13C Metabolic Flux Analysis Research Articles

Reductive carboxylation is a major metabolic pathway in the retinal pigment epithelium

The retinal pigment epithelium (RPE) is a monolayer of pigmented cells that requires an active metabolism to maintain outer retinal homeostasis and compensate for oxidative stress. Using 13C metabolic flux analysis in human RPE cells, we found that RPE has an exceptionally high capacity for reductive carboxylation, a metabolic pathway that has recently garnered significant interest because of its role in cancer cell survival. The capacity for reductive carboxylation in RPE exceeds that of all other cells tested, including retina, neural tissue, glial cells, and a cancer cell line. Loss of reductive carboxylation disrupts redox balance and increases RPE sensitivity to oxidative damage, suggesting that deficiencies of reductive carboxylation may contribute to RPE cell death. Supporting reductive carboxylation by supplementation with an NAD+ precursor or its substrate α-ketoglutarate or treatment with a poly(ADP ribose) polymerase inhibitor protects reductive carboxylation and RPE viability from excessive oxidative stress. The ability of these treatments to rescue RPE could be the basis for an effective strategy to treat blinding diseases caused by RPE dysfunction.

Comprehensive analysis of glucose and xylose metabolism in Escherichia coli under aerobic and anaerobic conditions by 13C metabolic flux analysis

Glucose and xylose are the two most abundant sugars derived from the breakdown of lignocellulosic biomass. While aerobic glucose metabolism is relatively well understood in E. coli, until now there have been only a handful of studies focused on anaerobic glucose metabolism and no 13C-flux studies on xylose metabolism. In the absence of experimentally validated flux maps, constraint-based approaches such as MOMA and RELATCH cannot be used to guide new metabolic engineering designs. In this work, we have addressed this critical gap in current understanding by performing comprehensive characterizations of glucose and xylose metabolism under aerobic and anaerobic conditions, using recent state-of-the-art techniques in 13C metabolic flux analysis (13C-MFA). Specifically, we quantified precise metabolic fluxes for each condition by performing parallel labeling experiments and analyzing the data through integrated 13C-MFA using the optimal tracers [1,2-13C]glucose, [1,6-13C]glucose, [1,2-13C]xylose and [5-13C]xylose. We also quantified changes in biomass composition and confirmed turnover of macromolecules by applying [U-13C]glucose and [U-13C]xylose tracers. We demonstrated that under anaerobic growth conditions there is significant turnover of lipids and that a significant portion of CO2 originates from biomass turnover. Using knockout strains, we also demonstrated that β-oxidation is critical for anaerobic growth on xylose. Quantitative analysis of co-factor balances (NADH/FADH2, NADPH, and ATP) for different growth conditions provided new insights regarding the interplay of energy and redox metabolism and the impact on E. coli cell physiology.

WUFlux: an open-source platform for 13C metabolic flux analysis of bacterial metabolism.

BackgroundFlux analyses, including flux balance analysis (FBA) and 13C-metabolic flux analysis (13C-MFA), offer direct insights into cell metabolism, and have been widely used to characterize model and non-model microbial species. Nonetheless, constructing the 13C-MFA model and performing flux calculation are demanding for new learners, because they require knowledge of metabolic networks, carbon transitions, and computer programming. To facilitate and standardize the 13C-MFA modeling work, we set out to publish a user-friendly and programming-free platform (WUFlux) for flux calculations in MATLAB®.ResultsWe constructed an open-source platform for steady-state 13C-MFA. Using GUIDE (graphical user interface design environment) in MATLAB, we built a user interface that allows users to modify models based on their own experimental conditions. WUFlux is capable of directly correcting mass spectrum data of TBDMS (N-tert-butyldimethylsilyl-N-methyltrifluoroacetamide)-derivatized proteinogenic amino acids by removing background noise. To simplify 13C-MFA of different prokaryotic species, the software provides several metabolic network templates, including those for chemoheterotrophic bacteria and mixotrophic cyanobacteria. Users can modify the network and constraints, and then analyze the microbial carbon and energy metabolisms of various carbon substrates (e.g., glucose, pyruvate/lactate, acetate, xylose, and glycerol). WUFlux also offers several ways of visualizing the flux results with respect to the constructed network. To validate our model’s applicability, we have compared and discussed the flux results obtained from WUFlux and other MFA software. We have also illustrated how model constraints of cofactor and ATP balances influence fluxome results.ConclusionOpen-source software for 13C-MFA, WUFlux, with a user-friendly interface and easy-to-modify templates, is now available at http://www.13cmfa.org/or (http://tang.eece.wustl.edu/ToolDevelopment.htm). We will continue documenting curated models of non-model microbial species and improving WUFlux performance.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1314-0) contains supplementary material, which is available to authorized users.

Combined 13C-assisted metabolomics and metabolic flux analysis reveals the impacts of glutamate on the central metabolism of high β-galactosidase-producing Pichia pastoris.

Background Pichia pastoris is a popular recombinant protein expression system for its accessibility of efficient gene manipulation and high protein production. Sufficient supply of precursors, energy, and redox cofactors is crucial for high recombinant protein production. In our present work, we found that the addition of glutamate improved the recombinant β-galactosidase (β-gal) production by P. pastoris G1HL.MethodsTo elucidate the impacts of glutamate on the central metabolism in detail, a combined 13C-assisted metabolomics and 13C metabolic flux analysis was conducted based on LC–MS/MS and GC–MS data.ResultsThe pool sizes of intracellular amino acids were obviously higher on glucose/glutamate (Glc/Glu). The fluxes in EMP entry reaction and in downstream TCA cycle were 50 and 67% higher on Glc/Glu than on Glc, respectively. While the fluxes in upstream TCA cycle kept almost unaltered, the fluxes in PPP oxidative branch decreased.ConclusionThe addition of glutamate leads to a remarkable change on the central metabolism of high β-galactosidase-producing P. pastoris G1HL. To meet the increased demands of redox cofactors and energy for higher β-galactosidase production on Glc/Glu, P. pastoris G1HL redistributes the fluxes in central metabolism through the inhibitions and/or activation of the enzymes in key nodes together with the energy and redox status.Electronic supplementary materialThe online version of this article (doi:10.1186/s40643-016-0124-6) contains supplementary material, which is available to authorized users.

Metabolic flux analyses of Pseudomonas aeruginosa cystic fibrosis isolates

Pseudomonas aeruginosa is a metabolically versatile wide-ranging opportunistic pathogen. In humans P. aeruginosa causes infections of the skin, urinary tract, blood, and the lungs of Cystic Fibrosis patients. In addition, P. aeruginosa's broad environmental distribution, relatedness to biotechnologically useful species, and ability to form biofilms have made it the focus of considerable interest. We used 13C metabolic flux analysis (MFA) and flux balance analysis to understand energy and redox production and consumption and to explore the metabolic phenotypes of one reference strain and five strains isolated from the lungs of cystic fibrosis patients. Our results highlight the importance of the oxidative pentose phosphate and Entner-Doudoroff pathways in P. aeruginosa growth. Among clinical strains we report two divergent metabolic strategies and identify changes between genetically related strains that have emerged during a chronic infection of the same patient. MFA revealed that the magnitude of fluxes through the glyoxylate cycle correlates with growth rates.

13C-metabolic flux analysis for mevalonate-producing strain of Escherichia coli

Mevalonate (MVA) is used to produce various useful products such as drugs, cosmetics and food additives. An MVA-producing strain of Escherichia coli (engineered) was constructed by introducing mvaES genes from Enterococcus faecalis. The engineered strain produced 1.84mmol/gDCW/h yielding 22% (C-mol/C-mol) of MVA from glucose in the aerobic exponential growth phase. The mass balance analysis revealed that the MVA yield of the engineered strain was close to the upper limit at the biomass yield. Since MVA is synthesized from acetyl-CoA using NADPH as a cofactor, the production of MVA affects central metabolism in terms of carbon utilization and NADPH requirements. The reason for this highly efficient MVA production was investigated based on 13C-metabolic flux analysis. The estimated flux distributions revealed that the fluxes of acetate formation and the TCA cycle in the engineered strain were lower than those in the control strain. Although the oxidative pentose phosphate pathway is considered as the NADPH generating pathway in E.coli, no difference of the flux was observed between the control and engineered strains. The production/consumption balance of NADPH suggested that additional requirement of NADPH for MVA synthesis was obtained from the transhydrogenase reaction in the engineered strain. Comparison between the measured flux distribution and the ideal values for MVA production proposes a strategy for further engineering to improve the MVA production in E.coli.

Elucidation of the co-metabolism of glycerol and glucose in Escherichia coli by genetic engineering, transcription profiling, and (13)C metabolic flux analysis.

BackgroundGlycerol, a byproduct of biodiesel, has become a readily available and inexpensive carbon source for the production of high-value products. However, the main drawback of glycerol utilization is the low consumption rate and shortage of NADPH formation, which may limit the production of NADPH-requiring products. To overcome these problems, we constructed a carbon catabolite repression-negative ΔptsGglpK* mutant by both blocking a key glucose PTS transporter and enhancing the glycerol conversion. The mutant can recover normal growth by co-utilization of glycerol and glucose after loss of glucose PTS transporter. To reveal the metabolic potential of the ΔptsGglpK* mutant, this study examined the flux distributions and regulation of the co-metabolism of glycerol and glucose in the mutant.ResultsBy labeling experiments using [1,3-13C]glycerol and [1-13C]glucose, 13C metabolic flux analysis was employed to decipher the metabolisms of both the wild-type strain and the ΔptsGglpK* mutant in chemostat cultures. When cells were maintained at a low dilution rate (0.1 h−1), the two strains showed similar fluxome profiles. When the dilution rate was increased, both strains upgraded their pentose phosphate pathway, glycolysis and anaplerotic reactions, while the ΔptsGglpK* mutant was able to catabolize much more glycerol than glucose (more than tenfold higher). Compared with the wild-type strain, the mutant repressed its flux through the TCA cycle, resulting in higher acetate overflow. The regulation of fluxomes was consistent with transcriptional profiling of several key genes relevant to the TCA cycle and transhydrogenase, namely gltA, icdA, sdhA and pntA. In addition, cofactor fluxes and their pool sizes were determined. The ΔptsGglpK* mutant affected the redox NADPH/NADH state and reduced the ATP level. Redox signaling activated the ArcA regulatory system, which was responsible for TCA cycle repression.ConclusionsThis work employs both 13C-MFA and transcription/metabolite analysis for quantitative investigation of the co-metabolism of glycerol and glucose in the ΔptsGglpK* mutant. The ArcA regulatory system dominates the control of flux redistribution. The ΔptsGglpK* mutant can be used as a platform for microbial cell factories for the production of biofuels and biochemicals, since most of fuel molecule (e.g., alcohols) synthesis requires excess reducing equivalents.Electronic supplementary materialThe online version of this article (doi:10.1186/s13068-016-0591-1) contains supplementary material, which is available to authorized users.

Investigate the Metabolic Reprogramming of Saccharomyces cerevisiae for Enhanced Resistance to Mixed Fermentation Inhibitors via 13C Metabolic Flux Analysis

The fermentation inhibitors from the pretreatment of lignocellulosic materials, e.g., acetic acid and furfural, are notorious due to their negative effects on the cell growth and chemical production. However, the metabolic reprogramming of the cells under these stress conditions, especially metabolic response for resistance to mixed inhibitors, has not been systematically investigated and remains mysterious. Therefore, in this study, 13C metabolic flux analysis (13C-MFA), a powerful tool to elucidate the intracellular carbon flux distributions, has been applied to two Saccharomyces cerevisiae strains with different tolerances to the inhibitors under acetic acid, furfural, and mixed (i.e., acetic acid and furfural) stress conditions to unravel the key metabolic responses. By analyzing the intracellular carbon fluxes as well as the energy and cofactor utilization under different conditions, we uncovered varied metabolic responses to different inhibitors. Under acetate stress, ATP and NADH production was slightly impaired, while NADPH tended towards overproduction. Under furfural stress, ATP and cofactors (including both NADH and NADPH) tended to be overproduced. However, under dual-stress condition, production of ATP and cofactors was severely impaired due to synergistic stress caused by the simultaneous addition of two fermentation inhibitors. Such phenomenon indicated the pivotal role of the energy and cofactor utilization in resisting the mixed inhibitors of acetic acid and furfural. Based on the discoveries, valuable insights are provided to improve the tolerance of S. cerevisiae strain and further enhance lignocellulosic fermentation.

Enhancing fatty acid production in Escherichia coli by Vitreoscilla hemoglobin overexpression.

Our recent 13 C-metabolic flux analysis (13 C-MFA) study indicates that energy metabolism becomes a rate-limiting factor for fatty acid overproduction in E. coli strains (after "Push-Pull-Block" based genetic modifications). To resolve this bottleneck, Vitreoscilla hemoglobin (VHb, a membrane protein facilitating O2 transport) was introduced into a fatty-acid-producing strain to promote oxygen supply and energy metabolism. The resulting strain, FAV50, achieved 70% percent higher fatty acid titer than the parent strain in micro-aerobic shake tube cultures. In high cell-density bioreactor fermentations, FAV50 achieved free fatty acids at a titer of 7.02 g/L (51% of the theoretical yield). In addition to "Push-Pull-Block-Power" strategies, our experiments and flux balance analysis also revealed the fatty acid over-producing strain is sensitive to metabolic burden and oxygen influx, and thus a careful evaluation of the cost-benefit tradeoff with the guidance of fluxome analysis will be fundamental for the rational design of synthetic biology strains. Biotechnol. Bioeng. 2017;114: 463-467. © 2016 Wiley Periodicals, Inc.

13 C-metabolic flux analysis of human adenovirus infection: Implications for viral vector production.

Adenoviruses are human pathogens increasingly used as gene therapy and vaccination vectors. However, their impact on cell metabolism is poorly characterized. We performed carbon labeling experiments with [1,2-13 C]glucose or [U-13 C]glutamine to evaluate metabolic alterations in the amniocyte-derived, E1-transformed 1G3 cell line during production of a human adenovirus type 5 vector (AdV5). Nonstationary 13 C-metabolic flux analysis revealed increased fluxes of glycolysis (17%) and markedly PPP (over fourfold) and cytosolic AcCoA formation (nearly twofold) following infection of growing cells. Interestingly, infection of growth-arrested cells increased overall carbon flow even more, including glutamine anaplerosis and TCA cycle activity (both over 1.5-fold), but was unable to stimulate the PPP and was associated with a steep drop in AdV5 replication (almost 80%). Our results underscore the importance of nucleic and fatty acid biosynthesis for adenovirus replication. Overall, we portray a metabolic blueprint of human adenovirus infection, highlighting similarities with other viruses and cancer, and suggest strategies to improve AdV5 production. Biotechnol. Bioeng. 2017;114: 195-207. © 2016 Wiley Periodicals, Inc.

Carbon 13-Metabolic Flux Analysis derived constraint-based metabolic modelling of Clostridium acetobutylicum in stressed chemostat conditions

The metabolism of butanol producing bacteria Clostridium acetobutylicum was studied in chemostat with glucose limited conditions, butanol stimulus, and as a reference cultivation. COnstraint-Based Reconstruction and Analysis (COBRA) was applied using additional constraints from 13C Metabolic Flux Analysis (13C-MFA) and experimental measurement results. A model consisting of 451 metabolites and 604 reactions was utilized in flux balance analysis (FBA). The stringency of the flux spaces considering different optimization objectives, i.e. growth rate maximization, ATP maintenance, and NADH/NADPH formation, for flux variance analysis (FVA) was studied in the different modelled conditions. Also a previously uncharacterized exopolysaccharide (EPS) produced by C. acetobutylicum was characterized on monosaccharide level. The major monosaccharide components of the EPS were 40n-% rhamnose, 34n-% glucose, 13n-% mannose, 10n-% galactose, and 2n-% arabinose. The EPS was studied to have butanol adsorbing property, 70(butanol)mg(EPS)g−1 at 37°C.

Purification, enzymatic activity and inhibitor discovery for recombinant human carbonic anhydrase XIV

In the important industrial yeast Saccharomyces cerevisiae, galactose metabolism requires energy production by respiration; therefore, this yeast cannot metabolize galactose under strict anaerobic conditions. While the respiratory dependence of galactose metabolism provides benefits in terms of cell growth and population stability, it is not advantageous for producing fuels and chemicals since a substantial fraction of consumed galactose is converted to carbon dioxide. In order to force S. cerevisiae to use galactose without respiration, a subunit (COX9) of a respiratory enzyme was deleted, but the resulting deletion mutant (Δcox9) was impaired in terms of galactose assimilation. Interestingly, after serial sub-cultures on galactose, the mutant evolved rapidly and was able to use galactose via fermentation only. The evolved strain (JQ-G1) produced ethanol from galactose with a 94% increase in yield and 6.9-fold improvement in specific productivity as compared to the wild-type strain. 13C-metabolic flux analysis demonstrated a three-fold reduction in carbon flux through the TCA cycle of the evolved mutant with redirection of flux toward the fermentation pathway. Genome sequencing of the JQ-G1 strain revealed a loss of function mutation in a master negative regulator of the Leloir pathway (Gal80p). The mutation (Glu348*) in Gal80p was found to act synergistically with deletion of COX9 for efficient galactose fermentation, and thus the double deletion mutant Δcox9Δgal80 produced ethanol 2.4 times faster and with 35% higher yield than a single knockout mutant with deletion of GAL80 alone. When we introduced a functional COX9 cassette back into the JQ-G1 strain, the JQ-G1-COX9 strain showed a 33% reduction in specific galactose uptake rate and a 49% reduction in specific ethanol production rate as compared to JQ-G1. The wild-type strain was also subjected to serial sub-cultures on galactose but we failed to isolate a mutant capable of utilizing galactose without respiration. We concluded that the metabolic “death valley” (i.e. no galactose utilization by the Δcox9 mutant) is a necessary intermediate phenotype to facilitate galactose utilization without respiration in yeast. The results in this study demonstrate a promising approach for directing adaptive evolution toward fermentative metabolism and for generating evolved yeast strains with improved phenotypes under anaerobic conditions.

13C Metabolic Flux Analysis of acetate conversion to lipids by Yarrowia lipolytica

Volatile fatty acids (VFAs) are an inexpensive and renewable carbon source that can be generated from gas fermentation and anaerobic digestion of fermentable wastes. The oleaginous yeast Yarrowia lipolytica is a promising biocatalyst that can utilize VFAs and convert them into triacylglycerides (TAGs). However, currently there is limited knowledge on the metabolism of Y. lipolytica when cultured on VFAs. To develop a better understanding, we used acetate as the sole carbon source to culture two strains, a control strain and a previously engineered strain for lipid overaccumulation. For both strains, metabolism during the growth phase and lipid production phase were investigated by metabolic flux analysis using two parallel sodium acetate tracers. The resolved flux distributions demonstrate that the glyoxylate shunt pathway is constantly active and the flux through gluconeogenesis varies depending on strain and phase. In particular, by regulating the activities of malate transport and pyruvate kinase, the cells divert only a portion of the glyoxylate shunt flux required to satisfy the needs for anaplerotic reactions and NADPH production through gluconeogenesis and the oxidative pentose phosphate pathway (PPP). Excess flux flows back to the tricarboxylic acid (TCA) cycle for energy production. As with the case of glucose as the substrate, the primary source for lipogenic NADPH is derived from the oxidative PPP.

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We applied isotopically nonstationary 13C metabolic flux analysis (INST-MFA) to compare the pathway fluxes of wild-type (WT) Synechococcus elongatus PCC 7942 to an engineered strain (SA590) that produces isobutyraldehyde (IBA). The flux maps revealed a potential bottleneck at the pyruvate kinase (PK) reaction step that was associated with diversion of flux into a three-step PK bypass pathway involving the enzymes PEP carboxylase (PEPC), malate dehydrogenase (MDH), and malic enzyme (ME). Overexpression of pk in SA590 led to a significant improvement in IBA specific productivity. Single-gene overexpression of the three enzymes in the proposed PK bypass pathway also led to improvements in IBA production, although to a lesser extent than pk overexpression. Combinatorial overexpression of two of the three genes in the proposed PK bypass pathway (mdh and me) led to improvements in specific productivity that were similar to those achieved by single-gene pk overexpression. Our work demonstrates how 13C flux analysis can be used to identify potential metabolic bottlenecks and novel metabolic routes, and how these findings can guide rational metabolic engineering of cyanobacteria for increased production of desired molecules.

GC-MS/MS survey of collision-induced dissociation of tert-butyldimethylsilyl-derivatized amino acids and its application to (13)C-metabolic flux analysis of Escherichia coli central metabolism.

Stable isotope labeling experiments using mass spectrometry have been employed to investigate carbon flow levels (metabolic flux) in mammalian, plant, and microbial cells. To achieve a more precise (13)C-metabolic flux analysis ((13)C-MFA), novel fragmentations of tert-butyldimethylsilyl (TBDMS)-amino acids were investigated by gas chromatography-tandem mass spectrometry (GC-MS/MS). The product ion scan analyses of 15 TBDMS-amino acids revealed 24 novel fragment ions. The amino acid-derived carbons included in the five fragment ions were identified by the analyses of (13)C-labeled authentic standards. The identification of the fragment ion at m/z 170 indicated that the isotopic abundance of S-methyl carbon in methionine could be determined from the cleavage of C5 in the precursor of [M-159](+) (m/z 218). It was also confirmed that the precision of (13)C-MFA in Escherichia coli central carbon metabolism could be improved by introducing (13)C-labeling data derived from novel fragmentations. Graphical Abstract Novel collision-induced dissociation fragmentations of tert-butyldimethylsilyl amino acids were investigated and identified by GC-MS/MS.

13C metabolic flux analysis of microbial and mammalian systems is enhanced with GC-MS measurements of glycogen and RNA labeling

13C metabolic flux analysis (13C-MFA) is a widely used tool for quantitative analysis of microbial and mammalian metabolism. Until now, 13C-MFA was based mainly on measurements of isotopic labeling of amino acids derived from hydrolyzed biomass proteins and isotopic labeling of extracted intracellular metabolites. Here, we demonstrate that isotopic labeling of glycogen and RNA, measured with gas chromatography-mass spectrometry (GC-MS), provides valuable additional information for 13C-MFA. Specifically, we demonstrate that isotopic labeling of glucose moiety of glycogen and ribose moiety of RNA greatly enhances resolution of metabolic fluxes in the upper part of metabolism; importantly, these measurements allow precise quantification of net and exchange fluxes in the pentose phosphate pathway. To demonstrate the practical importance of these measurements for 13C-MFA, we have used Escherichia coli as a model microbial system and CHO cells as a model mammalian system. Additionally, we have applied this approach to determine metabolic fluxes of glucose and xylose co-utilization in the E. coli ΔptsG mutant. The convenience of measuring glycogen and RNA, which are stable and abundant in microbial and mammalian cells, offers the following key advantages: reduced sample size, no quenching required, no extractions required, and GC-MS can be used instead of more costly LC-MS/MS techniques. Overall, the presented approach for 13C-MFA will have widespread applicability in metabolic engineering and biomedical research.

E-Flux2 and SPOT: Validated Methods for Inferring Intracellular Metabolic Flux Distributions from Transcriptomic Data.

BackgroundSeveral methods have been developed to predict system-wide and condition-specific intracellular metabolic fluxes by integrating transcriptomic data with genome-scale metabolic models. While powerful in many settings, existing methods have several shortcomings, and it is unclear which method has the best accuracy in general because of limited validation against experimentally measured intracellular fluxes.ResultsWe present a general optimization strategy for inferring intracellular metabolic flux distributions from transcriptomic data coupled with genome-scale metabolic reconstructions. It consists of two different template models called DC (determined carbon source model) and AC (all possible carbon sources model) and two different new methods called E-Flux2 (E-Flux method combined with minimization of l2 norm) and SPOT (Simplified Pearson cOrrelation with Transcriptomic data), which can be chosen and combined depending on the availability of knowledge on carbon source or objective function. This enables us to simulate a broad range of experimental conditions. We examined E. coli and S. cerevisiae as representative prokaryotic and eukaryotic microorganisms respectively. The predictive accuracy of our algorithm was validated by calculating the uncentered Pearson correlation between predicted fluxes and measured fluxes. To this end, we compiled 20 experimental conditions (11 in E. coli and 9 in S. cerevisiae), of transcriptome measurements coupled with corresponding central carbon metabolism intracellular flux measurements determined by 13C metabolic flux analysis (13C-MFA), which is the largest dataset assembled to date for the purpose of validating inference methods for predicting intracellular fluxes. In both organisms, our method achieves an average correlation coefficient ranging from 0.59 to 0.87, outperforming a representative sample of competing methods. Easy-to-use implementations of E-Flux2 and SPOT are available as part of the open-source package MOST (http://most.ccib.rutgers.edu/).ConclusionOur method represents a significant advance over existing methods for inferring intracellular metabolic flux from transcriptomic data. It not only achieves higher accuracy, but it also combines into a single method a number of other desirable characteristics including applicability to a wide range of experimental conditions, production of a unique solution, fast running time, and the availability of a user-friendly implementation.

Investigation of useful carbon tracers for 13C-metabolic flux analysis of Escherichia coli by considering five experimentally determined flux distributions

The 13C-MFA experiments require an optimal design since the precision or confidence intervals of the estimated flux levels depends on factors such as the composition of 13C-labeled carbon sources, as well as the metabolic flux distribution of interest. In this study, useful compositions of 13C-labeled glucose for 13C-metabolic flux analysis (13C-MFA) of Escherichia coli are investigated using a computer simulation of the stable isotope labeling experiment. Following the generation of artificial mass spectra datasets of amino acid fragments using five literature-reported flux distributions of E. coli, the best fitted flux distribution and the 95% confidence interval were estimated by the 13C-MFA procedure. A comparison of the precision scores showed that [1, 2-13C]glucose and a mixture of [1-13C] and [U-13C]glucose at 8:2 are one of the best carbon sources for a precise estimation of flux levels of the pentose phosphate pathway, glycolysis and the TCA cycle. Although the precision scores of the anaplerotic and glyoxylate pathway reactions were affected by both the carbon source and flux distribution, it was also shown that the mixture of non-labeled, [1-13C], and [U-13C]glucose at 4:1:5 was specifically effective for the flux estimation of the glyoxylate pathway reaction. These findings were confirmed by wet 13C-MFA experiments.

Optimal tracers for parallel labeling experiments and 13C metabolic flux analysis: A new precision and synergy scoring system

13C-Metabolic flux analysis (13C-MFA) is a widely used approach in metabolic engineering for quantifying intracellular metabolic fluxes. The precision of fluxes determined by 13C-MFA depends largely on the choice of isotopic tracers and the specific set of labeling measurements. A recent advance in the field is the use of parallel labeling experiments for improved flux precision and accuracy. However, as of today, no systemic methods exist for identifying optimal tracers for parallel labeling experiments. In this contribution, we have addressed this problem by introducing a new scoring system and evaluating thousands of different isotopic tracer schemes. Based on this extensive analysis we have identified optimal tracers for 13C-MFA. The best single tracers were doubly 13C-labeled glucose tracers, including [1,6-13C]glucose, [5,6-13C]glucose and [1,2-13C]glucose, which consistently produced the highest flux precision independent of the metabolic flux map (here, 100 random flux maps were evaluated). Moreover, we demonstrate that pure glucose tracers perform better overall than mixtures of glucose tracers. For parallel labeling experiments the optimal isotopic tracers were [1,6-13C]glucose and [1,2-13C]glucose. Combined analysis of [1,6-13C]glucose and [1,2-13C]glucose labeling data improved the flux precision score by nearly 20-fold compared to widely use tracer mixture 80% [1-13C]glucose +20% [U-13C]glucose.

Evidence for transketolase-like TKTL1 flux in CHO cells based on parallel labeling experiments and 13C-metabolic flux analysis

The pentose phosphate pathway (PPP) is a fundamental component of cellular metabolism. It provides precursors for the biosynthesis of nucleotides and contributes to the production of reducing power in the form of NADPH. It has been hypothesized that mammalian cells may contain a hidden reaction in PPP catalyzed by transketolase-like protein 1 (TKTL1) that is closely related to the classical transketolase enzyme; however, until now there has been no direct experimental evidence for this reaction. In this work, we have applied state-of-the-art techniques in 13C metabolic flux analysis (13C-MFA) based on parallel labeling experiments and integrated flux fitting to estimate the TKTL1 flux in CHO cells. We identified a set of three parallel labeling experiments with [1-13C]glucose+[4,5,6-13C]glucose, [2-13C]glucose+[4,5,6-13C]glucose, and [3-13C]glucose+[4,5,6-13C]glucose and developed a new method to measure 13C-labeling of fructose 6-phosphate by GC-MS that allows intuitive interpretation of mass isotopomer distributions to determine key fluxes in the model, including glycolysis, oxidative PPP, non-oxidative PPP, and the TKTL1 flux. Using these tracers we detected a significant TKTL1 flux in CHO cells at the stationary phase. The flux results suggest that the main function of oxidative PPP in CHO cells at the stationary phase is to fuel the TKTL1 reaction. Overall, this study demonstrates for the first time that carbon atoms can be lost in the PPP, by means other than the oxidative PPP, and that this loss of carbon atoms is consistent with the hypothesized TKTL1 reaction in mammalian cells.