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L-3,4-Dihydroxyphenylalanin (l-DOPA or levodopa) is currently the most used drug to treat symptoms of Parkinson’s disease (PD). After crossing the blood–brain barrier, it is enzymatically converted to dopamine by neuronal cells and restores depleted endogenous neurotransmitter levels. l-DOPA is prone to auto-oxidation and reactive intermediates of its degradation including reactive oxygen species (ROS) have been implicated in cellular damage. In this study, we investigated how oxygen tension effects l-DOPA stability. We applied oxygen tensions comparable to those in the mammalian brain and demonstrated that 2% oxygen almost completely stopped its auto-oxidation. l-DOPA even exerted a ROS scavenging function. Further mechanistic analysis indicated that l-DOPA reprogrammed mitochondrial metabolism and reduced oxidative phosphorylation, depolarized the mitochondrial membrane, induced reductive glutamine metabolism, and depleted the NADH pool. These results shed new light on the cellular effects of l-DOPA and its neuro-toxicity under physiological oxygen levels that are very distinct to normoxic in vitro conditions.

On an organismal level, metabolism needs to react in a well-orchestrated manner to metabolic challenges such as nutrient uptake. Key metabolic hubs in human blood are pyruvate and lactate, both of which are constantly interconverted by very fast exchange fluxes. The quantitative contribution of different food sources to these metabolite pools remains unclear. Here, we applied in vivo stable isotope labeling to determine postprandial metabolic fluxes in response to two carbohydrate sources of different complexity. Depending on the ingested carbohydrate source, glucose or wheat flour, the net direction of the lactate dehydrogenase, and the alanine amino transferase fluxes were adjusted in a way to ensure sufficient availability, while, at the same time, preventing an overflow in the respective metabolite pools. The systemic lactate pool acts as a metabolic buffer which is fueled in the early- and depleted in the late-postprandial phase and thus plays a key role for systemic metabolic homeostasis.

Since its discovery in inflammatory macrophages, itaconate has attracted much attention due to its antimicrobial and immunomodulatory activity1–3. However, instead of investigating itaconate itself, most studies used derivatized forms of itaconate and thus the role of non-derivatized itaconate needs to be scrutinized. Mesaconate, a metabolite structurally very close to itaconate, has never been implicated in mammalian cells. Here we show that mesaconate is synthesized in inflammatory macrophages from itaconate. We find that both, non-derivatized itaconate and mesaconate dampen the glycolytic activity to a similar extent, whereas only itaconate is able to repress tricarboxylic acid cycle activity and cellular respiration. In contrast to itaconate, mesaconate does not inhibit succinate dehydrogenase. Despite their distinct impact on metabolism, both metabolites exert similar immunomodulatory effects in pro-inflammatory macrophages, specifically a reduction of interleukin (IL)-6 and IL-12 secretion and an increase of CXCL10 production in a manner that is independent of NRF2 and ATF3. We show that a treatment with neither mesaconate nor itaconate impairs IL-1β secretion and inflammasome activation. In summary, our results identify mesaconate as an immunomodulatory metabolite in macrophages, which interferes to a lesser extent with cellular metabolism than itaconate.

A reliable method for metabolite extraction is central to mass spectrometry-based metabolomics. However, existing methods are lengthy, mostly due to the step of scraping cells from cell culture vessels, which restricts metabolomics in broader application such as lower cell numbers and high-throughput studies. Here, we present a simplified metabolite extraction (SiMeEx) method, to efficiently and quickly extract metabolites from adherent mammalian cells. Our method excludes the cell scraping step and therefore allows for a more efficient extraction of polar metabolites in less than 30 min per 12-well plate. We demonstrate that SiMeEx achieves the same metabolite recovery as using a standard method containing a scraping step, in various immortalized and primary cells. Omitting cell scraping does not compromise the performance of non-targeted and targeted GC-MS analysis, but enables metabolome analysis of cell culture on smaller well sizes down to 96-well plates. Therefore, SiMeEx demonstrates advantages not only on time and resources, but also on the applicability in high-throughput studies.

Summary Pathogenic viruses induce metabolic changes in host cells to secure the availability of biomolecules and energy to propagate. Influenza A virus (IAV) and severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) both infect the human airway epithelium and are important human pathogens. The metabolic changes induced by these viruses in a physiologically relevant human model and how this affects innate immune responses to limit viral propagation are not well known. Using an ex vivo model of pseudostratified primary human airway epithelium, we here demonstrate that infection with both IAV and SARS-CoV-2 resulted in distinct metabolic changes including increases in lactate dehydrogenase A (LDHA) expression and LDHA-mediated lactate formation. Interestingly, LDHA regulated both basal and induced mitochondrial anti-viral signaling protein (MAVS)-dependent type I interferon (IFN) responses to promote IAV, but not SARS-CoV-2, replication. Our data demonstrate that LDHA and lactate promote IAV but not SARS-CoV-2 replication by inhibiting MAVS-dependent induction of type I IFN in primary human airway epithelium., Graphical abstract, Highlights • IAV and SARS-CoV-2 infections yield virus-specific changes in glucose metabolism • IAV and SARS-CoV-2 induce LDHA and lactate production in human airway epithelium • Lactate is highly pro-viral to IAV but not to SARS-CoV-2 • Lactate decreases IFN production and the following ISG response, Immune response; Virology; Metabolomics

Performing long-term cell observations is a non-trivial task for conventional optical microscopy, since it is usually not compatible with environments of an incubator and its temperature and humidity requirements. Lensless holographic microscopy, being entirely based on semiconductor chips without lenses and without any moving parts, has proven to be a very interesting alternative to conventional microscopy. Here, we report on the integration of a computational parfocal feature, which operates based on wave propagation distribution analysis, to perform a fast autofocusing process. This unique non-mechanical focusing approach was implemented to keep the imaged object staying in-focus during continuous long-term and real-time recordings. A light-emitting diode (LED) combined with pinhole setup was used to realize a point light source, leading to a resolution down to 2.76 μm. Our approach delivers not only in-focus sharp images of dynamic cells, but also three-dimensional (3D) information on their (x, y, z)-positions. System reliability tests were conducted inside a sealed incubator to monitor cultures of three different biological living cells (i.e., MIN6, neuroblastoma (SH-SY5Y), and Prorocentrum minimum). Altogether, this autofocusing framework enables new opportunities for highly integrated microscopic imaging and dynamic tracking of moving objects in harsh environments with large sample areas.

In the last decade, metabolism has been recognized as a major determinant of immunological processes. During an inflammatory response, macrophages undergo striking changes in their metabolism. This metabolic reprogramming is governed by a complex interplay between metabolic enzymes and metabolites of different pathways and represents the basis for proper macrophage function. It is now evident that these changes go far beyond the well-known Warburg effect and the perturbation of metabolic targets is being investigated as a means to treat infections and auto-immune diseases. In the present review, we will aim to provide an overview of the metabolic responses during proinflammatory macrophage activation and show how these changes modulate the immune response.

Summary Since the discovery of mutations in isocitrate dehydrogenase 1 (IDH1) in gliomas and other tumors, significant efforts have been made to gain a deeper understanding of the consequences of this oncogenic mutation. One aspect of the neomorphic function of the IDH1 R132H enzyme that has received less attention is the perturbation of cellular redox homeostasis. Here, we describe a biosynthetic pathway exhibited by cells expressing mutant IDH1. By virtue of a change in cellular redox homeostasis, IDH1-mutated cells synthesize excess glutamine-derived proline through enhanced activity of pyrroline 5-carboxylate reductase 1 (PYCR1), coupled to NADH oxidation. Enhanced proline biosynthesis partially uncouples the electron transport chain from tricarboxylic acid (TCA) cycle activity through the maintenance of a lower NADH/NAD+ ratio and subsequent reduction in oxygen consumption. Thus, we have uncovered a mechanism by which tumor cell survival may be promoted in conditions associated with perturbed redox homeostasis, as occurs in IDH1-mutated glioma., Graphical Abstract, Highlights • IDH1 mutant cells exhibit increased PYCR1-dependent proline synthesis from glutamine • The increase in proline synthesis is coupled to the oxidation of mitochondrial NADH • PYCR1 activity partially uncouples respiration from TCA cycle activity • PYCR1 expression and proline concentrations are increased in IDH1-mutated gliomas, Hollinshead et al. demonstrate a role for PYCR1 in control of mitochondrial redox homeostasis. Expression of IDH1 R132H mutation leads to increased NADH-coupled proline biosynthesis, mediated by PYCR1. The resulting metabolic phenotype partially uncouples mitochondrial NADH oxidation from respiration, representing an oxygen-sparing metabolic phenotype.

Regulatory T cells (Tregs) maintain immune homeostasis and prevent autoimmunity. Serine stimulates glutathione (GSH) synthesis and feeds into the one-carbon metabolic network (1CMet) essential for effector T cell (Teff) responses. However, serine's functions, linkage to GSH, and role in stress responses in Tregs are unknown. Here, we show, using mice with Treg-specific ablation of the catalytic subunit of glutamate cysteine ligase (Gclc), that GSH loss in Tregs alters serine import and synthesis and that the integrity of this feedback loop is critical for Treg suppressive capacity. Although Gclc ablation does not impair Treg differentiation, mutant mice exhibit severe autoimmunity and enhanced anti-tumor responses. Gclc-deficient Tregs show increased serine metabolism, mTOR activation, and proliferation but downregulated FoxP3. Limitation of cellular serine in vitro and in vivo restores FoxP3 expression and suppressive capacity of Gclc-deficient Tregs. Our work reveals an unexpected role for GSH in restricting serine availability to preserve Treg functionality. Regulatory T cells (Tregs) rely on oxidative metabolism, which triggers the generation of reactive oxygen species (ROS). Accumulating ROS are controlled by the antioxidant glutathione (GSH). Kurniawan et al. reveal an unexpected subset-specific role of GSH in serine metabolism and Treg function.

Currently, changes in metabolic fluxes following consumption of stable isotope-enriched foods are usually limited to the analysis of postprandial kinetics of glucose. Kinetic information on a larger diversity of metabolites is often lacking, mainly due to the marginal percentage of fully isotopically enriched plant material in the administered food product, and hence, an even weaker 13C enrichment in downstream plasma metabolites. Therefore, we developed an analytical workflow to determine weak 13C enrichments of diverse plasma metabolites with conventional gas chromatography-mass spectrometry (GC-MS). The limit of quantification was increased by optimizing (1) the metabolite extraction from plasma, (2) the GC-MS measurement, and (3) most importantly, the computational data processing. We applied our workflow to study the catabolic dynamics of 13C-enriched wheat bread in three human subjects. For that purpose, we collected time-resolved human plasma samples at 16 timepoints after the consumption of 13C-labeled bread and quantified 13C enrichment of 12 metabolites (glucose, lactate, alanine, glycine, serine, citrate, glutamate, glutamine, valine, isoleucine, tyrosine, and threonine). Based on isotopomer specific analysis, we were able to distinguish catabolic profiles of starch and protein hydrolysis. More generally, our study highlights that conventional GC-MS equipment is sufficient to detect isotope traces below 1% if an appropriate data processing is integrated.

Food supplementation with a fiber mix of guar gum and chickpea flour represents a promising approach to reduce the risk of type 2 diabetes mellitus (T2DM) by attenuating postprandial glycemia. To investigate the effects on postprandial metabolic fluxes of glucose-derived metabolites in response to this fiber mix, a randomized, cross-over study was designed. Twelve healthy, male subjects consumed three different flatbreads either supplemented with 2% guar gum or 4% guar gum and 15% chickpea flour or without supplementation (control). The flatbreads were enriched with ~2% of 13C-labeled wheat flour. Blood was collected at 16 intervals over a period of 360 min after bread intake and plasma samples were analyzed by GC-MS based metabolite profiling combined with stable isotope-assisted metabolomics. Although metabolite levels of the downstream metabolites of glucose, specifically lactate and alanine, were not altered in response to the fiber mix, supplementation of 4% guar gum was shown to significantly delay and reduce the exogenous formation of these metabolites. Metabolic modeling and computation of appearance rates revealed that the effects induced by the fiber mix were strongest for glucose and attenuated downstream of glucose. Further investigations to explore the potential of fiber mix supplementation to counteract the development of metabolic diseases are warranted.

Graphical abstract Three-phase methanol–water–chloroform extraction for biological samples. Examples of components available from each phase are shown. These different phases can be then used for a variety of different analysis methods on different levels of cellular regulation., Proper sample preparation is an integral part of all omics approaches, and can drastically impact the results of a wide number of analyses. As metabolomics and proteomics research approaches often yield complementary information, it is desirable to have a sample preparation procedure which can yield information for both types of analyses from the same cell population. This protocol explains a method for the separation and isolation of metabolites and proteins from the same biological sample, in order for downstream use in metabolomics and proteomics analyses simultaneously. In this way, two different levels of biological regulation can be studied in a single sample, minimizing the variance that would result from multiple experiments. This protocol can be used with both adherent and suspension cell cultures, and the extraction of metabolites from cellular medium is also detailed, so that cellular uptake and secretion of metabolites can be quantified. Advantages of this technique includes:1.Inexpensive and quick to perform; this method does not require any kits.2.Can be used on any cells in culture, including cell lines and primary cells extracted from living organisms.3.A wide variety of different analysis techniques can be used, adding additional value to metabolomics data analyzed from a sample; this is of high value in experimental systems biology.

SummaryRecent studies have suggested that human pluripotent stem cells (hPSCs) depend primarily on glycolysis and only increase oxidative metabolism during differentiation. Here, we demonstrate that both glycolytic and oxidative metabolism can support hPSC growth and that the metabolic phenotype of hPSCs is largely driven by nutrient availability. We comprehensively characterized hPSC metabolism by using 13C/2H stable isotope tracing and flux analysis to define the metabolic pathways supporting hPSC bioenergetics and biosynthesis. Although glycolytic flux consistently supported hPSC growth, chemically defined media strongly influenced the state of mitochondrial respiration and fatty acid metabolism. Lipid deficiency dramatically reprogramed pathways associated with fatty acid biosynthesis and NADPH regeneration, altering the mitochondrial function of cells and driving flux through the oxidative pentose phosphate pathway. Lipid supplementation mitigates this metabolic reprogramming and increases oxidative metabolism. These results demonstrate that self-renewing hPSCs can present distinct metabolic states and highlight the importance of medium nutrients on mitochondrial function and development.

The evaluation of extraction protocols for untargeted metabolomics approaches is still difficult. We have applied a novel stable isotope-assisted workflow for untargeted LC-HRMS-based plant metabolomics , which allows for the first time every detected feature to be considered for method evaluation. The efficiency and complementarity of commonly used extraction solvents, namely 1 + 3 (v/v) mixtures of water and selected organic solvents (methanol, acetonitrile or methanol/acetonitrile 1 + 1 (v/v)), with and without the addition of 0.1% (v/v) formic acid were compared. Four different wheat organs were sampled, extracted and analysed by LC-HRMS. Data evaluation was performed with the in-house-developed MetExtract II software and R. With all tested solvents a total of 871 metabolites were extracted in ear, 785 in stem, 733 in leaf and 517 in root samples, respectively. Between 48% (stem) and 57% (ear) of the metabolites detected in a particular organ were found with all extraction mixtures, and 127 of 996 metabolites were consistently shared between all extraction agent/organ combinations. In aqueous methanol, acidification with formic acid led to pronounced pH dependency regarding the precision of metabolite abundance and the number of detectable metabolites, whereas extracts of acetonitrile-containing mixtures were less affected. Moreover, methanol and acetonitrile have been found to be complementary with respect to extraction efficiency. Interestingly, the beneficial properties of both solvents can be combined by the use of a water-methanol-acetonitrile mixture for global metabolite extraction instead of aqueous methanol or aqueous acetonitrile alone.

Graphical abstract Quantitative multi-component analysis of body fluids with GC–MS. After sample collection, the samples are pre-processed and used for metabolite extraction. After this, GC–MS analysis and subsequent data processing and analysis are performed., Metabolome analyses of body fluids are challenging due pre-analytical variations, such as pre-processing delay and temperature, and constant dynamical changes of biochemical processes within the samples. Therefore, proper sample handling starting from the time of collection up to the analysis is crucial to obtain high quality samples and reproducible results. A metabolomics analysis is divided into 4 main steps: 1) Sample collection, 2) Metabolite extraction, 3) Data acquisition and 4) Data analysis. Here, we describe a protocol for gas chromatography coupled to mass spectrometry (GC–MS) based metabolic analysis for biological matrices, especially body fluids. This protocol can be applied on blood serum/plasma, saliva and cerebrospinal fluid (CSF) samples of humans and other vertebrates. It covers sample collection, sample pre-processing, metabolite extraction, GC–MS measurement and guidelines for the subsequent data analysis. Advantages of this protocol include: • Robust and reproducible metabolomics results, taking into account pre-analytical variations that may occur during the sampling process • Small sample volume required • Rapid and cost-effective processing of biological samples • Logistic regression based determination of biomarker signatures for in-depth data analysis

Measuring intracellular metabolism has increasingly led to important insights in biomedical research. (13)C tracer analysis, although less information-rich than quantitative (13)C flux analysis that requires computational data integration, has been established as a time-efficient method to unravel relative pathway activities, qualitative changes in pathway contributions, and nutrient contributions. Here, we review selected key issues in interpreting (13)C metabolite labeling patterns, with the goal of drawing accurate conclusions from steady state and dynamic stable isotopic tracer experiments. ispartof: Current Opinion in Biotechnology vol:34 pages:189-201 ispartof: location:England status: published

A novel program suite was implemented for the functional interpretation of high-throughput gene expression data based on the identification of Gene Ontology (GO) nodes. The focus of the analysis lies on the interpretation of microarray data from prokaryotes. The three well established statistical methods of the threshold value-based Fisher's exact test, as well as the threshold value-independent Kolmogorov-Smirnov and Student's t-test were employed in order to identify the groups of genes with a significantly altered expression profile. Furthermore, we provide the application of the rank-based unpaired Wilcoxon's test for a GO-based microarray data interpretation. Further features of the program include recognition of the alternative gene names and the correction for multiple testing. Obtained results are visualized interactively both as a table and as a GO subgraph including all significant nodes. Currently, JProGO enables the analysis of microarray data from more than 20 different prokaryotic species, including all important model organisms, and thus constitutes a useful web service for the microbial research community. JProGO is freely accessible via the web at the following address: http://www.jprogo.de.

A novel method for the adaptation of target gene codon usage to most sequenced prokaryotes and selected eukaryotic gene expression hosts was developed to improve heterologous protein production. In contrast to existing tools, JCat (Java Codon Adaptation Tool) does not require the manual definition of highly expressed genes and is, therefore, a very rapid and easy method. Further options of JCat for codon adaptation include the avoidance of unwanted cleavage sites for restriction enzymes and Rho-independent transcription terminators. The output of JCat is both graphically and as Codon Adaptation Index (CAI) values given for the pasted sequence and the newly adapted sequence. Additionally, a list of genes in FASTA-format can be uploaded to calculate CAI values. In one example, all genes of the genome of Caenorhabditis elegans were adapted to Escherichia coli codon usage and further optimized to avoid commonly used restriction sites. In a second example, the Pseudomonas aeruginosa exbD gene codon usage was adapted to E.coli codon usage with parallel avoidance of the same restriction sites. For both, the degree of introduced changes was documented and evaluated. JCat is integrated into the PRODORIC database that hosts all required information on the various organisms to fulfill the requested calculations. JCat is freely accessible at http://www.prodoric.de/JCat.

The accurate determination of mass isotopomer distributions (MID) is of great significance for stable isotope-labeling experiments. Most commonly, MIDs are derived from gas chromatography/electron ionization mass spectrometry (GC/EI-MS) measurements. The analysis of fragment ions formed during EI, which contain only specific parts of the original molecule can provide valuable information on the positional distribution of the label. The chemical formula of a fragment ion is usually applied to derive the correction matrix for accurate MID calculation. Hence, the correct assignment of chemical formulas to fragment ions is of crucial importance for correct MIDs. Moreover, the positional distribution of stable isotopes within a fragment ion is of high interest for stable isotope-assisted metabolomics techniques. For example, (13)C-metabolic flux analyses ((13)C-MFA) are dependent on the exact knowledge of the number and position of retained carbon atoms of the unfragmented molecule. Fragment ions containing different carbon atoms are of special interest, since they can carry different flux information. However, the process of mass spectral fragmentation is complex, and identifying the substructures and chemical formulas for these fragment ions is nontrivial. For that reason, we developed an algorithm, based on a systematic bond cleavage, to determine chemical formulas and retained atoms for EI derived fragment ions. Here, we present the fragment formula calculator (FFC) algorithm that can calculate chemical formulas for fragment ions where the chemical bonding (e.g., Lewis structures) of the intact molecule is known. The proposed algorithm is able to cope with general molecular rearrangement reactions occurring during EI in GC/MS measurements. The FFC algorithm is able to integrate stable isotope labeling experiments into the analysis and can automatically exclude candidate formulas that do not fit the observed labeling patterns.1 We applied the FFC algorithm to create a fragment ion repository that contains the chemical formulas and retained carbon atoms of a wide range of trimethylsilyl and tert-butyldimethylsilyl derivatized compounds. In total, we report the chemical formulas and backbone carbon compositions for 160 fragment ions of 43 alkylsilyl-derivatives of primary metabolites. Finally, we implemented the FFC algorithm in an easy-to-use graphical user interface and made it publicly available at http://www.ffc.lu .

DNA damage and telomere dysfunction shorten organismal lifespan. Here we show that oral glucose administration at advanced age increases health and lifespan of telomere dysfunctional mice. The study reveals that energy consumption increases in telomere dysfunctional cells resulting in enhanced glucose metabolism both in glycolysis and in the tricarboxylic acid cycle at organismal level. In ageing telomere dysfunctional mice, normal diet provides insufficient amounts of glucose thus leading to impaired energy homeostasis, catabolism, suppression of IGF-1/mTOR signalling, suppression of mitochondrial biogenesis and tissue atrophy. A glucose-enriched diet reverts these defects by activating glycolysis, mitochondrial biogenesis and oxidative glucose metabolism. The beneficial effects of glucose substitution on mitochondrial function and glucose metabolism are blocked by mTOR inhibition but mimicked by IGF-1 application. Together, these results provide the first experimental evidence that telomere dysfunction enhances the requirement of glucose substitution for the maintenance of energy homeostasis and IGF-1/mTOR-dependent mitochondrial biogenesis in ageing tissues., Shortened telomeres and reduced mitochondrial biogenesis are cellular hallmarks of ageing. Here, Missios et al. show that old mice with telomere dysfunction have an increased energetic demand that cannot be met unless mice are fed a glucose-rich diet, which improves energy metabolism and extends lifespan.

Acetyl coenzyme A (AcCoA) is the central biosynthetic precursor for fatty-acid synthesis and protein acetylation. In the conventional view of mammalian cell metabolism, AcCoA is primarily generated from glucose-derived pyruvate through the citrate shuttle and ATP citrate lyase in the cytosol. However, proliferating cells that exhibit aerobic glycolysis and those exposed to hypoxia convert glucose to lactate at near-stoichiometric levels, directing glucose carbon away from the tricarboxylic acid cycle and fatty-acid synthesis. Although glutamine is consumed at levels exceeding that required for nitrogen biosynthesis, the regulation and use of glutamine metabolism in hypoxic cells is not well understood. Here we show that human cells use reductive metabolism of α-ketoglutarate to synthesize AcCoA for lipid synthesis. This isocitrate dehydrogenase-1 (IDH1)-dependent pathway is active in most cell lines under normal culture conditions, but cells grown under hypoxia rely almost exclusively on the reductive carboxylation of glutamine-derived α-ketoglutarate for de novo lipogenesis. Furthermore, renal cell lines deficient in the von Hippel–Lindau tumour suppressor protein preferentially use reductive glutamine metabolism for lipid biosynthesis even at normal oxygen levels. These results identify a critical role for oxygen in regulating carbon use to produce AcCoA and support lipid synthesis in mammalian cells., National Institutes of Health (U.S.) (Grant R01 DK075850-01), American Cancer Society (Postdoctoral Fellowship), National Institutes of Health (U.S.), Burroughs Wellcome Fund, Smith Family Foundation, Damon Runyon Cancer Research Foundation, National Cancer Institute (U.S.)

Oncogenes such as K‐ras mediate cellular and metabolic transformation during tumorigenesis. To analyze K‐Ras‐dependent metabolic alterations, we employed [superscript 13]C metabolic flux analysis (MFA), non‐targeted tracer fate detection (NTFD) of [superscript 15]N‐labeled glutamine, and transcriptomic profiling in mouse fibroblast and human carcinoma cell lines. Stable isotope‐labeled glucose and glutamine tracers and computational determination of intracellular fluxes indicated that cells expressing oncogenic K‐Ras exhibited enhanced glycolytic activity, decreased oxidative flux through the tricarboxylic acid (TCA) cycle, and increased utilization of glutamine for anabolic synthesis. Surprisingly, a non‐canonical labeling of TCA cycle‐associated metabolites was detected in both transformed cell lines. Transcriptional profiling detected elevated expression of several genes associated with glycolysis, glutamine metabolism, and nucleotide biosynthesis upon transformation with oncogenic K‐Ras. Chemical perturbation of enzymes along these pathways further supports the decoupling of glycolysis and TCA metabolism, with glutamine supplying increased carbon to drive the TCA cycle. These results provide evidence for a role of oncogenic K‐Ras in the metabolic reprogramming of cancer cells., National Institutes of Health (U.S.) (Grant 1R01 DK075850-01), American Cancer Society, Tecnomed Foundation (Postdoctoral Fellowship)