA in the drinking water at clinically relevant doses for up to 3 months prevents and reverses tumor growth in vivo, without apparent toxicity and without affecting hemoglobin, transaminases, or creatinine levels. The ease of delivery, selectivity, and effectiveness  make DCA an attractive candidate for proapoptotic cancer therapy which can be rapidly translated into phase II–III clinical trials.

A Mitochondria-K+ Channel Axis Is Suppressed in Cancer and Its Normalization Promotes Apoptosis and Inhibits Cancer Growth

Sebastien Bonnet, Stephen L. Archer, Joan Allalunis-Turner, et al.

Cancer Cell Jan 2007; 11: 37–51.
http://dx.doi.org:/10.1016/j.ccr.2006.10.020

Tumor cells, just as other living cells, possess the potential for proliferation, differentiation, cell cycle arrest, and apoptosis. There is a specific metabolic phenotype associated with each of these conditions, characterized by the production of both energy and special substrates necessary for the cells to function in that particular state. Unlike that of normal living cells, the metabolic phenotype of tumor cells supports the proliferative state. Aim: To present the metabolic hypothesis that (1) cell transformation and tumor growth are associated with the activation of metabolic enzymes that increase glucose carbon utilization for nucleic acid synthesis, while enzymes of the lipid and amino acid synthesis pathways are activated in tumor growth inhibition, and (2) phosphorylation and allosteric and transcriptional regulation of intermediary metabolic enzymes and their substrate availability together mediate and sustain cell transformation from one condition to another. Conclusion: Evidence is presented that demonstrates opposite changes in metabolic phenotypes induced by TGF-β, a cell transforming agent, and tumor growth-inhibiting phytochemicals such as genistein and Avemar, or novel synthetic antileukemic drugs such as STI571 (Gleevec).  Intermediary metabolic enzymes that mediate the growth signaling pathways and promote malignant cell transformation may serve as high efficacy nongenetic novel targets for cancer therapies.

A Metabolic Hypothesis of Cell Growth and Death in Pancreatic Cancer

Laszlo G. Boros, Wai-Nang Paul Lee, and Vay Liang W. Go
Pancreas 2002; 24(1):26–33

Clear cell renal cell carcinoma (ccRCC) is the most common pathological subtype of kidney cancer. Here, we integrated an unbiased genome-wide RNA interference screen for ccRCC survival regulators with an analysis of recurrently overexpressed genes in ccRCC to identify new therapeutic targets in this disease. One of the most potent survival regulators, the monocarboxylate transporter MCT4 (SLC16A3), impaired ccRCC viability in all eight ccRCC lines tested and was the seventh most overexpressed gene in a meta-analysis of five ccRCC expression datasets.

MCT4 silencing impaired secretion of lactate generated through glycolysis and induced cell cycle arrest and apoptosis. Silencing MCT4 resulted in intracellular acidosis, and reduction in intracellular ATP production together with partial reversion of the Warburg effect in ccRCC cell lines. Intra-tumoral heterogeneity in the intensity of MCT4 protein expression was observed in primary ccRCCs.

MCT4 protein expression analysis based on the highest intensity of expression in primary ccRCCs was associated with poorer relapse-free survival, whereas modal intensity correlated with Fuhrman nuclear grade. Consistent with the potential selection of subclones enriched for MCT4 expression during disease progression, MCT4 expression was greater at sites of metastatic disease. These data suggest that MCT4 may serve as a novel metabolic target to reverse the Warburg effect and limit disease progression in ccRCC.

Clear cell carcinoma (ccRCC) is the commonest subtype of renal cell carcinoma, accounting for 80% of cases. These tumors are highly resistant to cytotoxic chemotherapy and until recently, systemic treatment options for advanced ccRCC were limited to cytokine based therapies, such as interleukin-2 and interferon-α. Recently, anti-angiogenic drugs and mTOR inhibitors, all targeting the HIF–VEGF axis which is activated in up to 91% of ccRCCs through loss of the VHL tumor suppressor gene [1], have been shown to be effective in metastatic ccRCC [2–5]. Although these drugs increase overall survival to more than 2 years [6], resistance invariably occurs, making the identification of new molecular targets a major clinical need to improve outcomes in patients with metastatic ccRCC.

Genome-wide RNA interference analysis of renal carcinoma survival regulators identifies MCT4 as a Warburg effect metabolic target

Marco Gerlinger, Claudio R Santos, Bradley Spencer-Dene, et al.
J Pathol 2012; 227: 146–156
http://dx.doi.org:/10.1002/path.4006

Hypoxia-inducible factor 1 (HIF-1) plays a key role in the reprogramming of cancer metabolism by activating transcription of genes encoding glucose transporters and glycolytic enzymes, which take up glucose and convert it to lactate; pyruvate dehydrogenase kinase 1, which shunts pyruvate away from the mitochondria; and BNIP3, which triggers selective mitochondrial autophagy. The shift from oxidative to glycolytic metabolism allows maintenance of redox homeostasis and cell survival under conditions of prolonged hypoxia. Many metabolic abnormalities in cancer cells increase HIF-1 activity. As a result, a feed-forward mechanism can be activated that drives HIF-1 activation and may promote tumor progression.

Metastatic cancer is characterized by reprogramming of cellular metabolism leading to increased uptake of glucose for use as both an anabolic and a catabolic substrate. Increased glucose uptake is such a reliable feature that it is utilized clinically to detect metastases by positron emission tomography using 18F-fluorodeoxyglucose (FDG-PET) with a sensitivity of >90% [1]. As with all aspects of cancer biology, the details of metabolic reprogramming differ widely among individual tumors. However, the role of specific signaling pathways and transcription factors in this process is now understood in considerable detail. This review will focus on the involvement of hypoxia-inducible factor 1 (HIF-1) in both mediating metabolic reprogramming and responding to metabolic alterations. The placement of HIF-1 both upstream and downstream of cancer metabolism results in a feed-forward mechanism that may play a major role in the development of the invasive, metastatic, and lethal cancer phenotype.

O2 concentrations are significantly reduced in many human cancers compared with the surrounding normal tissue. The median PO2 in breast cancers is 10 mmHg, as compared with65 mmHg in normal breast tissue. Reduced O2 availability induces HIF-1, which regulates the transcription of hundreds of genes that encode proteins involved in every aspect of cancer biology, including: cell immortalization and stem cell maintenance; genetic instability; glucose and energy metabolism; vascularization; autocrine growth factor signaling; invasion and metastasis; immune evasion; and resistance to chemotherapy and radiation therapy.

HIF-1 is a transcription factor that consists of an O2 regulated HIF-1a and a constitutively expressed HIF-1b subunit. In well-oxygenated cells, HIF-1a is hydroxylated on proline residue 402 (Pro-402) and/or Pro-564 by prolyl hydroxylase domain protein 2 (PHD2), which uses O2 and a-ketoglutarate as substrates in a reaction that generates CO2 and succinate as byproducts. Prolylhydroxylated HIF-1a is bound by the von Hippel–Lindau tumor suppressor protein (VHL), which recruits an E3-ubiquitin ligase that targets HIF-1a for proteasomal degradation (Figure 1a). Asparagine 803 in the transactivation domain is hydroxylated in well-oxygenated cells by factor inhibiting HIF-1 (FIH-1), which blocks the binding of the coactivators p300 and CBP. Under hypoxic conditions, the prolyl and asparaginyl hydroxylation reactions are inhibited by substrate (O2) deprivation and/or the mitochondrial generation of reactive oxygen species (ROS), which may oxidize Fe(II) present in the catalytic center of the hydroxylases.

The finding that acute changes in PO2 increase mitochondrial ROS production suggests that cellular respiration is optimized at physiological PO2 to limit ROS generation and that any deviation in PO2 – up or down – results in increased ROS generation. If hypoxia persists, induction of HIF-1 leads to adaptive mechanisms to reduce ROS and re-establish homeostasis, as described below. Prolyl and asparaginyl hydroxylation provide a molecular mechanism by which changes in cellular oxygenation can be transduced to the nucleus as changes in HIF-1 activity.

HIF-1: upstream and downstream of cancer metabolism

Gregg L Semenza
Current Opinion in Genetics & Development 2010, 20:51–56

This review comes from a themed issue on Genetic and cellular mechanisms of oncogenesis Edited by Tony Hunter and Richard Marais

http://dx.doi.org:/10.1016/j.gde.2009.10.009

Hypoxia-inducible factor 1 (HIF-1) regulates the transcription of many genes involved in key aspects of cancer biology, including immortalization, maintenance of stem cell pools, cellular dedifferentiation, genetic instability, vascularization, metabolic reprogramming, autocrine growth factor signaling, invasion/metastasis, and treatment failure. In animal models, HIF-1 overexpression is associated with increased tumor growth, vascularization, and metastasis, whereas HIF-1 loss-of-function has the opposite effect, thus validating HIF-1 as a target. In further support of this conclusion, immunohistochemical detection of HIF-1a overexpression in biopsy sections is a prognostic factor in many cancers. A growing number of novel anticancer agents have been shown to inhibit HIF-1 through a  variety of molecular mechanisms. Determining which combination of drugs to administer to any given patient remains a major obstacle to improving cancer treatment outcomes.

Intratumoral hypoxia The majority of locally advanced solid tumors contain regions of reduced oxygen availability. Intratumoral hypoxia results when cells are located too far from a functional blood vessel for diffusion of adequate amounts of O2 as a result of rapid cancer cell proliferation and the formation of blood vessels that are structurally and functionally abnormal. In the most extreme case, O2 concentrations are below those required for survival, resulting in cell death and establishing a selection for cancer cells in which apoptotic pathways are inactivated, anti-apoptotic pathways are activated, or invasion/metastasis pathways that promote escape from the hypoxic microenvironment are activated. This hypoxic adaptation may arise by alterations in gene expression or by mutations in the genome or both and is associated with reduced patient survival.

Hypoxia-inducible factor 1 (HIF-1) The expression of hundreds of genes is altered in each cell exposed to hypoxia. Many of these genes are regulated by HIF-1. HIF-1 is a heterodimer formed by the association of an O2-regulated HIF1a subunit with a constitutively expressed HIF-1b subunit. The structurally and functionally related HIF-2a protein also dimerizes with HIF-1b and regulates an overlapping battery of target genes. Under nonhypoxic conditions, HIF-1a (as well as HIF-2a) is subject to O2-dependent prolyl hydroxylation and this modification is required for binding of the von Hippel–Lindau tumor suppressor protein (VHL), which also binds to Elongin C and thereby recruits a ubiquitin ligase complex that targets HIF-1a for ubiquitination and proteasomal degradation. Under hypoxic conditions, the rate of hydroxylation and ubiquitination declines, resulting in accumulation of HIF-1a. Immunohistochemical analysis of tumor biopsies has revealed high levels of HIF-1a in hypoxic but viable tumor cells surrounding areas of necrosis.

Genetic alterations in cancer cells increase HIF-1 activity In the majority of clear-cell renal carcinomas, VHL function is lost, resulting in constitutive activation of HIF-1. After re-introduction of functional VHL, renal carcinoma cell lines are no longer tumorigenic, but can be made tumorigenic by expression of HIF2a in which the prolyl residues that are subject to hydroxylation have been mutated. In addition to VHL loss-of-function, many other genetic alterations that inactivate tumor suppressors

Evaluation of HIF-1 inhibitors as anticancer agents

Gregg L. Semenza
Drug Discovery Today Oct 2007; 12(19/20).
http://dx.doi.org:/10.1016/j.drudis.2007.08.006

Hypoxia-inducible factor-1 (HIF-1), which is present at high levels in human tumors, plays crucial roles in tumor promotion by upregulating its target genes, which are involved in anaerobic energy metabolism, angiogenesis, cell survival, cell invasion, and drug resistance. Therefore, it is apparent that the inhibition of HIF-1 activity may be a strategy for treating cancer. Recently, many efforts to develop new HIF-1-targeting agents have been made by both academic and pharmaceutical industry laboratories. The future success of these efforts will be a new class of HIF-1-targeting anticancer agents, which would improve the prognoses of many cancer patients. This review focuses on the potential of HIF-1 as a target molecule for anticancer therapy, and on possible strategies to inhibit HIF-1 activity. In addition, we introduce YC-1 as a new anti-HIF-1, anticancer agent. Although YC-1 was originally developed as a potential therapeutic agent for thrombosis and hypertension, recent studies demonstrated that YC-1 suppressed HIF-1 activity and vascular endothelial growth factor expression in cancer cells. Moreover, it halted tumor growth in immunodeficient mice without serious toxicity during the treatment period. Thus, we propose that YC-1 is a good lead compound for the development of new anti-HIF-1, anticancer agents.

Although many anticancer regimens have been introduced to date, their survival benefits are negligible, which is the reason that a more innovative treatment is required. Basically, the identification of the specific molecular features of tumor promotion has allowed for rational drug discovery in cancer treatment, and drugs have been screened based upon the modulation of specific molecular targets in tumor cells. Target-based drugs should satisfy the following two conditions.

First, they must act by a described mechanism.

Second, they must reduce tumor growth in vivo, associated with this mechanism.

Many key factors have been found to be involved in the multiple steps of cell growth signal-transduction pathways. Targeting these factors offers a strategy for preventing tumor growth; for example, competitors or antibodies blocking ligand–receptor interaction, and receptor tyrosine kinase inhibitors, downstream pathway inhibitors (i.e., RAS farnesyl transferase inhibitors, mitogen-activated protein kinase and mTOR inhibitors), and cell-cycle arresters (i.e., cyclin-dependent kinase inhibitors) could all be used to inhibit tumor growth.

In addition to the intracellular events, tumor environmental factors should be considered to treat solid tumors. Of these, hypoxia is an important cancer-aggravating factor because it contributes to the progression of a more malignant phenotype, and to the acquisition of resistance to radiotherapy and chemotherapy. Thus, transcription factors that regulate these hypoxic events are good targets for anticancer therapy and in particular HIF-1 is one of most compelling targets. In this paper, we introduce the roles of HIF-1 in tumor promotion and provide a summary of new anticancer strategies designed to inhibit HIF-1 activity.

New anticancer strategies targeting HIF-1

Eun-Jin Yeo, Yang-Sook Chun, Jong-Wan Park
Biochemical Pharmacology 68 (2004) 1061–1069
http://dx.doi.org:/10.1016/j.bcp.2004.02.040

Classical work in tumor cell metabolism focused on bioenergetics, particularly enhanced glycolysis and suppressed oxidative phosphorylation (the ‘Warburg effect’). But the biosynthetic activities required to create daughter cells are equally important for tumor growth, and recent studies are now bringing these pathways into focus. In this review, we discuss how tumor cells achieve high rates of nucleotide and fatty acid synthesis, how oncogenes and tumor suppressors influence these activities, and how glutamine metabolism enables macromolecular synthesis in proliferating cells.

Otto Warburg’s demonstration that tumor cells rapidly use glucose and convert the majority of it to lactate is still the most fundamental and enduring observation in tumor metabolism. His work, which ushered in an era of study on tumor metabolism focused on the relationship between glycolysis and cellular bioenergetics, has been revisited and expanded by generations of tumor biologists. It is now accepted that a high rate of glucose metabolism, exploited clinically by 18FDGPET scanning, is a metabolic hallmark of rapidly dividing cells, correlates closely with transformation, and accounts for a significant percentage of ATP generated during cell proliferation. A ‘metabolic transformation’ is required for tumorigenesis. Research over the past few years has reinforced this idea, revealing the conservation of metabolic activities among diverse tumor types, and proving that oncogenic mutations can promote metabolic autonomy by driving nutrient uptake to levels that often exceed those required for cell growth and proliferation.

In order to engage in replicative division, a cell must duplicate its genome, proteins, and lipids and assemble the components into daughter cells; in short, it must become a factory for macromolecular biosynthesis. These activities require that cells take up extracellular nutrients like glucose and glutamine and allocate them into metabolic pathways that convert them into biosynthetic precursors (Figure 1). Tumor cells can achieve this phenotype through changes in the expression of enzymes that determine metabolic flux rates, including nutrient transporters and enzymes [8– 10]. Current studies in tumor metabolism are revealing novel mechanisms for metabolic control, establishing which enzyme isoforms facilitate the tumor metabolic phenotype, and suggesting new targets for cancer therapy.

The ongoing challenge in tumor cell metabolism is to understand how individual pathways fit together into the global metabolic phenotype of cell growth. Here we discuss two biosynthetic activities required by proliferating tumor cells: production of ribose-5 phosphate for nucleotide biosynthesis and production of fatty acids for lipid biosynthesis. Nucleotide and lipid biosynthesis share three important characteristics.

  • First, both use glucose as a carbon source.
  • Second, both consume TCA cycle intermediates, imposing the need for a mechanism to replenish the cycle.
  • Third, both require reductive power in the form of NADPH.

In this Essay, we discuss the possible drivers, advantages, and potential liabilities of the altered metabolism of cancer cells (Figure 1, not shown). Although our emphasis on the Warburg effect reflects the focus of the field, we would also like to encourage a broader approach to the study of cancer metabolism that takes into account the contributions of all interconnected small molecule pathways of the cell.

The Tumor Microenvironment Selects for Altered Metabolism One compelling idea to explain the Warburg effect is that the altered metabolism of cancer cells confers a selective advantage for survival and proliferation in the unique tumor microenvironment. As the early tumor expands, it outgrows the diffusion limits of its local blood supply, leading to hypoxia and stabilization of the hypoxia-inducible transcription factor, HIF. HIF initiates a transcriptional program that provides multiple solutions to hypoxic stress (reviewed in Kaelin and Ratcliffe, 2008). Because a decreased dependence on aerobic respiration becomes advantageous, cell metabolism is shifted toward glycolysis by the increased expression of glycolytic enzymes, glucose transporters, and inhibitors of mitochondrial metabolism. In addition, HIF stimulates angiogenesis (the formation of new blood vessels) by upregulating several factors, including most prominently vascular endothelial growth factor (VEGF).

Blood vessels recruited to the tumor microenvironment, however, are disorganized, may not deliver blood effectively, and therefore do not completely alleviate hypoxia (reviewed in Gatenby and Gillies, 2004). The oxygen levels within a tumor vary both spatially and temporally, and the resulting rounds of fluctuating oxygen levels potentially select for tumors that constitutively upregulate glycolysis. Interestingly, with the possible exception of tumors that have lost the von Hippel-Lindau protein (VHL), which normally mediates degradation of HIF, HIF is still coupled to oxygen levels, as evident from the heterogeneity of HIF expression within the tumor microenvironment. Therefore, the Warburg effect—that is, an uncoupling of glycolysis from oxygen levels—cannot be explained solely by upregulation of HIF. Other molecular mechanisms are likely to be important, such as the metabolic changes induced by oncogene activation and tumor suppressor loss.

Oncogene Activation Drives Changes in Metabolism Not only may the tumor microenvironment select for a deranged metabolism, but oncogene status can also drive metabolic changes. Since Warburg’s time, the biochemical study of cancer metabolism has been overshadowed by efforts to identify the mutations that contribute to cancer initiation and progression. Recent work, however, has demonstrated that the key components of the Warburg effect—

  • increased glucose consumption,
  • decreased oxidative phosphorylation, and
  • accompanying lactate production—
  • are also distinguishing features of oncogene activation.

The signaling molecule Ras, a powerful oncogene when mutated, promotes glycolysis (reviewed in Dang and Semenza, 1999; Ramanathan et al., 2005). Akt kinase, a well-characterized downstream effector of insulin signaling, reprises its role in glucose uptake and utilization in the cancer setting (reviewed in Manning and Cantley, 2007), whereas the Myc transcription factor upregulates the expression of various metabolic genes (reviewed in Gordan et al., 2007). The most parsimonious route to tumorigenesis may be activation of key oncogenic nodes that execute a proliferative program, of which metabolism may be one important arm. Moreover, regulation of metabolism is not exclusive to oncogenes.

Cancer Cell Metabolism: Warburg & Beyond

Hsu PP & Sabatini DM
Cell  Sep 5, 2008; 134, 703-705
http://dx.doi.org:/10.1016/j.cell.2008.08.021

Tumor cells respond to growth signals by the activation of protein kinases, altered gene expression and significant modifications in substrate flow and redistribution among biosynthetic pathways. This results in a proliferating phenotype with altered cellular function. These transformed cells exhibit unique anabolic characteristics, which includes increased and preferential utilization of glucose through the non-oxidative steps of the pentose cycle for nucleic acid synthesis but limited de novo fatty  acid   synthesis   and   TCA   cycle   glucose   oxidation. This  primarily nonoxidative anabolic profile reflects an undifferentiated highly proliferative aneuploid cell phenotype and serves as a reliable metabolic biomarker to determine cell proliferation rate and the level of cell transformation/differentiation in response to drug treatment.

Novel drugs effective in particular cancers exert their anti-proliferative effects by inducing significant reversions of a few specific non-oxidative anabolic pathways. Here we present evidence that cell transformation of various mechanisms is sustained by a unique disproportional substrate distribution between the two branches of the pentose cycle for nucleic acid synthesis, glycolysis and the TCA cycle for fatty acid synthesis and glucose oxidation. This can be demonstrated by the broad labeling and unique specificity of [1,2-13C2]glucose to trace a large number of metabolites in the metabolome. Stable isotope-based dynamic metabolic profiles (SIDMAP) serve the drug discovery process by providing a powerful new tool that integrates the metabolome into a functional genomics approach to developing new drugs. It can be used in screening kinases and their metabolic targets, which can therefore be more efficiently characterized, speeding up and improving drug testing, approval and labeling processes by saving trial and error type study costs in drug testing.

Metabolic Biomarker and Kinase Drug Target Discovery in Cancer Using Stable Isotope-Based Dynamic Metabolic Profiling (SIDMAP)

László G. Boros, Daniel J. Brackett and George G. Harrigan
Current Cancer Drug Targets, 2003, 3, 447-455 447

Pyruvate constitutes a critical branch point in cellular carbon metabolism. We have identified two proteins, Mpc1 and Mpc2, as essential for mitochondrial pyruvate transport in yeast, Drosophila, and humans. Mpc1 and Mpc2 associate to form an ~150 kilodalton complex in the inner mitochondrial membrane. Yeast and Drosophila mutants lacking MPC1 display impaired pyruvate metabolism, with an accumulation of upstream metabolites and a depletion of tricarboxylic acid cycle intermediates. Loss of yeast Mpc1 results in defective mitochondrial pyruvate uptake, while silencing of MPC1 or MPC2 in mammalian cells impairs pyruvate oxidation. A point mutation in MPC1 provides resistance to a known inhibitor of the mitochondrial pyruvate carrier. Human genetic studies of three families with children suffering from lactic acidosis and hyperpyruvatemia revealed a causal locus that mapped to MPC1, changing single amino acids that are conserved throughout eukaryotes. These data demonstrate that Mpc1 and Mpc2 form an essential part of the mitochondrial pyruvate carrier.

A Mitochondrial Pyruvate Carrier Required for Pyruvate Uptake in Yeast, Drosophila , and Humans

Daniel K. Bricker, Eric B. Taylor, John C. Schell, Thomas Orsak, et al.
Science Express 24 May 2012
http://dx.doi.org:/10.1126/science.1218099

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

Review ADAR Enzyme and miRNA Story: A Nucleotide that Can Make the Difference 

Sara Tomaselli, Barbara Bonamassa, Anna Alisi, Valerio Nobili, Franco Locatelli and Angela Gallo
Int. J. Mol. Sci. 19 Nov 2013; 14, 22796-22816 http://dx.doi.org:/10.3390/ijms141122796

The fermented wheat germ extract (FWGE) nutraceutical (Avemar™), manufactured under “good manufacturing practice” conditions and, fulfilling the self-affirmed “generally recognized as safe” status in the United States, has been approved as a “dietary food for special medical purposes for cancer patients” in Europe. In this paper, we report the adjuvant use of this nutraceutical in the treatment of high-risk skin melanoma patients. Methods: In a randomized, pilot, phase II clinical trial, the efficacy of dacarbazine (DTIC)-based adjuvant chemotherapy on survival parameters of melanoma patients was compared to that of the same treatment supplemented with a 1-year long administration of FWGE. Results: At the end of an additional 7-year-long follow-up period, log-rank analyses (Kaplan-Meier estimates) showed significant differences in both progression-free (PFS) and overall survival (OS) in favor of the FWGE group. Mean PFS: 55.8 months (FWGE group) versus 29.9 months (control group), p  0.0137. Mean OS: 66.2 months (FWGE group) versus 44.7 months (control group), p < 0.0298. Conclusions: The inclusion of Avemar into the adjuvant protocols of high-risk skin melanoma patients is highly recommended.

Adjuvant Fermented Wheat Germ Extract (Avemar™) Nutraceutical Improves Survival of High-Risk Skin Melanoma Patients: A Randomized, Pilot, Phase II Clinical Study with a 7-Year Follow-Up

LV Demidov, LV Manziuk, GY Kharkevitch, NA Pirogova, and EV Artamonova
Cancer Biotherapy & Radiopharmaceuticals 2008; 23(4)
http://dx.doi.org:/10.1089/cbr.2008.0486

Cancer cells possess unique metabolic signatures compared to normal cells, including shifts in aerobic glycolysis, glutaminolysis, and de novo biosynthesis of macromolecules. Targeting these changes with agents (drugs and dietary components) has been employed as strategies to reduce the complications associated with tumorigenesis. This paper highlights the ability of several food components to suppress tumor-specific metabolic pathways, including increased expression of glucose transporters, oncogenic tyrosine kinase, tumor-specific M2-type pyruvate kinase, and fatty acid synthase, and the detection of such effects using various metabonomic technologies, including liquid chromatography/mass spectrometry (LC/MS) and stable isotope-labeled MS. Stable isotope-mediated tracing technologies offer exciting opportunities for defining specific target(s) for food components. Exposures, especially during the early transition phase from normal to cancer, are critical for the translation of knowledge about food components into effective prevention strategies. Although appropriate dietary exposures needed to alter cellular metabolism remain inconsistent and/or ill-defined, validated metabonomic biomarkers for dietary components hold promise for establishing effective strategies for cancer prevention.

Bioactive Food Components and Cancer-Specific Metabonomic Profiles

Young S. Kim and John A. Milner
Journal of Biomedicine and Biotechnology 2011, Art ID 721213, 9 pages
http://dx.doi.org:/10.1155/2011/721213

This reviewer poses the following observation.  The importance of the pyridine nucleotide reduced/oxidized ratio has not been alluded to here, but the importance cannot be understated. It has relevance to the metabolic functions of anabolism and catabolism of the visceral organs.  The importance of this has ties to the pentose monophosphate pathway. The importance of the pyridine nucleotide transhydrogenase reaction remains largely unexplored.  In reference to the NAD-redox state, the observation was made by Nathan O. Kaplan that the organs may be viewed with respect to their primary functions in anabolic or high energy catabolic activities. Thus we find that the endocrine organs are largely tied to anabolic functioning, and to NADP, whereas cardiac and skeletal muscle are highly dependent on NAD. The consequence of this observed phenomenon appears to be related to a difference in the susceptibility to malignant transformation.  In the case of the gastrointestinal tract, the rate of turnover of the epithelium is very high. However, with the exception of the liver, there is no major activity other than cell turnover. In the case of the liver, there is a major commitment to synthesis of lipids, storage of fuel, and synthesis of proteins, which is largely anabolic, but there is also a major activity in detoxification, which is not.  In addition, the liver has a double circulation. As a result, a Zahn infarct is uncommon.  Now we might also consider the heart.  The heart is a muscle syncytium with a high need for oxygen.  Cutting of the oxygen supply makes the myocytes vulnerable to ischemic insult and abberant rhythm abnormalities.  In addition, the cardiomyocyte can take up lactic acid from the circulation for fuel, which is tied to the utilization of lactate from vigorous skeletal muscle activity.  The skeletal muscle is tied to glycolysis in normal function, which has a poor generation of ATP, so that the recycling of excess lactic acid is required by cardiac muscle and hepatocytes.  This has not been a part of the discussion, but this reviewer considers it important to remember in considering the organ-specific tendencies to malignant transformation.

Comment (Aurelian Udristioiu):

Otto Warburg observed that many cancers lose their capacity for mitochondrial respiration, limiting ATP production to anaerobic glycolytic pathways. The phenomenon is particularly prevalent in aggressive malignancies, most of which are also hypoxic [1].
Hypoxia induces a stochastic imbalance between the numbers of reduced mitochondrial species vs. available oxygen, resulting in increased reactive oxygen species (ROS) whose toxicity can lead to apoptotic cell death.
Mechanism involves inhibition of glycolytic ATP production via a Randle-like cycle while increased uncoupling renders cancers unable to produce compensatory ATP from respiration-.generation in the presence of intact tricarboxylic acid (TCA) enzyme.
One mitochondrial adaptation to increased ROS is over-expression of the uncoupling protein 2 (UCP2) that has been reported in multiple human cancer cell lines [2-3]. Increased UCP2 expression was also associated with reduced ATP production in malignant oxyphilic mouse leukemia and human lymphoma cell lines [4].
Hypoxia reduces the ability of cells to maintain their energy levels, because less ATP is obtained from glycolysis than from oxidative phosphorylation. Cells adapt to hypoxia by activating the expression of mutant genes in glycolysis.
-Severe hypoxia causes a high mutation rate, resulting in point mutations that may be explained by reduced DNA mismatch repairing activity.
The most direct induction of apoptosis caused by hypoxia is determined by the inhibition of the electron carrier chain from the inner membrane of the mitochondria. The lack of oxygen inhibits the transport of protons and thereby causes a decrease in membrane potential. Cell survival under conditions of mild hypoxia is mediated by phosphoinositide-3 kinase (PIK3) using severe hypoxia or anoxia, and then cells initiate a cascade of events that lead to apoptosis [5].
After DNA damage, a very important regulator of apoptosis is the p53 protein. This tumor suppressor gene has mutations in over 60% of human tumors and acts as a suppressor of cell division. The growth-suppressive effects of p53 are considered to be mediated through the transcriptional trans-activation activity of the protein. In addition to the maturational state of the clonal tumor, the prognosis of patients with CLL is dependent of genetic changes within the neoplastic cell population.

1.Warburg O. On the origin of cancer cells. Science 1956; 123 (3191):309-314
PubMed Abstract ; Publisher Full Text

2.Giardina TM, Steer JH, Lo SZ, Joyce DA. Uncoupling protein-2 accumulates rapidly in the inner mitochondrial membrane during mitochondrial reactive oxygen stress in macrophages. Biochim Biophys Acta 2008, 1777(2):118-129. PubMed Abstract | Publisher Full Text

3. Horimoto M, Resnick MB, Konkin TA, Routhier J, Wands JR, Baffy G. Expression of uncoupling protein-2 in human colon cancer. Clin Cancer Res 2004; 10 (18 Pt1):6203-6207. PubMed Abstract | Publisher Full Text

4. Randle PJ, England PJ, Denton RM. Control of the tricarboxylate cycle and it interactions with glycolysis during acetate utilization in rat heart. Biochem J 1970; 117(4):677-695. PubMed Abstract | PubMed Central Full Text

5. Gillies RJ, Robey I, Gatenby RA. Causes and consequences of increased glucose metabolism of cancers. J Nucl Med 2008; 49(Suppl 2):24S-42S. PubMed Abstract | Publisher Full Text

Shortened version of Comment –

Hypoxia induces a stochastic imbalance between the numbers of reduced mitochondrial species vs. available oxygen, resulting in increased reactive oxygen species (ROS) whose toxicity can lead to apoptotic cell death.
Mechanism involves inhibition of glycolytic ATP production via a Randle-like cycle while increased uncoupling renders cancers unable to produce compensatory ATP from respiration-.generation in the presence of intact tricarboxylic acid (TCA) enzyme.
One mitochondrial adaptation to increased ROS is over-expression of the uncoupling protein 2 (UCP2) that has been reported in multiple human cancer cell lines. Increased UCP2 expression was also associated with reduced ATP production in malignant oxyphilic mouse leukemia and human lymphoma cell lines.
Severe hypoxia causes a high mutation rate, resulting in point mutations that may be explained by reduced DNA mismatch repairing activity.

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The Colors of Respiration and Electron Transport

Reporter & Curator: Larry H. Bernstein, MD, FCAP 

 

 

Molecular Biology of the Cell. 4th edition

Electron-Transport Chains and Their Proton Pumps
http://www.ncbi.nlm.nih.gov/books/NBK26904/

Having considered in general terms how a mitochondrion uses electron
transport to create an electrochemical proton gradient, we need to
examine the mechanisms that underlie this membrane-based energy-conversion process. In doing so, we also accomplish a larger purpose.
As emphasized at the beginning of this chapter, very similar chemi-
osmotic mechanisms are used by mitochondria, chloroplasts, archea,
and bacteria. In fact, these mechanisms underlie the function of nearly
all living organisms— including anaerobes that derive all their energy
from electron transfers between two inorganic molecules. It is therefore
rather humbling for scientists to remind themselves that the existence
of chemiosmosis has been recognized for only about 40 years.

mitochondria

mitochondria

 

Overview of The Electron Transport Chain

Overview of The Electron Transport Chain

We begin with a look at some of the principles that underlie the electron-transport process, with the aim of explaining how it can pump protons
across a membrane.

Although protons resemble other positive ions such as Na+ and K+
in their movement across membranes, in some respects they are unique.
Hydrogen atoms are by far the most abundant type of atom in living
organisms; they are plentiful not only in all carbon-containing
biological molecules, but also in the water molecules that surround
them. The protons in water are highly mobile, flickering through the
hydrogen-bonded network of water molecules by rapidly
dissociating from one water molecule to associate with its neighbor,
as illustrated in Figure 14-20A. Protons are thought to move across a
protein pump embedded in a lipid bilayer in a similar way: they
transfer from one amino acid side chain to another, following a
special channel through the protein.

Protons are also special with respect to electron transport. Whenever
a molecule is reduced by acquiring an electron, the electron (e -) brings
with it a negative charge. In many cases, this charge is rapidly
neutralized by the addition of a proton (H+) from water, so that
the net effect of the reduction is to transfer an entire hydrogen atom,
H+ + e – (Figure 14-20B). Similarly, when a molecule is oxidized,
a hydrogen atom removed from it can be readily dissociated into
its constituent electron and proton—allowing the electron to
be transferred separately to a molecule that accepts electrons,
while the proton is passed to the water. Therefore, in a membrane
in which electrons are being passed along an electron-transport
chain, pumping protons from one side of the membrane to
another can be relatively simple. The electron carrier merely
needs to be arranged in the membrane in a way that causes it to
pick up a proton from one side of the membrane when it accepts
an electron, and to release the proton on the other side of the
membrane as the electron is passed to the next carrier molecule
in the chain (Figure 14-21).

protons pumped across membranes ch14f21

protons pumped across membranes ch14f21

http://www.ncbi.nlm.nih.gov/books/NBK26904/bin/ch14f21.gif

Figure 14-21

How protons can be pumped across membranes. As an electron
passes along an electron-transport chain embedded in a lipid-bilayer
membrane, it can bind and release a proton at each step.
In this diagram, electron carrier B picks up a proton (H+)
from one (more…)

e_transfer

e_transfer

The Redox Potential Is a Measure of Electron Affinities

In biochemical reactions, any electrons removed from one
molecule are always passed to another, so that whenever one
molecule is oxidized, another is reduced. Like any other chemical r
eaction, the tendency of such oxidation-reduction reactions, or
redox reactions, to proceed spontaneously depends on the free-
energy change (ΔG) for the electron transfer, which in turn
depends on the relative affinities of the two molecules for electrons.

Because electron transfers provide most of the energy for living
things, it is worth spending the time to understand them. Many
readers are already familiar with acids and bases, which donate
and accept protons (see Panel 2-2, pp. 112–113). Acids and bases
exist in conjugate acid-base pairs, in which the acid is readily
converted into the base by the loss of a proton. For example,
acetic acid (CH3COOH) is converted into its conjugate base
(CH3COO-) in the reaction:

Image ch14e3.jpg

In exactly the same way, pairs of compounds such as NADH and
NAD+ are called redox pairs, since NADH is converted to NAD+
by the loss of electrons in the reaction:

Image ch14e4.jpg

NAD+_NADH

NAD+_NADH

NADH is a strong electron donor: because its electrons are held
in a high-energy linkage, the free-energy change for passing its
electrons to many other molecules is favorable (see Figure 14-9).
It is difficult to form a high-energy linkage. Therefore its redox
partner, NAD+, is of necessity a weak electron acceptor.

The tendency to transfer electrons from any redox pair can be
measured experimentally. All that is required is the formation
of an electrical circuit linking a 1:1 (equimolar) mixture of the
redox pair to a second redox pair that has been arbitrarily selected
as a reference standard, so the voltage difference can be measured
between them (Panel 14-1, p. 784). This voltage difference is
defined as the redox potential; as defined, electrons move
spontaneously from a redox pair like NADH/NAD+ with a low
redox potential (a low affinity for electrons) to a redox pair like
O2/H2O with a high redox potential (a high affinity for electrons).
Thus, NADH is a good molecule for donating electrons to the
respiratory chain, while O2 is well suited to act as the “sink” for
electrons at the end of the pathway. As explained in Panel 14-1,
the difference in redox potential, ΔE0′, is a direct measure of
the standard free-energy change (ΔG°) for the transfer of an
electron from one molecule to another.

Proteins of inner space

Proteins of inner space

energetics-of-cellular-respiration

energetics-of-cellular-respiration

Box Icon

Panel 14-1

Redox Potentials.

Electron Transfers Release Large Amounts of Energy

As just discussed, those pairs of compounds that have the most negative
redox potentials have the weakest affinity for electrons and therefore
contain carriers with the strongest tendency to donate electrons.
Conversely, those pairs that have the most positive redox potentials
have the strongest affinity for electrons and therefore contain carriers
with the strongest tendency to accept electrons. A 1:1 mixture of NADH
and NAD+ has a redox potential of -320 mV, indicating that NADH has
a strong tendency to donate electrons; a 1:1 mixture of H2O and ½O2
has a redox potential of +820 mV, indicating that O2 has a strong
tendency to accept electrons. The difference in redox potential is
1.14 volts (1140 mV), which means that the transfer of each electron
from NADH to O2 under these standard conditions is enormously
favorable, where ΔG° = -26.2 kcal/mole (-52.4 kcal/mole for the two
electrons transferred per NADH molecule; see Panel 14-1). If we
compare this free-energy change with that for the formation of the
phosphoanhydride bonds in ATP (ΔG° = -7.3 kcal/mole, see Figure 2-75), we see that more than enough energy is released by the oxidization
of one NADH molecule to synthesize several molecules of ATP from
ADP and Pi.

 Phosphate dependence of pyruvate oxidation

Phosphate dependence of pyruvate oxidation

Living systems could certainly have evolved enzymes that would
allow NADH to donate electrons directly to O2 to make water in the reaction:

Image ch14e5.jpg

But because of the huge free-energy drop, this reaction would proceed
with almost explosive force and nearly all of the energy would be released
as heat. Cells do perform this reaction, but they make it proceed much
more gradually by passing the high-energy electrons from NADH to
O2 via the many electron carriers in the electron-transport chain.
Since each successive carrier in the chain holds its electrons more
tightly, the highly energetically favorable reaction 2H+ + 2e – + ½O2
→ H2O is made to occur in many small steps. This enables nearly half
of the released energy to be stored, instead of being lost to the
environment as heat.

Spectroscopic Methods Have Been Used to Identify Many Electron
Carriers in the Respiratory Chain

Many of the electron carriers in the respiratory chain absorb visible
light and change color when they are oxidized or reduced. In general,
each has an absorption spectrum and reactivity that are distinct enough
to allow its behavior to be traced spectroscopically, even in crude mixtures.
It was therefore possible to purify these components long before their
exact functions were known. Thus, the cytochromes were discovered
in 1925 as compounds that undergo rapid oxidation and reduction in
living organisms as disparate as bacteria, yeasts, and insects. By observing
cells and tissues with a spectroscope, three types of cytochromes were
identified by their distinctive absorption spectra and designated
cytochromes a, b, and c. This nomenclature has survived, even though
cells are now known to contain several cytochromes of each type and
the classification into types is not functionally important.

The cytochromes constitute a family of colored proteins that are
related by the presence of a bound heme group, whose iron atom
changes from the ferric oxidation state (Fe3+) to the ferrous oxidation
state (Fe2+) whenever it accepts an electron. The heme group consists
of a porphyrin ring with a tightly bound iron atom held by four nitrogen
atoms at the corners of a square (Figure 14-22). A similar porphyrin ring
is responsible for the red color of blood and for the green color of
leaves, being bound to iron in hemoglobin and to magnesium in
chlorophyll, respectively.

The structure of the heme group attached covalently to cytochrome c ch14f22

The structure of the heme group attached covalently to cytochrome c ch14f22

http://www.ncbi.nlm.nih.gov/books/NBK26904/bin/ch14f22.jpg

Figure 14-22. The structure of the heme group attached covalently
to cytochrome c.

Figure 14-22

The structure of the heme group attached covalently to cytochrome c.
The porphyrin ring is shown in blue. There are five different
cytochromes in the respiratory chain. Because the hemes in different
cytochromes have slightly different structures and (more…)

Iron-sulfur proteins are a second major family of electron carriers. In these
proteins, either two or four iron atoms are bound to an equal number of
sulfur atoms and to cysteine side chains, forming an iron-sulfur center
on the protein (Figure 14-23). There are more iron-sulfur centers than
cytochromes in the respiratory chain. But their spectroscopic detection
requires electron spin resonance (ESR) spectroscopy, and they are less
completely characterized. Like the cytochromes, these centers carry one
electron at a time.

structure of iron sulfur centers ch14f23

structure of iron sulfur centers ch14f23

http://www.ncbi.nlm.nih.gov/books/NBK26904/bin/ch14f23.jpg

Figure 14-23. The structures of two types of iron-sulfur centers.

Figure 14-23

The structures of two types of iron-sulfur centers. (A) A center of the
2Fe2S type. (B) A center of the 4Fe4S type. Although they contain
multiple iron atoms, each iron-sulfur center can carry only one
electron at a time. There are more than seven different (more…)

The simplest of the electron carriers in the respiratory chain—and
the only one that is not part of a protein—is a small hydrophobic
molecule that is freely mobile in the lipid bilayer known as ubiquinone,
or coenzyme Q. A quinone (Q) can pick up or donate either one or
two electrons; upon reduction, it picks up a proton from the medium
along with each electron it carries (Figure 14-24).

quinone electron carriers ch14f24

quinone electron carriers ch14f24

http://www.ncbi.nlm.nih.gov/books/NBK26904/bin/ch14f24.jpg

Figure 14-24. Quinone electron carriers.

Figure 14-24

Quinone electron carriers. Ubiquinone in the respiratory chain picks
up one H+ from the aqueous environment for every electron it accepts,
and it can carry either one or two electrons as part of a hydrogen atom
(yellow). When reduced ubiquinone donates (more…)

In addition to six different hemes linked to cytochromes, more than
seven iron-sulfur centers, and ubiquinone, there are also two copper
atoms and a flavin serving as electron carriers tightly bound to respiratory-chain proteins in the pathway from NADH to oxygen. This pathway
involves more than 60 different proteins in all.

As one would expect, the electron carriers have higher and higher
affinities for electrons (greater redox potentials) as one moves along
the respiratory chain. The redox potentials have been fine-tuned
during evolution by the binding of each electron carrier in a particular
protein context, which can alter its normal affinity for electrons. However,
because iron-sulfur centers have a relatively low affinity for electrons,
they predominate in the early part of the respiratory chain; in contrast,
the cytochromes predominate further down the chain, where a higher
affinity for electrons is required.

The order of the individual electron carriers in the chain was
determined by sophisticated spectroscopic measurements (Figure 14-25),
and many of the proteins were initially isolated and characterized as
individual polypeptides. A major advance in understanding the
respiratory chain, however, was the later realization that most of
the proteins are organized into three large enzyme complexes.

path of electrons ch14f25

path of electrons ch14f25

http://www.ncbi.nlm.nih.gov/books/NBK26904/bin/ch14f25.gif

Figure 14-25. The general methods used to determine the path of
electrons along an electron-transport chain.

Figure 14-25

The general methods used to determine the path of electrons along
an electron-transport chain. The extent of oxidation of electron
carriers a, b, c, and d is continuously monitored by following their
distinct spectra, which differ in their oxidized and (more…)

The Respiratory Chain Includes Three Large Enzyme Complexes
Embedded in the Inner Membrane

Membrane proteins are difficult to purify as intact complexes
because they are insoluble in aqueous solutions, and some of
the detergents required to solubilize them can destroy normal
protein-protein interactions. In the early 1960s, however, it
was found that relatively mild ionic detergents, such as deoxycholate,
can solubilize selected components of the inner mitochondrial
membrane in their native form. This permitted the identification
and purification of the three major membrane-bound respiratory
enzyme complexes in the pathway from NADH to oxygen (Figure 14-26).
As we shall see in this section, each of these complexes acts as an
electron-transport-driven H+ pump; however, they were
initially characterized in terms of the electron carriers that
they interact with and contain:

mitochondrial oxidative phosphorylation

mitochondrial oxidative phosphorylation

http://www.ncbi.nlm.nih.gov/books/NBK26904/bin/ch14f26.gif

Figure 14-26. The path of electrons through the three respiratory
enzyme complexes.

Figure 14-26

The path of electrons through the three respiratory enzyme complexes.
The relative size and shape of each complex are shown. During the
transfer of electrons from NADH to oxygen (red lines), ubiquinone
and cytochrome c serve as mobile carriers that ferry (more…)

The NADH dehydrogenase complex (generally known as complex I)
is the largest of the respiratory enzyme complexes, containing more
than 40 polypeptide chains. It accepts electrons from NADH and
passes them through a flavin and at least seven iron-sulfur centers
to ubiquinone. Ubiquinone then transfers its electrons to a second
respiratory enzyme complex, the cytochrome b-c1 complex.

The cytochrome b-c1 complex contains at least 11 different
polypeptide chains and functions as a dimer. Each monomer
contains three hemes bound to cytochromes and an iron-sulfur
protein. The complex accepts electrons from ubiquinone
and passes them on to cytochrome c, which carries its electron
to the cytochrome oxidase complex.

The cytochrome oxidase complex also functions as a dimer; each
monomer contains 13 different polypeptide chains, including two
cytochromes and two copper atoms. The complex accepts one electron
at a time from cytochrome c and passes them four at a time to oxygen.

The cytochromes, iron-sulfur centers, and copper atoms can carry
only one electron at a time. Yet each NADH donates two electrons,
and each O2 molecule must receive four electrons to produce water.
There are several electron-collecting and electron-dispersing points
along the electron-transport chain where these changes in electron
number are accommodated. The most obvious of these is cytochrome
oxidase.

An Iron-Copper Center in Cytochrome Oxidase Catalyzes Efficient
O2 Reduction

Because oxygen has a high affinity for electrons, it releases a
large amount of free energy when it is reduced to form water.
Thus, the evolution of cellular respiration, in which O2 is
converted to water, enabled organisms to harness much more
energy than can be derived from anaerobic metabolism. This
is presumably why all higher organisms respire. The ability of
biological systems to use O2 in this way, however, requires a
very sophisticated chemistry. We can tolerate O2 in the air we
breathe because it has trouble picking up its first electron; this
fact allows its initial reaction in cells to be controlled closely by
enzymatic catalysis. But once a molecule of O2 has picked up one
electron to form a superoxide radical (O2 -), it becomes dangerously
reactive and rapidly takes up an additional three electrons wherever
it can find them. The cell can use O2 for respiration only because
cytochrome oxidase holds onto oxygen at a special bimetallic
center, where it remains clamped between a heme-linked iron
atom and a copper atom until it has picked up a total of four electrons.
Only then can the two oxygen atoms of the oxygen molecule be
safely released as two molecules of water (Figure 14-27).

Figure 14-27. The reaction of O2 with electrons in cytochrome oxidase.

Figure 14-27

The reaction of O2 with electrons in cytochrome oxidase. As indicated,
the iron atom in heme a serves as an electron queuing point; this
heme feeds four electrons into an O2 molecule held at the bimetallic
center active site, which is formed by the other (more…)

The cytochrome oxidase reaction is estimated to account for 90%
of the total oxygen uptake in most cells. This protein complex is
therefore crucial for all aerobic life. Cyanide and azide are extremely
toxic because they bind tightly to the cell’s cytochrome oxidase
complexes to stop electron transport, thereby greatly reducing
ATP production.

Although the cytochrome oxidase in mammals contains 13
different protein subunits, most of these seem to have a subsidiary
role, helping to regulate either the activity or the assembly of the
three subunits that form the core of the enzyme. The complete
structure of this large enzyme complex has recently been determined
by x-ray crystallography, as illustrated in Figure 14-28. The atomic
resolution structures, combined with mechanistic studies of the effect
of precisely tailored mutations introduced into the enzyme by genetic
engineering of the yeast and bacterial proteins, are revealing the
detailed mechanisms of this finely tuned protein machine.

Figure 14-28. The molecular structure of cytochrome oxidase.

Figure 14-28

The molecular structure of cytochrome oxidase. This protein
is a dimer formed from a monomer with 13 different protein
subunits (monomer mass of 204,000 daltons). The three colored
subunits are encoded by the mitochondrial genome, and they
form the functional (more…)

Electron Transfers Are Mediated by Random Collisions in
the Inner Mitochondrial Membrane

The two components that carry electrons between the three
major enzyme complexes of the respiratory chain—ubiquinone
and cytochrome c—diffuse rapidly in the plane of the inner
mitochondrial membrane. The expected rate of random collisions
between these mobile carriers and the more slowly diffusing
enzyme complexes can account for the observed rates of electron
transfer (each complex donates and receives an electron about
once every 5–20 milliseconds). Thus, there is no need to postulate
a structurally ordered chain of electron-transfer proteins in the
lipid bilayer; indeed, the three enzyme complexes seem to exist as
independent entities in the plane of the inner membrane, being
present in different ratios in different mitochondria.

The ordered transfer of electrons along the respiratory chain
is due entirely to the specificity of the functional interactions
between the components of the chain: each electron carrier is
able to interact only with the carrier adjacent to it in the sequence
shown in Figure 14-26, with no short circuits.

Electrons move between the molecules that carry them in
biological systems not only by moving along covalent bonds
within a molecule, but also by jumping across a gap as large
as 2 nm. The jumps occur by electron “tunneling,” a quantum-
mechanical property that is critical for the processes we are
discussing. Insulation is needed to prevent short circuits that
would otherwise occur when an electron carrier with a low redox
potential collides with a carrier with a high redox potential. This
insulation seems to be provided by carrying an electron deep
enough inside a protein to prevent its tunneling interactions
with an inappropriate partner.

How the changes in redox potential from one electron carrier
to the next are harnessed to pump protons out of the mitochondrial
matrix is the topic we discuss next.

A Large Drop in Redox Potential Across Each of the Three Respiratory
Enzyme Complexes Provides the Energy for H+ Pumping

We have previously discussed how the redox potential reflects
electron affinities (see p. 783). An outline of the redox potentials
measured along the respiratory chain is shown in Figure 14-29.
These potentials drop in three large steps, one across each major
respiratory complex. The change in redox potential between any
two electron carriers is directly proportional to the free energy
released when an electron transfers between them. Each enzyme
complex acts as an energy-conversion device by harnessing some
of this free-energy change to pump H+ across the inner membrane,
thereby creating an electrochemical proton gradient as electrons
pass through that complex. This conversion can be demonstrated
by purifying each respiratory enzyme complex and incorporating
it separately into liposomes: when an appropriate electron donor
and acceptor are added so that electrons can pass through the complex,
H+ is translocated across the liposome membrane.

Figure 14-29. Redox potential changes along the mitochondrial
electron-transport chain.

Figure 14-29

Redox potential changes along the mitochondrial electron-transport
chain. The redox potential (designated E′0) increases as electrons
flow down the respiratory chain to oxygen. The standard free-energy
change, ΔG°, for the transfer (more…)

The Mechanism of H+ Pumping Will Soon Be Understood in
Atomic Detail

Some respiratory enzyme complexes pump one H+ per electron
across the inner mitochondrial membrane, whereas others pump
two. The detailed mechanism by which electron transport is coupled
to H+ pumping is different for the three different enzyme complexes.
In the cytochrome b-c1 complex, the quinones clearly have a role.
As mentioned previously, a quinone picks up a H+ from the aqueous
medium along with each electron it carries and liberates it when it
releases the electron (see Figure 14-24). Since ubiquinone is freely
mobile in the lipid bilayer, it could accept electrons near the inside
surface of the membrane and donate them to the cytochrome b-c1
complex near the outside surface, thereby transferring one H+
across the bilayer for every electron transported. Two protons are
pumped per electron in the cytochrome b-c1 complex, however, and
there is good evidence for a so-called Q-cycle, in which ubiquinone
is recycled through the complex in an ordered way that makes this
two-for-one transfer possible. Exactly how this occurs can now be
worked out at the atomic level, because the complete structure of
the cytochrome b-c1 complex has been determined by x-ray
crystallography (Figure 14-30).

Figure 14-30. The atomic structure of cytochrome b-c 1.

Figure 14-30

The atomic structure of cytochrome b-c 1. This protein is a dimer.
The 240,000-dalton monomer is composed of 11 different protein
molecules in mammals. The three colored proteins form the
functional core of the enzyme: cytochrome b (green), cytochrome (more…)

Allosteric changes in protein conformations driven by electron
transport can also pump H+, just as H+ is pumped when ATP
is hydrolyzed by the ATP synthase running in reverse. For both the
NADH dehydrogenase complex and the cytochrome oxidase complex,
it seems likely that electron transport drives sequential allosteric
changes in protein conformation that cause a portion of the protein
to pump H+ across the mitochondrial inner membrane. A general
mechanism for this type of H+ pumping is presented in Figure 14-31.

Figure 14-31. A general model for H+ pumping.

Figure 14-31

A general model for H+ pumping. This model for H+ pumping
by a transmembrane protein is based on mechanisms that are
thought to be used by both cytochrome oxidase and the light-driven
procaryotic proton pump, bacteriorhodopsin. The protein
is driven through (more…)

H+ Ionophores Uncouple Electron Transport from ATP Synthesis

Since the 1940s, several substances—such as 2,4-dinitrophenol—
have been known to act as uncoupling agents, uncoupling electron
transport from ATP synthesis. The addition of these low-molecular-weight organic compounds to cells stops ATP synthesis by mitochondria
without blocking their uptake of oxygen. In the presence of an
uncoupling agent, electron transport and H+ pumping continue at
a rapid rate, but no H+ gradient is generated. The explanation for
this effect is both simple and elegant: uncoupling agents are lipid-
soluble weak acids that act as H+ carriers (H+ ionophores), and
they provide a pathway for the flow of H+ across the inner mitochondrial
membrane that bypasses the ATP synthase. As a result of this short-
circuiting, the proton-motive force is dissipated completely, and
ATP can no longer be made.

Respiratory Control Normally Restrains Electron Flow
Through the Chain

When an uncoupler such as dinitrophenol is added to cells,
mitochondria increase their oxygen uptake substantially because
of an increased rate of electron transport. This increase reflects
the existence of respiratory control. The control is thought to
act via a direct inhibitory influence of the electrochemical proton
gradient on the rate of electron transport. When the gradient is
collapsed by an uncoupler, electron transport is free to run unchecked
at the maximal rate. As the gradient increases, electron transport
becomes more difficult, and the process slows. Moreover, if an
artificially large electrochemical proton gradient is experimentally
created across the inner membrane, normal electron transport
stops completely, and a reverse electron flow can be detected in
some sections of the respiratory chain. This observation suggests
that respiratory control reflects a simple balance between the
free-energy change for electron-transport-linked proton pumping
and the free-energy change for electron transport—that is, the
magnitude of the electrochemical proton gradient affects both
the rate and the direction of electron transport, just as it affects
the directionality of the ATP synthase (see Figure 14-19).

Respiratory control is just one part of an elaborate interlocking
system of feedback controls that coordinate the rates of glycolysis,
fatty acid breakdown, the citric acid cycle, and electron transport.
The rates of all of these processes are adjusted to the ATP:ADP ratio,
increasing whenever an increased utilization of ATP causes the ratio
to fall. The ATP synthase in the inner mitochondrial membrane,
for example, works faster as the concentrations of its substrates
ADP and Pi increase. As it speeds up, the enzyme lets more H+ flow
into the matrix and thereby dissipates the electrochemical proton
gradient more rapidly. The falling gradient, in turn, enhances the
rate of electron transport.

Similar controls, including feedback inhibition of several key enzymes
by ATP, act to adjust the rates of NADH production to the rate of
NADH utilization by the respiratory chain, and so on. As a result of
these many control mechanisms, the body oxidizes fats and sugars
5–10 times more rapidly during a period of strenuous exercise than
during a period of rest.

Natural Uncouplers Convert the Mitochondria in Brown Fat into
Heat-generating Machines

In some specialized fat cells, mitochondrial respiration is normally
uncoupled from ATP synthesis. In these cells, known as brown fat
cells, most of the energy of oxidation is dissipated as heat rather
than being converted into ATP. The inner membranes of the large
mitochondria in these cells contain a special transport protein that
allows protons to move down their electrochemical gradient, by-
passing ATP synthase. As a result, the cells oxidize their fat stores
at a rapid rate and produce more heat than ATP. Tissues containing
brown fat serve as “heating pads,” helping to revive hibernating animals
and to protect sensitive areas of newborn human babies from the cold.

Bacteria Also Exploit Chemiosmotic Mechanisms to Harness Energy

Bacteria use enormously diverse energy sources. Some, like animal
cells, are aerobic; they synthesize ATP from sugars they oxidize to
CO2 and H2O by glycolysis, the citric acid cycle, and a respiratory
chain in their plasma membrane that is similar to the one in the
inner mitochondrial membrane. Others are strict anaerobes, deriving
their energy either from glycolysis alone (by fermentation) or from an
electron-transport chain that employs a molecule other than oxygen
as the final electron acceptor. The alternative electron acceptor can
be a nitrogen compound (nitrate or nitrite), a sulfur compound
(sulfate or sulfite), or a carbon compound (fumarate or carbonate),
for example. The electrons are transferred to these acceptors by a
series of electron carriers in the plasma membrane that are comparable
to those in mitochondrial respiratory chains.

Despite this diversity, the plasma membrane of the vast majority of
bacteria contains an ATP synthase that is very similar to the one in
mitochondria. In bacteria that use an electron-transport chain to
harvest energy, the electron-transport pumps H+ out of the cell and
thereby establishes a proton-motive force across the plasma membrane
that drives the ATP synthase to make ATP. In other bacteria, the
ATP synthase works in reverse, using the ATP produced by glycolysis
to pump H+ and establish a proton gradient across the plasma
membrane. The ATP used for this process is generated by
fermentation processes (discussed in Chapter 2).

Thus, most bacteria, including the strict anaerobes, maintain a proton
gradient across their plasma membrane. It can be harnessed to drive
a flagellar motor, and it is used to pump Na+ out of the bacterium via
a Na+-H+ antiporter that takes the place of the Na+-K+ pump of
eucaryotic cells. This gradient is also used for the active inward transport
of nutrients, such as most amino acids and many sugars: each nutrient is
dragged into the cell along with one or more H+ through a specific symporter
(Figure 14-32). In animal cells, by contrast, most inward transport across
the plasma membrane is driven by the Na+ gradient that is established by the
Na+-K+ pump.

Figure 14-32. The importance of H+-driven transport in bacteria.

Figure 14-32

The importance of H+-driven transport in bacteria. A proton-motive force
generated across the plasma membrane pumps nutrients into the cell and
expels Na+. (A) In an aerobic bacterium, an electrochemical proton gradient
across the plasma membrane is produced (more…)

Some unusual bacteria have adapted to live in a very alkaline
environment and yet must maintain their cytoplasm at a physiological
pH. For these cells, any attempt to generate an electrochemical H+
gradient would be opposed by a large H+ concentration gradient in
the wrong direction (H+ higher inside than outside). Presumably for
this reason, some of these bacteria substitute Na+ for H+ in all of their
chemiosmotic mechanisms. The respiratory chain pumps Na+ out of
the cell, the transport systems and flagellar motor are driven by an
inward flux of Na+, and a Na+-driven ATP synthase synthesizes
ATP. The existence of such bacteria demonstrates that the principle
of chemiosmosis is more fundamental than the proton-motive force
on which it is normally based.

Summary

The respiratory chain in the inner mitochondrial membrane contains
three respiratory enzyme complexes through which electrons pass on
their way from NADH to O2.

Each of these can be purified, inserted into synthetic lipid vesicles,
and then shown to pump H+ when electrons are transported through it.
In the intact membrane, the mobile electron carriers ubiquinone and
cytochrome c complete the electron-transport chain by shuttling between
the enzyme complexes. The path of electron flow is NADH → NADH
dehydrogenase complex → ubiquinone → cytochrome b-c1 complex →
cytochrome c → cytochrome oxidase complex → molecular oxygen (O2).

The respiratory enzyme complexes couple the energetically favorable
transport of electrons to the pumping of H+ out of the matrix. The
resulting electrochemical proton gradient is harnessed to make ATP
by another transmembrane protein complex, ATP synthase, through
which H+ flows back into the matrix. The ATP synthase is a reversible
coupling device that normally converts a backflow of H+ into ATP
phosphate bond energy by catalyzing the reaction ADP + Pi → ATP,
but it can also work in the opposite direction and hydrolyze ATP to
pump H+ if the electrochemical proton gradient is sufficiently reduced.
Its universal presence in mitochondria, chloroplasts, and procaryotes
testifies to the central importance of chemiosmotic mechanisms in cells.

By agreement with the publisher, this book is accessible by the search
feature, but cannot be browsed.

Copyright © 2002, Bruce Alberts, Alexander Johnson, Julian Lewis,
Martin Raff, Keith Roberts, and Peter Walter; Copyright © 1983, 1989,
1994, Bruce Alberts, Dennis Bray, Julian Lewis, Martin Raff, Keith
Roberts, and James D. Watson .

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Introduction to Metabolic Pathways

Author: Larry H. Bernstein, MD, FCAP

 

Humans, mammals, plants and animals, and eukaryotes and prokaryotes all share a common denominator in their manner of existence.  It makes no difference whether they inhabit the land, or the sea, or another living host. They exist by virtue of their metabolic adaptation by way of taking in nutrients as fuel, and converting the nutrients to waste in the expenditure of carrying out the functions of motility, breakdown and utilization of fuel, and replication of their functional mass.

There are essentially two major sources of fuel, mainly, carbohydrate and fat.  A third source, amino acids which requires protein breakdown, is utilized to a limited extent as needed from conversion of gluconeogenic amino acids for entry into the carbohydrate pathway. Amino acids follow specific metabolic pathways related to protein synthesis and cell renewal tied to genomic expression.

Carbohydrates are a major fuel utilized by way of either of two pathways.  They are a source of readily available fuel that is accessible either from breakdown of disaccharides or from hepatic glycogenolysis by way of the Cori cycle.  Fat derived energy is a high energy source that is metabolized by one carbon transfers using the oxidation of fatty acids in mitochondria. In the case of fats, the advantage of high energy is conferred by chain length.

Carbohydrate metabolism has either of two routes of utilization.  This introduces an innovation by way of the mitochondrion or its equivalent, for the process of respiration, or aerobic metabolism through the tricarboxylic acid, or Krebs cycle.  In the presence of low oxygen supply, carbohydrate is metabolized anaerobically, the six carbon glucose being split into two three carbon intermediates, which are finally converted from pyruvate to lactate.  In the presence of oxygen, the lactate is channeled back into respiration, or mitochondrial oxidation, referred to as oxidative phosphorylation. The actual mechanism of this process was of considerable debate for some years until it was resolved that the mechanism involve hydrogen transfers along the “electron transport chain” on the inner membrane of the mitochondrion, and it was tied to the formation of ATP from ADP linked to the so called “active acetate” in Acetyl-Coenzyme A, discovered by Fritz Lipmann (and Nathan O. Kaplan) at Massachusetts General Hospital.  Kaplan then joined with Sidney Colowick at the McCollum Pratt Institute at Johns Hopkins, where they shared tn the seminal discovery of the “pyridine nucleotide transhydrogenases” with Elizabeth Neufeld,  who later established her reputation in the mucopolysaccharidoses (MPS) with L-iduronidase and lysosomal storage disease.

This chapter covers primarily the metabolic pathways for glucose, anaerobic and by mitochondrial oxidation, the electron transport chain, fatty acid oxidation, galactose assimilation, and the hexose monophosphate shunt, essential for the generation of NADPH. The is to be more elaboration on lipids and coverage of transcription, involving amino acids and RNA in other chapters.

The subchapters are as follows:

1.1      Carbohydrate Metabolism

1.2      Studies of Respiration Lead to Acetyl CoA

1.3      Pentose Shunt, Electron Transfer, Galactose, more Lipids in brief

1.4      The Multi-step Transfer of Phosphate Bond and Hydrogen Exchange Energy

Complex I or NADH-Q oxidoreductase

Complex I or NADH-Q oxidoreductase

Fatty acid oxidation and ETC

Fatty acid oxidation and ETC

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Larry H Bernstein, MD, FCAP, Author and Curator

Chief, Scientific Communication

Leaders in Pharmaceutical Intelligence

with contributions from JEDS Rosalis, Brazil
and Radislov Rosov, Univ of Virginia, VA, USA

A Brief Curation of Proteomics, Metabolomics, and Metabolism

This article is a continuation of a series of elaborations of the recent and
accelerated scientific discoveries that are enlarging the scope of and
integration of biological and medical knowledge leading to new drug
discoveries.  The work that has led us to this point actually has roots
that go back 150 years.  The roots go back to studies in the mid-nineteenth century, with the emergence of microbiology, physiology,
pathology, botany, chemistry and physics, and the laying down of a
mechanistic approach divergent from descriptive observation in the
twentieth century. Medicine took on the obligation to renew the method
of training physicians after the Flexner Report (The Flexner Report of
1910 transformed the nature and process of medical education in America
with a resulting elimination of proprietary schools), funded by the Carnegie
Foundation.  Johns Hopkins University Medical School became the first to
adopt the model, as did Harvard, Yale, University of Chicago, and others.

The advances in biochemistry, genetics and genomics, were large, as was
structural organic chemistry in the remainder of the centrury.  The advances
in applied mathematics and in instrumental analysis opened a new gateway
into the 21st century with the Human Genome Project, the Proteome Library,
Signaling Pathways, and the Metabolomes – human, microbial, and plants.

shall elaborate on how the key processes of life are being elucidated as
these interrelated disciplines converge.  I shall not be covering in great
detail the contribution of the genetic code and transcripton because they
have been covered at great length in this series.

Part I.  The foundation for the emergence of a revitalized molecular
biology 
and biochemistry.

In a series of discussions with Jose des Salles Roselino (Brazil) over a
period of months we have come to an important line of reasoning. DNA
to protein link goes from triplet sequence to amino acid sequence. The
realm of genetics. Further, protein conformation, activity and function
requires that environmental and microenvironmental factors should be
considered (Biochemistry).  This has been opened in several articles
preceding this.

In the cAMP coupled hormonal response the transfer of conformation
from protein to protein is paramount. For instance, if your scheme goes
beyond cAMP, it will show an effect over a self-assembly (inhibitor
protein and protein kinase). Therefore, sequence alone does not
explain conformation, activity and function of regulatory proteins.
Recall that sequence is primar structure, determined by the translation
of the code, but secondary structure is determined by disulfide bonds.
There is another level of structure, tertiary structure, that is molded by
steric influences of near neighbors and by noncovalent attractions
and repulsions.

A few comments ( contributed by Assoc. Prof. JEDS Roselino) are in
order to stress the importance of self-assembly (Prigogine, R. A
Marcus, conformation energy) in a subject that is the best for this
connection. We have to stress again that in the cAMP
coupled hormonal response the transfer of conformation from
protein to protein is paramount. For instance, in case the
reaction sequence follows beyond the production of the
second messenger, as in the case of cAMP, this second
messenger will remove a self-assembly of inhibitor protein
with the enzyme protein kinase. Therefore, sequence alone
does not explain conformation, activity and function of
regulatory proteins. In this case, if this important mechanism
was not ignored, the work of Stanley Prusiner would most
certainly have been recognized earlier, and “rogue” proteins
would not have been seen as so rogue as some assumed.
For the general idea of importance of self-assembly versus
change in covalent modification of proteins (see R. A Kahn
and A. G Gilman (1984) J. Biol. Chem.  259(10), pp 6235-
6240. In this case, trimeric or dimeric G does not matter.
“Signaling transduction tutorial”.
G proteins in the G protein coupled-receptor proteins are
presented following a unidirectional series of arrows.
This is adequate to convey the idea of information being
transferred from outside the cell towards cell´s interior
(therefore, against the dogma that says all information
moves from DNA to RNA to protein.  It is important to
consider the following: The entire process is driven by
a very delicate equilibrium between possible conform-
ational states of the proteins. Empty receptors have very
low affinity for G proteins. On the other hand, hormone
bound receptors have a change in conformation that
allows increasing the affinity for the G-trimer. When
hormone receptors bind to G-trimers two things happen:

  1. Receptors transfer conformation information to
    the G-triplex and
  2. the G-triplex transfers information back to the
    complex hormone-receptor.

In the first case , the dissociated G protein exchanges
GDP for GTP and has its affinity for the cyclase increased,
while by the same interaction receptor releases the
hormone which then places the first required step for the
signal. After this first interaction step, on the second and
final transduction system step is represented by an
opposite arrow. When, the G-protein + GTP complex
interacts with the cyclase two things happen:

  1. It changes the cyclase to an active conformation
    starting the production of cAMP as the single
    arrow of the scheme. However, the interaction
    also causes a backward effect.
  2. It activates the GTPase activity of this subunit
    and the breakdown of GTP to GDP moves this 
    subunit back to the initial trimeric inactive
    state
     of G complex.

This was very well studied when the actions of cholera toxin
required better understanding. Cholera toxin changes the
GTPase subunit by ADP-ribosilation (a covalent and far more
stable change in proteins) producing a permanent conformation
of GTP bound G subunit. This keeps the cyclase in permanent
active conformation because ADP-ribosilation inhibits GTPase
activity required to put an end in the hormonal signal.

The study made while G-proteins were considered a dimer still
holds despite its limited vision of the real complexity of the
transduction system. It was also possible to get this very same
“freezing” in the active state using GTP stable analogues. This
transduction system is one of the best examples of the delicate
mechanisms of conformational interaction of proteins. Further-
more, this system also shows on the opposite side of our
reasoning scheme, how covalent changes are adequate for
more stable changes than those mediated by Van der Wall’s
forces between proteins. Yet, these delicate forces are the
same involved when Sc-Prion transfers its rogue
conformation to c-Prion proteins and other similar events.
The Jacob-Monod Model

A combination of genetic and biochemical experiments in
bacteria led to the initial recognition of

  1. protein-binding regulatory sequences associated with genes and
  2. proteins whose binding to a gene’s regulatory sequences
    either activate or repress its transcription.

These key components underlie the ability of both prokaryotic and
eukaryotic cells to turn genes on and off. The  experimental findings lead to a general model of bacterial transcription control.

Gene control serves to allow a single cell to adjust to changes in its
nutritional environment so that its growth and division can be optimized.
Thus, the prime focus of research has been on genes that encode
inducible proteins whose production varies depending on the nutritional
status of the cells. Its most characteristic and biologically far-reaching
purpose in eukaryotes, distinctive from single cell organisms is the
regulation of a genetic program that underlies embryological
development and tissue differentiation.

The principles of transcription have already been described in this
series under the translation of the genetic code into amino acids
that are the building blocks for proteins.

E.coli can use either glucose or other sugars such as the
disaccharide lactose as the sole source of carbon and energy.
When E. coli cells are grown in a glucose-containing medium,
the activity of the enzymes needed to metabolize lactose is
very low. When these cells are switched to a medium
containing lactose but no glucose, the activities of the lactose-metabolizing enzymes increase. Early studies showed that the
increase in the activity of these enzymes resulted from the
synthesis of new enzyme molecules, a phenomenon termed
induction. The enzymes induced in the presence of lactose
are encoded by the lac operon, which includes two genes, Z
and Y, that are required for metabolism of lactose and a third
gene. The lac Y gene encodes lactose permease, which spans the E. coli cell membrane and uses the energy available from
the electrochemical gradient across the membrane to pump
lactose into the cell. The lac Z gene encodes β-galactosidase,
which splits the disaccharide lactose into the monosaccharides
glucose and galactose, which are further metabolized through
the action of enzymes encoded in other operons. The third
gene encodes thiogalactoside transacetylase.

Synthesis of all three enzymes encoded in the lac operon is rapidly
induced when E. coli cells are placed in a medium containing lactose
as the only carbon source and repressed when the cells are switched
to a medium without lactose. Thus all three genes of the lac operon
are coordinately regulated. The lac operon in E. coli provides one
of the earliest and still best-understood examples of gene control.
Much of the pioneering research on the lac operon was conducted by
Francois Jacob, Jacques Monod, and their colleagues in the 1960s.

Some molecules similar in structure to lactose can induce expression
of the lacoperon genes even though they cannot be hydrolyzed by β-galactosidase. Such small molecules (i.e., smaller than proteins) are
called inducers. One of these, isopropyl-β-D-thiogalactoside,
abbreviated IPTG,is particularly useful in genetic studies of the lac
operon, because it can diffuse into cells and, it is not metabolized.
Insight into the mechanisms controlling synthesis of β-galactosidase
and lactose permease came from the study of mutants in which control
of β-galactosidase expression was abnormal and used a colorimetric
assay for β-galactosidase.

When the cells are exposed to chemical mutagens before plating on
X-gal/glucose plates, rare blue colonies appear, but when cells
from these blue colonies are recovered and grown in media containing
glucose, they overexpress all the genes of the lac operon. These cells
are called constitutive mutants because they fail to repress the lac
operon in media lacking lactose and instead continuously express the
enzymes, and the genes were mapped to a region on the E. coli
chromosome. This led to the conclusion that these cells had a defect
in a protein that normally repressed expression of the lac operon in
the absence of lactose, and that it blocks transcription by binding to
a site on the E. coli genome where transcription of the lac operon is
initiated. In addition, it binds to the lac repressor in the lactose
medium and decreases its affinity for the repressor-binding site
on the DNA causing the repressor to unbind the DNA. Thereby,
transcription of the lac operon is initiated, leading to synthesis of
β-galactosidase, lactose permease, and thiogalactoside
transacetylase.

 regulation of the lac operon by lac repressor

Jacob and Monod model of transcriptional regulation of the lac operon

Next, Jacob and Monod isolated mutants that expressed the lac operon
constitutively even when two copies of the wild-type lacI gene
encoding the lac repressor were present in the same cell, and the
constitutive mutations mapped to one end of the lac operon, as the
model predicted.  Further, there are rare cells that carry a mutation
located at the region, promoter, that block initiation of transcription by
RNA polymerase.

lac I+ gene is trans-acting, & encodes a protein, which binds to a lac operator

 lac I+ gene is trans-acting, & encodes a protein, which
binds to a lac operator

They further demonstrated that the two types of mutations lac I and
lac I+, were cis- and trans-acting, the latter encoding a protein that
binds to the lac operator. The cis-acting Oc mutations prevent
binding of the lac repressor to the operator, and  mutations in the
lac promoter are cis-acting, since they alter the binding site for RNA
polymerase. In general, trans-acting genes that regulate expression
of genes on other DNA molecules encode diffusible products. In
most cases these are proteins, but in some cases RNA molecules
can act in trans to regulate gene expression.

According to the Jacob and Monod model of transcriptional control,
transcription of the lac operon, which encodes three inducible
proteins, is repressed by binding of lac repressor protein to the
operator sequence.

 (Section 10.1Bacterial Gene Control: The Jacob-Monod Model.)
This book is accessible by the search feature.

Comment: This seminal work was done a half century ago. It was a
decade after the Watson-Crick model for DNA. The model is
elaborated for the Eukaryote in the examples that follow.

(The next two articles were called to my attention by R. Bosov at
University of Virginia).

An acetate switch regulates stress erythropoiesis

M Xu,  JS Nagati, Ji Xie, J Li, H Walters, Young-Ah Moon, et al.
Nature Medicine 10 Aug 2014(20): 1018–1026.
http://dx.doi.org:/10.1038/nm.3587

message: 1- ( -CH3 ) = Ln ( (1/sqrt(1-Acetate^2) –
sqrt oxalate))/ Ln(oxygen) – K(o)
rsb5n@virginia.edu

The hormone erythropoietin (EPO), synthesized in the kidney or liver
of adult mammals, controls erythrocyte production and is regulated by
the stress-responsive transcription factor hypoxia-inducible factor-2
(HIF-2).
 HIFα acetylation and efficient HIF-2–dependent EPO
induction during hypoxia requires  the lysine acetyltransferase CREB-binding protein (CBP) . These processes require acetate-dependent
acetyl CoA synthetase 2 (ACSS2) as follows.Acetate levels rise and
ACSS2 is required for HIF-2α acetylation, CBP–HIF-2α complex
formation, CBP–HIF-2α recruitment to the EPO enhancer and induction
of EPO gene expression
 in human Hep3B hepatoma cells and in EPO-generating organs of hypoxic or acutely anemic mice. In acutely anemic
mice, acetate supplementation augments stress erythropoiesis in an
ACSS2-dependent manner. Moreover, in acquired and inherited
chronic anemia mouse models, acetate supplementation increases
EPO expression
 and the resting hematocrit. Thus, a mammalian
stress-responsive acetate switch controls HIF-2 signaling and EPO
induction during pathophysiological states marked by tissue hypoxia.

Figure 1: Acss2 controls HIF-2 signaling in hypoxic cells.
Time course of endogenous HIF-2α acetylation during hypoxia following
immunoprecipitation (IP) of HIF-2α from whole-cell extracts and detection
of acetylated lysines by immunoblotting (IB).
http://www.nature.com/nm/journal/v20/n9/carousel/nm.3587-F1.jpg

Figure 2: Acss2 regulates hypoxia-induced renal Epo expression in mice.
http://www.nature.com/nm/journal/v20/n9/carousel/nm.3587-F2.jpg

Figure 3: Acute anemia induces Acss2-dependent HIF-2 signaling in mice.
http://www.nature.com/nm/journal/v20/n9/carousel/nm.3587-F3.jpg

Figure 4: An acetate switch regulates Cbp–HIF-2 interactions in cells.
(a) HIF-2α acetylation following immunoprecipitation of endogenous
HIF-2α and detection by immunoblotting with antibodies to acetylated
lysine or HIF-2α.
http://www.nature.com/nm/journal/v20/n9/carousel/nm.3587-F4.jpg

Figure 5: Acss2 signaling in cells requires intact HIF-2 acetylation.
http://www.nature.com/nm/journal/v20/n9/carousel/nm.3587-F5.jpg

Figure 6: Acetate facilitates recovery from anemia.

Acetate facilitates recovery from anemia

Acetate facilitates recovery from anemia

(a) Serial hematocrits of CD1 wild-type female mice after PHZ treatment, followed
by once daily per os (p.o.) supplementation with water vehicle (Veh; n = 7 mice),
GTA (n = 6 mice), GTB (n = 8 mice) or GTP (n = 7 mice) (single measurem…

http://www.nature.com/nm/journal/v20/n9/carousel/nm.3587-F6.jpg

see also-.
1. Bunn, H.F. & Poyton, R.O. Oxygen sensing and molecular adaptation to
hypoxia. Physiol. Rev. 76, 839–885 (1996).

  1. .Richalet, J.P. Oxygen sensors in the organism: examples of regulation
    under altitude hypoxia in mammals. Comp. Biochem. Physiol. A Physiol.
    118, 9–14 (1997).
  2. .Koury, M.J. Erythropoietin: the story of hypoxia and a finely regulated
    hematopoietic hormone. Exp. Hematol. 33, 1263–1270 (2005).
  3. Wang, G.L., Jiang, B.H., Rue, E.A. & Semenza, G.L. Hypoxia-inducible
    factor 1 is a basic-helix-loop-helix-PAS heterodimer regulated
    by cellular O2 tension. Proc. Natl. Acad. Sci. USA92, 5510–5514 (1995).
  4. Chen, R. et al. The acetylase/deacetylase couple CREB-binding
    protein/sirtuin 1 controls hypoxia-inducible factor 2 signaling. J. Biol.
    Chem. 287, 30800–30811 (2012).
  5. .Papandreou, I., Cairns, R.A., Fontana, L., Lim, A.L. & Denko, N.C.
    HIF-1 mediates adaptation to hypoxia by actively down-regulating
    mitochondrial oxygen consumption. Cell Metab. 3,187–197 (2006).

14. Kim, J.W., Tchernyshyov, I., Semenza, G.L. & Dang, C.V. HIF-1-
mediated expression of pyruvate dehydrogenase kinase: a metabolic
switch required for cellular adaptation to hypoxia. Cell Metab. 3,
177–185 (2006).

16. Fujino, T., Kondo, J., Ishikawa, M., Morikawa, K. & Yamamoto, T.T.
Acetyl-CoA synthetase 2, a mitochondrial matrix enzyme involved in the
oxidation of acetate. J. Biol. Chem. 276,11420–11426 (2001).

17..Luong, A., Hannah, V.C., Brown, M.S. & Goldstein, J.L. Molecular
characterization of human acetyl-CoA synthetase, an enzyme regulated
by sterol regulatory element-binding proteins. J. Biol. Chem. 275,
26458–26466 (2000).

20 .Wellen, K.E. et al. ATP-citrate lyase links cellular metabolism to
histone acetylation. Science324, 1076–1080 (2009).

24. McBrian, M.A. et al. Histone acetylation regulates intracellular pH.
Mol. Cell 49, 310–321(2013).

Asymmetric mRNA localization contributes to fidelity and sensitivity
of spatially localized systems

Robert J Weatheritt, Toby J Gibson & M Madan Babu
Nature Structural & Molecular Biology 21, 833–839 (2014)
http://www.nature.com/nsmb/journal/v21/n9/abs/nsmb.2876.html 

Although many proteins are localized after translation, asymmetric
protein distribution is also achieved by translation after mRNA localization.
Why are certain mRNA transported to a distal location and translated
on-site? Here we undertake a systematic, genome-scale study of
asymmetrically distributed protein and mRNA in mammalian cells.
Our findings suggest that asymmetric protein distribution by mRNA
localization enhances interaction fidelity and signaling sensitivity
.
Proteins synthesized at distal locations frequently contain intrinsically
disordered segments. These regions are generally rich in assembly-
promoting modules and are often regulated by post-translational
modifications. Such proteins are tightly regulated but display distinct
temporal dynamics upon stimulation with growth factors. Thus, proteins
synthesized on-site may rapidly alter proteome composition and
act as dynamically regulated scaffolds to promote the formation
of reversible cellular assemblies. 
Our observations are consistent
across multiple mammalian species, cell types and developmental stages,
suggesting that localized translation is a recurring feature of cell
signaling and regulation.

Figure 1: Classification and characterization of TAS and DSS proteins.

The two major mechanisms for localizing proteins to distal sites in the cell

The two major mechanisms for localizing proteins to distal sites in the cell

(a)The two major mechanisms for localizing proteins to distal sites in the cell.
(b) Data sets used to identify groups of DSS and TAS transcripts, as well as
DSS and TAS proteins in mouse neuroblastoma cells

http://www.nature.com/nsmb/journal/v21/n9/carousel/nsmb.2876-F1.jpg

Figure 2: Structural analysis of DSS proteins reveals an enrichment
in disordered regions.

Distributions of the various structural properties of the DSS and TAS proteins of the mouse neuroblastoma data sets

Distributions of the various structural properties of the DSS and TAS proteins of the mouse neuroblastoma data sets

(a,b) Distributions of the various structural properties of the DSS and TAS
proteins of the mouse neuroblastoma data sets (a), the mouse pseudopodia,
the rat embryonic sensory neuron data set and the adult sensory neuron data set (b).…

http://www.nature.com/nsmb/journal/v21/n9/carousel/nsmb.2876-F2.jpg

Figure 3: Analysis of DSS proteins reveals an enrichment for linear motifs, phase-
transition (i.e., higher-order assembly) promoting segments and PTM sites that act
as molecular switches.

(a,b) Distributions of the various regulatory and structural properties of the DSS
and TAS proteins of the mouse neuroblastoma data sets
http://www.nature.com/nsmb/journal/v21/n9/carousel/nsmb.2876-F3.jpg

Figure 4: Dynamic regulation of DSS transcripts and proteins.

Dynamic regulation of DSS transcripts and proteins

Dynamic regulation of DSS transcripts and proteins

Genome-wide quantitative measurements of gene expression of DSS (n = 289)
and TAS (n = 1,292) proteins in mouse fibroblast cells. DSS transcripts and
proteins have a lower abundance and shorter half-lives

http://www.nature.com/nsmb/journal/v21/n9/carousel/nsmb.2876-F4.jpg

Figure 5: An overview of the potential advantages conferred by distal-site protein
synthesis, inferred from our analysis.

An overview of the potential advantages conferred by distal-site protein synthesis, inferred from our analysis

An overview of the potential advantages conferred by distal-site protein synthesis, inferred from our analysis

Turquoise and red filled circle represents off-target and correct interaction partners,
respectively. Wavy lines – a disordered region within a distal site synthesis protein.

http://www.nature.com/nsmb/journal/v21/n9/carousel/nsmb.2876-F5.jpg

The identification of asymmetrically localized proteins and transcripts.

The identification of asymmetrically localized proteins and transcripts

The identification of asymmetrically localized proteins and transcripts

An illustrative explanation of the resolution of the study and the concept of asymmetric
localization of proteins and mRNA. In this example, on the left a neuron is divided into
its cell body and axon terminal, and transcriptome/proteo…

http://www.nature.com/nsmb/journal/v21/n9/carousel/nsmb.2876-SF1.jpg

Graphs and boxplots of functional and structural properties for distal site synthesis
(DSS) proteins (red) and transport after synthesis (TAS) proteins (gray).
See Online Methods for details and legend of Figure 2 for a description of boxplots
and statistical tests.
http://www.nature.com/nsmb/journal/v21/n9/carousel/nsmb.2876-SF2.jpg

See also –
1. Martin, K.C. & Ephrussi, A. mRNA localization: gene expression in the spatial
dimension. Cell136, 719–730 (2009).

  1. Scott, J.D. & Pawson, T. Cell signaling in space and time: where proteins come
    together and when they’re apart. Science 326, 1220–1224 (2009).

4..Holt, C.E. & Bullock, S.L. Subcellular mRNA localization in animal cells
and why it matters.Science 326, 1212–1216 (2009).

  1. Jung, H., Gkogkas, C.G., Sonenberg, N. & Holt, C.E. Remote control of
    gene function by local translation. Cell 157, 26–40 (2014). 

Regulation of metabolism by hypoxia-inducible factor 1.   
Semenza GL.    Author information
Cold Spring Harb Symp Quant Biol. 2011;76:347-53.
http://dx.doi.org:/10.1101/sqb.2011.76.010678.

The maintenance of oxygen homeostasis is critical for survival, and the
master regulator of this process in metazoan species is hypoxia-inducible
factor 1 (HIF-1), which

  • controls both O(2) delivery and utilization.

Under conditions of reduced O(2) availability,

  • HIF-1 activates the transcription of genes, whose protein products
  • mediate a switch from oxidative to glycolytic metabolism.

HIF-1 is activated in cancer cells as a result of intratumoral hypoxia
and/or genetic alterations.

In cancer cells, metabolism is reprogrammed to

  • favor glycolysis even under aerobic conditions.

Pyruvate kinase M2 (PKM2) has been implicated in cancer growth and
metabolism, although the mechanism by which it exerts these effects is
unclear. Recent studies indicate that

PKM2 interacts with HIF-1α physically and functionally to

  1. stimulate the binding of HIF-1 at target genes,
  2. the recruitment of coactivators,
  3. histone acetylation, and
  4. gene transcription.

Interaction with HIF-1α is facilitated by

  • hydroxylation of PKM2 at proline-403 and -408 by PHD3.

Knockdown of PHD3

  • decreases glucose transporter 1, lactate dehydrogenase A, and
    pyruvate dehydrogenase kinase 1 expression;
  • decreases glucose uptake and lactate production; and
  • increases O(2) consumption.

The effect of PKM2/PHD3 is not limited to genes encoding metabolic
enzymes because VEGF is similarly regulated.

These results provide a mechanism by which PKM2

  • promotes metabolic reprogramming and

suggest that it plays a broader role in cancer progression than has
previously been appreciated.   PMID: 21785006   

Cadherins

Cadherins are thought to be the primary mediators of adhesion
between the cells
 of vertebrate animals, and also function in cell
adhesion in many invertebrates. The expression of numerous cadherins
during development is highly regulated, and the precise pattern of
cadherin expression plays a pivotal role in the morphogenesis of tissues
and organs. The cadherins are also important in the continued maintenance
of tissue structure and integrity. The loss of cadherin expression appears
to be highly correlated with the invasiveness of some types of tumors. Cadherin adhesion is also dependent on the presence of calcium ions
in the extracellular milieu.

The cadherin protein superfamily, defined as proteins containing a
cadherin-like domain, can be divided into several sub-groups. These include

  • the classical (type I) cadherins, which mediate adhesion at adherens junctions;
  • the highly-related type II cadherins;
  • the desmosomal cadherins found in desmosome junctions;
  • protocadherins, expressed only in the nervous system; and
  • atypical cadherin-like domain containing proteins.

Members of all but the atypical group have been shown to play a role
in intercellular adhesion.

Part II.  PKM2 and regulation of glycolysis

PKM2 regulates the Warburg effect and promotes ​HMGB1
release in sepsis

L Yang, M Xie, M Yang, Y Yu, S Zhu, W Hou, R Kang, …, & D Tang
Nature Communic 14 July 2014; 5(4436)
http://dx.doi.org/doi:10.1038/ncomms5436

Increasing evidence suggests the important role of metabolic reprogramming

  • in the regulation of the innate inflammatory response,

We provide evidence to support a novel role for the

  • ​pyruvate kinase M2 (​PKM2)-mediated Warburg effect,

namely aerobic glycolysis,

  • in the regulation of ​high-mobility group box 1 (​HMGB1) release. ​
  1. PKM2 interacts with ​hypoxia-inducible factor 1α (​HIF1α) and
  2. activates the ​HIF-1α-dependent transcription of enzymes necessary
    for aerobic glycolysis in macrophages.

Knockdown of ​PKM2, ​HIF1α and glycolysis-related genes

  • uniformly decreases ​lactate production and ​HMGB1 release.

Similarly, a potential ​PKM2 inhibitor, ​shikonin,

  1. reduces serum ​lactate and ​HMGB1 levels, and
  2. protects mice from lethal endotoxemia and sepsis.

Collectively, these findings shed light on a novel mechanism for

  • metabolic control of inflammation by
  • regulating ​HMGB1 release and

highlight the importance of targeting aerobic glycolysis in the treatment
of sepsis and other inflammatory diseases.

  1. Glycolytic inhibitor ​2-D G attenuates ​HMGB1 release by activated macrophages.
    http://www.nature.com/ncomms/2014/140714/ncomms5436/carousel/ncomms5436-f1.jpg
  2. Figure 2: Upregulated ​PKM2 promotes aerobic glycolysis and ​HMGB1
    release in activated macrophages.
    http://www.nature.com/ncomms/2014/140714/ncomms5436/carousel/ncomms5436-f2.jpg
  3. Figure 3: ​PKM2-mediated ​HIF1α activation is required for ​HMGB1
    release in activated macrophages.
    http://www.nature.com/ncomms/2014/140714/ncomms5436/carousel/ncomms5436-f3.jpg

 

ERK1/2-dependent phosphorylation and nuclear translocation of
PKM2 promotes the Warburg effect  

W Yang, Y Zheng, Y Xia, Ha Ji, X Chen, F Guo, CA Lyssiotis, & Zhimin Lu
Nature Cell Biology  2012 (27 June 2014); 14: 1295–1304
Corrigendum (January, 2013)  http://dx.doi.org:/10.1038/ncb2629

Pyruvate kinase M2 (PKM2) is upregulated in multiple cancer types and
contributes to the Warburg. We demonstrate that

  • EGFR-activated ERK2 binds directly to PKM2 Ile 429/Leu 431
  • through the ERK2 docking groove
  • and phosphorylates PKM2 at Ser 37, but
  • does not phosphorylate PKM1.

Phosphorylated PKM2 Ser 37

  1. recruits PIN1 for cis–trans isomerization of PKM2, which
  2. promotes PKM2 binding to importin α5
  3. and PKM2 translocates to the nucleus.

Nuclear PKM2 acts as

  • a coactivator of β-catenin to
  • induce c-Myc expression,

This is followed by

  1. the upregulation of GLUT1, LDHA and,
  2. in a positive feedback loop,
  • PTB-dependent PKM2 expression.

Replacement of wild-type PKM2 with

  • a nuclear translocation-deficient mutant (S37A)
  • blocks the EGFR-promoted Warburg effect
    and brain tumour development in mice.

In addition, levels of PKM2 Ser 37 phosphorylation

  • correlate with EGFR and ERK1/2 activity
    in human glioblastoma specimens.

Our findings highlight the importance of

  • nuclear functions of PKM2 in the Warburg effect
    and tumorigenesis.
  1. ERK is required for PKM2 nucleus translocation.
    http://www.nature.com/ncb/journal/v14/n12/carousel/ncb2629-f1.jpg
  2. ERK2 phosphorylates PKM2 Ser 37.
    http://www.nature.com/ncb/journal/v14/n12/carousel/ncb2629-f2.jpg
  3. Figure 3: PKM2 Ser 37 phosphorylation recruits PIN1.
    http://www.nature.com/ncb/journal/v14/n12/carousel/ncb2629-f3.jpg

 Pyruvate kinase M2 activators promote tetramer formation
and suppress tumorigenesis

D Anastasiou, Y Yu, WJ Israelsen, Jian-Kang Jiang, MB Boxer, B Hong, et al.
Nature Chemical Biology  11 Oct 2012; 8: 839–847

Cancer cells engage in a metabolic program to

  • enhance biosynthesis and support cell proliferation.

The regulatory properties of pyruvate kinase M2 (PKM2)

  • influence altered glucose metabolism in cancer.

The interaction of PKM2 with phosphotyrosine-containing proteins

  • inhibits PTM2 enzyme activity and
  • increases the availability of glycolytic metabolites
  • supporting cell proliferation.

This suggests that high pyruvate kinase activity may suppress
tumor growth
.

  1. expression of PKM1,  the pyruvate kinase isoform with high
    constitutive activity, or
  2. exposure to published small-molecule PKM2 activators
  • inhibits the growth of xenograft tumors.

Structural studies reveal that

  • small-molecule activators bind PKM2
  • at the subunit interaction interface,
  • a site that is distinct from that of the
    • endogenous activator fructose-1,6-bisphosphate (FBP).

However, unlike FBP,

  • binding of activators to PKM2 promotes
  • a constitutively active enzyme state that is resistant to inhibition
  • by tyrosine-phosphorylated proteins.

These data support the notion that small-molecule activation of PKM2
can interfere with anabolic metabolism

  1. PKM1 expression in cancer cells impairs xenograft tumor growth.
    http://www.nature.com/nchembio/journal/v8/n10/carousel/nchembio.1060-F1.jpg
  2. TEPP-46 and DASA-58 isoform specificity in vitro and in cells.
    TEPP-46 and DASA-58 isoform specificity in vitro and in cells.

    TEPP-46 and DASA-58 isoform specificity in vitro and in cells.

    (a) Structures of the PKM2 activators TEPP-46 and DASA-58. (b) Pyruvate kinase (PK) activity in purified recombinant human
    PKM1 or PKM2 expressed in bacteria in the presence of increasing
    concentrations of TEPP-46 or DASA-58. M1, PKM1;…
    http://www.nature.com/nchembio/journal/v8/n10/carousel/nchembio.1060-F2.jpg

  3. Activators promote PKM2 tetramer formation and prevent
    inhibition by phosphotyrosine signaling.
Activators promote PKM2 tetramer formation and prevent inhibition by phosphotyrosine signaling.

Activators promote PKM2 tetramer formation and prevent inhibition by phosphotyrosine signaling.

Sucrose gradient ultracentrifugation profiles of purified recombinant
PKM2 (rPKM2) and the effects of FBP and TEPP-46 on PKM2 subunit stoichiometry.
http://www.nature.com/nchembio/journal/v8/n10/carousel/nchembio.1060-F3.jpg

Figure 5: Metabolic effects of cell treatment with PKM2 activators.
(a) Effects of TEPP-46, DASA-58 (both used at 30 μM) or PKM1
expression on the doubling time of H1299 cells under normoxia
(21% O2) or hypoxia (1% O2). (b) Effects of DASA-58 on lactate
production from glucose. The P value shown was ca…
http://www.nature.com/nchembio/journal/v8/n10/carousel/nchembio.1060-F5.jpg

EGFR has a tumour-promoting role in liver macrophages during
hepatocellular carcinoma formation

H Lanaya, A Natarajan, K Komposch, L Li, N Amberg, …, & Maria Sibilia
Nature Cell Biology 31 Aug 2014   http://dx.doi.org:/10.1038/ncb3031

Tumorigenesis has been linked with macrophage-mediated chronic
inflammation and diverse signaling pathways, including the ​epidermal
growth factor receptor (​EGFR) pathway. ​EGFR is expressed in liver
macrophages in both human HCC and in a mouse HCC model. Mice
lacking ​EGFR in macrophages show impaired hepatocarcinogenesis,
Mice lacking ​EGFR in hepatocytes develop HCC owing to increased
hepatocyte damage and compensatory proliferation. EGFR is required
in liver macrophages to transcriptionally induce ​interleukin-6 following
interleukin-1 stimulation, which triggers hepatocyte proliferation and HCC.
Importantly, the presence of ​EGFR-positive liver macrophages in HCC
patients is associated with poor survival. This study demonstrates a

  • tumour-promoting mechanism for ​EGFR in non-tumour cells,
  • which could lead to more effective precision medicine strategies.
  1. HCC formation in mice lacking ​EGFRin hepatocytes or all liver cells.
    http://www.nature.com/ncb/journal/vaop/ncurrent/carousel/ncb3031-f1.jpg

2. EGFR expression in Kupffer cells/liver macrophages promotes HCC development.

EGFR c2a expression in Kupffer cells.liver macrophages promotes HCC development.

EGFR c2a expression in Kupffer cells.liver macrophages promotes HCC development.

http://www.nature.com/ncb/journal/vaop/ncurrent/carousel/ncb3031-f2.jpg

Hypoxia-inducible factor 1 activation by aerobic glycolysis implicates
the Warburg effect in carcinogenesis
.

Lu H1, Forbes RA, Verma A.
J Biol Chem. 2002 Jun 28;277(26):23111-5. Epub 2002 Apr 9

Cancer cells display high rates of aerobic glycolysis, a phenomenon
known historically as the Warburg effect. Lactate and pyruvate, the end
products of glycolysis, are highly produced by cancer cells even in the
presence of oxygen
.

Hypoxia-induced gene expression in cancer cells

  • has been linked to malignant transformation.

Here we provide evidence that lactate and pyruvate

  • regulate hypoxia-inducible gene expression
  • independently of hypoxia
  • by stimulating the accumulation of hypoxia-inducible Factor 1alpha
    (HIF-1alpha).

In human gliomas and other cancer cell lines,

  • the accumulation of HIF-1alpha protein under aerobic conditions
  • requires the metabolism of glucose to pyruvate that
  1. prevents the aerobic degradation of HIF-1alpha protein,
  2. activates HIF-1 DNA binding activity, and
  3. enhances the expression of several HIF-1-activated genes
  4. erythropoietin,
  5. vascular endothelial growth factor,
  6. glucose transporter 3, and
  7. aldolase A.

Our findings support a novel role for pyruvate in metabolic signaling
and suggest a mechanism by which

  • high rates of aerobic glycolysis
  • can promote the malignant transformation and
  • survival of cancer cells.PMID: 11943784

Part IV. Transcription control and innate immunity

 c-Myc-induced transcription factor AP4 is required for
host protection mediated by CD8+ T cells

C Chou, AK Pinto, JD Curtis, SP Persaud, M Cella, Chih-Chung Lin, … & T Egawa Nature Immunology 17 Jun 2014;   http://dx.doi.org:/10.1038/ni.2943

The transcription factor c-Myc is essential for

  • the establishment of a metabolically active and proliferative state
  • in T cells after priming,

We identified AP4 as the transcription factor

  • that was induced by c-Myc and
  • sustained activation of antigen-specific CD8+ T cells.

Despite normal priming,

  • AP4-deficient CD8+ T cells
  • failed to continue transcription of a broad range of
    c-Myc-dependent targets.

Mice lacking AP4 specifically in CD8+ T cells showed

  • enhanced susceptibility to infection with West Nile virus.

Genome-wide analysis suggested that

  • many activation-induced genes encoding molecules
  • involved in metabolism were shared targets of
  • c-Myc and AP4.

Thus, AP4 maintains c-Myc-initiated cellular activation programs

  • in CD8+ T cells to control microbial infection.
  1. AP4 is regulated post-transcriptionally in CD8+ T cells.

Microarray analysis of transcription factor–encoding genes with a difference
in expression of >1.8-fold in activated CD8+ T cells treated for 12 h with
IL-2 (100 U/ml; + IL-2) relative to their expression in activated CD8+ T cells…
http://www.nature.com/ni/journal/vaop/ncurrent/carousel/ni.2943-F1.jpg

2. AP4 is required for the population expansion of antigen specific
CD8+ T cells following infection with LCMV-Arm.

Expression of CD4, CD8α and KLRG1 (a) and binding of an
H-2Db–gp(33–41) tetramer and expression of CD8α, KLRG1 and
CD62L (b) in splenocytes from wild-type (WT) and Tfap4−/− mice,
assessed by flow cytometry 8 d after infection
http://www.nature.com/ni/journal/vaop/ncurrent/carousel/ni.2943-F2.jpg

3. AP4 is required for the sustained clonal expansion of CD8+ T cells
but  not for their initial proliferation.
http://www.nature.com/ni/journal/vaop/ncurrent/carousel/ni.2943-F3.jpg

  1. AP4 is essential for host protection against infection with WNV, in
    a CD8+ T cell–intrinsic manner.
AP4 is essential for host protection against infection with WNV, in a CD8+ T cell–intrinsic manner.

AP4 is essential for host protection against infection with WNV, in a CD8+ T cell–intrinsic manner.

  •  Survival of Tfap4F/FCre− control mice (Cre−; n = 16) and
  • Tfap4F/FCD8-Cre+ mice (CD8-Cre+; n = 22) following infection with WNV.
    (b,c) Viral titers in the brain (b) and spleen (c) of Tfap4F/F Cre− and Tfap4F/F
    CD8-Cre+ mice  on day 9…
    http://www.nature.com/ni/journal/vaop/ncurrent/carousel/ni.2943-F4.jpg

AP4 is essential for the sustained expression of genes that are targets of c-Myc.

Normalized signal intensity (NSI) of endogenous transcripts in
Tfap4+/+ and Tfap4−/− OT-I donor T cells adoptively transferred into
host mice and assessed on day 4 after infection of the host with LM-OVA
(top), and that of ERCC controls
http://www.nature.com/ni/journal/vaop/ncurrent/carousel/ni.2943-F6.jpg

Sustained c-Myc expression ‘rescues’ defects of Tfap4−/− CD8+ T cells.
http://www.nature.com/ni/journal/vaop/ncurrent/carousel/ni.2943-F7.jpg

AP4 and c-Myc have distinct biological functions.
http://www.nature.com/ni/journal/vaop/ncurrent/carousel/ni.2943-SF7.jpg

Mucosal memory CD8+ T cells are selected in the periphery
by an MHC class I molecule

Y Huang, Y Park, Y Wang-Zhu, …A Larange, R Arens, & H Cheroutre

Nature Immunology 2 Oct 2011; 12: 1086–1095
http://dx.doi.org:/10.1038/ni.2106

The presence of immune memory at pathogen-entry sites is a prerequisite
for protection. We show that the non-classical major histocompatibility
complex (MHC) class I molecule

  • thymus leukemia antigen (TL),
  • induced on dendritic cells interacting with CD8αα on activated CD8αβ+ T cells,
  • mediated affinity-based selection of memory precursor cells.

Furthermore, constitutive expression of TL on epithelial cells

  • led to continued selection of mature CD8αβ+ memory T cells.

The memory process driven by TL and CD8αα

  • was essential for the generation of CD8αβ+ memory T cells in the intestine and
  • the accumulation of highly antigen-sensitive CD8αβ+ memory T cells
  • that form the first line of defense at the largest entry port for pathogens.

The metabolic checkpoint kinase mTOR is essential for IL-15 signaling during the development and activation of NK cells.

Marçais A, Cherfils-Vicini J, Viant C, Degouve S, Viel S, Fenis A, Rabilloud J,
Mayol K, Tavares A, Bienvenu J, Gangloff YG, Gilson E, Vivier E,Walzer T.
Nat Immunol. 2014 Aug; 15(8):749-757. Epub 2014 Jun 29
http://dx.doi.org:/10.1038/ni.2936  .    PMID: 24973821

Interleukin 15 (IL-15) controls

  • both the homeostasis and the peripheral activation of natural killer (NK) cells.

We found that the metabolic checkpoint kinase

  • mTOR was activated and boosted bioenergetic metabolism
  • after exposure of NK cells to high concentrations of IL-15,

whereas low doses of IL-15 triggered

  • only phosphorylation of the transcription factor STAT5.

mTOR

  • stimulated the growth and nutrient uptake of NK cells and
  • positively fed back on the receptor for IL-15.

This process was essential for

  • sustaining NK cell proliferation during development and
  • the acquisition of cytolytic potential during inflammation
    or viral infection.

The mTORC1 inhibitor rapamycin 

  • inhibited NK cell cytotoxicity both in mice and humans;
    • this probably contributes to the immunosuppressive
      activity of this drug in different clinical settings.

The Critical Role of IL-15-PI3K-mTOR Pathway in Natural Killer Cell
Effector Functions.
Nandagopal NAli AKKomal AKLee SH.   Author information
Front Immunol. 2014 Apr 23; 5:187. eCollection 2014.
http://dx.doi.org:/10.3389/fimmu.2014.00187

Natural killer (NK) cells were so named for their uniqueness in killing
certain tumor and virus-infected cells without prior sensitization.
Their functions are modulated in vivo by several soluble immune mediators;

  • interleukin-15 (IL-15) being the most potent among them in
    enabling NK cell homeostasis, maturation, and activation.

During microbial infections,

  • NK cells stimulated with IL-15 display enhanced cytokine responses.

This priming effect has previously been shown with respect to increased
IFN-γ production in NK cells

  • upon IL-12 and IL-15/IL-2 co-stimulation.
  • we explored if this effect of IL-15 priming 
  • can be extended to various other cytokines and
  • observed enhanced NK cell responses to stimulation
    • with IL-4, IL-21, IFN-α, and IL-2 in addition to IL-12.
  • we also observed elevated IFN-γ production in primed NK cells

Currently, the fundamental processes required for priming and

  • whether these signaling pathways work collaboratively or
    independently 

    • for NK cell functions are poorly understood.

We examined IL-15 effects on NK cells in which

  • the pathways emanating from IL-15 receptor activation
    • were blocked with specific inhibitors
    • To identify the key signaling events for NK cell priming,

Our results demonstrate that

the PI3K-AKT-mTOR pathway is critical for cytokine responses
in IL-15 primed NK cells. 

This pathway is also implicated in a broad range of

  • IL-15-induced NK cell effector functions such as
    • proliferation and cytotoxicity.

Likewise, NK cells from mice

  • treated with rapamycin to block the mTOR pathway
  • displayed defects in proliferation, and IFN-γ and granzyme B productions
  • resulting in elevated viral burdens upon murine cytomegalovirus infection.

Taken together, our data demonstrate

  • the requirement of PI3K-mTOR pathway
    • for enhanced NK cell functions by IL-15, thereby
  • coupling the metabolic sensor mTOR to NK cell anti-viral responses.

KEYWORDS: IL-15; JAK–STAT pathway; mTOR pathway; natural killer cells; signal transduction

Part V. Predicting Therapeutic Targets 

New discovery approach accelerates identification of potential cancer treatments
 Laura Williams, Univ. of Michigan   09/30/2014
http://www.rdmag.com/news/2014/09/new-discovery-approach-accelerates-identification-potential-cancer-treatments

Researchers at the Univ. of Michigan have described a new approach to
discovering potential cancer treatments that

  • requires a fraction of the time needed for more traditional methods.

They used the platform to identify

  • a novel antibody that is undergoing further investigation as a potential
    treatment for breast, ovarian and other cancers.

In research published online in the Proceedings of the National Academy
of Sciences
, researchers in the laboratory of Stephen Weiss at the U-M Life
Sciences Institute detail an approach

  • that replicates the native environment of cancer cells and
  • increases the likelihood that drugs effective against the growth of
    tumor cells in test tube models
  • will also stop cancer from growing in humans.

The researchers have used their method

  • to identify an antibody that stops breast cancer tumor growth in animal models, and
  • they are investigating the antibody as a potential treatment in humans.

“Discovering new targets for cancer therapeutics is a long and tedious undertaking, and

  • identifying and developing a potential drug to specifically hit that
    target without harming healthy cells is a daunting task,” Weiss said.
  • “Our approach allows us to identify potential therapeutics
    • in a fraction of the time that traditional methods require.”

The researchers began by

  • creating a 3-D “matrix” of collagen, a connective tissue molecule very similar to that found
    • surrounding breast cancer cells in human patients.
  • They then embedded breast cancer cells into the collagen matrix,
    • where the cells grew as they would in human tissue.

The investigators then injected the cancer-collagen tissue composites into mice that then

  • recognize the human cancer cells as foreign tissue.
    • Much in the way that our immune system generates antibodies
      to fight infection,
  • the mice began to generate thousands of antibodies directed against
    the human cancer cells.
  • These antibodies were then tested for the ability to stop the growth
    of the human tumor cells.

“We create an environment in which cells cultured in the laboratory ‘think’
they are growing in the body and then

  • rapidly screen large numbers of antibodies to see if any exert
    anti-cancer effects,” Weiss said.
  • “This allows us to select promising antibodies very quickly and then

They discovered a particular antibody, 4C3, which was able to

  • almost completely stop the proliferation of the breast cancer cells.

They then identified the molecule on the cancer cells that the antibody targets.

The antibody can be further engineered to generate

  • humanized monoclonal antibodies for use in patients

“We still need to do a lot more work to determine how effective 4C3 might be as a
treatment for breast and other cancers, on its own or in conjunction with other
therapies,” Weiss said. “But we have enough data to warrant further pursuit,
and are expanding our efforts to use this discovery platform to find similarly promising antibodies.”

Source: Univ. of Michigan

  1. Jose Eduardo de Salles Roselino

    Larry,
    I think you have made a great effort in order to connect basic ideas of metabolic regulation with those of gene expression control “modern” mechanisms.
    Yet, I do not think that at this stage it will be clear for all readers. At least, for the great majority of the readers. The most important factor I my opinion, is derived from the fact that modern readers considers that metabolic regulation deals with so called “housekeeping activities” of the cell. Something that is of secondary, tertiary or even less level of relevance.
    My idea, that you have mentioned in the text when you write at the beginning, the word biochemistry, in order to resume it, derives from the reading of What is life together with Prof. Leloir . For me and also, for him, biochemistry comprises a set of techniques and also a framework of reasoning about scientific results. As a set of techniques, Schrodinger has considered that it will lead to better understanding of genetics and of physiology as a two legs structure supporting the future progress related to his time (mid-forties). For Leloir, the key was the understanding of chemical reactivity and I agree with him. However, as I was able to talk and discuss it with him in detail, we should also take into account levels of stabilities of macromolecules and above all, regulation of activities and function (this is where) Pasteur effect that I was studying in Leloir´s lab at that time, 1970-72, gets into the general picture.
    Regulation for complex living beings , that also have cancer cell as a great topic of research problem can be understood through the understanding of two quite different results when opposition with lack of regulation is taken into account or experimentally elicited. The most clearly line of experiments can follow the Pasteur Effect as the intracellular result best seen when aerobiosis is compared with anaerobiosis as conditions in which maintenance of ATP levels and required metabolic regulation (Energy charge D.E, Atkinson etc) is studied. Another line of experiments is one that takes into account the extracellular result or for instance the homeostatic regulation of blood glucose levels. The blood glucose level is the most conspicuous and related to Pasteur Effect regulatory event that can be studied in the liver taking into account both final results tested or compared regarding its regulation, ATP levels maintenance (intracellular) and blood glucose maintenance (extracellular).
    My key idea is to consider that the same factors that elicits fast regulatory responses also elicits the slow energetic expensive regulatory responses. The biologic logic behind this common root is the ATP economy. In case, the regulatory stimulus fades out quickly the fast regulatory responses are good enough to maintain life and the time requiring, energetic costly responses will soon be stopped cutting short the ATP expenditure. In case, the stimulus last for long periods of time the fast responses are replaced by adaptive responses that in general will follow the line of cell differentiation mechanisms with changes in gene expression etc.
    The change from fast response mechanisms to long lasting developmentally linked ones is not sharp. Therefore, somehow, cancer cells becomes trapped into a metastable regulatory mechanism that prevents cell differentiation and reinforces those mechanisms linked to its internal regulatory goals. This metastable mechanism takes advantage from the fact that other cells, tissues and organs will take good care of homeostatic mechanisms that provide for their nutritional needs. In the case of my Hepatology work you will see a Piruvate kinase that does not responds to homeostatic signals .

Read Full Post »


Metabolomic analysis of two leukemia cell lines. I.

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

Leaders in Pharmaceutical Intelligence

 

I have just posted a review of metabolomics.  In the last few weeks, the Human Metabolome was published.  I am hopeful that my decision has taken the right path to prepare my readers adequately if they will have read the articles that preceded this.  I pondered how I would present this massive piece of work, a study using two leukemia cell lines and mapping the features and differences that drive the carcinogenesis pathways, and identify key metabolic signatures in these differentiated cell types and subtypes.  It is a culmination of a large collaborative effort that required cell culture, enzymatic assays, mass spectrometry, the full measure of which I need not present here, and a very superb validation of the model with a description of method limitations or conflicts.  This is a beautiful piece of work carried out by a small group by today’s standards.

I shall begin this by asking a few questions that will be addressed in the article, which I need to beak up into parts, to draw the readers in more effectively.

Q 1. What metabolic pathways do you expect to have the largest role in the study about to be presented?

Q2. What are the largest metabolic differences that one expects to see in compairing the two lymphoblastic cell lines?

Q3. What methods would be used to extract the information based on external metabolites, enzymes, substrates, etc., to create the model for the cell internal metabolome?

 

 

Abstract

Metabolic models can provide a mechanistic framework to analyze information-rich omics data sets, and are increasingly being used

  • to investigate metabolic alternations in human diseases.

An expression of the altered metabolic pathway utilization is

  • the selection of metabolites consumed and released by cells.

However, methods for the inference of intracellular metabolic states from extracellular measurements in the context of metabolic models

  • remain underdeveloped compared to methods for other omics data.

Herein, we describe a workflow for such an integrative analysis

  • extracting the information from extracellular metabolomics data.

We demonstrate, using the lymphoblastic leukemia cell lines Molt-4 and CCRF-CEM, how

  • our methods can reveal differences in cell metabolism.

Our models explain metabolite uptake and secretion by

  • predicting a more glycolytic phenotype for the CCRF-CEM model and
  • a more oxidative phenotype for the Molt-4 model, which
  • was supported by our experimental data.

Gene expression analysis revealed altered expression of gene products at

  • key regulatory steps in those central metabolic pathways,

and literature query emphasized

  • the role of these genes in cancer metabolism.

Moreover, in silico gene knock-outs identified

  • unique control points for each cell line model, e.g., phosphoglycerate dehydrogenase for the Molt-4 model.

Thus, our workflow is well suited to the characterization of cellular metabolic traits based on

  • extracellular metabolomic data, and
  • it allows the integration of multiple omics data sets into a cohesive picture based on a defined model context.

Keywords Constraint-based modeling _ Metabolomics _Multi-omics _ Metabolic network _ Transcriptomics

 

Reviewer Summary:

  1. A model is introduced to demonstrate a lymphocytic integrated data set using to cell lines.
  2. The method is required to integrate extracted data sets from extracellular metabolites to an intracellular picture of cellular metabolism for each cell line.
  3. The method predicts a more glycolytic or a more oxidative metabolic framework for one or the othe cell line.
  4. The genetic phenotypes differ with a unique control point for each cell line.
  5. The model presents an integration of omics data sets into a cohesive picture based on the model context.

Without having seen the full presentation –

  1. Is the method a snapshot of the neoplastic processes described?
  2. Does the model give insight into the cellular metabolism of an initial cell state for either one or both cell lines?
  3. Would one be able to predict a therapeutic strategy based on the model for either or both cell lines?

Before proceeding further into the study, I would conjecture that there is no way of knowing the initial state ( consistent with what is described by Ilya Prigogine for a self-organizing system) because the model is based on the study of cultured cells that had an unknown metabolic control profile in a host proliferating bone marrow that is likely B-cell origin.  So this is a snapshot of a stable state of two incubated cell lines.  Then the question that is raised is whether there is not only a genetic-phenotypic relationship between the cells in culture and the external metabolites produced, but also whether differences can be discerned between the  internal metabolic constructions that would fit into a family tree.

 

Introduction

Modern high-throughput techniques

  • have increased the pace of biological data generation.

Also referred to as the ‘‘omics avalanche’’, this wealth of data

  • provides great opportunities for metabolic discovery.

Omics data sets contain a snapshot of almost the entire repertoire of

  • mRNA, protein, or metabolites at a given time point or
  • under a particular set of experimental conditions.

Because of the high complexity of the data sets,

  • computational modeling is essential for their integrative analysis.

Currently, such data analysis

  • is a bottleneck in the research process and
  • methods are needed to facilitate the use of these data sets, e.g.,
  1. through meta-analysis of data available in public databases
    [e.g., the human protein atlas (Uhlen et al. 2010)
  2. or the gene expression omnibus (Barrett  et al.  2011)], and
  3. to increase the accessibility of valuable information
    for the biomedical research community.

Constraint-based modeling and analysis (COBRA) is

  • a computational approach that has been successfully used
  • to investigate and engineer microbial metabolism through
    the prediction of steady-states (Durot et al.2009).

The basis of COBRA is network reconstruction: networks are assembled

  1. in a bottom-up fashion based on genomic data and
  2. extensive organism-specific information from the literature.

Metabolic reconstructions

  1. capture information on the known biochemical transformations
    taking place in a target organism
  2. to generate a biochemical, genetic and genomic knowledge base
    (Reed et al. 2006).

Once assembled, a metabolic reconstruction

  • can be converted into a mathematical model
    (Thiele and Palsson 2010), and
  • model properties can be interrogated using a great variety of methods
    (Schellenberger et al. 2011).

The ability of COBRA models to represent

  • genotype–phenotype and environment–phenotype relationships
  • arises through the imposition of constraints,
  • which limit the system to a subset of possible network states
    (Lewis et al. 2012).

Currently, COBRA models exist for more than 100 organisms, including humans
(Duarte et al. 2007; Thiele et al. 2013).

Since the first human metabolic reconstruction was described
[Recon 1 (Duarte et al. 2007)],

  • biomedical applications of COBRA have increased
    (Bordbar and Palsson 2012).

One way to contextualize networks is to

  • define their system boundaries
  • according to the metabolic states of the system,
    e.g., disease or dietary regimes.

The consequences of the applied constraints

  • can then be assessed for the entire network
    (Sahoo and Thiele 2013).

Additionally, omics data sets have frequently been used

  • to generate cell-type or condition-specific metabolic models.

Models exist for specific cell types, such as

  • enterocytes (Sahoo and Thiele2013),
  • macrophages (Bordbar et al. 2010), and
  • adipocytes (Mardinoglu et al. 2013), and
  • even multi-cell assemblies that represent
    the interactions of brain cells (Lewis et al. 2010).

All of these cell type specific models,

  • except the enterocyte reconstruction
  • were generated based on omics data sets.

Cell-type-specific models have been used

  • to study diverse human disease conditions.

For example, an adipocyte model was generated using

  • transcriptomic,
  • proteomic, and
  • metabolomics data.

This model was subsequently used to investigate

  • metabolic alternations in adipocytes
  • that would allow for the stratification of obese patients
    (Mardinoglu et al. 2013).

One highly active field within the biomedical applications of COBRA is

  • cancer metabolism (Jerby and Ruppin, 2012).

Omics-driven large-scale models have been used

  • to predict drug targets (Folger et al. 2011; Jerby et al. 2012).

A cancer model was generated using

  • multiple gene expression data sets and
  • subsequently used to predict synthetic lethal gene pairs
  • as potential drug targets selective for the cancer model,
  • but non-toxic to the global model (Recon 1),
  • a consequence of the reduced redundancy in the
    cancer specific model (Folger et al. 2011).

In a follow up study, lethal synergy between

  • FH and enzymes of the heme metabolic pathway
    were experimentally validated and
  • resolved the mechanism by which FH deficient cells,
    e.g., in renal-cell cancer cells
  • survive a non-functional TCA cycle (Frezza et al. 2011).

Contextualized models, which contain only 

  • the subset of reactions active in 
  • a particular tissue (or cell-) type,
  • can be generated in different ways
    (Becker and Palsson, 2008; Jerby et al. 2010).

However, the existing algorithms mainly consider

  • gene expression and proteomic data to define the reaction sets
  • that comprise the contextualized metabolic models.

These subset of reactions are usually defined based on

  • the expression or absence of expression of the genes or proteins
    (present and absent calls), or
  • inferred from expression values or differential gene expression.

Comprehensive reviews of the methods are available
(Blazier and Papin, 2012; Hyduke et al. 2013).

Only the compilation of a large set of omics data sets

  • can result in a tissue (or cell-type) specific metabolic model, whereas

the representation of one particular experimental condition is achieved through

  • the integration of omics data set generated from one experiment only
    (condition-specific cell line model).

Recently, metabolomic data sets

  • have become more comprehensive and using these data sets allow
  • direct determination of the metabolic network components (the metabolites).

Additionally, metabolomics has proven to be

  1. stable,
  2. relatively inexpensive, and
  3. highly reproducible
    (Antonucci et al. 2012).

These factors make metabolomic data sets

  •  particularly valuable for interrogation of metabolic phenotypes. 

Thus, the integration of these data sets is now an active field of research
(Li et al. 2013; Mo et al. 2009; Paglia et al. 2012b; Schmidt et al. 2013).

Generally, metabolomic data can be incorporated into metabolic networks as

  1. qualitative,
  2. quantitative, and
  3. thermodynamic constraints
    (Fleming et al. 2009; Mo et al. 2009).

Mo et al. used metabolites detected in the spent medium
of yeast cells to determine

  • intracellular flux states through a sampling analysis (Mo et al. 2009),
  • which allowed unbiased interrogation of the possible network states
    (Schellenberger and Palsson 2009)
  • and prediction of internal pathway use.

Such analyses have also been used

  • to reveal the effects of enzymopathies on red blood cells (Price et al. 2004),
  • to study effects of diet on diabetes (Thiele et al. 2005) and
  • to define macrophage metabolic states (Bordbar et al. 2010).

This type of analysis is available as a function in the COBRA toolbox
(Schellenberger et al. 2011).

 

 

 

In this study, we established a workflow for the generation and analysis of

  • condition-specific metabolic cell line models that
  • can facilitate the interpretation of metabolomic data.

Our modeling yields meaningful predictions regarding

  • metabolic differences between two lymphoblastic leukemia cell lines
    (Fig. 1A).
Differences in the use of the TCA cycle by the CCRF-CEM

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

 

 

 

http://link.springer.com/static-content/images/404/art%253A10.1007%252
Fs11306-014-0721-3/MediaObjects/11306_2014_721_Fig1_HTML.gif

Fig. 1

A  Combined experimental and computational pipeline to study human metabolism.
Experimental work and omics data analysis steps precede computational modeling. Model

  • predictions are validated based on targeted experimental data.

Metabolomic and transcriptomic data are used for

  • model refinement and submodel extraction.

Functional analysis methods are used to characterize

  • the metabolism of the cell-line models and compare it to additional experimental
    data.

The validated models are subsequently 

  • used for the prediction of drug targets.

B Uptake and secretion pattern of model.
All metabolite uptakes and secretions that were mapped during model
generation are shown.
Metabolite uptakes are depicted on the left, and

  • secreted metabolites are shown on the right.

A number of metabolite exchanges mapped to the model

  • were unique to one cell line.

Differences between cell lines were used to set

  • quantitative constraints for the sampling analysis.

C Statistics about the cell line-specific network generation.

 Quantitative constraints.
For the sampling analysis, an additional

  • set of constraints was imposed on the cell line specific models,
  • emphasizing the differences in metabolite uptake and secretion between cell lines.

Higher uptake of a metabolite was allowed in the model of the cell line

  • that consumed more of the metabolite in vitro, whereas
  • the supply was restricted for the model with lower in vitro uptake.

This was done by establishing the same ratio between the models bounds as detected in vitro.
X denotes the factor(slope ratio) that

  1. distinguishes the bounds, and
  2. which was individual for each metabolite.
  • (a) The uptake of a metabolite could be x times higher in CCRF-CEM cells,
    (b) the metabolite uptake could be x times higher in Molt-4,
    (c) metabolite secretion could be x times higher in CCRF-CEM, or
    (d) metabolite secretion could be x times higher in Molt-4 cells. LOD limit of detection.

The consequence of the adjustment was, in case of uptake, that  one model

  1. was constrained to a lower metabolite uptake (A, B), and the difference
  2. depended on the ratio detected in vitro.

In case of secretion,

  • one model had to secrete more of the metabolite, and again

the difference depended on

  • the experimental difference detected between the cell lines.

Q5. What is your expectation that this type of integrative approach could be used for facilitating medical data interpretations?

The most inventive approach was made years ago by using data constructions from the medical literature by a pioneer in the medical record development, but the technology was  not what it is today, and the cost of data input was high.  Nevertheless, the data acquisition would not be uniform across institutions, except for those that belong to a consolidated network with all of the data in the cloud, and the calculations would be carried out with a separate engine.  However, whether the uniform capture of the massive amount of data needed is not possible in the near foreseeable future.  There is no accurate way of assessing the system cost, and predicting the benefits.  In carrying this model forward there has to be a minimal amount of insufficient data.  The developments in the regulatory sphere have created a high barrier.

This concludes a first portion of this presentation.

 

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Metabolomics, Metabonomics and Functional Nutrition: the next step in nutritional metabolism and biotherapeutics


Metabolomics, Metabonomics and Functional Nutrition: the next step in nutritional metabolism and biotherapeutics

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

 

The human genome is estimated to encode over 30,000 genes, and to be responsible for generating more than 100,000 functionally distinct proteins. Understanding the interrelationships among

  1. genes,
  2. gene products, and
  3. dietary habits

is fundamental to identifying those who will benefit most from or be placed at risk by intervention strategies.

Unraveling the multitude of

  • nutrigenomic,
  • proteomic, and
  • metabolomic patterns

that arise from the ingestion of foods or their

  • bioactive food components

will not be simple but is likely to provide insights into a tailored approach to diet and health. The use of new and innovative technologies, such as

  • microarrays,
  • RNA interference, and
  • nanotechnologies,

will provide needed insights into molecular targets for specific bioactive food components and

  • how they harmonize to influence individual phenotypes(1).

Nutrigenetics asks the question how individual genetic disposition, manifesting as

  • single nucleotide polymorphisms,
  • copy-number polymorphisms and
  • epigenetic phenomena,

affects susceptibility to diet.

Nutrigenomics addresses the inverse relationship, that is how diet influences

  • gene transcription,
  • protein expression and
  • metabolism.

A major methodological challenge and first pre-requisite of nutrigenomics is integrating

  • genomics (gene analysis),
  • transcriptomics (gene expression analysis),
  • proteomics (protein expression analysis) and
  • metabonomics (metabolite profiling)

to define a “healthy” phenotype. The long-term deliverable of nutrigenomics is personalised nutrition (2).

Science is beginning to understand how genetic variation and epigenetic events

  • alter requirements for, and responses to, nutrients (nutrigenomics).

At the same time, methods for profiling almost all of the products of metabolism in a single sample of blood or urine are being developed (metabolomics). Relations between

  • diet and nutrigenomic and metabolomic profiles and
  • between those profiles and health

have become important components of research that could change clinical practice in nutrition.

Most nutrition studies assume that all persons have average dietary requirements, and the studies often

  • do not plan for a large subset of subjects who differ in requirements for a nutrient.

Large variances in responses that occur when such a population exists

  • can result in statistical analyses that argue for a null effect.

If nutrition studies could better identify responders and differentiate them from nonresponders on the basis of nutrigenomic or metabolomic profiles,

  • the sensitivity to detect differences between groups could be greatly increased, and
  • the resulting dietary recommendations could be appropriately targeted (3).

In recent years, nutrition research has moved from classical epidemiology and physiology to molecular biology and genetics. Following this trend,

  • Nutrigenomics has emerged as a novel and multidisciplinary research field in nutritional science that
  • aims to elucidate how diet can influence human health.

It is already well known that bioactive food compounds can interact with genes affecting

  • transcription factors,
  • protein expression and
  • metabolite production.

The study of these complex interactions requires the development of

  • advanced analytical approaches combined with bioinformatics.

Thus, to carry out these studies

  • Transcriptomics,
  • Proteomics and
  • Metabolomics

approaches are employed together with an adequate integration of the information that they provide(4).

Metabonomics is a diagnostic tool for metabolic classification of individuals with the asset of quantitative, non-invasive analysis of easily accessible human body fluids such as urine, blood and saliva. This feature also applies to some extent to Proteomics, with the constraint that

  • the latter discipline is more complex in terms of composition and dynamic range of the sample.

Apart from addressing the most complex “Ome”, Proteomics represents

  • the only platform that delivers not only markers for disposition and efficacy
  • but also targets of intervention.

Application of integrated Omic technologies will drive the understanding of

  • interrelated pathways in healthy and pathological conditions and
  • will help to define molecular ‘switchboards’,
  • necessary to develop disease related biomarkers.

This will contribute to the development of new preventive and therapeutic strategies for both pharmacological and nutritional interventions (5).

Human health is affected by many factors. Diet and inherited genes play an important role. Food constituents,

  • including secondary metabolites of fruits and vegetables, may
  • interact directly with DNA via methylation and changes in expression profiles (mRNA, proteins)
  • which results in metabolite content changes.

Many studies have shown that

  • food constituents may affect human health and
  • the exact knowledge of genotypes and food constituent interactions with
  • both genes and proteins may delay or prevent the onset of diseases.

Many high throughput methods have been employed to get some insight into the whole process and several examples of successful research, namely in the field of genomics and transcriptomics, exist. Studies on epigenetics and RNome significance have been launched. Proteomics and metabolomics need to encompass large numbers of experiments and linked data. Due to the nature of the proteins, as well as due to the properties of various metabolites, experimental approaches require the use of

  • comprehensive high throughput methods and a sufficiency of analysed tissue or body fluids (6).

New experimental tools that investigate gene function at the subcellular, cellular, organ, organismal, and ecosystem level need to be developed. New bioinformatics tools to analyze and extract meaning

  • from increasingly systems-based datasets will need to be developed.

These will require, in part, creation of entirely new tools. An important and revolutionary aspect of “The 2010 Project”  is that it implicitly endorses

  • the allocation of resources to attempts to assign function to genes that have no known function.

This represents a significant departure from the common practice of defining and justifying a scientific goal based on the biological phenomena. The rationale for endorsing this radical change is that

  • for the first time it is feasible to envision a whole-systems approach to gene and protein function.

This whole-systems approach promises to be orders of magnitude more efficient than the conventional approach (7).

The Institute of Medicine recently convened a workshop to review the state of the various domains of nutritional genomics research and policy and to provide guidance for further development and translation of this knowledge into nutrition practice and policy (8). Nutritional genomics holds the promise to revolutionize both clinical and public health nutrition practice and facilitate the establishment of

(a) genome-informed nutrient and food-based dietary guidelines for disease prevention and healthful aging,

(b) individualized medical nutrition therapy for disease management, and

(c) better targeted public health nutrition interventions (including micronutrient fortification and supplementation) that

  • maximize benefit and minimize adverse outcomes within genetically diverse human populations.

As the field of nutritional genomics matures, which will include filling fundamental gaps in

  • knowledge of nutrient-genome interactions in health and disease and
  • demonstrating the potential benefits of customizing nutrition prescriptions based on genetics,
  • registered dietitians will be faced with the opportunity of making genetically driven dietary recommendations aimed at improving human health.

The new era of nutrition research translates empirical knowledge to evidence-based molecular science (9). Modern nutrition research focuses on

  • promoting health,
  • preventing or delaying the onset of disease,
  • optimizing performance, and
  • assessing risk.

Personalized nutrition is a conceptual analogue to personalized medicine and means adapting food to individual needs. Nutrigenomics and nutrigenetics

  • build the science foundation for understanding human variability in
  • preferences, requirements, and responses to diet and
  • may become the future tools for consumer assessment

motivated by personalized nutritional counseling for health maintenance and disease prevention.

The primary aim of ―omic‖ technologies is

  • the non-targeted identification of all gene products (transcripts, proteins, and metabolites) present in a specific biological sample.

By their nature, these technologies reveal unexpected properties of biological systems.

A second and more challenging aspect of ―omic‖ technologies is

  • the refined analysis of quantitative dynamics in biological systems (10).

For metabolomics, gas and liquid chromatography coupled to mass spectrometry are well suited for coping with

  • high sample numbers in reliable measurement times with respect to
  • both technical accuracy and the identification and quantitation of small-molecular-weight metabolites.

This potential is a prerequisite for the analysis of dynamic systems. Thus, metabolomics is a key technology for systems biology.

In modern nutrition research, mass spectrometry has developed into a tool

  • to assess health, sensory as well as quality and safety aspects of food.

In this review, we focus on health-related benefits of food components and, accordingly,

  • on biomarkers of exposure (bioavailability) and bioefficacy.

Current nutrition research focuses on unraveling the link between

  • dietary patterns,
  • individual foods or
  • food constituents and

the physiological effects at cellular, tissue and whole body level

  • after acute and chronic uptake.

The bioavailability of bioactive food constituents as well as dose-effect correlations are key information to understand

  • the impact of food on defined health outcomes.

Both strongly depend on appropriate analytical tools

  • to identify and quantify minute amounts of individual compounds in highly complex matrices–food or biological fluids–and
  • to monitor molecular changes in the body in a highly specific and sensitive manner.

Based on these requirements,

  • mass spectrometry has become the analytical method of choice
  • with broad applications throughout all areas of nutrition research (11).

Recent advances in high data-density analytical techniques offer unrivaled promise for improved medical diagnostics in the coming decade. Genomics, proteomics and metabonomics (as well as a whole slew of less well known ―omics‖ technologies) provide a detailed descriptor of each individual. Relating the large quantity of data on many different individuals to their current (and possibly even future) phenotype is a task not well suited to classical multivariate statistics. The datasets generated by ―omics‖ techniques very often violate the requirements for multiple regression. However, another statistical approach exists, which is already well established in areas such as medicinal chemistry and process control, but which is new to medical diagnostics, that can overcome these problems. This approach, called megavariate analysis (MVA),

  • has the potential to revolutionise medical diagnostics in a broad range of diseases.

It opens up the possibility of expert systems that can diagnose the presence of many different diseases simultaneously, and

  • even make exacting predictions about the future diseases an individual is likely to suffer from (12).

Cardiovascular diseases

Cardiovascular diseases are the leading cause of morbidity and mortality in Western countries. Although coronary thrombosis is the final event in acute coronary syndromes,

  • there is increasing evidence that inflammation also plays a role in development of atherosclerosis and its clinical manifestations, such as
  • myocardial infarction, stroke, and peripheral vascular disease.

The beneficial cardiovascular health effects of

  • diets rich in fruits and vegetables are in part mediated by their flavanol content.

This concept is supported by findings from small-scale intervention studies with surrogate endpoints including

  1. endothelium-dependent vasodilation,
  2. blood pressure,
  3. platelet function, and
  4. glucose tolerance.

Mechanistically, short term effects on endothelium-dependent vasodilation

  • following the consumption of flavanol-rich foods, as well as purified flavanols,
  • have been linked to an increased nitric oxide bioactivity.

The critical biological target(s) for flavanols have yet to be identified (13), but we are beginning to see over the horizon.

Nutritional sciences

Nutrition sciences apply

  1. transcriptomics,
  2. proteomics and
  3. metabolomics

to molecularly assess nutritional adaptations.

Transcriptomics can generate a

  • holistic overview on molecular changes to dietary interventions.

Proteomics is most challenging because of the higher complexity of proteomes as compared to transcriptomes and metabolomes. However, it delivers

  • not only markers but also
  • targets of intervention, such as
  • enzymes or transporters, and
  • it is the platform of choice for discovering bioactive food proteins and peptides.

Metabolomics is a tool for metabolic characterization of individuals and

  • can deliver metabolic endpoints possibly related to health or disease.

Omics in nutrition should be deployed in an integrated fashion to elucidate biomarkers

  • for defining an individual’s susceptibility to diet in nutritional interventions and
  • for assessing food ingredient efficacy (14).

The more elaborate tools offered by metabolomics opened the door to exploring an active role played by adipose tissue that is affected by diet, race, sex, and probably age and activity. When the multifactorial is brought into play, and the effect of changes in diet and activities studied we leave the study of metabolomics and enter the world of ―metabonomics‖. Adiponectin and adipokines arrive (15-22). We shall discuss ―adiposity‖ later.

Potential Applications of Metabolomics

Either individually or grouped as a profile, metabolites are detected by either

  • nuclear magnetic resonance spectroscopy or mass spectrometry.

There is potential for a multitude of uses of metabolome research, including

  1. the early detection and diagnosis of cancer and as
  2. both a predictive and pharmacodynamic marker of drug effect.

However, the knowledge regarding metabolomics, its technical challenges, and clinical applications is unappreciated

  • even though when used as a translational research tool,
  • it can provide a link between the laboratory and clinic.

Precise numbers of human metabolites is unknown, with estimates ranging from the thousands to tens of thousands. Metabolomics is a term that encompasses several types of analyses, including

(a) metabolic fingerprinting, which measures a subset of the whole profile with little differentiation or quantitation of metabolites;

(b) metabolic profiling, the quantitative study of a group of metabolites, known or unknown, within or associated with a particular metabolic pathway; and

(c) target isotope-based analysis, which focuses on a particular segment of the metabolome by analyzing

  • only a few selected metabolites that comprise a specific biochemical pathway.

 

Dynamic Construct of the –Omics

Dynamic Construct of the –Omics

 

Dynamic Construct of the –Omics

 

 

Iron metabolism – Anemia

Hepcidin is a key hormone governing mammalian iron homeostasis and may be directly or indirectly involved in the development of most iron deficiency/overload and inflammation-induced anemia. The anemia of chronic disease (ACD) is characterized by macrophage iron retention induced by cytokines and hepcidin regulation. Hepcidin controls cellular iron efflux on binding to the iron export protein ferroportin. While patients present with both ACD and iron deficiency anemia (ACD/IDA), the latter results from chronic blood loss. Iron retention during inflammation occurs in macrophages and the spleen, but not in the liver. In ACD, serum hepcidin concentrations are elevated, which is related to reduced duodenal and macrophage expression of ferroportin. Individuals with ACD/IDA have significantly lower hepcidin levels than ACD subjects. ACD/IDA patients, in contrast to ACD subjects, were able to absorb dietary iron from the gut and to mobilize iron from macrophages. Hepcidin elevation may affect iron transport in ACD and ACD/IDA and it is more responsive to iron demand with IDA than to inflammation. Hepcidin determination may aid in selecting appropriate therapy for these patients (23).

There is correlation between serum hepcidin, iron and inflammatory indicators associated with anemia of chronic disease (ACD), ACD, ACD concomitant iron-deficiency anemia (ACD/IDA), pure IDA and acute inflammation (AcI) patients. Hepcidin levels in anemia types were statistically different, from high to low: ACD, AcI > ACD/IDA > the control > IDA. Serum ferritin levels were significantly increased in ACD and AcI patients but were decreased significantly in ACD/IDA and IDA. Elevated serum EPO concentrations were found in ACD, ACD/IDA and IDA patients but not in AcI patients and the controls. A positive correlation exists between hepcidin and IL-6 levels only in ACD/IDA, AcI and the control groups. A positive correlation between hepcidin and ferritin was marked in the control group, while a negative correlation between hepcidin and ferritin was noted in IDA. The significant negative correlation between hepcidin expression and reticulocyte count was marked in both ACD/IDA and IDA groups. If the hepcidin role in pathogenesis of ACD, ACD/IDA and IDA, it could be a potential marker for detection and differentiation of these anemias (24).

Cancer

Because cancer cells are known to possess a highly unique metabolic phenotype, development of specific biomarkers in oncology is possible and might be used in identifying fingerprints, profiles, or signatures to detect the presence of cancer, determine prognosis, and/or assess the pharmacodynamic effects of therapy (25).

HDM2, a negative regulator of the tumor suppressor p53, is over-expressed in many cancers that retain wild-type p53. Consequently, the effectiveness of chemotherapies that induce p53 might be limited, and inhibitors of the HDM2–p53 interaction are being sought as tumor-selective drugs. A binding site within HDM2 has been dentified which can be blocked with peptides inducing p53 transcriptional activity. A recent report demonstrates the principle using drug-like small molecules that target HDM2 (26).

Obesity, CRP, interleukins, and chronic inflammatory disease

Elevated CRP levels and clinically raised CRP levels were present in 27.6% and 6.7% of the population, respectively. Both overweight (body mass index [BMI], 25-29.9 kg/m2) and obese (BMI, 30 kg/m2) persons were more likely to have elevated CRP levels than their normal-weight counterparts (BMI, <25 kg/m2). After adjusting for potential confounders, the odds ratio (OR) for elevated CRP was 2.13 for obese men and 6.21 for obese women. In addition, BMI was associated with clinically raised CRP levels in women, with an OR of 4.76 (95% CI, 3.42-6.61) for obese women. Waist-to-hip ratio was positively associated with both elevated and clinically raised CRP levels, independent of BMI. Restricting the analyses to young adults (aged 17-39 years) and excluding smokers, persons with inflammatory disease, cardiovascular disease, or diabetes mellitus and estrogen users did not change the main findings (27).

A study of C-reactive protein and interleukin-6 with measures of obesity and of chronic infection as their putative determinants related levels of C-reactive protein and interleukin-6 to markers of the insulin resistance syndrome and of endothelial dysfunction. Levels of C-reactive protein were significantly related to those of interleukin-6 (r=0.37, P<0.0005) and tumor necrosis factor-a (r=0.46, P<0.0001), and concentrations of C-reactive protein were related to insulin resistance as calculated from the homoeostasis model and to markers of endothelial dysfunction (plasma levels of von Willebrand factor, tissue plasminogen activator, and cellular fibronectin). A mean standard deviation score of levels of acute phase markers correlated closely with a similar score of insulin resistance syndrome variables (r=0.59, P<0.00005) and the data suggested that adipose tissue is an important determinant of a low level, chronic inflammatory state as reflected by levels of interleukin-6, tumor necrosis factor-a, and C-reactive protein (28).

A number of other studies have indicated the inflammatory ties of visceral obesity to adipose tissue metabolic profiles, suggesting a role in ―metabolic syndrome‖. There is now a concept of altered liver metabolism in ―non-alcoholic‖ fatty liver disease (NAFLD) progressing from steatosis to steatohepatitis (NASH) (31,32).

These unifying concepts were incomprehensible 50 years ago. It was only known that insulin is anabolic and that insulin deficiency (or resistance) would have consequences in the point of entry into the citric acid cycle, which generates 16 ATPs. In fat catabolism, triglycerides are hydrolyzed to break them into fatty acids and glycerol. In the liver the glycerol can be converted into glucose via dihydroxyacetone phosphate and glyceraldehyde-3-phosphate by way of gluconeogenesis. In the case of this cycle there is a tie in with both catabolism and anabolism.

 

TCA_reactions

TCA_reactions

 http://www.newworldencyclopedia.org/entry/Image:TCA_reactions.gif

 

For bypass of the Pyruvate Kinase reaction of Glycolysis, cleavage of 2 ~P bonds is required. The free energy change associated with cleavage of one ~P bond of ATP is insufficient to drive synthesis of phosphoenolpyruvate (PEP), since PEP has a higher negative G of phosphate hydrolysis than ATP.

The two enzymes that catalyze the reactions for bypass of the Pyruvate Kinase reaction are the following:

(a) Pyruvate Carboxylase (Gluconeogenesis) catalyzes:

pyruvate + HCO3 + ATP — oxaloacetate + ADP + Pi

(b) PEP Carboxykinase (Gluconeogenesis) catalyzes:

oxaloacetate + GTP — phosphoenolpyruvate + GDP + CO2

The concept of anomalies in the pathways with respect to diabetes was sketchy then, and there was much to be filled in. This has been substantially done, and is by no means complete. However, one can see how this comes into play with diabetic ketoacidosis accompanied by gluconeogenesis and in severe injury or sepsis with peripheral proteolysis to provide gluconeogenic precursors. The reprioritization of liver synthetic processes is also brought into play with the conundrum of protein-energy malnutrition.

The picture began to be filled in with the improvements in technology that emerged at the end of the 1980s with the ability to profile tissue and body fluids by NMR and by MS. There was already a good inkling of a relationship of type 2 diabetes to major indicators of CVD (29,30). And a long suspected relationship between obesity and type 2 diabetes was evident. But how did it tie together?

End Stage Renal Disease and Cardiovascular Risk

Mortality is markedly elevated in patients with end-stage renal disease. The leading cause of death is cardiovascular disease.

As renal function declines,

  • the prevalence of both malnutrition and cardiovascular disease increase.

Malnutrition and vascular disease correlate with the levels of

  • markers of inflammation in patients treated with dialysis and in those not yet on dialysis.

The causes of inflammation are likely to be multifactorial. CRP levels are associated with cardio-vascular risk in the general population.

The changes in endothelial cell function,

  • in plasma proteins, and
  • in lpiids in inflammation

are likely to be atherogenic.

That cardiovascular risk is inversely correlated with serum cholesterol in dialysis patients, suggests that

  • hyperlipidemia plays a minor role in the incidence of cardiovascular disease.

Hypoalbuminemia, ascribed to malnutrition, has been one of the most powerful risk factors that predict all-cause and cardiovascular mortality in dialysis patients. The presence of inflammation, as evidenced by increased levels of specific cytokines (interleukin-6 and tumor necrosis factor a) or acute-phase proteins (C-reactive protein and serum amyloid A), however, has been found to be associated with vascular disease in the general population as well as in dialysis patients. Patients have

  • loss of muscle mass and changes in plasma composition—decreases in serum albumin, prealbumin, and transferrin levels, also associated with malnutrition.

Inflammation alters

  • lipoprotein structure and function as well as
  • endothelial structure and function

to favor atherogenesis and increases

  • the concentration of atherogenic proteins in serum.

In addition, proinflammatory compounds, such as

  • advanced glycation end products, accumulate in renal failure, and
  • defense mechanisms against oxidative injury are reduced,

contributing to inflammation and to its effect on the vascular endothelium (33,34).

Endogenous copper can play an important role in postischemic reperfusion injury, a condition associated with endothelial cell activation and increased interleukin 8 (IL-8) production. Excessive endothelial IL-8 secreted during trauma, major surgery, and sepsis may contribute to the development of systemic inflammatory response syndrome (SIRS), adult respiratory distress syndrome (ARDS), and multiple organ failure (MOF). No previous reports have indicated that copper has a direct role in stimulating human endothelial IL-8 secretion. Copper did not stimulate secretion of other cytokines. Cu(II) appeared to be the primary copper ion responsible for the observed increase in IL-8 because a specific high-affinity Cu(II)-binding peptide, d-Asp-d-Ala-d-Hisd-Lys (d-DAHK), completely abolished this effect in a dose-dependent manner. These results suggest that Cu(II) may induce endothelial IL-8 by a mechanism independent of known Cu(I) generation of reactive oxygen species (35).

Blood coagulation plays a key role among numerous mediating systems that are activated in inflammation. Receptors of the PAR family serve as sensors of serine proteinases of the blood clotting system in the target cells involved in inflammation. Activation of PAR_1 by thrombin and of PAR_2 by factor Xa leads to a rapid expression and exposure on the membrane of endothelial cells of both adhesive proteins that mediate an acute inflammatory reaction and of the tissue factor that initiates the blood coagulation cascade. Other receptors that can modulate responses of the cells activated by proteinases through PAR receptors are also involved in the association of coagulation and inflammation together with the receptors of the PAR family. The presence of PAR receptors on mast cells is responsible for their reactivity to thrombin and factor Xa , essential to the inflammation and blood clotting processes (36).

The understanding of regulation of the inflammatory process in chronic inflammatory diseases is advancing.

Evidence consistently indicates that T-cells play a key role in initiating and perpetuating inflammation, not only via the production of soluble mediators but also via cell/cell contact interactions with a variety of cell types through membrane receptors and their ligands. Signalling through CD40 and CD40 ligand is a versatile pathway that is potently involved in all these processes. Many inflammatory genes relevant to atherosclerosis are influenced by the transcriptional regulator nuclear factor κ B (NFκB). In these events T-cells become activated by dendritic cells or inflammatory cytokines, and these T-cells activate, in turn, monocytes / macrophages, endothelial cells, smooth muscle cells and fibroblasts to produce pro-inflammatory cytokines, chemokines, the coagulation cascade in vivo, and finally matrix metalloproteinases, responsible for tissue destruction. Moreover, CD40 ligand at inflammatory sites stimulates fibroblasts and tissue monocyte/macrophage production of VEGF, leading to angiogenesis, which promotes and maintains the chronic inflammatory process.

NFκB plays a pivotal role in co-ordinating the expression of genes involved in the immune and inflammatory response, evoking tumor necrosis factor α (TNFα), chemokines such as monocyte chemoattractant protein-1 (MCP-1) and interleukin (IL)-8, matrix metalloproteinase enzymes (MMP), and genes involved in cell survival. A complex array of mechanisms, including T cell activation, leukocyte extravasation, tissue factor expression, MMP expression and activation, as well induction of cytokines and chemokines, implicated in atherosclerosis, are regulated by NFκB.

Expression of NFκB in the atherosclerotic milieu may have a number of potentially harmful consequences. IL-1 activates NFκB upregulating expression of MMP-1, -3, and -9. Oxidized LDL increases macrophage MMP-9, associated with increased nuclear binding of NFκB and AP-1. Expression of tissue factor, initiating the coagulation cascade, is regulated by NFκB. In atherosclerotic plaque cells, tissue factor antigen and activity were inhibited following over-expression of IκBα and dominant-negative IKK-2, but not by dominant negative IKK-1 or NIK. Tis supports the concept that activation of the ―canonical‖ pathway upregulates pro-thrombotic mediators involved in disease. Many of the cytokines and chemokines which have been detected in human atherosclerotic plaques are also regulated by NFκB. Over-expression of IκBα inhibits release of TNFα, IL-1, IL-6, and IL-8 in macrophages stimulated with LPS and CD40 ligand (CD40L). This report describes how NFκB activation upregulates major pro-inflammatory and pro-thrombotic mediators of atherosclerosis (37-41).

This review is both focused and comprehensive. The details of evolving methods are avoided in order to build the argument that a very rapid expansion of discovery has been evolving depicting disease, disease mechanisms, disease associations, metabolic biomarkers, study of effects of diet and diet modification, and opportunities for targeted drug development. The extent of future success will depend on the duration and strength of the developed interventions, and possibly the avoidance of dead end interventions that are unexpectedly bypassed. I anticipate the prospects for the interplay between genomics, metabolomics, metabonomics, and personalized medicine may be realized for several of the most common conditions worldwide within a few decades (42-44).

References

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  2. Albert L, Girola A, Gilardini L, Conti A, et al. Type 2 diabetes and metabolic syndrome are associated with increased expression of 11 beta-hydroxysteroid dehydrogenase 1 in obese subjects. Int J Obesity (Lond) 2007;31:1826-31;
  3. Fabbrini E, Markos F, Mohammed BS, Pietka T, et al. Intrahepatic fat, not visceral fat, is linked with metabolic complications of obesity. PNAS 2009;106:15430-5;
  4. Tong J, Boyko EJ, Utzschneider KM, McNeely MJ, et al. Intraabdominal fat accumulation predicts the development of the metabolic syndrome in non-diabetic Japanese-Americans. Diabetologia 2007;50:1156-60;
  5. Kim K, Valentine RJ, Shin Y, Gong K. Association of visceral adiposity and exercise participation with C- reactive protein, insulin resistance, and endothelial dysfunction in Korean healthy adults. Metabolism 2008;57:1181-9. [(VAT-EC exhibits a marked angiogenic and proinflammatory state];
  6. Villaret A, Galitzky J, Decaunes P, Exteve D, et al. Adipose tisue endothelial cells from obese human subjects: differences among depots in angiogenic, metabolic, and inflammatory gene expression and cellular senescence. Diabetes 2010;59:2755-63;
  7. van Dijk -, Feskens EJ, Bos MB, Hoelen DW, et al. A saturated fatty acid-rich diet induces an obesity-linked proinflammatory gene expression profile in adipose tissue of subjects at risk of metabolic syndrome. Am J Clin Nutr 2009;90:1656-64.[MUFA in LDL lowering].
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  10. Spratlin JL, Serkova NJ, and Eckhardt SG. Clinical Applications of Metabolomics in Oncology: A Review. Clin Cancer Res. 2009 ;15; 15(2): 431–440.
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  29. Sharp, P, and MIT faculty. ‘Convergence’ offers potential for revolutionary advance in biomedicine. The Third Revolution: Convergence of the Life Sciences, Physical Sciences and Engineering. White paper. Reported in Biotechnology Jan 5, 2011. [Convergence is a new paradigm that can yield critical advances in a broad array of sectors]

 

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Epilogue: Envisioning New Insights in Cancer Translational Biology

Author and Curator: Larry H Bernstein, MD, FCAP

 

The foregoing  summary leads to a beginning as it is a conclusion.  It concludes a body of work in the e-book series,

Series C: e-Books on Cancer & Oncology

Series C Content Consultant: Larry H. Bernstein, MD, FCAP

 

VOLUME ONE 

Cancer Biology and Genomics for Disease Diagnosis

2014

Stephen J. Williams, PhD, Senior Editor

sjwilliamspa@comcast.net

Tilda Barliya, PhD, Editor

tildabarliya@gmail.com

Ritu Saxena, PhD, Editor

ritu.uab@gmail.com

Leaders in Pharmaceutical Business Intelligence 

that has been presented by the cancer team of professional experts, e-Book concept was conceived by Aviva Lev-Ari, PhD, RN, e-Series Editor-in-Chief and Founder of Leaders in Pharmaceutical Business Intelligence 

and the Open Access Online Scientific Journal

http://pharmaceuticalintelligence.com

Stephen J. Williams, PhD, Senior Editor, and other notable contributors in  various aspects of cancer research in the emerging fields of targeted  pharmacology,  nanotechnology, cancer imaging, molecular pathology, transcriptional and regulatory ‘OMICS’, metabolism, medical and allied health related sciences, synthetic biology, pharmaceutical discovery, and translational medicine.

This  volume and its content have been conceived and organized to capture the organized events that emerge in embryological development, leading to the major organ systems that we recognize anatomically and physiologically as an integrated being.  We capture the dynamic interactions between the systems under stress  that are elicited by cytokine-driven hormonal responses, long thought to be circulatory and multisystem, that affect the major compartments of  fat and lean body mass, and are as much the drivers of metabolic pathway changes that emerge as epigenetics, without disregarding primary genetic diseases.

The greatest difficulty in organizing such a work is in whether it is to be merely a compilation of cancer expression organized by organ systems, or whether it is to capture developing concepts of underlying stem cell expressed changes that were once referred to as “dedifferentiation”.  In proceeding through the stages of neoplastic transformation, there occur adaptive local changes in cellular utilization of anabolic and catabolic pathways, and a retention or partial retention of functional specificities.

This  effectively results in the same cancer types not all fitting into the same “shoe”. There is a sequential loss of identity associated with cell migration, cell-cell interactions with underlying stroma, and metastasis., but cells may still retain identifying “signatures” in microRNA combinatorial patterns.  The story is still incomplete, with gaps in our knowledge that challenge the imagination.

What we have laid out is a map with substructural ordered concepts forming subsets within the structural maps.  There are the traditional energy pathways with terms aerobic and anaerobic glycolysis, gluconeogenesis, triose phosphate branch chains, pentose shunt, and TCA cycle vs the Lynen cycle, the Cori cycle, glycogenolysis, lipid peroxidation, oxidative stress, autosomy and mitosomy, and genetic transcription, cell degradation and repair, muscle contraction, nerve transmission, and their involved anatomic structures (cytoskeleton, cytoplasm, mitochondria, liposomes and phagosomes, contractile apparatus, synapse.

Then there is beneath this macro-domain the order of signaling pathways that regulate these domains and through mechanisms of cellular regulatory control have pleiotropic inhibitory or activation effects, that are driven by extracellular and intracellular energy modulating conditions through three recognized structures: the mitochondrial inner membrane, the intercellular matrix, and the ion-channels.

What remains to be done?

  1. There is still to be elucidated the differences in patterns within cancer types the distinct phenotypic and genotypic features  that mitigate anaplastic behavior. One leg of this problem lies in the density of mitochondria, that varies between organ types, but might vary also within cell type of a common function.  Another leg of this problem has also appeared to lie in the cell death mechanism that relates to the proeosomal activity acting on both the ribosome and mitochondrion in a coordinated manner.  This is an unsolved mystery of molecular biology.

 

  1. Then there is a need to elucidate the major differences between tumors of endocrine, sexual, and structural organs, which are distinguished by primarily a synthetic or primarily a catabolic function, and organs that are neither primarily one or the other.  For example, tumors of the thyroid and paratnhyroids, islet cells of pancreas, adrenal cortex, and pituitary glands have the longest 5 year survivals.  They and the sexual organs are in the visceral compartment.  The rest of the visceral compartment would be the liver, pancreas, salivary glands, gastrointestinal tract, and lungs (which are embryologically an outpouching of the gastrointestinal tract), kidneys and lower urinary tract.  Cancers of these organs have a much less favorable survival (brain, breast and prostate, lymphatic, blood forming organ, skin).  The case  is intermediate for breast and prostate between the endocrine organs and GI tract, based on natural history, irrespective of the available treatments.  Just consider the dilemma over what we do about screening for prostate cancer in men over the age of 60 years age who have a 70 percent incident silent carcinoma of the prostate that could be associated with unrelated cause of death.  The very rapid turnover of the gastric and colonic GI epithelium, and of the  subepithelial  B cell mucosal lymphocytic structures  is associated  with a greater aggressiveness of the tumor.

 

  1. However, we  have to reconsider the observation by NO Kaplan than the synthetic and catabolic functions are highlighted by differences in the expressions of the balance of  the two major pyridine nucleotides – DPN (NAD) and TPN (NADP) – which also might be related to the density of mitochondria  which is associated with both NADP and synthetic activity, and  with efficient aerobic function.  These are in an equilibrium through the “transhydrogenase reaction” co-discovered by Kaplan, in Fritz Lipmann’s laboratory. There does  arise a conundrum involving the regulation of mitochondria in these high turnover epithelial tissues  that rely on aerobic energy, and generate ATP through TPN linked activity, when they undergo carcinogenesis. The cells  replicate and they become utilizers of glycolysis, while at the same time, the cell death pathway is quiescent. The result becomes the introduction of peripheral muscle and liver synthesized protein cannabolization (cancer cachexia) to provide glucose  from proteolytic amino acid sources.

 

  1. There is also the structural compartment of the lean body mass. This is the heart, skeletal  structures (includes smooth muscle of GI tract, uterus, urinary bladder, brain, bone, bone marrow).  The contractile component is associated with sarcomas.  What is most striking is that the heart, skeletal muscle, and inflammatory cells are highly catabolic, not anabolic.  NO Kaplan referred tp them as DPN (NAD) tissues. This compartment requires high oxygen supply, and has a high mechanical function. But again, we return to the original observations of enrgy requirements at rest being different than at high demand.  At work, skeletal muscle generates lactic acid, but the heart can use lactic acid as fuel,.

 

  1. The liver is supplied by both the portal vein and the hepatic artery, so it is not prone to local ischemic injury (Zahn infarct). It is exceptional in that it carries out synthesis of all the circulating transport proteins, has a major function in lipid synthesis and in glycogenesis and glycogenolysis, with the added role of drug detoxification through the P450 system.  It is not only the largest organ (except for brain), but is highly active both anabolically and catabolically (by ubiquitilation).
  2. The expected cellular turnover rates for these tissues and their balance of catabolic and anabolic function would have to be taken into account to account for the occurrence and the activities of oncogenesis. This is by no means a static picture, but a dynamic organism constantly in flux imposed by internal and external challenges.  It is also important to note the the organs have a concentration of mitochondria, associated with energy synthetic and catabolic requirements provided by oxygen supply and the electron transport mechanism for oxidative phosphorylation.  For example, tissues that are primarily synthetic do not have intermitent states of resting and high demand, as seen in skeletal muscle, or perhaps myocardium (which is syncytial and uses lactic acid generated from skeletal muscle when there is high demand).
  3. The existence of  lncDNA has been discovered only as a result of the human genome project (HGP). This was previously known only as “dark DNA”.  It has become clear that lncDNA has an important role in cellular regulatory activities centered in the chromatin modeling.  Moreover, just as proteins exhibit functionality in their folding, related to tertiary structure and highly influenced by location of –S-S- bridges and amino acid residue distances (allosteric effects), there is a less studied effect as the chromatin becomes more compressed within the nucleus, that should have a bearing on cellular expression.

According to Jose Eduardo de Salles Roselino , when the Na/Glucose transport system (for a review Silvermann, M. in Annu. Rev. Biochem.60: 757-794(1991)) was  found in kidneys as well as in key absorptive cells of digestive tract, it should be stressed its functional relationship with “internal milieu” and real meaning, homeostasis. It is easy to understand how the major topic was presented as how to prevent diarrheal deaths in infants, while detected in early stages. However, from a biochemical point of view, as presented in Schrödinger´s What is life?, (biochemistry offering a molecular view for two legs of biology, physiology and genetics). Why should it be driven to the sole target of understanding genetics? Why the understanding of physiology in molecular terms should be so neglected?

From a biochemical point of view, here in a single protein. It is found the transport of the cation most directly related to water maintenance, the internal solvent that bath our cells and the hydrocarbon whose concentration is kept under homeostatic control on that solvent. Completely at variance with what is presented in microorganisms as previously mentioned in Moyed and Umbarger revision (Ann. Rev42: 444(1962)) that does not regulates the environment where they live and appears to influence it only as an incidental result of their metabolism.

In case any attempt is made in order to explain why the best leg that supports scientific reasoning from biology for medical purposes was led to atrophy, several possibilities can be raised. However, none of them could be placed strictly in scientific terms. Factors that bare little relationship with scientific progress in general terms must also be taken into account.

One simple possibility of explanation can be found in one review (G. Scatchard – Solutions of Electrolytes Ann. Rev. Physical Chemistry 14: 161-176 (1963)).  A simple reading of it and the sophisticated differences among researchers will discourage one hundred per cent of biologists to keep in touch with this line of research. Biochemists may keep on reading.  However, consider that first: Complexity is not amenable to reductionist vision in all cases. Second, as coupling between scalar flows such as chemical reactions and vector flows such as diffusion flows, heat flows, and electrical current can occur only in anisotropic system…let them with their problems of solvents, ions and etc. and let our biochemical reactions on another basket. At the interface, for instance, at membrane level, we will agree that ATP is converted to ADP because it is far from equilibrium and the continuous replenishment of ATP that maintain relatively constant ATP levels inside the cell and this requires some non-stationary flow.

Our major point must be to understand that our biological limits are far clearer present in our limited ability to regulate the information stored in the DNA than in the amount of information we have in the DNA as the master regulator of the cells.

The amazing revelation that Masahiro Chiga   (discovery of liver adenylate kinase  distinct from that of muscle) taught  me (LHB) is – draw 2 circles  that intersect, one of which represents what we know, the other – what we don’t know.  We don’t teach how much we don’t know!  Even today, as much as 40 years ago, there is a lot we need to get on top of this.

 

The observation is rather similar to the presentations I  (Jose Eduardo de Salles Rosalino) was previously allowed to make of the conformational energy as made by R Marcus in his Nobel lecture revised (J. of  Electroanalytical Chemistry 438:(1997) p251-259. His description of the energetic coordinates of a landscape of a chemical reaction is only a two-dimensional cut of what in fact is a volcano crater (in three dimensions) ( each one varie but the sum of the two is constant. Solvational+vibrational=100% in ordinate) nuclear coordinates in abcissa. In case we could represent it by research methods that allow us to discriminate in one by one degree of different pairs of energy, we would most likely have 360 other similar representations of the same phenomenon. The real representation would take into account all those 360 representation together. In case our methodology was not that fine, for instance it discriminate only differences of minimal 10 degrees in 360 possible, will have 36 partial representations of something that to be perfectly represented will require all 36 being taken together. Can you reconcile it with ATGC? Yet, when complete genome sequences were presented they were described as we will know everything about this living being. The most important problems in biology will be viewed by limited vision always and the awareness of this limited is something we should acknowledge and teach it. Therefore, our knowledge is made up of partial representations.

 

Even though we may have complete genome data for the most intricate biological problems, they are not so amenable to this level of reductionism. However, from general views of signals and symptoms we could get to the most detailed molecular view and in this case the genome provides an anchor. This is somehow, what Houssay was saying to me and to Leloir when he pointed out that only in very rare occasions biological phenomena could be described in three terms: Pacco, the dog and the anesthetic (previous e-mail). The non-coding region, to me will be important guiding places for protein interactions.

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