Metabolic flux analysis for a ppc mutant Escherichia coli based on 13C-labelling experiments together with enzyme activity assays and intracellular metabolite measurements

The physiology and central metabolism of a ppc mutant Escherichia coli were investigated based on the metabolic flux distribution obtained by (13)C-labelling experiments using gas chromatography-mass spectrometry (GC-MS) and 2-dimensional nuclear magnetic resonance (2D NMR) strategies together with enzyme activity assays and intracellular metabolite concentration measurements. Compared to the wild type, its ppc mutant excreted little acetate and produced less carbon dioxide at the expense of a slower growth rate and a lower glucose uptake rate. Consequently, an improvement of the biomass yield on glucose was observed in the ppc mutant. Enzyme activity measurements revealed that isocitrate lyase activity increased by more than 3-fold in the ppc mutant. Some TCA cycle enzymes such as citrate synthase, aconitase and malate dehydrogenase were also upregulated, but enzymes of glycolysis and the pentose phosphate pathway were downregulated. The intracellular intermediates in the glycolysis and the pentose phosphate pathway, therefore, accumulated, while acetyl coenzyme A and oxaloacetate concentrations decreased in the ppc mutant. The intracellular metabolic flux analysis uncovered that deletion of ppc resulted in the appearance of the glyoxylate shunt, with 18.9% of the carbon flux being channeled via the glyoxylate shunt. However, the flux of the pentose phosphate pathway significantly decreased in the ppc mutant.     

Selective 13C-labelling of cyclosporin A.

Cyclosporin A is biosynthetically labelled with 13C by growing an overproducing strain of Tolypocladium inflatum on minimal media containing either [1-13C]-, [2-13C]-, [3-13C]- or [6-13C]glucose as the only carbon source. NMR analysis of the 13C-labelled peptide showed a labelling pattern in which 13C occurs at specific sites. These can be predicted by consideration of the relevant biosynthetic pathways. Quantitation of the site-specific enrichments revealed that the 13C-label incorporation is efficient and selective. Metabolic fluxes through alternative pathways can also be estimated from these results. Isotopically labelled peptides will be a very useful tool for the study of molecular interactions with their receptors.     

Possible pitfalls of flux calculations based on (13)C-labeling

Metabolic engineers have enthusiastically adopted the (13)C-labeling technique as a powerful tool for elucidating fluxes in metabolic networks. This tracer technique makes it possible to determine fluxes that are unobservable using only metabolite balances and allows the elimination of doubtful cofactor balances that are indispensable in flux analysis based on metabolite balancing alone. The (13)C-labeling technique, however, relies on a number of assumptions that are not free from uncertainties. Two possible errors in the models that are needed to determine the metabolic fluxes from labeling data are omitted reactions and ignored occurrence of channeling. By means of two representative examples it is shown that these modeling errors may lead to serious errors in the calculated flux distributions despite the use of labeling data. A complicating fact is that the model errors are not always easily detected as poor models may still yield good fits of experimental data. Results of (13)C-labeling experiments should therefore be interpreted with appropriate caution.     

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.     

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.     

Biosynthesis of cannabinoids. Incorporation experiments with (13)C-labeled glucoses.

The biosynthesis of cannabinoids was studied in cut sprouts of Cannabis sativa by incorporation experiments using mixtures of unlabeled glucose and [1-(13)C]glucose or [U-(13)C(6)]glucose. (13)C-labeling patterns of cannabichromenic acid and tetrahydrocannabinolic acid were analyzed by quantitative NMR spectroscopy. (13)C enrichments and coupling patterns show that the C(10)-terpenoid moiety is biosynthesized entirely or predominantly (> 98%) via the recently discovered deoxyxylulose phosphate pathway. The phenolic moiety is generated by a polyketide-type reaction sequence. The data support geranyl diphosphate and the polyketide, olivetolic acid, as specific intermediates in the biosynthesis of cannabinoids.     

Metabolic flux analysis of a glycerol-overproducing Saccharomyces cerevisiae strain based on GC-MS, LC-MS and NMR-derived C-labelling data

This study focuses on unravelling the carbon and redox metabolism of a previously developed glycerol-overproducing Saccharomyces cerevisiae strain with deletions in the structural genes encoding triosephosphate isomerase (TPI1), the external mitochondrial NADH dehydrogenases (NDE1 and NDE2) and the respiratory chain-linked glycerol-3-phosphate dehydrogenase (GUT2). Two methods were used for analysis of metabolic fluxes: metabolite balancing and (13)C-labelling-based metabolic flux analysis. The isotopic enrichment of intracellular primary metabolites was measured both directly (liquid chromatography-MS) and indirectly through proteinogenic amino acids (nuclear magnetic resonance and gas chromatography-MS). Because flux sensitivity around several important metabolic nodes proved to be dependent on the applied technique, the combination of the three (13)C quantification techniques generated the most accurate overall flux pattern. When combined, the measured conversion rates and (13)C-labelling data provided evidence that a combination of assimilatory metabolism and pentose phosphate pathway activity diverted some of the carbon away from glycerol formation. Metabolite balancing indicated that this results in excess cytosolic NADH, suggesting the presence of a cytosolic NADH sink in addition to those that were deleted. The exchange flux of four-carbon dicarboxylic acids across the mitochondrial membrane, as measured by the (13)C-labelling data, supports a possible role of a malate/aspartate or malate/oxaloacetate redox shuttle in the transfer of these redox equivalents from the cytosol to the mitochondrial matrix.     

13C metabolic flux analysis: optimal design of isotopic labeling experiments

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Highlights► Design of isotopic labeling experiments determines the precision of flux estimates. ► New approaches were developed to select optimal isotopic tracers and measurements. ► Tandem mass spectrometry provides more informative data for ¹³C flux analysis. ► Parallel labeling experiments can improve the quality of flux estimates. ► New methods are needed for optimal design of parallel labeling experiments.     

Parallel labeling experiments for pathway elucidation and 13C metabolic flux analysis

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Effect of the global redox sensing/regulation networks on Escherichia coli and metabolic flux distribution based on C-13 labeling experiments

Escherichia coli has several elaborate sensing mechanisms for response to the availability of oxygen and the presence of other electron acceptors. Among them, the one component Fnr protein and the two-component Arc system coordinate the adaptive responses to oxygen availability. To systematically investigate the contribution of Arc- and Fnr-dependent regulation in catabolism, glucose-limited chemostat cultures were conducted on wild-type E. coli, an arcA mutant, an fnr mutant, and an arcAfnr double mutant strains under a well-defined semi-aerobic condition. The metabolic flux distributions of the cultures of these strains were estimated based on C-13 labeling experiments. It was shown that the oxidative pentose phosphate (PP) pathway was functioning at low level under semi-aerobic condition. The fluxes through pyruvate dehydrogenase (PDH) and tricarboxylic acid (TCA) cycle were found to be lower in the arcA mutant and the arcAfnr double mutant strains than that in the wild-type strain, although the expression of the genes involved in these pathways have been proved to be derepressed in the mutant strains ([Shalel-Levanon, S., San, K.Y., Bennett, G.N., 2005a. Effect of ArcA and FNR on the expression of genes related to the oxygen regulation and the glycolysis pathway in Escherichia coli under microaerobic growth conditions. Biotechnol. Bioeng. 92, 147-159; Shalel-Levanon, S., San, K.Y., Bennett, G.N., 2005c. Effect of oxygen, and ArcA and FNR regulators on the expression of genes related to the electron transfer chain and the TCA cycle in Escherichia coli. Metab. Eng. 7, 364-374]). The significantly higher lactate production in the arcAfnr double mutant strain was shown to be an indirect effect caused by the reduced pyruvate formate-lyase (PFL) and PDH fluxes as well as the intracellular redox state.     

Rational design of 13C-labeling experiments for metabolic flux analysis in mammalian cells

ABSTRACT: BACKGROUND: 13C-Metabolic flux analysis (13C-MFA) is a standard technique to probe cellular metabolism and elucidate in vivo metabolic fluxes. 13C-Tracer selection is an important step in conducting 13C-MFA, however, current methods are restricted to trial-and-error approaches, which commonly focus on an arbitrary subset of the tracer design space. To systematically probe the complete tracer design space, especially for complex systems such as mammalian cells, there is a pressing need for new rational approaches to identify optimal tracers. RESULTS: Recently, we introduced a new framework for optimal 13C-tracer design based on elementary metabolite units (EMU) decomposition, in which a measured metabolite is decomposed into a linear combination of so-called EMU basis vectors. In this contribution, we applied the EMU method to a realistic network model of mammalian metabolism with lactate as the measured metabolite. The method was used to select optimal tracers for the two free fluxes in the system, the oxidative pentose phosphate pathway (oxPPP) flux and anaplerosis by pyruvate carboxylase (PC). Our approach was based on sensitivity analysis of EMU basis vector coefficients with respect to free fluxes. Through efficient grouping of coefficient sensitivities, simple tracer selection rules were derived for high-resolution quantification of the fluxes in the mammalian network model. The approach resulted in a significant reduction of the number of possible tracers and the feasible tracers were evaluated using numerical simulations. Two optimal, novel tracers were identified that have not been previously considered for 13C-MFA of mammalian cells, specifically [2,3,4,5,6-13C]glucose for elucidating oxPPP flux and [3,4-13C]glucose for elucidating PC flux. We demonstrate that 13C-glutamine tracers perform poorly in this system in comparison to the optimal glucose tracers. CONCLUSIONS: In this work, we have demonstrated that optimal tracer design does not need to be a pure simulation-based trial-and-error process; rather, rational insights into tracer design can be gained through the application of the EMU basis vector methodology. Using this approach, rational labeling rules can be established a priori to guide the selection of optimal 13C-tracers for high-resolution flux elucidation in complex metabolic network models.     

Integrated 13C-metabolic flux analysis of 14 parallel labeling experiments in Escherichia coli

The use of parallel labeling experiments for ¹³C metabolic flux analysis (¹³C-MFA) has emerged in recent years as the new gold standard in fluxomics. The methodology has been termed COMPLETE-MFA, short for complementary parallel labeling experiments technique for metabolic flux analysis. In this contribution, we have tested the limits of COMPLETE-MFA by demonstrating integrated analysis of 14 parallel labeling experiments with Escherichia coli. An effort on such a massive scale has never been attempted before. In addition to several widely used isotopic tracers such as [1,2-¹³C]glucose and mixtures of [1-¹³C]glucose and [U-¹³C]glucose, four novel tracers were applied in this study: [2,3-¹³C]glucose, [4,5,6-¹³C]glucose, [2,3,4,5,6-¹³C]glucose and a mixture of [1-¹³C]glucose and [4,5,6-¹³C]glucose. This allowed us for the first time to compare the performance of a large number of isotopic tracers. Overall, there was no single best tracer for the entire E. coli metabolic network model. Tracers that produced well-resolved fluxes in the upper part of metabolism (glycolysis and pentose phosphate pathways) showed poor performance for fluxes in the lower part of metabolism (TCA cycle and anaplerotic reactions), and vice versa. The best tracer for upper metabolism was 80% [1-¹³C]glucose+20% [U-¹³C]glucose, while [4,5,6-¹³C]glucose and [5-¹³C]glucose both produced optimal flux resolution in the lower part of metabolism. COMPLETE-MFA improved both flux precision and flux observability, i.e. more independent fluxes were resolved with smaller confidence intervals, especially exchange fluxes. Overall, this study demonstrates that COMPLETE-MFA is a powerful approach for improving flux measurements and that this methodology should be considered in future studies that require very high flux resolution.     

13C metabolic flux analysis.

Metabolic flux analysis using 13C-labeled substrates has become an important tool in metabolic engineering. It allows the detailed quantification of all intracellular fluxes in the central metabolism of a microorganism. The method has strongly evolved in recent years by the introduction of new experimental procedures, measurement techniques, and mathematical data evaluation methods. Many of these improvements require advanced skills in the application of nuclear magnetic resonance and mass spectrometry techniques on the one hand and computational and statistical experience on the other hand. This minireview summarizes these recent developments and sketches the major practical problems. An outlook to possible future developments concludes the text.     

Evaluation of isotope discrimination in (13)C-based metabolic flux analysis

This paper describes a modified noninvasive microtest electrophysiological technology (NMT) for vacuolar H⁺ flux detection. In this NMT system, the vacuole isolation procedure and buffer slope were modified, and the measuring errors from small spherical geometry were corrected. The trends in changes of vacuolar H⁺ flux (ΔH⁺ flux) after ATP or PP_i supply calculated by NMT were consistent with the activities of V-ATPase and PPase measured by traditional methods. These findings indicate that our modified NMT is an appropriate method for vacuolar H⁺ flux detection.     

Mapping photoautotrophic metabolism with isotopically nonstationary (13)C flux analysis

Understanding in vivo regulation of photoautotrophic metabolism is important for identifying strategies to improve photosynthetic efficiency or re-route carbon fluxes to desirable end products. We have developed an approach to reconstruct comprehensive flux maps of photoautotrophic metabolism by computational analysis of dynamic isotope labeling measurements and have applied it to determine metabolic pathway fluxes in the cyanobacterium Synechocystis sp. PCC6803. Comparison to a theoretically predicted flux map revealed inefficiencies in photosynthesis due to oxidative pentose phosphate pathway and malic enzyme activity, despite negligible photorespiration. This approach has potential to fill important gaps in our understanding of how carbon and energy flows are systemically regulated in cyanobacteria, plants, and algae.     

Synergy between (13)C-metabolic flux analysis and flux balance analysis for understanding metabolic adaptation to anaerobiosis in E. coli

Genome-based Flux Balance Analysis (FBA) and steady-state isotopic-labeling-based Metabolic Flux Analysis (MFA) are complimentary approaches to predicting and measuring the operation and regulation of metabolic networks. Here, genome-derived models of Escherichia coli (E. coli) metabolism were used for FBA and 13C-MFA analyses of aerobic and anaerobic growths of wild-type E. coli (K-12 MG1655) cells. Validated MFA flux maps reveal that the fraction of maintenance ATP consumption in total ATP production is about 14% higher under anaerobic (51.1%) than aerobic conditions (37.2%). FBA revealed that an increased ATP utilization is consumed by ATP synthase to secrete protons from fermentation. The TCA cycle is shown to be incomplete in aerobically growing cells and submaximal growth is due to limited oxidative phosphorylation. An FBA was successful in predicting product secretion rates in aerobic culture if both glucose and oxygen uptake measurement were constrained, but the most-frequently predicted values of internal fluxes yielded from sampling the feasible space differ substantially from MFA-derived fluxes.     

Application of isotope labeling experiments and 13C flux analysis to enable rational pathway engineering

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A priori analysis of metabolic flux identifiability from (13)C-labeling data

The (13)C-labeling technique was introduced in the field of metabolic engineering as a tool for determining fluxes that could not be found using the 'classical' method of flux balancing. An a priori flux identifiability analysis is required in order to determine whether a (13)C-labeling experiment allows the identification of all the fluxes. In this article, we propose a method for identifiability analysis that is based on the recently introduced 'cumomer' concept. The method improves upon previous identifiability methods in that it provides a way of systematically reducing the metabolic network on the basis of structural elements that constitute a network and to use the implicit function theorem to analytically determine whether the fluxes in the reduced network are theoretically identifiable for various types of real measurement data. Application of the method to a realistic flux identification problem shows both the potential of the method in yielding new, interesting conclusions regarding the identifiability and its practical limitations that are caused by the fact that symbolic calculations grow fast with the dimension of the studied system.     

Synthesis and NMR experiments of (4,5,6-13C)-deoxymannojirimycin. A new entry to 13C-labeled glycosidase inhibitors

The synthesis of (4,5,6-13C)-deoxymannojirimycin is described. The route employed is based on Sharpless asymmetric epoxidation of (1,2,3-13C)(E)-2,4-pentadien-1-ol and uses ring-closing metathesis as a key step. The labeled compound may be easily used for protein-binding experiments using NMR spectroscopic methods.