Glyphosate tolerant genetically modified (GM) maize NK603 was assessed as ‘substantially equivalent’ to its isogenic counterpart by a nutrient composition analysis in order to be granted market approval. We have applied contemporary in depth molecular profiling methods of NK603 maize kernels (sprayed or unsprayed with Roundup) and the isogenic corn to reassess its substantial equivalence status. Proteome profiles of the maize kernels revealed alterations in the levels of enzymes of glycolysis and TCA cycle pathways, which were reflective of an imbalance in energy metabolism. Changes in proteins and metabolites of glutathione metabolism were indicative of increased oxidative stress. The most pronounced metabolome differences between NK603 and its isogenic counterpart consisted of an increase in polyamines including N-acetyl-cadaverine (2.9-fold), N-acetylputrescine (1.8-fold), putrescine (2.7-fold) and cadaverine (28-fold), which depending on context can be either protective or a cause of toxicity. Our molecular profiling results show that NK603 and its isogenic control are not substantially equivalent.
The propensity of cancer cells to convert high levels of glucose to lactate through aerobic glycolysis has been intensively studied in vitro, and is now understood to be a metabolic adaptation that shunts glucose carbons toward building blocks for the growing cell, as well as producing ATP. Much less is known, however, about the role of aerobic glycolysis and glycolytic enzymes in vivo. A paper in Cancer and Metabolism now documents aerobic glycolysis in the proliferating neural progenitors that form the cerebellum in normal newborn mice, as well as in medulloblastoma tumors derived from these cells in transgenic mice. Hexokinase II is demonstrated to be an essential driver of the observed aerobic glycolysis and the malignancy of the tumors.See research article: http://www.cancerandmetabolism.com/content/1/½.
BACKGROUND: Increased glycolysis is a hallmark of cancer metabolism, yet relatively little is known about this phenotype at premalignant stages of progression. Periodic ischemia occurs in the premalignant condition Barrett’s esophagus (BE) due to tissue damage from chronic acid-bile reflux and may select for early adaptations to hypoxia, including upregulation of glycolysis. METHODOLOGYPRINCIPAL FINDINGS: We compared rates of glycolysis and oxidative phosphorylation in four cell lines derived from patients with BE (CP-A, CP-B, CP-C and CP-D) in response to metabolic inhibitors and changes in glucose concentration. We report that cell lines derived from patients with more advanced genetically unstable BE have up to two-fold higher glycolysis compared to a cell line derived from a patient with early genetically stable BE; however, all cell lines preserve active mitochondria. In response to the glycolytic inhibitor 2-deoxyglucose, the most glycolytic cell lines (CP-C and CP-D) had the greatest suppression of extra-cellular acidification, but were able to compensate with upregulation of oxidative phosphorylation. In addition, these cell lines showed the lowest compensatory increases in glycolysis in response to mitochondrial uncoupling by 2,4-dinitrophenol. Finally, these cell lines also upregulated their oxidative phosphorylation in response to glucose via the Crabtree effect, and demonstrate a greater range of modulation of oxygen consumption. CONCLUSIONSSIGNIFICANCE: Our findings suggest that cells from premalignant Barrett’s esophagus tissue may adapt to an ever-changing selective microenvironment through changes in energy metabolic pathways typically associated with cancer cells.
Natal dispersal of sea turtles is an energetically demanding activity that is fuelled primarily by aerobic metabolism. However, during intense exercise reptiles can use anaerobic metabolism to supplement their energy requirements. We assessed anaerobic metabolism in dispersing hatchling loggerhead and flatback turtles by measuring the concentrations of blood lactate during crawling and at different times during the first four hours of their frenzy swim. We also measured concentrations of blood glucose and corticosterone. Blood lactate (12.13 to 2.03 mmol/L), glucose (6.25 to 3.8 mmol/L) and corticosterone (8.13 to 2.01 ng/mL) concentrations decreased significantly over time in both loggerhead and flatback hatchlings and no significant differences were found between the species. These results indicate that anaerobic metabolism makes a significant contribution to the dispersal phase of hatchling sea turtles during the beach crawl and the first few hours of the frenzy swim.
Recent development of high-throughput analytical techniques has made it possible to qualitatively identify a number of metabolites simultaneously. Correlation and multivariate analyses such as principal component analysis have been widely used to analyse those data and evaluate correlations among the metabolic profiles. However, these analyses cannot simultaneously carry out identification of metabolic reaction networks and prediction of dynamic behaviour of metabolites in the networks. The present study, therefore, proposes a new approach consisting of a combination of statistical technique and mathematical modelling approach to identify and predict a probable metabolic reaction network from time-series data of metabolite concentrations and simultaneously construct its mathematical model. Firstly, regression functions are fitted to experimental data by the locally estimated scatter plot smoothing method. Secondly, the fitted result is analysed by the bivariate Granger causality test to determine which metabolites cause the change in other metabolite concentrations and remove less related metabolites. Thirdly, S-system equations are formed by using the remaining metabolites within the framework of biochemical systems theory. Finally, parameters including rate constants and kinetic orders are estimated by the Levenberg-Marquardt algorithm. The estimation is iterated by setting insignificant kinetic orders at zero, i.e., removing insignificant metabolites. Consequently, a reaction network structure is identified and its mathematical model is obtained. Our approach is validated using a generic inhibition and activation model and its practical application is tested using a simplified model of the glycolysis of Lactococcus lactis MG1363, for which actual time-series data of metabolite concentrations are available. The results indicate the usefulness of our approach and suggest a probable pathway for the production of lactate and acetate. The results also indicate that the approach pinpoints a probable strong inhibition of lactate on the glycolysis pathway.
Metabolic modifications of tumor cells are hallmarks of cancer. They exhibit an altered metabolism that allows them to sustain higher proliferation rates in hostile environment outside the cell. In thyroid tumors, the expression of the estrogen-related receptor α (ERRα), a major factor of metabolic adaptation, is closely related to the oxidative metabolism and the proliferative status of the cells. To elucidate the role played by ERRα in the glycolytic adaptation of tumor cells, we focused on the regulation of lactate dehydrogenases A and B (LDHA, LDHB) and the LDHA/LDHB ratio. Our study included tissue samples from 10 classical and 10 oncocytic variants of follicular thyroid tumors and 10 normal thyroid tissues, as well as samples from three human thyroid tumor cell lines: FTC-133, XTC.UC1 and RO82W-1. We identified multiple cis-acting promoter elements for ERRα, in both the LDHA and LDHB genes. The interaction between ERRα and LDH promoters was confirmed by chromatin immunoprecipitation assays and in vitro analysis for LDHB. Using knock-in and knock-out cellular models, we found an inverse correlation between ERRα expression and LDH activity. This suggests that thyroid tumor cells may reprogram their metabolic pathways through the up-regulation of ERRα by a process distinct from that proposed by the recently revisited Warburg hypothesis.
Glucose stimulated insulin secretion (GSIS) from pancreatic β-cells is triggered by metabolism of the sugar to increase ATP/ADP ratio that blocks the KATP channel leading to membrane depolarization and insulin exocytosis. Other metabolic pathways believed to augment insulin secretion have yet to be fully elucidated. To study metabolic changes during GSIS, liquid chromatography with mass spectrometry was used to determine levels of 87 metabolites temporally following a change in glucose from 3 mM to 10 mM glucose and in response to increasing concentrations of glucose in the INS-1 832/13 β-cell line. 13C-glucose was used to probe flux in specific metabolic pathways. Results include a rapid increase in ATP/ADP, anaplerotic tricarboxylic acid cycle flux, and increases in the malonyl CoA pathway, support prevailing theories of GSIS. Novel findings include that aspartate used for anaplerosis does not derive from the glucose fuel added to stimulate insulin secretion, glucose flux into glycerol-3-phosphate, and esterification of long chain CoAs resulting in rapid consumption of long chain CoAs and de novo generation of phosphatidic acid and diacylglycerol. Further, novel metabolites with potential roles in GSIS such as 5-aminoimidazole-4-carboxamide ribotide (ZMP), GDP-mannose, and farnesyl pyrophosphate were found to be rapidly altered following glucose exposure.
Copy number alteration (CNA) profiling of human tumors has revealed recurrent patterns of DNA amplifications and deletions across diverse cancer types. These patterns are suggestive of conserved selection pressures during tumor evolution but cannot be fully explained by known oncogenes and tumor suppressor genes. Using a pan-cancer analysis of CNA data from patient tumors and experimental systems, here we show that principal component analysis-defined CNA signatures are predictive of glycolytic phenotypes, including (18)F-fluorodeoxy-glucose (FDG) avidity of patient tumors, and increased proliferation. The primary CNA signature is enriched for p53 mutations and is associated with glycolysis through coordinate amplification of glycolytic genes and other cancer-linked metabolic enzymes. A pan-cancer and cross-species comparison of CNAs highlighted 26 consistently altered DNA regions, containing 11 enzymes in the glycolysis pathway in addition to known cancer-driving genes. Furthermore, exogenous expression of hexokinase and enolase enzymes in an experimental immortalization system altered the subsequent copy number status of the corresponding endogenous loci, supporting the hypothesis that these metabolic genes act as drivers within the conserved CNA amplification regions. Taken together, these results demonstrate that metabolic stress acts as a selective pressure underlying the recurrent CNAs observed in human tumors, and further cast genomic instability as an enabling event in tumorigenesis and metabolic evolution.
There is a considerable resurgence of interest in the role of aerobic glycolysis in cancer; however, increased glycolysis is frequently viewed as a consequence of oncogenic events that drive malignant cell growth and survival. Here we provide evidence that increased glycolytic activation itself can be an oncogenic event in a physiologically relevant 3D culture model. Overexpression of glucose transporter type 3 (GLUT3) in nonmalignant human breast cells activated known oncogenic signaling pathways, including EGFR, β1 integrin, MEK, and AKT, leading to loss of tissue polarity and increased growth. Conversely, reduction of glucose uptake in malignant cells promoted the formation of organized and growth-arrested structures with basal polarity, and suppressed oncogenic pathways. Unexpectedly and importantly, we found that unlike reported literature, in 3D the differences between “normal” and malignant phenotypes could not be explained by HIF-1α/2α, AMPK, or mTOR pathways. Loss of epithelial integrity involved activation of RAP1 via exchange protein directly activated by cAMP (EPAC), involving also O-linked N-acetylglucosamine modification downstream of the hexosamine biosynthetic pathway. The former, in turn, was mediated by pyruvate kinase M2 (PKM2) interaction with soluble adenylyl cyclase. Our findings show that increased glucose uptake activates known oncogenic pathways to induce malignant phenotype, and provide possible targets for diagnosis and therapeutics.
Herein we use lessons learned in exercise physiology and metabolism to propose that augmented lactate production (“lactagenesis)”, initiated by gene mutations, is the reason and purpose of the Warburg effect and that dysregulated lactate metabolism and signaling are key elements in carcinogenesis. Lactate producing (“lactagenic”) cancer cells are characterized by increased aerobic glycolysis and excessive lactate formation, a phenomenon described by Otto Warburg 93 years ago, which still remains unexplained. After a hiatus of several decades, interest in lactate as a player in cancer has been renewed. In normal physiology, lactate, the obligatory product of glycolysis, is an important metabolic fuel energy source, the most important gluconeogenic precursor, and a signaling molecule (i.e., a “lactormone”) with major regulatory properties. In lactagenic cancers, oncogenes and tumor suppressor mutations behave in a highly orchestrated manner, apparently with the purpose of increasing glucose utilization for lactagenesis purposes and lactate exchange between, within and among cells. Five main steps are identified: (1) increased glucose uptake, (2) increased glycolytic enzyme expression and activity, 3) decreased mitochondrial function, (4) increased lactate production, accumulation and release, and 5) upregulation of monocarboxylate transporters MTC1 and MCT4 for lactate exchange. Lactate is probably the only metabolic compound involved and necessary in all main sequela for carcinogenesis, specifically: angiogenesis, immune escape, cell migration, metastasis and self-sufficient metabolism. We hypothesize that lactagenesis for carcinogenesis is the explanation and purpose of the Warburg effect. Accordingly, therapies to limit lactate exchange and signaling within and among cancer cells should be priorities for discovery.