GC-MS analysis of amino acids rapidly provides rich information for isotopomer balancing

Gas chromatography-mass spectrometry (GC-MS) is a rapid method that provides rich information on isotopomer distributions for metabolic flux analysis. First, we established a fast and reliable experimental protocol for GC-MS analysis of amino acids from total biomass hydrolyzates, and common experimental pitfalls are discussed. Second, a suitable interface for the use of mass isotopomer data is presented. For this purpose, a general, matrix-based correction procedure that accounts for naturally occurring isotopes is introduced. Simulated and experimentally determined mass distributions of unlabeled amino acids showed a deviation of less than 3% for 89% of the analyzed fragments. Third, to investigate general properties of GC-MS-based isotopomer balancing, altered flux ratios through glycolysis and pentose phosphate pathway and/or exchange fluxes were simulated. Different fluxes were found to exert specific and significant influence on the mass isotopomer distributions, thus indicating that GC-MS data contain valuable information for metabolic flux analysis. Fourth, comparison of different methods revealed that GC-MS analysis provides the largest number of independent constraints on amino acid isotopomer abundance, followed by correlation spectroscopy and fractional enrichment analysis by nuclear magnetic resonance.     

Determination of full 13C isotopomer distributions for metabolic flux analysis using heteronuclear spin echo difference NMR spectroscopy

13C-isotopomer labeling experiments play an increasingly important role in the analysis of intracellular metabolic fluxes for genetic engineering purposes. 13C NMR spectroscopy is a key technique in the experimental determination of isotopomer distributions. However, only subsets of isotopomers can be quantitated using this technique due to redundancies in the scalar coupling patterns and due to invisibility of the 12C isotope in NMR. Therefore, we developed and describe in this paper a 1H NMR spectroscopy method that allows to determine the complete isotopomer distribution in metabolites having a backbone consisting of up to at least four carbons. The proposed pulse sequences employ up to three alternately applied frequency-selective inversion pulses in the 13C channel. In a first application study, the complete isotopomer distribution of aspartate isolated from [1-13C]ethanol-grown Ashbya gossypii was determined. A tentative model of the central metabolism of this organism was constructed and used for metabolic flux analysis. The aspartate isotopomer NMR data played a key role in the successful determination of the flux through the peroxisomal glyoxylate pathway. The new NMR method can be highly instrumental in generating the data upon which isotopomer labeling experiments for flux analysis, that are becoming increasingly important, are based.     

Modeling isotopomer distributions in biochemical networks using isotopomer mapping matrices

Within the last decades NMR spectroscopy has undergone tremendous development and has become a powerful analytical tool for the investigation of intracellular flux distributions in biochemical networks using (13)C-labeled substrates. Not only are the experiments much easier to conduct than experiments employing radioactive tracer elements, but NMR spectroscopy also provides additional information on the labeling pattern of the metabolites. Whereas the maximum amount of information obtainable with (14)C-labeled substrates is the fractional enrichment in the individual carbon atom positions, NMR spectroscopy can also provide information on the degree of labeling at neighboring carbon atom positions by analyzing multiplet patterns in NMR spectra or using 2-dimensional NMR spectra. It is possible to quantify the mole fractions of molecules that show a specific labeling pattern, i.e., information of the isotopomer distribution in metabolite pools can be obtained. The isotopomer distribution is the maximum amount of information that in theory can be obtained from (13)C-tracer studies. The wealth of information contained in NMR spectra frequently leads to overdetermined algebraic systems. Consequently, fluxes must be estimated by nonlinear least squares analysis, in which experimental labeling data is compared with simulated steady state isotopomer distributions. Hence, mathematical models are required to compute the steady state isotopomer distribution as a function of a given set of steady state fluxes. Because 2(n) possible labeling patterns exist in a molecule of n carbon atoms, and each pattern corresponds to a separate state in the isotopomer model, these models are inherently complex. Model complexity, so far, has restricted usage of isotopomer information to relatively small metabolic networks. A general methodology for the formulation of isotopomer models is described. The model complexity of isotopomer models is reduced to that of classical metabolic models by expressing the 2(n) isotopomer mass balances of a metabolite pool in a single matrix equation. Using this approach an isotopomer model has been implemented that describes label distribution in primary carbon metabolism, i.e., in a metabolic network including the Embden-Meyerhof-Parnas and pentose phosphate pathway, the tricarboxylic acid cycle, and selected anaplerotic reaction sequences. The model calculates the steady state label distribution in all metabolite pools as a function of the steady state fluxes and is applied to demonstrate the effect of selected anaplerotic fluxes on the labeling pattern of the pathway intermediates. (c) 1997 John Wiley & Sons, Inc. Biotechnol Bioeng 55:831-840, 1997.     

一种中间代谢途径代谢通量的定量分析方法

以¹³C标记的碳源,用二维核磁共振技术(¹H-¹³C,HMQC)测定代谢中产生的氨基酸标记模式,研究对中间代谢途径胞内代谢通量进行定量分析的方法.通过开发软件包,改进同位素分布的数学模型,提出了反应映射矩阵(RMM)等概念.由简化算法,提高程序的执行效率,建立了定量分析胞内代谢通量的平台.代谢模型涉及了糖酵解途径、磷酸戊糖途径、三羧酸循环、几种回补反应、发酵途径和氨基酸合成途径.     

Reciprocal 13C-labeling: a method for investigating the catabolism of cosubstrates

The principle of reciprocal labeling is to use a uniformly 13C-labeled substrate as the primary carbon source and a naturally labeled cosubstrate. Metabolites derived from a naturally labeled cosubstrate, in this case amino acids, can then be identified by their relatively lower content of 13C, and information on the degradation pathway can be deduced. The technique is based on GC-MS measurements of amino acid labeling patterns, making the technique well suited for investigating the relative importance of amino acid biosynthesis and amino acid uptake from the medium, as the 13C content of the amino acids incorporated into biomass is a direct measure of the amino acid biosyntheses. The technique is illustrated by the investigation of the degradation of phenoxyacetic acid, a medium component that is essential for production of penicillin V by Penicillium chrysogenum. Glucose was used as the uniformly labeled primary carbon source.     

Retrobiosynthetic nuclear magnetic resonance analysis of amino acid biosynthesis and intermediary metabolism. Metabolic flux in developing maize kernels

Information on metabolic networks could provide the basis for the design of targets for metabolic engineering. To study metabolic flux in cereals, developing maize (Zea mays) kernels were grown in sterile culture on medium containing [U-(13)C(6)]glucose or [1,2-(13)C(2)]acetate. After growth, amino acids, lipids, and sitosterol were isolated from kernels as well as from the cobs, and their (13)C isotopomer compositions were determined by quantitative nuclear magnetic resonance spectroscopy. The highly specific labeling patterns were used to analyze the metabolic pathways leading to amino acids and the triterpene on a quantitative basis. The data show that serine is generated from phosphoglycerate, as well as from glycine. Lysine is formed entirely via the diaminopimelate pathway and sitosterol is synthesized entirely via the mevalonate route. The labeling data of amino acids and sitosterol were used to reconstruct the labeling patterns of key metabolic intermediates (e.g. acetyl-coenzyme A, pyruvate, phosphoenolpyruvate, erythrose 4-phosphate, and Rib 5-phosphate) that revealed quantitative information about carbon flux in the intermediary metabolism of developing maize kernels. Exogenous acetate served as an efficient precursor of sitosterol, as well as of amino acids of the aspartate and glutamate family; in comparison, metabolites formed in the plastidic compartments showed low acetate incorporation.     

Simultaneous tracers and a unified model of positional and mass isotopomers for quantification of metabolic flux in liver

Computational models based on the metabolism of stable isotope tracers can yield valuable insight into the metabolic basis of disease. The complexity of these models is limited by the number of tracers and the ability to characterize tracer labeling in downstream metabolites. NMR spectroscopy is ideal for multiple tracer experiments since it precisely detects the position of tracer nuclei in molecules, but it lacks sensitivity for detecting low-concentration metabolites. GC-MS detects stable isotope mass enrichment in low-concentration metabolites, but lacks nuclei and positional specificity. We performed liver perfusions and in vivo infusions of ²H and ¹³C tracers, yielding complex glucose isotopomers that were assigned by NMR and fit to a newly developed metabolic model. Fluxes regressed from ²H and ¹³C NMR positional isotopomer enrichments served to validate GC-MS-based flux estimates obtained from the same experimental samples. NMR-derived fluxes were largely recapitulated by modeling the mass isotopomer distributions of six glucose fragment ions measured by GC-MS. Modest differences related to limited fragmentation coverage of glucose C1–C3 were identified, but fluxes such as gluconeogenesis, glycogenolysis, cataplerosis and TCA cycle flux were tightly correlated between the methods. Most importantly, modeling of GC-MS data could assign fluxes in primary mouse hepatocytes, an experiment that is impractical by ²H or ¹³C NMR.     

Gas chromatography-mass spectrometry analysis of 13C labeling in sugars for metabolic flux analysis

Metabolic flux analysis, using 13C labeled substrates, has become a powerful methodology for quantifying intracellular fluxes. Most often, analysis is restricted to nuclear magnetic resonance or mass spectrometry measurement of 13C label incorporation into protein amino acids. However, amino acid isotopomer distribution insufficiently covers the entire network of central metabolism, especially in plant cells with highly compartmented metabolism, and analysis of other metabolites is required. Analysis of label in saccharides provides complementary data to better define fluxes around hexose, pentose, and triose phosphate pools. Here, we propose a gas chromatography-mass spectrometry (GC-MS) method to analyze 13C labeling in glucose and fructose moieties of sucrose, free glucose, fructose, maltose, inositol, and starch. Our results show that saccharide labeling for isotopomer quantification is better analyzed by chemical ionization than by electron ionization. The structure of the generated fragments was simulated and validated using labeled standards. The method is illustrated by analysis of saccharides extracted from developing rapeseed (Brassica napus L.) embryos. It is shown that glucose 6-phosphate isomerase and plastidial glucose 6-phosphate transport reactions are not at equilibrium, and light is shed on the pathways leading to fructose, maltose, and inositol synthesis.     

Metabolic flux analysis in Synechocystis using isotope distribution from 13C-labeled glucose

Using the carbon isotope labeling technique, the response of cyanobacterial central carbon metabolism to the change in environmental conditions was investigated. Synechocystis was grown in the heterotrophic and mixotrophic cultures fed with 13C-labeled glucose. The labeling patterns of the amino acids in biomass hydrolysates for both cultures were detected by the two-dimensional 1H-13C correlation nuclear magnetic resonance (2D 1H-13C COSY NMR) spectroscopy and gas chromatography-mass spectrometry (GC-MS) technique. The in vivo intracellular flux distributions were then quantitated from the labeling measurements and metabolite balances using a parameters fitting approach. From the estimated flux distributions, it was found that the pentose phosphate pathway was the major pathway of glucose catabolism in the heterotrophic culture, while in the mixotrophic culture, the flux of CO2 fixation through the Calvin cycle was about two-fold of the glucose input flux. The relative flux through the phosphoenolpyruvate carboxylase was very high in both cultures, and this reaction represented about 25% of the assimilated CO2 in the mixotrophic culture. More importantly, we found a substantial outflow from the tricarboxylic acid cycle to glycolysis pathway carried by the malic enzyme, demonstrating the operation of a C4 pathway in cyanobacterial cells through the PEP carboxylase and malic enzyme. The estimated flux distributions also revealed that the NADPH synthesis was in excess relative to its requirement, and the excess NADPH might be reoxidized in cyanobacterial respiration to provide the energy for cellular requirement. Moreover, the analyzed result also suggested that the activity of the respiratory electron transport chain in cyanobacterial cells was not inhibited by light.     

13C isotopomer analysis of glutamate by J-resolved heteronuclear single quantum coherence spectroscopy

13C NMR isotopomer analysis is a powerful method for measuring metabolic fluxes through pathways intersecting in the tricarboxylic acid cycle. However, the inherent insensitivity of 13C NMR spectroscopy makes application of isotopomer analysis to small tissue samples (mouse tissue, human biopsies, or cells grown in tissue culture) problematic. (1)H NMR is intrinsically more sensitive than 13C NMR and can potentially supply the same information via indirect detection of 13C providing that isotopomer information can be preserved. We report here the use of J-resolved HSQC (J-HSQC) for 13C isotopomer analysis of tissue samples. We show that J-HSQC reports isotopomer multiplet patterns identical to those reported by direct 13C detection but with improved sensitivity.     

Metabolic flux analysis with a comprehensive isotopomer model in Bacillus subtilis

Fluxes in central carbon metabolism of a genetically engineered, riboflavin-producing Bacillus subtilis strain were investigated in glucose-limited chemostat cultures at low (0.11 h(-1)) and high (0.44 h(-1)) dilution rates. Using a mixture of 10% [U-(13)C] and 90% glucose labeled at natural abundance, (13)C-labeling experiments were carried out to provide additional information for metabolic flux balancing. The resulting labeling pattern in the proteinogenic amino acids were analyzed by two-dimensional [(13)C, (1)H] nuclear magnetic resonance (NMR) spectroscopy. To account rigorously for all available data from these experiments, we developed a comprehensive isotopomer model of B. subtilis central metabolism. Using this model, intracellular carbon net and exchange fluxes were estimated on the basis of validated physiological data and biomass composition in combination with 2D NMR data from 45 individual carbon atom spectra in the amino acids. Glucose catabolism proceeded primarily via glycolysis but pentose phosphate pathway fluxes increased with increasing growth rate. Moreover, significant back fluxes from the TCA cycle to the lower part of glycolysis via the gluconeogenic PEP carboxykinase were detected. The malic enzyme reaction, in contrast, was found to be inactive. A thorough statistical analysis was performed to prove the reliability of the isotopomer balance model and the obtained results. Specifically, a chi(2) test was applied to validate the model and the chi-square criterion was used to explore the sensitivity of model predictions to the experimental data.     

13C-NMR, 1H-NMR and gas-chromatography mass-spectrometry studies of the biosynthesis of 13C-enriched L-lysine by Brevibacterium flavum

The basic metabolic pathways of lysine biosynthesis in Brevibacterium flavum, a strain which excretes excessive amounts of L-lysine, have been followed by using two 13C-labeled precursors. 13C- and 1H-NMR spectroscopies in conjunction with gas chromatography mass spectrometry (GC-MS) have revealed the various metabolic pathways leading to L-[13C]lysine. Discrete metabolic pathways give rise to distinct labeling patterns. L-Lysine resulting from [1-13C]glucose fermentation is relatively specifically labeled: L-[3,5-13C]lysine is the main product. Experimental and theoretical approaches based on the 13C-enrichment values of intracellular glutamate, a major intermediate metabolite, allowed us to assess the relative contribution of the major metabolic pathways forming lysine. The labeling pattern of glutamate reflects the isotope distribution in 2-oxoglutarate. When [2-13C]acetate is used as the sole carbon source in the culture, the energy-producing steps of the Krebs cycle are essential. The higher activity of the Krebs cycle, when endogenous carbohydrates are exhausted from the culture, is indicated by the increased 13C enrichment in C-1 of lysine and reveal a high content of isotopomers of four, five and six 13C atoms in the lysine molecule, pointing out that the four-carbon intermediates of the cycle are being derived from the glyoxylate shunt pathway. Such a phenomenon does not occur in glucose fermentation. GC-MS analyses of 13C enrichments and isotopomer distributions in metabolites and end products are in good agreement with the predicted contribution of each metabolic pathway. This new methodological approach of combined NMR and GC-MS has been demonstrated to be applicable to various other metabolic studies.     

Stable isotope peptide mass spectrometry to decipher amino acid metabolism in Dehalococcoides strain CBDB1

Dehalococcoides species are key players in the anaerobic transformation of halogenated solvents at contaminated sites. Here, we analyze isotopologue distributions in amino acid pools from peptides of Dehalococcoides strain CBDB1 after incubation with (13)C-labeled acetate or bicarbonate as a carbon source. The resulting data were interpreted with regard to genome annotations to identify amino acid biosynthesis pathways. In addition to using gas chromatography-mass spectrometry (GC-MS) for analyzing derivatized amino acids after protein hydrolysis, we introduce a second, much milder method, in which we directly analyze peptide masses after tryptic digest and peptide fragments by nano-liquid chromatography-electrospray ionization-tandem mass spectrometry (nano-LC-ESI-MS/MS). With this method, we identify isotope incorporation patterns for 17 proteinaceous amino acids, including proline, cysteine, lysine, and arginine, which escaped previous analyses in Dehalococcoides. Our results confirmed lysine biosynthesis via the α-aminoadipate pathway, precluding lysine formation from aspartate. Similarly, the isotopologue pattern obtained for arginine provided biochemical evidence of its synthesis from glutamate. Direct peptide MS/MS analysis of the labeling patterns of glutamine and asparagine, which were converted to glutamate and aspartate during protein hydrolysis, gave biochemical evidence of their precursors and confirmed glutamate biosynthesis via a Re-specific citrate synthase. By addition of unlabeled free amino acids to labeled cells, we show that in strain CBDB1 none of the 17 tested amino acids was incorporated into cell mass, indicating that they are all synthesized de novo. Our approach is widely applicable and provides a means to analyze amino acid metabolism by studying specific proteins even in mixed consortia.     

Catabolism of Branched Chain Amino Acids Contributes Significantly to Synthesis of Odd-Chain and Even-Chain Fatty Acids in 3T3-L1 Adipocytes

The branched chain amino acids (BCAA) valine, leucine and isoleucine have been implicated in a number of diseases including obesity, insulin resistance, and type 2 diabetes mellitus, although the mechanisms are still poorly understood. Adipose tissue plays an important role in BCAA homeostasis by actively metabolizing circulating BCAA. In this work, we have investigated the link between BCAA catabolism and fatty acid synthesis in 3T3-L1 adipocytes using parallel ¹³C-labeling experiments, mass spectrometry and model-based isotopomer data analysis. Specifically, we performed parallel labeling experiments with four fully ¹³C-labeled tracers, [U-¹³C]valine, [U-¹³C]leucine, [U-¹³C]isoleucine and [U-¹³C]glutamine. We measured mass isotopomer distributions of fatty acids and intracellular metabolites by GC-MS and analyzed the data using the isotopomer spectral analysis (ISA) framework. We demonstrate that 3T3-L1 adipocytes accumulate significant amounts of even chain length (C14:0, C16:0 and C18:0) and odd chain length (C15:0 and C17:0) fatty acids under standard cell culture conditions. Using a novel GC-MS method, we demonstrate that propionyl-CoA acts as the primer on fatty acid synthase for the production of odd chain fatty acids. BCAA contributed significantly to the production of all fatty acids. Leucine and isoleucine contributed at least 25% to lipogenic acetyl-CoA pool, and valine and isoleucine contributed 100% to lipogenic propionyl-CoA pool. Our results further suggest that low activity of methylmalonyl-CoA mutase and mass action kinetics of propionyl-CoA on fatty acid synthase result in high rates of odd chain fatty acid synthesis in 3T3-L1 cells. Overall, this work provides important new insights into the connection between BCAA catabolism and fatty acid synthesis in adipocytes and underscores the high capacity of adipocytes for metabolizing BCAA.     

Quantification of intracellular metabolic fluxes from fractional enrichment and 13C-13C coupling constraints on the isotopomer distribution in labeled biomass components

A method for the quantification of intracellular metabolic flux distributions from steady-state mass balance constraints and from the constraints posed by the measured 13C labeling state of biomass components is presented. Two-dimensional NMR spectroscopy is used to analyze the labeling state of cell protein hydrolysate and cell wall components. No separation of the biomass hydrolysate is required to measure the degree of 13C-13C coupling and the fractional 13C enrichment in various carbon atom positions. A mixture of [1-13C]glucose and uniformly labeled [13C6]glucose is applied to make fractional 13C enrichment data and measurements of the degree of 13C-13C coupling informative with respect to the intracellular flux distribution. Simulation models that calculate the complete isotopomer distribution in biomass components on the basis of isotopomer mapping matrices are used for the estimation of intracellular fluxes by least-squares minimization. The statistical quality of the estimated intracellular flux distributions is assessed by Monte Carlo methods. Principal component analysis is performed on the outcome of the Monte Carlo procedure to identify groups of fluxes that contribute major parts to the total variance in the multiple flux estimations. The methods described are applied to a steady-state culture of a glucoamylase-producing recombinant Aspergillus niger strain.     

Computing positional isotopomer distributions from tandem mass spectrometric data

The isotopomer distributions of metabolites are invaluable pieces of information in the computation of the flux distribution in a metabolic network. We describe the use of tandem mass spectrometry with the daughter ion scanning technique in the discovery of positional isotopomer distributions (PID). This technique increases the possibilities of mass spectrometry since given the same fragment ions, it uncovers more information than the full scanning mode. The mathematics of the new technique is slightly more complicated than the techniques needed by full scanning mode methods. Our experiments, however, show that in practice the inadequacy of the fragmentation of amino acids in the tandem mass spectrometer does not allow uncovering the PID exactly even if the daughter ion scanning is used. The computational techniques have been implemented in a MATLAB application called PIDC (Positional Isotopomer Distribution Calculator).     

Metabolite and isotopomer balancing in the analysis of metabolic cycles: I. Theory

Proper analysis of label distribution in metabolic pathway intermediates is critical for correct interpretation of experimental data and strategic experimental design. While, for example, 13C nuclear magnetic resonance (NMR) spectroscopy is usually limited to the measurement of degrees of 13C enrichment, more information about metabolic fluxes can be extracted from the fine structure of NMR spectra, or molecular weight distributions of isotopomers of metabolic intermediates (measured by gas chromatography-mass spectrometry). For this purpose, rigorous accounting for the contribution of all pathways to label distribution is required, especially contributions resulting from multiple turns of metabolic cycles. In this paper we present a mathematical model developed to analyze isotopomer distributions of tricarboxylic acid cycle (TCA) intermediates following the administration of 13C (or 14C) labeled substrates. The theory presented provides the basis to analyze 13C NMR spectra and molecular weight distributions of metabolites. In a companion paper (Park et al., 1999), the theory is applied to the analysis of several cases of biological significance. Copyright 1999 John Wiley & Sons, Inc.     

Metabolic flux analysis in Escherichia coli by integrating isotopic dynamic and isotopic stationary 13C labeling data

The novel concept of isotopic dynamic 13C metabolic flux analysis (ID-13C MFA) enables integrated analysis of isotopomer data from isotopic transient and/or isotopic stationary phase of a 13C labeling experiment, short-time experiments, and an extended range of applications of 13C MFA. In the presented work, an experimental and computational framework consisting of short-time 13C labeling, an integrated rapid sampling procedure, a LC-MS analytical method, numerical integration of the system of isotopomer differential equations, and estimation of metabolic fluxes was developed and applied to determine intracellular fluxes in glycolysis, pentose phosphate pathway (PPP), and citric acid cycle (TCA) in Escherichia coli grown in aerobic, glucose-limited chemostat culture at a dilution rate of D = 0.10 h(-1). Intracellular steady state concentrations were quantified for 12 metabolic intermediates. A total of 90 LC-MS mass isotopomers were quantified at sampling times t = 0, 91, 226, 346, 589 s and at isotopic stationary conditions. Isotopic stationarity was reached within 10 min in glycolytic and PPP metabolites. Consistent flux solutions were obtained by ID-13C MFA using isotopic dynamic and isotopic stationary 13C labeling data and by isotopic stationary 13C MFA (IS-13C MFA) using solely isotopic stationary data. It is demonstrated that integration of dynamic 13C labeling data increases the sensitivity of flux estimation, particularly at the glucose-6-phosphate branch point. The identified split ratio between glycolysis and PPP was 55%:44%. These results were confirmed by IS-13C MFA additionally using labeling data in proteinogenic amino acids (GC-MS) obtained after 5 h from sampled biomass.     

Profiling of central metabolism in human cancer cells by two-dimensional NMR, GC-MS analysis, and isotopomer modeling

Tracking metabolic profiles has the potential to reveal crucial enzymatic steps that could be targeted in the drug discovery process. It is of special importance for various types of cancer known to be associated with substantial rewiring of metabolic networks. Here we introduce an integrated approach for the analysis of metabolome that allows us to simultaneously assess pathway activities (fluxes) and concentrations of a large number of the key components involved in central metabolism of human cells. This is accomplished by in vivo labeling with [U-¹³C]glucose followed by two-dimensional nuclear magnetic resonance (NMR) spectroscopy and gas chromatography-mass spectrometry (GC-MS) analysis. A comprehensive isotopomer model was developed, which enabled us to compare fluxes through the key central metabolic pathways including glycolysis, pentose phosphate pathway, tricarboxylic acid cycle, anaplerotic reactions, and biosynthetic pathways of fatty acids and amino acids. The validity and strength of this approach is illustrated by its application to a number of perturbations to breast cancer cells, including exposure to hypoxia, drug treatment, and tumor progression. We observed significant differences in the activities of specific metabolic pathways resulting from these perturbations and providing new mechanistic insights. Based on these findings we conclude that the developed metabolomic approach constitutes a promising analytical tool for revealing specific metabolic phenotypes in a variety of cell types and pathological conditions. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users. Chen Yang and Adam D. Richardson contributed equally to this work.