Application of metabolic flux analysis for the identification of metabolic bottlenecks in the biosynthesis of penicillin-G

A detailed stoichiometric model was developed for growth and penicillin-G production in Penicillium chrysogenum. From an a priori metabolic flux analysis using this model it appeared that penicillin production requires significant changes in fluxes through the primary metabolic pathways. This is brought about by the biosynthesis of carbon precursors for the beta-lactan nucleus and an increased demand for NADPH, mainly for sulfate reduction. As a result, significant changes in flux partitioning occur around four principal nodes in primary metabolism. These are located at: (1) glucose-6-phosphate; (2) 3-phosphoglycerate; (3) mitochondrial pyruvate; and (4) mitochondrial isocitrate. These nodes should be regarded as potential bottlenecks for increased productivity. The flexibility of these principal nodes was investigated by experimental manipulation of the fluxes through the central metabolic pathways using a high-producing strain of P. chrysogenum. Metabolic fluxes were manipulated through growth of the cells on different substrates in carbon-limited chemostat culture. Metabolic flux analysis, based on measured input and output fluxes, was used to calculate the fluxes around the principal nodes. It was found that, for growth on glucose, ethanol, and acetate, the flux partitioning around these nodes differed significantly. However, this had hardly any effect on penicillin productivity, showing that primary carbon metabolism is not likely to contain potential bottlenecks. Further experiments were performed to manipulate the total metabolic demand for the cofactor nicotinamide adenine dinucleotide phosphate (NADPH). NADPH demand was increased stepwise by cultivating the cells on glucose or xylose as the carbon source combined with either ammonia or nitrate as the nitrogen source, which resulted in a stepwise decrease of penicillin production. This clearly shows that, in penicillin fermentation, possible limitations in primary metabolism reside in the supply/regeneration of cofactors (NADPH) rather than in the supply of carbon precursors.     

Understanding fatty acid synthesis in developing maize embryos using metabolic flux analysis

The efficiency with which developing maize embryos convert substrates into seed storage reserves was determined to be 57–71%, by incubating developing maize embryos with uniformly labeled ¹⁴C substrates and measuring their conversion to CO₂ and biomass products. To map the pattern of metabolic fluxes underlying this efficiency, maize embryos were labeled to isotopic steady state using a combination of labeled ¹³C-substrates. Intermediary metabolic fluxes were estimated by computer-aided modeling of the central metabolic network using the labeling data collected by NMR and GC-MS and the biomass composition. The resultant flux map reveals that even though 36% of the entering carbon goes through the oxidative pentose-phosphate pathway, this does not fully meet the NADPH demands for fatty acid synthesis. Metabolic flux analysis and enzyme activities highlight the importance of plastidic NADP-dependent malic enzyme, which provides one-third of the carbon and NADPH required for fatty acid synthesis in developing maize embryos.     

Metabolic flux profiling of Escherichia coli mutants in central carbon metabolism using GC-MS.

We describe here a novel methodology for rapid diagnosis of metabolic changes, which is based on probabilistic equations that relate GC-MS-derived mass distributions in proteinogenic amino acids to in vivo enzyme activities. This metabolic flux ratio analysis by GC-MS provides a comprehensive perspective on central metabolism by quantifying 14 ratios of fluxes through converging pathways and reactions from [1-13C] and [U-13C]glucose experiments. Reliability and accuracy of this method were experimentally verified by successfully capturing expected flux responses of Escherichia coli to environmental modifications and seven knockout mutations in all major pathways of central metabolism. Furthermore, several mutants exhibited additional, unexpected flux responses that provide new insights into the behavior of the metabolic network in its entirety. Most prominently, the low in vivo activity of the Entner-Doudoroff pathway in wild-type E. coli increased up to a contribution of 30% to glucose catabolism in mutants of glycolysis and TCA cycle. Moreover, glucose 6-phosphate dehydrogenase mutants catabolized glucose not exclusively via glycolysis, suggesting a yet unidentified bypass of this reaction. Although strongly affected by environmental conditions, a stable balance between anaplerotic and TCA cycle flux was maintained by all mutants in the upper part of metabolism. Overall, our results provide quantitative insight into flux changes that bring about the resilience of metabolic networks to disruption.     

Mitochondrial metabolism in developing embryos of Brassica napus

The metabolism of developing plant seeds is directed toward transforming primary assimilatory products (sugars and amino acids) into seed storage compounds. To understand the role of mitochondria in this metabolism, metabolic fluxes were determined in developing embryos of Brassica napus. After labeling with [1,2-(13)C2]glucose + [U-(13)C6]glucose, [U-(13)C3]alanine, [U-(13)C5]glutamine, [(15)N]alanine, (amino)-[(15)N]glutamine, or (amide)-[(15)N]glutamine, the resulting labeling patterns in protein amino acids and in fatty acids were analyzed by gas chromatography-mass spectrometry. Fluxes through mitochondrial metabolism were quantified using a steady state flux model. Labeling information from experiments using different labeled substrates was essential for model validation and reliable flux estimation. The resulting flux map shows that mitochondrial metabolism in these developing seeds is very different from that in either heterotrophic or autotrophic plant tissues or in most other organisms: (i) flux around the tricarboxylic acid cycle is absent and the small fluxes through oxidative reactions in the mitochondrion can generate (via oxidative phosphorylation) at most 22% of the ATP needed for biosynthesis; (ii) isocitrate dehydrogenase is reversible in vivo; (iii) about 40% of mitochondrial pyruvate is produced by malic enzyme rather than being imported from the cytosol; (iv) mitochondrial flux is largely devoted to providing precursors for cytosolic fatty acid elongation; and (v) the uptake of amino acids rather than anaplerosis via PEP carboxylase determines carbon flow into storage proteins.     

Quantification of central metabolic fluxes in the facultative methylotroph methylobacterium extorquens AM1 using 13C-label tracing and mass spectrometry

The metabolic fluxes of central carbon metabolism were measured in chemostat-grown cultures of Methylobacterium extorquens AM1 with methanol as the sole organic carbon and energy source and growth-limiting substrate. Label tracing experiments were carried out using 70% (13)C-methanol in the feed, and the steady-state mass isotopomer distributions of amino acids derived from total cell protein were measured by gas chromatography coupled to mass spectrometry. Fluxes were calculated from the isotopomer distribution data using an isotopomer balance model and evolutionary error minimization algorithm. The combination of labeled methanol with unlabeled CO(2), which enters central metabolism in two different reactions, provided the discriminatory power necessary to allow quantification of the unknown fluxes within a reasonably small confidence interval. In wild-type M. extorquens AM1, no measurable flux was detected through pyruvate dehydrogenase or malic enzyme, and very little flux through alpha-ketoglutarate dehydrogenase (1.4% of total carbon). In contrast, the alpha-ketoglutarate dehydrogenase flux was 25.5% of total carbon in the regulatory mutant strain phaR, while the pyruvate dehydrogenase and malic enzyme fluxes remained insignificant. The success of this technique with growth on C(1) compounds suggests that it can be applied to help characterize the effects of other regulatory mutations, and serve as a diagnostic tool in the metabolic engineering of methylotrophic bacteria.     

Systems analysis of the tricarboxylic acid cycle in Dictyostelium discoideum. II. Control analysis.

A steady-state computer model of the tricarboxylic cycle in Dictyostelium discoideum was analyzed using metabolic control theory. The steady state had variations of less than 0.04% over the last half of the simulation for both metabolite concentrations and fluxes. Metabolite and flux control coefficients were determined by varying enzymatic activities within 2% of their initial values and simulating the responses of metabolite concentrations and fluxes to these changes. Under these conditions, summation properties were met for most metabolite and all flux control coefficients. Maximum flux control coefficients were found for succinate dehydrogenase (0.35), malic enzyme (0.24), and malate dehydrogenase (-0.18). Comparable control was found for the reaction supplying pyruvate (0.14) and for the sum of the input amino acids (0.43), which serve as an energy source for D. discoideum. The time-dependent processes by which a new steady state was established were examined after increasing malic enzyme or malate dehydrogenase activities. This provided a method for an analysis of the mechanisms by which the observed control coefficients were generated. In addition, the effects of increasing the stimuli within 5-20% of the original enzyme activity were examined. Under these conditions, more typical of experimental stimuli and measurable responses, the metabolic model failed to return to steady state, and thus summation properties were not met. Whether "true" steady states ever occur or whether metabolic control theory can be applied in vivo is discussed.     

Identification of Enzymes and Quantification of Metabolic Fluxes in the Wild Type and in a Recombinant Aspergillus oryzae Strain

Two α-amylase-producing strains of Aspergillus oryzae, a wild-type strain and a recombinant containing additional copies of the α-amylase gene, were characterized with respect to enzyme activities, localization of enzymes to the mitochondria or cytosol, macromolecular composition, and metabolic fluxes through the central metabolism during glucose-limited chemostat cultivations. Citrate synthase and isocitrate dehydrogenase (NAD) activities were found only in the mitochondria, glucose-6-phosphate dehydrogenase and glutamate dehydrogenase (NADP) activities were found only in the cytosol, and isocitrate dehydrogenase (NADP), glutamate oxaloacetate transaminase, malate dehydrogenase, and glutamate dehydrogenase (NAD) activities were found in both the mitochondria and the cytosol. The measured biomass components and ash could account for 95% (wt/wt) of the biomass. The protein and RNA contents increased linearly with increasing specific growth rate, but the carbohydrate and chitin contents decreased. A metabolic model consisting of 69 fluxes and 59 intracellular metabolites was used to calculate the metabolic fluxes through the central metabolism at several specific growth rates, with ammonia or nitrate as the nitrogen source. The flux through the pentose phosphate pathway increased with increasing specific growth rate. The fluxes through the pentose phosphate pathway were 15 to 26% higher for the recombinant strain than for the wild-type strain.     

Integration of in vivo and in silico metabolic fluxes for improvement of recombinant protein production

The filamentous fungus Aspergillus niger is an efficient host for the recombinant production of the glycosylated enzyme fructofuranosidase, a biocatalyst of commercial interest for the synthesis of pre-biotic sugars. In batch culture on a minimal glucose medium, the recombinant strain A. niger SKAn1015, expressing the fructofuranosidase encoding suc1 gene secreted 45U/mL of the target enzyme, whereas the parent wild type SKANip8 did not exhibit production. The production of the recombinant enzyme induced a significant change of in vivo fluxes in central carbon metabolism, as assessed by (13)C metabolic flux ratio analysis. Most notably, the flux redistribution enabled an elevated supply of NADPH via activation of the cytosolic pentose phosphate pathway (PPP) and mitochondrial malic enzyme, whereas the flux through energy generating TCA cycle was reduced. In addition, the overall possible flux space of fructofuranosidase producing A. niger was investigated in silico by elementary flux mode analysis. This provided theoretical flux distributions for multiple scenarios with differing production capacities. Subsequently, the measured flux changes linked to improved production performance were projected into the in silico flux space. This provided a quantitative evaluation of the achieved optimization and a priority ranked target list for further strain engineering. Interestingly, the metabolism was shifted largely towards the optimum flux pattern by sole expression of the recombinant enzyme, which seems an inherent attractive property of A. niger. Selected fluxes, however, changed contrary to the predicted optimum and thus revealed novel targets-including reactions linked to NADPH metabolism and gluconate formation.     

Computational analysis of storage synthesis in developing Brassica napus L. (oilseed rape) embryos: flux variability analysis in relation to ¹³C metabolic flux analysis

Plant oils are an important renewable resource, and seed oil content is a key agronomical trait that is in part controlled by the metabolic processes within developing seeds. A large‐scale model of cellular metabolism in developing embryos of Brassica napus (bna572) was used to predict biomass formation and to analyze metabolic steady states by flux variability analysis under different physiological conditions. Predicted flux patterns are highly correlated with results from prior ¹³C metabolic flux analysis of B. napus developing embryos. Minor differences from the experimental results arose because bna572 always selected only one sugar and one nitrogen source from the available alternatives, and failed to predict the use of the oxidative pentose phosphate pathway. Flux variability, indicative of alternative optimal solutions, revealed alternative pathways that can provide pyruvate and NADPH to plastidic fatty acid synthesis. The nutritional values of different medium substrates were compared based on the overall carbon conversion efficiency (CCE) for the biosynthesis of biomass. Although bna572 has a functional nitrogen assimilation pathway via glutamate synthase, the simulations predict an unexpected role of glycine decarboxylase operating in the direction of NH₄⁺ assimilation. Analysis of the light‐dependent improvement of carbon economy predicted two metabolic phases. At very low light levels small reductions in CO₂ efflux can be attributed to enzymes of the tricarboxylic acid cycle (oxoglutarate dehydrogenase, isocitrate dehydrogenase) and glycine decarboxylase. At higher light levels relevant to the ¹³C flux studies, ribulose‐1,5‐bisphosphate carboxylase activity is predicted to account fully for the light‐dependent changes in carbon balance.     

Dynamic flux cartography of hairy roots primary metabolism

A dynamic model for plant cell and hairy root primary metabolism is presented. The model includes nutrient uptake (Pi, sugars, nitrogen sources), the glycolysis and pentose phosphate pathways, the TCA cycle, amino acid biosynthesis, respiratory chain, biosynthesis of cell building blocks (structural hexoses, organic acids, lipids, and organic phosphated molecules). The energy shuttles (ATP, ADP) and cofactors (NAD/H, NADP/H) are also included. The model describes the kinetics of 44 biochemical reactions (fluxes) of the primary metabolism of plant cells and includes 41 biochemical species (metabolites, nutrients, biomass components). Multiple Michaelis-Menten type kinetics are used to describe biochemical reaction rates. Known regulatory phenomena on metabolic pathways are included using sigmoid switch functions. A visualization framework showing fluxes and metabolite concentrations over time is presented. The visualization of fluxes and metabolites is used to analyze simulation results from Catharanthus roseus hairy root 50 d batch cultures. The visualization of the metabolic system allows analyzing split ratios between pathways and flux time-variations. For carbon metabolism, the cells were observed to have relatively high and stable fluxes for the central carbon metabolism and low and variable fluxes for anabolic pathways. For phosphate metabolism, a very high free intracellular Pi turnover rate was observed with higher flux variations than for the carbon metabolism. Nitrogen metabolism also exhibited large flux variations. The potential uses of the model are also discussed.     

Optimization-driven identification of genetic perturbations accelerates the convergence of model parameters in ensemble modeling of metabolic networks

The ensemble modeling (EM) approach has shown promise in capturing kinetic and regulatory effects in the modeling of metabolic networks. Efficacy of the EM procedure relies on the identification of model parameterizations that adequately describe all observed metabolic phenotypes upon perturbation. In this study, we propose an optimization-based algorithm for the systematic identification of genetic/enzyme perturbations to maximally reduce the number of models retained in the ensemble after each round of model screening. The key premise here is to design perturbations that will maximally scatter the predicted steady-state fluxes over the ensemble parameterizations. We demonstrate the applicability of this procedure for an Escherichia coli metabolic model of central metabolism by successively identifying single, double, and triple enzyme perturbations that cause the maximum degree of flux separation between models in the ensemble. Results revealed that optimal perturbations are not always located close to reaction(s) whose fluxes are measured, especially when multiple perturbations are considered. In addition, there appears to be a maximum number of simultaneous perturbations beyond which no appreciable increase in the divergence of flux predictions is achieved. Overall, this study provides a systematic way of optimally designing genetic perturbations for populating the ensemble of models with relevant model parameterizations.     

A transient isotopic labeling methodology for 13C metabolic flux analysis of photoautotrophic microorganisms

Metabolic flux analysis is increasingly recognized as an integral component of systems biology. However, techniques for experimental measurement of system-wide metabolic fluxes in purely photoautotrophic systems (growing on CO(2) as the sole carbon source) have not yet been developed due to the unique problems posed by such systems. In this paper, we demonstrate that an approach that balances positional isotopic distributions transiently is the only route to obtaining system-wide metabolic flux maps for purely autotrophic metabolism. The outlined transient (13)C-MFA methodology enables measurement of fluxes at a metabolic steady-state, while following changes in (13)C-labeling patterns of metabolic intermediates as a function of time, in response to a step-change in (13)C-label input. We use mathematical modeling of the transient isotopic labeling patterns of central intermediates to assess various experimental requirements for photoautotrophic MFA. This includes the need for intracellular metabolite concentration measurements and isotopic labeling measurements as a function of time. We also discuss photobioreactor design and operation in order to measure fluxes under precise environmental conditions. The transient MFA technique can be used to measure and compare fluxes under different conditions of light intensity, nitrogen sources or compare strains with various mutations or gene deletions and additions.     

Metabolic flux analysis ofBeijerinckia indica for PS-7 production

In order to investigate central metabolic changes inBeijerinckia indica, cells were grown on different carbon sources and intracellular flux distributions were studied under varying concentrations of nitrogen. Metabolic fluxes were estimated by combining material balances with extracellular substrate uptake rate, biomass formation rate, and exopolysaccharide (EPS) accumulation rate. Thirty-one metabolic reactions and 30 intracellular metabolites were considered for the flux analysis. The results revealed that most of the carbon source was directed into the Entner-Doudoroff pathway, followed by the recycling of triose-3-phosphate back to Hexose-6-phosphate. The pentose phosphate pathway was operated at a minimal level to supply the precursors for biomass formation. The different metabolic behaviors under varying nitrogen concentrations were observed with flux analysis.     

Shewanella oneidensis MR-1 fluxome under various oxygen conditions

The central metabolic fluxes of Shewanella oneidensis MR-1 were examined under carbon-limited (aerobic) and oxygen-limited (microaerobic) chemostat conditions, using 13C-labeled lactate as the sole carbon source. The carbon labeling patterns of key amino acids in biomass were probed using both gas chromatography-mass spectrometry (GC-MS) and 13C nuclear magnetic resonance (NMR). Based on the genome annotation, a metabolic pathway model was constructed to quantify the central metabolic flux distributions. The model showed that the tricarboxylic acid (TCA) cycle is the major carbon metabolism route under both conditions. The Entner-Doudoroff and pentose phosphate pathways were utilized primarily for biomass synthesis (with a flux below 5% of the lactate uptake rate). The anaplerotic reactions (pyruvate to malate and oxaloacetate to phosphoenolpyruvate) and the glyoxylate shunt were active. Under carbon-limited conditions, a substantial amount (9% of the lactate uptake rate) of carbon entered the highly reversible serine metabolic pathway. Under microaerobic conditions, fluxes through the TCA cycle decreased and acetate production increased compared to what was found for carbon-limited conditions, and the flux from glyoxylate to glycine (serine-glyoxylate aminotransferase) became measurable. Although the flux distributions under aerobic, microaerobic, and shake flask culture conditions were different, the relative flux ratios for some central metabolic reactions did not differ significantly (in particular, between the shake flask and aerobic-chemostat groups). Hence, the central metabolism of S. oneidensis appears to be robust to environmental changes. Our study also demonstrates the merit of coupling GC-MS with 13C NMR for metabolic flux analysis to reduce the use of 13C-labeled substrates and to obtain more-accurate flux values.     

The Ability of Flux Balance Analysis to Predict Evolution of Central Metabolism Scales with the Initial Distance to the Optimum

The most powerful genome-scale framework to model metabolism, flux balance analysis (FBA), is an evolutionary optimality model. It hypothesizes selection upon a proposed optimality criterion in order to predict the set of internal fluxes that would maximize fitness. Here we present a direct test of the optimality assumption underlying FBA by comparing the central metabolic fluxes predicted by multiple criteria to changes measurable by a ¹³C-labeling method for experimentally-evolved strains. We considered datasets for three Escherichia coli evolution experiments that varied in their length, consistency of environment, and initial optimality. For ten populations that were evolved for 50,000 generations in glucose minimal medium, we observed modest changes in relative fluxes that led to small, but significant decreases in optimality and increased the distance to the predicted optimal flux distribution. In contrast, seven populations evolved on the poor substrate lactate for 900 generations collectively became more optimal and had flux distributions that moved toward predictions. For three pairs of central metabolic knockouts evolved on glucose for 600–800 generations, there was a balance between cases where optimality and flux patterns moved toward or away from FBA predictions. Despite this variation in predictability of changes in central metabolism, two generalities emerged. First, improved growth largely derived from evolved increases in the rate of substrate use. Second, FBA predictions bore out well for the two experiments initiated with ancestors with relatively sub-optimal yield, whereas those begun already quite optimal tended to move somewhat away from predictions. These findings suggest that the tradeoff between rate and yield is surprisingly modest. The observed positive correlation between rate and yield when adaptation initiated further from the optimum resulted in the ability of FBA to use stoichiometric constraints to predict the evolution of metabolism despite selection for rate.     

Metabolic design based on a coupled gene expression-metabolic network model of tryptophan production in Escherichia coli

The presumably high potential of a holistic design approach for complex biochemical reaction networks is exemplified here for the network of tryptophan biosynthesis from glucose, a system whose components have been investigated thoroughly before. A dynamic model that combines the behavior of the trp operon gene expression with the metabolic network of central carbon metabolism and tryptophan biosynthesis is investigated. This model is analyzed in terms of metabolic fluxes, metabolic control, and nonlinear optimization. We compare two models for a wild-type strain and another model for a tryptophan producer. An integrated optimization of the whole network leads to a significant increase in tryptophan production rate for all systems under study. This enhancement is well above the increase that can be achieved by an optimization of subsystems. A constant ratio of control coefficients on tryptophan synthesis rate has been identified for the models regarding or disregarding trp operon expression. Although we found some examples where flux control coefficients even contradict the trends of enzyme activity changes in an optimized profile, flux control can be used as an indication for enzymes that have to be taken into account in optimization.