Analysis of metabolic fluxes for hyaluronic acid (HA) production by Streptococcus zooepidemicus

Summary A detailed metabolic flux analysis (MFA) for hyaluronic acid (HA) production by Streptococcus zooepidemicus was carried out. A metabolic network was constructed for the metabolism of S. zooepidemicus. Fluxes through these reactions were estimated by MFA using accumulation rates of biomass and product, consumption rate of glucose in batch fermentation and dissolved oxygen-controlled fermentation. The changes of the fluxes were observed at different stages of batch fermentation and in different dissolved oxygen tension (DOT)-controlled fermentation processes. The effects of metabolic nodes on HA accumulation under various culture conditions were investigated. The results showed that high concentration of glucose in the medium did not affect metabolic flux distribution, but did influence the uptake rate of glucose. HA synthesis was influenced by DOT via flux redistribution in the principal node. Adenosine triphosphate (ATP) and reduced nicotinamide adenine dinucleotide (NADH) produced in the fermentation process are associated with cell growth and HA synthesis.     

Comparative metabolic analysis of lactate for CHO cells in glucose and galactose

t-PA producing CHO cells have been shown to undergo a metabolic shift when the culture medium is supplemented with a mixture of glucose and galactose. This metabolic change is characterized by the reincorporation of lactate and its use as an additional carbon source. The aim of this work is to understand lactate metabolism. To do so, Chinese hamster ovary cells were grown in batch cultures in four different conditions consisting in different combinations of glucose and galactose. In experiments supplemented with glucose, only lactate production was observed. Cultures with glucose and galactose consumed glucose first and produced lactate at the same time, after glucose depletion galactose consumption began and lactate uptake was observed. Comparison of the metabolic state of cells with and without the shift by metabolic flux analysis show that the metabolic fluxes distribution changes mostly in the reactions involving pyruvate metabolism. When not enough pyruvate is being produced for cells to support their energy requirements, lactate dehydrogenase complex changes the direction of the reaction yielding pyruvate to feed the TCA cycle. The slow change from high fluxes during glucose consumption to low fluxes in galactose consumption generates intracellular conditions that allow the influx of lactate. Lactate consumption is possible in cell cultures supplemented with glucose and galactose due to the low rates at which galactose is consumed. Evidence suggests that an excessive production and accumulation of pyruvate during glucose consumption leads to lactate production and accumulation inside the cell. Other internal conditions such as a decrease in internal pH, forces the flow of lactate outside the cell. After metabolic shift the intracellular pool of pyruvate, lactate and H⁺ drops permitting the reversal of the monocarboxylate transporter direction, therefore leading to lactate uptake. Metabolic analysis comparing glucose and galactose consumption indicates that after metabolic shift not enough pyruvate is produced to supply energy metabolism and lactate is used for pyruvate synthesis. In addition, MFA indicates that most carbon consumed during low carbon flux is directed towards maintaining energy metabolism.     

The impact of anti-apoptotic gene Bcl-2∆ expression on CHO central metabolism

Anti-apoptosis engineering is an established technique to prolong the viability of mammalian cell cultures used for industrial production of recombinant proteins. However, the effect of overexpressing anti-apoptotic proteins on central carbon metabolism has not been systematically studied. We transfected CHO-S cells to express Bcl-2∆, an engineered anti-apoptotic gene, and selected clones that differed in their Bcl-2∆ expression and caspase activity. ¹³C metabolic flux analysis (MFA) was then applied to elucidate the metabolic alterations induced by Bcl-2∆. Expression of Bcl-2Δ reduced lactate accumulation by redirecting the fate of intracellular pyruvate toward mitochondrial oxidation during the lactate-producing phase, and it significantly increased lactate re-uptake during the lactate-consuming phase. This flux redistribution was associated with significant increases in biomass yield, peak viable cell density (VCD), and integrated VCD. Additionally, Bcl-2∆ expression was associated with significant increases in isocitrate dehydrogenase and NADH oxidase activities, both rate-controlling mitochondrial enzymes. This is the first comprehensive ¹³C MFA study to demonstrate that expression of anti-apoptotic genes has a significant impact on intracellular metabolic fluxes, especially in controlling the fate of pyruvate carbon, which has important biotechnology applications for reducing lactate accumulation and enhancing productivity in mammalian cell cultures.     

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.     

Comparative study on central metabolic fluxes of <Emphasis Type="Italic">Bacillus megaterium</Emphasis> strains in continuous culture using <Superscript>13</Superscript>C labelled substrates

Fluxes of central carbon metabolism [glycolysis, pentose phosphate pathway (PPP), tricarboxylic acid cycle (TCA cycle), biomass formation] were determined for several Bacillus megaterium strains (DSM319, WH320, WH323, MS941) in C- and N-limited chemostat cultures by ¹³C labelling experiments. The labelling patterns of proteinogenic amino acids were analysed by GC/MS and therefrom flux ratios at important nodes within the metabolic network could be calculated. On the basis of a stoichiometric metabolic model flux distributions were estimated for the different B. megaterium strains used at various cultivation conditions. Generally all strains exhibited similar metabolic flux distributions, however, several significant changes were found in (1) the glucose flux entering the PPP via the oxidative branch, (2) the reversibilities within the PPP, (3) the relative fluxes of pyruvate and acetyl-CoA fed to the TCA cycle, (4) the fluxes around the pyruvate node involving a futile cycle.     

Oxygen supply strongly influences metabolic fluxes,the production of poly(3-hydroxybutyrate) and alginate,and the degree of acetylation of alginate in Azotobacter vinelandii

The aim of this study was to evaluate carbon flux in Azotobacter vinelandii using metabolic flux analysis (MFA) under high and low aeration conditions to achieve an improved understanding of how these changes could be related to alginate acetylation and PHB production. Changes in oxygen availability had a considerable impact on the metabolic fluxes and were reflected in the growth rate, the specific glucose consumption rate, and the alginate and PHB yields. The main differences at the metabolic flux level were observed in three important pathways. The first important difference was consistent with respiratory protection; an increase in the flux generated through the tricarboxylic acid (TCA) cycle for cultures grown under high aeration conditions (up to 2.61 times higher) was observed. In the second important difference, the fluxes generated through pyruvate dehydrogenase, phosphoenol pyruvate carboxykinase and pyruvate kinase, all of which are involved in acetyl-CoA metabolism, increased by 10, 43.9 and 17.5%, respectively, in cultures grown under low aeration conditions compared with those grown under high aeration conditions. These changes were related to alginate acetylation, which was 2.6 times higher in the cultures with limited oxygen, and the changes were also related to a drastic increase in PHB production. Finally, the glyoxylate shunt was active under both of the conditions that were tested, and a 2.79-fold increase was observed in cultures that were grown under the low aeration condition.     

Elucidating the role of copper in CHO cell energy metabolism using 13C metabolic flux analysis

¹³C‐metabolic flux analysis was used to understand copper deficiency‐related restructuring of energy metabolism, which leads to excessive lactate production in recombinant protein‐producing CHO cells. Stationary‐phase labeling experiments with U‐¹³C glucose were conducted on CHO cells grown under high and limiting copper in 3 L fed‐batch bioreactors. The resultant labeling patterns of soluble metabolites were measured by GC‐MS and used to estimate metabolic fluxes in the central carbon metabolism pathways using OpenFlux. Fluxes were evaluated 300 times from stoichiometrically feasible random guess values and their confidence intervals calculated by Monte Carlo simulations. Results from metabolic flux analysis exhibited significant carbon redistribution throughout the metabolic network in cells under Cu deficiency. Specifically, glycolytic fluxes increased (25%–79% relative to glucose uptake) whereas fluxes through the TCA and pentose phosphate pathway (PPP) were lower (15%–23% and 74%, respectively) compared with the Cu‐containing condition. Furthermore, under Cu deficiency, 33% of the flux entering TCA via the pyruvate node was redirected to lactate and malate production. Based on these results, we hypothesize that Cu deficiency disrupts the electron transport chain causing ATP deficiency, redox imbalance, and oxidative stress, which in turn drive copper‐deficient CHO cells to produce energy via aerobic glycolysis, which is associated with excessive lactate production, rather than the more efficient route of oxidative phosphorylation. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1179–1186, 2015     

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.     

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.     

Computational tools for isotopically instationary 13C labeling experiments under metabolic steady state conditions

(13)C metabolic flux analysis (MFA) has become an important and powerful tool for the quantitative analysis of metabolic networks in the framework of metabolic engineering. Isotopically instationary (13)C MFA under metabolic stationary conditions is a promising refinement of classical stationary MFA. It accounts for the experimental requirements of non-steady-state cultures as well as for the shortening of the experimental duration. This contribution extends all computational methods developed for classical stationary (13)C MFA to the instationary situation by using high-performance computing methods. The developed tools allow for the simulation of instationary carbon labeling experiments (CLEs), sensitivity calculation with respect to unknown parameters, fitting of the model to the measured data, statistical identifiability analysis and an optimal experimental design facility. To explore the potential of the new approach all these tools are applied to the central metabolism of Escherichia coli. The achieved results are compared to the outcome of the stationary counterpart, especially focusing on statistical properties. This demonstrates the specific strengths of the instationary method. A new ranking method is proposed making both an a priori and an a posteriori design of the sampling times available. It will be shown that although still not all fluxes are identifiable, the quality of flux estimates can be strongly improved in the instationary case. Moreover, statements about the size of some immeasurable pool sizes can be made.     

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.     

Inferring Metabolic States in Uncharacterized Environments Using Gene-Expression Measurements

The large size of metabolic networks entails an overwhelming multiplicity in the possible steady-state flux distributions that are compatible with stoichiometric constraints. This space of possibilities is largest in the frequent situation where the nutrients available to the cells are unknown. These two factors: network size and lack of knowledge of nutrient availability, challenge the identification of the actual metabolic state of living cells among the myriad possibilities. Here we address this challenge by developing a method that integrates gene-expression measurements with genome-scale models of metabolism as a means of inferring metabolic states. Our method explores the space of alternative flux distributions that maximize the agreement between gene expression and metabolic fluxes, and thereby identifies reactions that are likely to be active in the culture from which the gene-expression measurements were taken. These active reactions are used to build environment-specific metabolic models and to predict actual metabolic states. We applied our method to model the metabolic states of Saccharomyces cerevisiae growing in rich media supplemented with either glucose or ethanol as the main energy source. The resulting models comprise about 50% of the reactions in the original model, and predict environment-specific essential genes with high sensitivity. By minimizing the sum of fluxes while forcing our predicted active reactions to carry flux, we predicted the metabolic states of these yeast cultures that are in large agreement with what is known about yeast physiology. Most notably, our method predicts the Crabtree effect in yeast cells growing in excess glucose, a long-known phenomenon that could not have been predicted by traditional constraint-based modeling approaches. Our method is of immediate practical relevance for medical and industrial applications, such as the identification of novel drug targets, and the development of biotechnological processes that use complex, largely uncharacterized media, such as biofuel production.     

Metabolic flux analysis of cultured hepatocytes exposed to plasma

Hepatic metabolism can be investigated using metabolic flux analysis (MFA), which provides a comprehensive overview of the intracellular metabolic flux distribution. The characterization of intermediary metabolism in hepatocytes is important for all biotechnological applications involving liver cells, including the development of bioartificial liver (BAL) devices. During BAL operation, hepatocytes are exposed to plasma or blood from the patient, at which time they are prone to accumulate intracellular lipids and exhibit poor liver-specific functions. In a prior study, we found that preconditioning the primary rat hepatocytes in culture medium containing physiological levels of insulin, as opposed to the typical supraphysiological levels found in standard hepatocyte culture media, reduced lipid accumulation during subsequent plasma exposure. Furthermore, supplementing the plasma with amino acids restored hepatospecific functions. In the current study, we used MFA to quantify the changes in intracellular pathway fluxes of primary rat hepatocytes in response to low-insulin preconditioning and amino acid supplementation. We found that culturing hepatocytes in medium containing lower physiological levels of insulin decreased the clearance of glucose and glycerol with a concomitant decrease in glycolysis. These findings are consistent with the general notion that low insulin, especially in the presence of high glucagon levels, downregulates glycolysis in favor of gluconeogenesis in hepatocytes. The MFA model shows that, during subsequent plasma exposure, low-insulin preconditioning upregulated gluconeogenesis, with lactate as the primary precursor in unsupplemented plasma, with a greater contribution from deaminated amino acids in amino acid-supplemented plasma. Concomitantly, low-insulin preconditioning increased fatty acid oxidation, an effect that was further enhanced by amino acid supplementation to the plasma. The increase in fatty acid oxidation reduced intracellular triglyceride accumulation. Overall, these findings are consistent with the notion that the insulin level in medium culture presets the metabolic machinery of hepatocytes such that it directly impacts on their metabolic behavior during subsequent plasma culture.     

Strategies for investigating the plant metabolic network with steady-state metabolic flux analysis: lessons from an Arabidopsis cell culture and other systems

Steady-state (13)C metabolic flux analysis (MFA) is currently the experimental method of choice for generating flux maps of the compartmented network of primary metabolism in heterotrophic and mixotrophic plant tissues. While statistically robust protocols for the application of steady-state MFA to plant tissues have been developed by several research groups, the implementation of the method is still far from routine. The effort required to produce a flux map is more than justified by the information that it contains about the metabolic phenotype of the system, but it remains the case that steady-state MFA is both analytically and computationally demanding. This article provides an overview of principles that underpin the implementation of steady-state MFA, focusing on the definition of the metabolic network responsible for redistribution of the label, experimental considerations relating to data collection, the modelling process that allows a set of metabolic fluxes to be deduced from the labelling data, and the interpretation of flux maps. The article draws on published studies of Arabidopsis cell cultures and other systems, including developing oilseeds, with the aim of providing practical guidance and strategies for handling the issues that arise when applying steady-state MFA to the complex metabolic networks encountered in plants.     

Insights into plant metabolic networks from steady-state metabolic flux analysis

Steady-state metabolic flux analysis (MFA) is an experimental approach that allows the measurement of multiple fluxes in the core network of primary carbon metabolism. It is based on isotopic labelling experiments, and although well established in the analysis of micro-organisms, and some mammalian systems, the extension of the method to plant cells has been challenging because of the extensive subcellular compartmentation of the metabolic network. Despite this difficulty there has been substantial progress in developing robust protocols for the analysis of heterotrophic plant metabolism by steady-state MFA, and flux maps have now been published that reflect the metabolic phenotypes of excised root tips, developing embryos and cotyledons, hairy root cultures, and cell suspensions under a variety of physiological conditions. There has been a steady improvement in the quality, extent and statistical reliability of these analyses, and new information is emerging on the performance of the plant metabolic network and the contributions of specific pathways.     

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 thermodynamic meaning of metabolic exchange fluxes

Metabolic flux analysis (MFA) deals with the experimental determination of steady-state fluxes in metabolic networks. An important feature of the ¹³C MFA method is its capability to generate information on both directions of bidirectional reaction steps given by exchange fluxes. The biological interpretation of these exchange fluxes and their relation to thermodynamic properties of the respective reaction steps has never been systematically investigated. As a central result, it is shown here that for a general class of enzyme reaction mechanisms the quotients of net and exchange fluxes measured by ¹³C MFA are coupled to Gibbs energies of the reaction steps. To establish this relation the concept of apparent flux ratios of enzymatic isotope-labeling networks is introduced and some computing rules for these flux ratios are given. Application of these rules reveals a conceptional pitfall of ¹³C MFA, which is the inherent dependency of measured exchange fluxes on the chosen tracer atom. However, it is shown that this effect can be neglected for typical biochemical reaction steps under physiological conditions. In this situation, the central result can be formulated as a two-sided inequality relating fluxes, pool sizes, and standard Gibbs energies. This relation has far-reaching consequences for metabolic flux analysis, quantitative metabolomics, and network thermodynamics.     

Metabolic flux analysis of CHO cell metabolism in the late non‐growth phase

Chinese hamster ovary (CHO) cell cultures are commonly used for production of recombinant human therapeutic proteins. Often the goal of such a process is to separate the growth phase of the cells, from the non‐growth phase where ideally the cells are diverting resources to produce the protein of interest. Characterizing the way that the cells use nutrients in terms of metabolic fluxes as a function of culture conditions can provide a deeper understanding of the cell biology offering guidance for process improvements. To evaluate the fluxes, metabolic flux analysis of the CHO cell culture in the non‐growth phase was performed by a combination of steady‐state isotopomer balancing and stoichiometric modeling. Analysis of the glycolytic pathway and pentose phosphate pathway (PPP) indicated that almost all of the consumed glucose is diverted towards PPP with a high NADPH production; with even recycle from PPP to G6P in some cases. Almost all of the pyruvate produced from glycolysis entered the TCA cycle with little or no lactate production. Comparison of the non‐growth phase against previously reported fluxes from growth phase cultures indicated marked differences in the fluxes, in terms of the split between glycolysis and PPP, and also around the pyruvate node. Possible reasons for the high NADPH production are also discussed. Evaluation of the fluxes indicated that the medium strength, carbon dioxide level, and temperature with dissolved oxygen have statistically significant impacts on different nodes of the flux network. Biotechnol. Bioeng. 2011; 108:82–92. © 2010 Wiley Periodicals, Inc.     

Altered regulation of pyruvate kinase or co-overexpression of phosphofructokinase increases glycolytic fluxes in resting Escherichia coli

Glycolytic fluxes in resting Escherichia coli were enhanced by overexpression of heterologous pyruvate kinases (Pyk) from Bacillus stearothermophilus and Zymomonas mobilis, but not homologous Pyk. Compared to the control, an increase of 10% in specific glucose consumption and of 15% in specific ethanol production rates was found in anaerobic resting cells, expressing the heterologous Pyks, that were harvested from exponentially growing aerobic cultures. A further increase in glycolytic flux was achieved by simultaneous overexpression of E. coli phosphofructokinase (Pfk) and Pyk with specific glucose consumption and ethanol production rates of 25% and 35% greater, respectively, than the control. Fluxes to lactate were not significantly affected, contrary to previous observations with resting cells harvested from anaerobically growing cultures. To correlate the physiology of resting cells with the physiology of cells prior to harvest, we determined the relevant growth parameters from aerobic and anaerobic precultures. We conclude that glycolytic fluxes in E. coli with submaximal (aerobic) metabolic activity can be increased by overexpression of pyruvate kinases which do not require allosteric activation or co-overexpression with Pfk. However, such improvements require more extensive engineering in E. coli with near maximal (anaerobic) metabolic activity.