13C-Labeled Gluconate Tracing as a Direct and Accurate Method for Determining the Pentose Phosphate Pathway Split Ratio in Penicillium chrysogenum

In this study we developed a new method for accurately determining the pentose phosphate pathway (PPP) split ratio, an important metabolic parameter in the primary metabolism of a cell. This method is based on simultaneous feeding of unlabeled glucose and trace amounts of [U-¹³C]gluconate, followed by measurement of the mass isotopomers of the intracellular metabolites surrounding the 6-phosphogluconate node. The gluconate tracer method was used with a penicillin G-producing chemostat culture of the filamentous fungus Penicillium chrysogenum. For comparison, a ¹³C-labeling-based metabolic flux analysis (MFA) was performed for glycolysis and the PPP of P. chrysogenum. For the first time mass isotopomer measurements of ¹³C-labeled primary metabolites are reported for P. chrysogenum and used for a ¹³C-based MFA. Estimation of the PPP split ratio of P. chrysogenum at a growth rate of 0.02 h⁻¹ yielded comparable values for the gluconate tracer method and the ¹³C-based MFA method, 51.8% and 51.1%, respectively. A sensitivity analysis of the estimated PPP split ratios showed that the 95% confidence interval was almost threefold smaller for the gluconate tracer method than for the ¹³C-based MFA method (40.0 to 63.5% and 46.0 to 56.5%, respectively). From these results we concluded that the gluconate tracer method permits accurate determination of the PPP split ratio but provides no information about the remaining cellular metabolism, while the ¹³C-based MFA method permits estimation of multiple fluxes but provides a less accurate estimate of the PPP split ratio.     

Isotopic non-stationary 13C gluconate tracer method for accurate determination of the pentose phosphate pathway split-ratio in Penicillium chrysogenum

Current (13)C labeling experiments for metabolic flux analysis (MFA) are mostly limited by either the requirement of isotopic steady state or the extremely high computational effort due to the size and complexity of large metabolic networks. The presented novel approach circumvents these limitations by applying the isotopic non-stationary approach to a local metabolic network. The procedure is demonstrated in a study of the pentose phosphate pathway (PPP) split-ratio of Penicillium chrysogenum in a penicillin-G producing chemostat-culture grown aerobically at a dilution rate of 0.06h(-1) on glucose, using a tracer amount of uniformly labeled [U-(13)C(6)] gluconate. The rate of labeling inflow can be controlled by using different cell densities and/or different fractions of the labeled tracer in the feed. Due to the simplicity of the local metabolic network structure around the 6-phosphogluconate (6pg) node, only three metabolites need to be measured for the pool size and isotopomer distribution. Furthermore, the mathematical modeling of isotopomer distributions for the flux estimation has been reduced from large scale differential equations to algebraic equations. Under the studied cultivation condition, the estimated split-ratio (41.2+/-0.6%) using the novel approach, shows statistically no difference with the split-ratio obtained from the originally proposed isotopic stationary gluconate tracing method.     

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.     

Insights into metabolic efficiency from flux analysis

The efficiency of carbon and energy flows throughout metabolism defines the potential for growth and reproductive success of plants. Understanding the basis for metabolic efficiency requires relevant definitions of efficiency as well as measurements of biochemical functions through metabolism. Here insights into the basis of efficiency provided by (13)C-based metabolic flux analysis (MFA) as well as the uses and limitations of efficiency in predictive flux balance analysis (FBA) are highlighted. (13)C-MFA studies have revealed unusual features of central metabolism in developing green seeds for the efficient use of light to conserve carbon and identified metabolic inefficiencies in plant metabolism due to dissipation of ATP by substrate cycling. Constraints-based FBA has used efficiency to guide the prediction of the growth and actual internal flux distribution of plant systems. Comparisons in a few cases have been made between flux maps measured by (13)C-based MFA and those predicted by FBA assuming one or more maximal efficiency parameters. These studies suggest that developing plant seeds and photoautotrophic microorganisms may indeed have patterns of metabolic flux that maximize efficiency. MFA and FBA are synergistic toolsets for uncovering and explaining the metabolic basis of efficiencies and inefficiencies in plant systems.     

Cytosolic NADPH metabolism in penicillin-G producing and non-producing chemostat cultures of Penicillium chrysogenum

This study addresses the relation between NADPH supply and penicillin synthesis, by comparing the flux through the oxidative branch of the pentose phosphate pathway (PPP; the main source of cytosolic NADPH) in penicillin-G producing and non-producing chemostat cultures of Penicillium chrysogenum. The fluxes through the oxidative part of the PPP were determined using the recently introduced gluconate-tracer method. Significantly higher oxidative PPP fluxes were observed in penicillin-G producing chemostat cultures, indicating that penicillin production puts a major burden on the supply of cytosolic NADPH. To our knowledge this is the first time direct experimental proof is presented for the causal relationship between penicillin production and NADPH supply. Additional insight in the metabolism of P. chrysogenum was obtained by comparing the PPP fluxes from the gluconate-tracer experiment to oxidative PPP fluxes derived via metabolic flux analysis, using different assumptions for the stoichiometry of NADPH consumption and production.     

Parallel labeling experiments with [U-(13)C]glucose validate E. coli metabolic network model for (13)C metabolic flux analysis

(13)C-metabolic flux analysis (MFA) is a widely used method for measuring intracellular metabolic fluxes in living cells. (13)C MFA relies on several key assumptions: (1) the assumed metabolic network model is complete, in that it accounts for all significant enzymatic and transport reactions; (2) (13)C-labeling measurements are accurate and precise; and (3) enzymes and transporters do not discriminate between (12)C- and (13)C-labeled metabolites. In this study, we tested these inherent assumptions of (13)C MFA for wild-type E. coli by parallel labeling experiments with [U-(13)C]glucose as tracer. Cells were grown in six parallel cultures in custom-constructed mini-bioreactors, starting from the same inoculum, on medium containing different mixtures of natural glucose and fully labeled [U-(13)C]glucose, ranging from 0% to 100% [U-(13)C]glucose. Macroscopic growth characteristics of E. coli showed no observable kinetic isotope effect. The cells grew equally well on natural glucose, 100% [U-(13)C]glucose, and mixtures thereof. (13)C MFA was then used to determine intracellular metabolic fluxes for several metabolic network models: an initial network model from literature; and extended network models that accounted for potential dilution effects of isotopic labeling. The initial network model did not give statistically acceptable fits and produced inconsistent flux results for the parallel labeling experiments. In contrast, an extended network model that accounted for dilution of intracellular CO(2) by exchange with extracellular CO(2) produced statistically acceptable fits, and the estimated metabolic fluxes were consistent for the parallel cultures. This study illustrates the importance of model validation for (13)C MFA. We show that an incomplete network model can produce statistically unacceptable fits, as determined by a chi-square test for goodness-of-fit, and return biased metabolic fluxes. The validated metabolic network model for E. coli from this study can be used in future investigations for unbiased metabolic flux measurements.     

Optimization of 13C isotopic tracers for metabolic flux analysis in mammalian cells

Mammalian cells consume and metabolize various substrates from their surroundings for energy generation and biomass synthesis. Glucose and glutamine, in particular, are the primary carbon sources for proliferating cancer cells. While this combination of substrates generates static labeling patterns for use in (13)C metabolic flux analysis (MFA), the inability of single tracers to effectively label all pathways poses an obstacle for comprehensive flux determination within a given experiment. To address this issue we applied a genetic algorithm to optimize mixtures of (13)C-labeled glucose and glutamine for use in MFA. We identified tracer combinations that minimized confidence intervals in an experimentally determined flux network describing central carbon metabolism in tumor cells. Additional simulations were used to determine the robustness of the [1,2-(13)C(2)]glucose/[U-(13)C(5)]glutamine tracer combination with respect to perturbations in the network. Finally, we experimentally validated the improved performance of this tracer set relative to glucose tracers alone in a cancer cell line. This versatile method allows researchers to determine the optimal tracer combination to use for a specific metabolic network, and our findings applied to cancer cells significantly enhance the ability of MFA experiments to precisely quantify fluxes in higher organisms.     

13C metabolic flux analysis for larger scale cultivation using gas chromatography-combustion-isotope ratio mass spectrometry

¹³C-based metabolic flux analysis (¹³CMFA) is limited to smaller scale experiments due to very high costs of labeled substrates. We measured ¹³C enrichment in proteinogenic amino acid hydrolyzates using gas chromatography-combustion-isotope ratio mass spectrometry (GC-C-IRMS) from a series of parallel batch cultivations of Corynebacterium glutamicum utilizing mixtures of natural glucose and [1-¹³C] glucose, containing 0%, 0.5%, 1%, 2%, and 10% [1-¹³C] glucose. Decreasing the [1-¹³C] glucose content, kinetic isotope effects played an increasing role but could be corrected. From the corrected ¹³C enrichments in vivo fluxes in the central metabolism were determined by numerical optimization. The obtained flux distribution was very similar to those obtained from parallel labeling experiments using conventional high labeling GC-MS method and to published results. The GC-C-IRMS-based method involving low labeling degree of expensive tracer substrate, e.g. 1%, is well suited for larger laboratory and industrial pilot scale fermentations.     

Modeling and experimental design for metabolic flux analysis of lysine-producing Corynebacteria by mass spectrometry

Experimental design of (13)C-tracer studies for metabolic flux analysis with mass spectrometric determination of labeling patterns was performed for the central metabolism of Corynebacterium glutamicum comprising various flux scenarios. Ratio measurement of mass isotopomer pools of Corynebacterium products lysine, alanine, and trehalose is sufficient to quantify the flux partitioning ratios (i) between glycolysis and pentose phosphate pathways (Phi(PPP)), (ii) between the split pathways in the lysine biosynthesis (Phi(DH)), (iii) at the pyruvate node (Phi(PC)), and reversibilities of (iv) glucose 6-phosphate isomerase (zeta(PGI)), (v) at the pyruvate node (zeta(PC/PEPCK)), and (vi) of transaldolase and transketolases in the PPP. Weighted sensitivities for flux parameters were derived from partial derivatives to quantitatively evaluate experimental approaches and predict precision for estimated flux parameters. Deviation of intensity ratios from ideal values of 1 was used as weighting function. Weighted flux sensitivities can be used to identify optimal type and degree of tracer labeling or potential intensity ratios to be measured. Experimental design for lysine-producing strain C. glutamicum MH 20-22B (Marx et al., Biotechnol. Bioeng. 49, 111-129, 1996) and various potential mutants with different alterations in the flux pattern showed that specific tracer labelings are optimal to quantify a certain flux parameter uninfluenced by the overall flux situation. Identified substrates of choice are [1-(13)C]glucose for the estimation of Phi(PPP) and zeta(PGI) and a 1 : 1 mixture of [U-(12)C/U-(13)C]glucose for the determination of zeta(PC/PEPCK). Phi(PC) can be quantified by feeding [4-(13)C]glucose or [U-(12)C/U-(13)C]glucose (1 : 1), whereas Phi(DH) is accessible via [4-(13)C]glucose. The sensitivity for the quantification of a certain flux parameter can be influenced by superposition through other flux parameters in the network, but substrate and measured mass isotopomers of choice remain the same. In special cases, reduced labeling degree of the tracer substrate can increase the precision of flux analysis. Enhanced precision and flux information can be achieved via multiply labeled substrates. The presented approach can be applied for effective experimental design of (13)C tracer studies for metabolic flux analysis. Intensity ratios of other products such as glutamate, valine, phenylalanine, and riboflavin also sensitively reflect flux parameters, which underlines the great potential of mass spectrometry for flux analysis.     

Tandem mass spectrometry: a novel approach for metabolic flux analysis

The goal of metabolic flux analysis (MFA) is the accurate estimation of intracellular fluxes in metabolic networks. Here, we introduce a new method for MFA based on tandem mass spectrometry (MS) and stable-isotope tracer experiments. We demonstrate that tandem MS provides more labeling information than can be obtained from traditional full scan MS analysis and allows estimation of fluxes with better precision. We present a modeling framework that takes full advantage of the additional labeling information obtained from tandem MS for MFA. We show that tandem MS data can be computed for any network model, any compound and any tandem MS fragmentation using linear mapping of isotopomers. The inherent advantages of tandem MS were illustrated in two network models using simulated and literature data. Application of tandem MS increased the observability of the models and improved the precision of estimated fluxes by 2- to 5-fold compared to traditional MS analysis.     

Comparative 13C metabolic flux analysis of pyruvate dehydrogenase complex-deficient, L-valine-producing Corynebacterium glutamicum

L-Valine can be formed successfully using C. glutamicum strains missing an active pyruvate dehydrogenase enzyme complex (PDHC). Wild-type C. glutamicum and four PDHC-deficient strains were compared by (13)C metabolic flux analysis, especially focusing on the split ratio between glycolysis and the pentose phosphate pathway (PPP). Compared to the wild type, showing a carbon flux of 69% ± 14% through the PPP, a strong increase in the PPP flux was observed in PDHC-deficient strains with a maximum of 113% ± 22%. The shift in the split ratio can be explained by an increased demand of NADPH for l-valine formation. In accordance, the introduction of the Escherichia coli transhydrogenase PntAB, catalyzing the reversible conversion of NADH to NADPH, into an L-valine-producing C. glutamicum strain caused the PPP flux to decrease to 57% ± 6%, which is below the wild-type split ratio. Hence, transhydrogenase activity offers an alternative perspective for sufficient NADPH supply, which is relevant for most amino acid production systems. Moreover, as demonstrated for L-valine, this bypass leads to a significant increase of product yield due to a concurrent reduction in carbon dioxide formation via the PPP.     

Resolving the TCA cycle and pentose-phosphate pathway of Clostridium acetobutylicum ATCC 824: Isotopomer analysis, in vitro activities and expression analysis

Solventogenic clostridia are an important class of microorganisms that can produce various biofuels. One of the bottlenecks in engineering clostridia stems from the fact that central metabolic pathways remain poorly understood. Here, we utilized the power of (13) C-based isotopomer analysis to re-examine central metabolic pathways of Clostridium acetobutylicum ATCC 824. We demonstrate using [1,2-(13) C]glucose, MS analysis of intracellular metabolites, and enzymatic assays that C. acetobutylicum has a split TCA cycle where only Re-citrate synthase (CS) contributes to the production of α-ketoglutarate via citrate. Furthermore, we show that there is no carbon exchange between α-ketoglutarate and fumarate and that the oxidative pentose-phosphate pathway (oxPPP) is inactive. Dynamic gene expression analysis of the putative Re-CS gene (CAC0970), its operon, and all glycolysis, pentose-phosphate pathway, and TCA cycle genes identify genes and their degree of involvement in these core pathways that support the powerful primary metabolism of this industrial organism.     

Measurement of intracellular metabolites of primary metabolism and adenine nucleotides in chemostat cultivated Penicillium chrysogenum

An experimental platform has been developed for rapid sampling and quenching of chemostat cultivated Penicillium chrysogenum broth for metabolome analysis in highly dynamic experiments, aimed at the elucidation of the in vivo kinetic properties of metabolism. The sampling and quenching protocol available from Saccharomyces cerevisiae had to be modified for Penicillium chrysogenum mainly because of its filamentous character. Intracellular metabolites of glycolysis, TCA cycle, and adenine nucleotides were measured with isotope dilution mass spectrometry (IDMS) using a U-(13)C-labeled metabolite mix produced from yeast cells as internal standard. By addition of the U-(13)C internal standard mix prior to the metabolite extraction procedure, partial degradation of metabolites as well as non-linearity and drift of the LC-MS/MS could be successfully compensated for. It was found that there is a serious matrix effect on metabolite extraction between different organisms, which is however completely corrected for by the IDMS approach. Intracellular metabolites could be analyzed with standard deviations of around 5%. A comparison of the metabolite levels between Saccharomyces cerevisiae and Penicillium chrysogenum showed both significant similarities and large differences, which seem to be related to the presence of the penicillin pathway.     

Improving metabolic flux estimation via evolutionary optimization for convex solution space

MOTIVATION: Flux estimation by using (13) C-labeling pattern information of metabolites is currently the only method that can give accurate, detailed quantification of all intracellular fluxes in the central metabolism of a microorganism. In essence, it corresponds to a constrained optimization problem which minimizes a weighted distance between measured and simulated results. Characteristics, such as existence of multiple local minima, non-linear and non-differentiable make this problem a special difficulty. RESULTS: In the present work, we propose an evolutionary-based global optimization algorithm taking advantage of the convex feature of the problem's solution space. Based on the characteristics of convex spaces, specialized initial population and evolutionary operators are designed to solve (13)C-based metabolic flux estimation problem robustly and efficiently. The algorithm was applied to estimate the central metabolic fluxes in Escherichia coli and compared with conventional optimization technique. Experimental results illustrated that our algorithm is capable of achieving fast convergence to good near-optima and maintaining the robust nature of evolutionary algorithms at the same time. AVAILABILITY: Available from the authors upon request.     

Achiral-chiral LC/LC-MS/MS coupling for determination of chiral discrimination effects in phenprocoumon metabolism

Many physiological processes show a high degree of stereoselectivity, including the metabolism of xenobiotics as catalyzed by cytochrome P450 enzymes. An analysis of these chiral discrimination effects in drug metabolism is essential for an in-depth understanding of metabolic pathways that differ between enantiomers of a given chiral drug or metabolite thereof. Achiral chromatographic separation and structural identification followed by chiral analysis of metabolites from blood specimens usually requires a time-consuming multistage analytical technique. In an effort to optimize such a complicated analytical scheme, a novel two-dimensional online achiral-chiral liquid chromatography-tandem mass spectrometry (LC/LC-MS/MS) coupling method was developed by using a peak parking technique in combination with a makeup flow system. Metabolites were separated in the first dimension using a C18 reversed-phase system. A makeup eluent of water/methanol (95/5) was split into the flow before storing the metabolites separately on chiral cartridges. Subsequently, the metabolite enantiomers were eluted backward onto the analytical chiral column and separated, and the ratio of enantiomers was determined. The method was successfully validated with respect to limit of detection, linearity, intra- and interday accuracy, and precision. In the course of a human volunteer study investigating the influence of CYP (cytochrome) 2C9 genetic polymorphism on phenprocoumon (PPC) metabolism, we used this new two-dimensional online analytical technique for the analysis of PPC metabolites in plasma. The enantiomeric forms of 4'-, 6-, and 7-hydroxy-PPC metabolites as well as two novel metabolites were identified, and the ratio of the enantiomers was calculated. We found that the enantiomeric ratio for the different metabolites in the plasma sample of each measured individual differs markedly from a nearly 100% chiral discrimination for the two new putative metabolites. This new analytical coupling method possesses general utility in the analysis of chiral discrimination effects, particularly as it relates to pharmacokinetics and dynamics, a scientific field that is rapidly becoming an area of concern and interest.     

Attenuation of Slc27a5 gene expression followed by LC-MS measurement of bile acid reconjugation using metabolomics and a stable isotope tracer strategy

The purpose of this study was to evaluate the use of high resolution LC-MS together with metabolomics and D(4)-cholic acid (D(4)-CA) as a metabolic tracer to measure the metabolism and reconjugation of bile acids (BAs) in vitro and in vivo. Metabolic tracers are very important because they allow for the direct detection (substrate-to-product) of small and significant biological perturbations that may not be apparent when monitoring "static" endogenous levels of particular metabolites. Slc27a5, also known as fatty acid transport protein 5 (FATP5), is the hepatic BA-CoA ligase involved in reconjugating BAs during enterohepatic BA recycling. Using Slc27a5-cKD mice, silencing of ～90% gene expression was achieved followed by reduction in the reconjugation of D(4)-CA to D(4)-taurocholic acid (D(4)-TCA), as well as other conjugated BA metabolites in plasma (p = 0.0031). The method described allowed a rapid measure of many D(4) and endogenous BA. Analysis of bile resulted in the detection of 39 BA metabolites from a 13 min analytical run. Finally, the utilization of a novel high resolution mass spectrometry method in combination with metabolomics and a stable isotope metabolic tracer allowed for the detection of targeted and untargeted BAs following silencing of the Slc27a5 gene in primary hepatocytes and in mice.     

Evaluation of isotope discrimination in C-based metabolic flux analysis

In a ¹³C experiment for metabolic flux analysis (¹³C MFA), we examined isotope discrimination by measuring the labeling of glucose, amino acids, and hexose monophosphates via mass spectrometry. When Escherichia coli grew in a mix of 20% fully labeled and 80% naturally labeled glucose medium, the cell metabolism favored light isotopes and the measured isotopic ratios (δ¹³C) were in the range of −35 to −92. Glucose transporters might play an important role in such isotopic fractionation. Flux analysis showed that both isotopic discrimination and isotopic impurities in labeled substrates could affect the solution of ¹³C MFA.     

Thermodynamics-based metabolic flux analysis

A new form of metabolic flux analysis (MFA) called thermodynamics-based metabolic flux analysis (TMFA) is introduced with the capability of generating thermodynamically feasible flux and metabolite activity profiles on a genome scale. TMFA involves the use of a set of linear thermodynamic constraints in addition to the mass balance constraints typically used in MFA. TMFA produces flux distributions that do not contain any thermodynamically infeasible reactions or pathways, and it provides information about the free energy change of reactions and the range of metabolite activities in addition to reaction fluxes. TMFA is applied to study the thermodynamically feasible ranges for the fluxes and the Gibbs free energy change, Delta(r)G', of the reactions and the activities of the metabolites in the genome-scale metabolic model of Escherichia coli developed by Palsson and co-workers. In the TMFA of the genome scale model, the metabolite activities and reaction Delta(r)G' are able to achieve a wide range of values at optimal growth. The reaction dihydroorotase is identified as a possible thermodynamic bottleneck in E. coli metabolism with a Delta(r)G' constrained close to zero while numerous reactions are identified throughout metabolism for which Delta(r)G' is always highly negative regardless of metabolite concentrations. As it has been proposed previously, these reactions with exclusively negative Delta(r)G' might be candidates for cell regulation, and we find that a significant number of these reactions appear to be the first steps in the linear portion of numerous biosynthesis pathways. The thermodynamically feasible ranges for the concentration ratios ATP/ADP, NAD(P)/NAD(P)H, and H(extracellular)(+)/H(intracellular)(+) are also determined and found to encompass the values observed experimentally in every case. Further, we find that the NAD/NADH and NADP/NADPH ratios maintained in the cell are close to the minimum feasible ratio and maximum feasible ratio, respectively.