Stoichiometric network constraints on xylose metabolism by recombinant Saccharomyces cerevisiae

Metabolic pathway engineering is constrained by the thermodynamic and stoichiometric feasibility of enzymatic activities of introduced genes. Engineering of xylose metabolism in Saccharomyces cerevisiae has focused on introducing genes for the initial xylose assimilation steps from Pichia stipitis, a xylose-fermenting yeast, into S. cerevisiae, a yeast traditionally used in ethanol production from hexose. However, recombinant S. cerevisiae created in several laboratories have used xylose oxidatively rather than in the fermentative manner that this yeast metabolizes glucose. To understand the differences between glucose and engineered xylose metabolic networks, we performed a flux balance analysis (FBA) and calculated extreme pathways using a stoichiometric model that describes the biochemistry of yeast cell growth. FBA predicted that the ethanol yield from xylose exhibits a maximum under oxygen-limited conditions, and a fermentation experiment confirmed this finding. Fermentation results were largely consistent with in silico phenotypes based on calculated extreme pathways, which displayed several phases of metabolic phenotype with respect to oxygen availability from anaerobic to aerobic conditions. However, in contrast to the model prediction, xylitol production continued even after the optimum aeration level for ethanol production was attained. These results suggest that oxygen (or some other electron accepting system) is required to resolve the redox imbalance caused by cofactor difference between xylose reductase and xylitol dehydrogenase, and that other factors limit glycolytic flux when xylose is the sole carbon source.     

Biomass content governs fermentation rate in nitrogen-deficient wine musts

Problematic fermentations are common in the wine industry. Assimilable nitrogen deficiency is the most prevalent cause of sluggish fermentations and can reduce fermentation rates significantly. A lack of nitrogen diminishes a yeast's metabolic activity, as well as the biomass yield, although it has not been clear which of these two interdependent factors is more significant in sluggish fermentations. Under winemaking conditions with different initial nitrogen concentrations, metabolic flux analysis was used to isolate the effects. We quantified yeast physiology and identified key metabolic fluxes. We also performed cell concentration experiments to establish how biomass yield affects the fermentation rate. Intracellular analysis showed that trehalose accumulation, which is highly correlated with ethanol production, could be responsible for sustaining cell viability in nitrogen-poor musts independent of the initial assimilable nitrogen content. Other than the higher initial maintenance costs in sluggish fermentations, the main difference between normal and sluggish fermentations was that the metabolic flux distributions in nitrogen-deficient cultures revealed that the specific sugar uptake rate was substantially lower. The results of cell concentration experiments, however, showed that in spite of lower sugar uptake, adding biomass from sluggish cultures not only reduced the time to finish a problematic fermentation but also was less likely to affect the quality of the resulting wine as it did not alter the chemistry of the must.     

Biomass Content Governs Fermentation Rate in Nitrogen-Deficient Wine Musts

Problematic fermentations are common in the wine industry. Assimilable nitrogen deficiency is the most prevalent cause of sluggish fermentations and can reduce fermentation rates significantly. A lack of nitrogen diminishes a yeast's metabolic activity, as well as the biomass yield, although it has not been clear which of these two interdependent factors is more significant in sluggish fermentations. Under winemaking conditions with different initial nitrogen concentrations, metabolic flux analysis was used to isolate the effects. We quantified yeast physiology and identified key metabolic fluxes. We also performed cell concentration experiments to establish how biomass yield affects the fermentation rate. Intracellular analysis showed that trehalose accumulation, which is highly correlated with ethanol production, could be responsible for sustaining cell viability in nitrogen-poor musts independent of the initial assimilable nitrogen content. Other than the higher initial maintenance costs in sluggish fermentations, the main difference between normal and sluggish fermentations was that the metabolic flux distributions in nitrogen-deficient cultures revealed that the specific sugar uptake rate was substantially lower. The results of cell concentration experiments, however, showed that in spite of lower sugar uptake, adding biomass from sluggish cultures not only reduced the time to finish a problematic fermentation but also was less likely to affect the quality of the resulting wine as it did not alter the chemistry of the must.     

Quantitative comparison of transient growth of Saccharomyces cerevisiae,Saccharomyces kluyveri,and Kluyveromyces lactis

A multitude of metabolic regulations occur in yeast, particularly under dynamic process conditions, such as under sudden glucose excess. However, quantification of regulations and classification of yeast strains under these conditions have yet to be elucidated, which requires high-frequency and consistent quantification of the metabolic response. The present study aimed at quantifying the dynamic regulation of the central metabolism of strains Saccharomyces cerevisiae, S. kluyveri, and Kluyveromyces lactis upon sudden glucose excess, accomplished by a shift-up in dilution rate inside of the oxidative region using a small metabolic flux model. It was found that, under transient growth conditions, S. kluyveri behaved like K. lactis, while classification using steady-state conditions would position S. kluyveri close to S. cerevisiae. For transient conditions and based on the observation whether excess glucose is initially used for catabolism (energy) or anabolism (carbon), we propose to classify strains into energy-driven, such as S. cerevisiae, and carbon-driven, such as S. kluyveri and K. lactis, strains. Furthermore, it was found that the delayed onset of fermentative catabolism in carbon-driven strains is a consequence of low catabolic flux and the initial shunt of glucose in non-nitrogen-containing biomass constituents. The MFA model suggests that energy limitation forced the cell to ultimately increase catabolic flux, while the capacity of oxidative catabolism is not sufficient to process this flux oxidatively. The combination of transient experiments and its exploitation with reconciled intrinsic rates using a small metabolic model could corroborate earlier findings of metabolic regulations, such as tight glucose control in carbon-driven strains and transient changes in biomass composition, as well as explore new regulations, such as assimilation of ethanol before glucose. The benefit from using small metabolic flux models is the richness of information and the enhanced insight into intrinsic metabolic pathways without a priori knowledge of adaptation kinetics. Used in an online context, this approach serves as an efficient tool for strain characterization and physiological studies.     

The acetone butanol fermentation on glucose and xylose. II. Regulation and kinetics in fed-batch cultures

The kinetics in fed-batch cultures of acetone butanol fermentation by Clostridium acetobutylicum is compared on glucose, xylose, and mixtures of both sugars. The final conversion yield of sugars into solvents always increases with the sugar feeding rate. At low feeding rates, the sugar concentration in the medium becomes limiting, which results in a slower cellular growth, a slower metabolic transition from an acid to a solvent fermentation and, thus, a higher accumulation of acids. It is only at sufficiently high feeding rates that fed-batch fermentations yield kinetic results comparable to those of batch fermentations. With mixtures of glucose and xylose, because of a maintained low glucose level, both sugars are taken up at the same rate during a first fermentation period. An earlier accumulation of xylose when the fermentation becomes inhibited suggest that xylose utilization is inhibited when the catabolic flux of glucose alone can satisfy the metabolic activity of the cell. Kinetic results with batch and fed-batch fermentations indicate several important features of the regulation of C. acetobutylicum metabolism: an early inhibition by the produced acids; an initiation of solvent formation between 4 and 6 g/L acetic and butyric acid depending on the metabolic activity of the cell; a metabolic transition from acids to solvents production at a rate closely related to the rate of sugar uptake; during solvent production, a reassimilation of acids above a minimal rate of sugar consumption of 0.2 h(-1); a final inhibition of the fermentation at a total butanol and acids concentration of ca. 20 g/L.     

Comparative studies of Escherichia coli strains using different glucose uptake systems: Metabolism and energetics

Modifying substrate uptake systems is a potentially powerful tool in metabolic engineering. This research investigates energetic and metabolic changes brought about by the genetic modification of the glucose uptake and phosphorylation system of Escherichia coli. The engineered strain PPA316, which lacks the E. coli phosphotransferase system (PTS) and uses instead the galactose-proton symport system for glucose uptake, exhibited significantly altered metabolic patterns relative to the parent strain PPA305 which retains PTS activity. Replacement of a PTS uptake system by the galactose-proton symport system is expected to lower the carbon flux to pyruvate in both aerobic and anaerobic cultivations. The extra energy cost in substrate uptake for the non-PTS strain PPA 316 had a greater effect on anaerobic specific growth rate, which was reduced by a factor of five relative to PPA 305, while PPA 316 reached a specific growth rate of 60% of that of the PTS strain under aerobic conditions. The maximal cell densities obtained with PPA 316 were approximately 8% higher than those of the PTS strain under aerobic conditions and 14% lower under anaerobic conditions. In vivo NMR results showed that the non-PTS strain possesses a dramatically different intracellular environment, as evidenced by lower levels of total sugar phosphate, NAD(H), nucleoside triphosphates and phosphoenolpyruvate, and higher levels of nucleoside diphosphates. The sugar phosphate compositions, as measured by extract NMR, were considerably different between these two strains. Data suggest that limitations in the rates of steps catalyzed by glucokinase, glyceraldehyde-3-phosphate dehydrogenase, phosphofructokinase, and pyruvate kinase may be responsible for the low overall rate of glucose metabolism in PPA316. (c) 1997 John Wiley & Sons, Inc. Biotechnol Bioeng 56: 583-590, 1997.     

Conservation of expression and sequence of metabolic genes is reflected by activity across metabolic states

Variation in gene expression levels on a genomic scale has been detected among different strains, among closely related species, and within populations of genetically identical cells. What are the driving forces that lead to expression divergence in some genes and conserved expression in others? Here we employ flux balance analysis to address this question for metabolic genes. We consider the genome-scale metabolic model of Saccharomyces cerevisiae, and its entire space of optimal and near-optimal flux distributions. We show that this space reveals underlying evolutionary constraints on expression regulation, as well as on the conservation of the underlying gene sequences. Genes that have a high range of optimal flux levels tend to display divergent expression levels among different yeast strains and species. This suggests that gene regulation has diverged in those parts of the metabolic network that are less constrained. In addition, we show that genes that are active in a large fraction of the space of optimal solutions tend to have conserved sequences. This supports the possibility that there is less selective pressure to maintain genes that are relevant for only a small number of metabolic states.     

Metabolic flux analysis of Escherichia coli K12 grown on 13C-labeled acetate and glucose using GC-MS and powerful flux calculation method

A new algorithm was developed for the estimation of the metabolic flux distribution based on GC-MS data of proteinogenic amino acids. By using a sensitive GC-MS protocol as well as by combining the global search algorithm such as the genetic algorithm with the local search algorithm such as the Levenberg-Marquardt algorithm, not only the distribution of the net fluxes in the entire network, but also certain exchange fluxes which contribute significantly to the isotopomer distribution could be quantified. This mass isotopomer analysis could identify the biochemical changes involved in the regulation where acetate or glucose was used as a main carbon source. The metabolic flux analysis clearly revealed that when the specific growth rate increased, only a slight change in flux distribution was observed for acetate metabolism, indicating that subtle regulation mechanism exists in certain key junctions of this network system. Different from acetate metabolism, when glucose was used as a carbon source, as the growth rate increased, a significant increase in relative pentose phosphate pathway (PPP) flux was observed for Escherichia coli K12 at the expense of the citric acid cycle, suggesting that when growing on glucose, the flux catalyzed by isocitrate dehydrogenase could not fully fulfill the NADPH demand for cell growth, causing the oxidative PPP to be utilized to a larger extent so as to complement the NADPH demand. The GC-MS protocol as well as the new algorithm demonstrated here proved to be a powerful tool for characterizing metabolic regulation and can be utilized for strain improvement and bioprocess optimization.     

System-level insights into yeast metabolism by thermodynamic analysis of elementary flux modes

One of the most obvious phenotypes of a cell is its metabolic activity, which is defined by the fluxes in the metabolic network. Although experimental methods to determine intracellular fluxes are well established, only a limited number of fluxes can be resolved. Especially in eukaryotes such as yeast, compartmentalization and the existence of many parallel routes render exact flux analysis impossible using current methods. To gain more insight into the metabolic operation of S. cerevisiae we developed a new computational approach where we characterize the flux solution space by determining elementary flux modes (EFMs) that are subsequently classified as thermodynamically feasible or infeasible on the basis of experimental metabolome data. This allows us to provably rule out the contribution of certain EFMs to the in vivo flux distribution. From the 71 million EFMs in a medium size metabolic network of S. cerevisiae, we classified 54% as thermodynamically feasible. By comparing the thermodynamically feasible and infeasible EFMs, we could identify reaction combinations that span the cytosol and mitochondrion and, as a system, cannot operate under the investigated glucose batch conditions. Besides conclusions on single reactions, we found that thermodynamic constraints prevent the import of redox cofactor equivalents into the mitochondrion due to limits on compartmental cofactor concentrations. Our novel approach of incorporating quantitative metabolite concentrations into the analysis of the space of all stoichiometrically feasible flux distributions allows generating new insights into the system-level operation of the intracellular fluxes without making assumptions on metabolic objectives of the cell.     

Metabolic Engineering in the -omics Era: Elucidating and Modulating Regulatory Networks

The importance of regulatory control in metabolic processes is widely acknowledged, and several enquiries (both local and global) are being made in understanding regulation at various levels of the metabolic hierarchy. The wealth of biological information has enabled identifying the individual components (genes, proteins, and metabolites) of a biological system, and we are now in a position to understand the interactions between these components. Since phenotype is the net result of these interactions, it is immensely important to elucidate them not only for an integrated understanding of physiology, but also for practical applications of using biological systems as cell factories. We present some of the recent “-omics” approaches that have expanded our understanding of regulation at the gene, protein, and metabolite level, followed by analysis of the impact of this progress on the advancement of metabolic engineering. Although this review is by no means exhaustive, we attempt to convey our ideology that combining global information from various levels of metabolic hierarchy is absolutely essential in understanding and subsequently predicting the relationship between changes in gene expression and the resulting phenotype. The ultimate aim of this review is to provide metabolic engineers with an overview of recent advances in complementary aspects of regulation at the gene, protein, and metabolite level and those involved in fundamental research with potential hurdles in the path to implementing their discoveries in practical applications.     

Loss of the major isoform of phosphoglucomutase results in altered calcium homeostasis in Saccharomyces cerevisiae

Phosphoglucomutase (PGM) is a key enzyme in glucose metabolism, where it catalyzes the interconversion of glucose 1-phosphate (Glc-1-P) and glucose 6-phosphate (Glc-6-P). In this study, we make the novel observation that PGM is also involved in the regulation of cellular Ca(2+) homeostasis in Saccharomyces cerevisiae. When a strain lacking the major isoform of PGM (pgm2Delta) was grown on media containing galactose as sole carbon source, its rate of Ca(2+) uptake was 5-fold higher than an isogenic wild-type strain. This increased rate of Ca(2+) uptake resulted in a 9-fold increase in the steady-state total cellular Ca(2+) level. The fraction of cellular Ca(2+) located in the exchangeable pool in the pgm2Delta strain was found to be as large as the exchangeable fraction observed in wild-type cells, suggesting that the depletion of Golgi Ca(2+) stores is not responsible for the increased rate of Ca(2+) uptake. We also found that growth of the pgm2Delta strain on galactose media is inhibited by 10 microM cyclosporin A, suggesting that activation of the calmodulin/calcineurin signaling pathway is required to activate the Ca(2+) transporters that sequester the increased cytosolic Ca(2+) load caused by this high rate of Ca(2+) uptake. We propose that these Ca(2+)-related alterations are attributable to a reduced metabolic flux between Glc-1-P and Glc-6-P due to a limitation of PGM enzymatic activity in the pgm2Delta strain. Consistent with this hypothesis, we found that this "metabolic bottleneck" resulted in an 8-fold increase in the Glc-1-P level compared with the wild-type strain, while the Glc-6-P and ATP levels were normal. These results suggest that Glc-1-P (or a related metabolite) may participate in the control of Ca(2+) uptake from the environment.     

Metabolic engineering in the -omics era: elucidating and modulating regulatory networks.

The importance of regulatory control in metabolic processes is widely acknowledged, and several enquiries (both local and global) are being made in understanding regulation at various levels of the metabolic hierarchy. The wealth of biological information has enabled identifying the individual components (genes, proteins, and metabolites) of a biological system, and we are now in a position to understand the interactions between these components. Since phenotype is the net result of these interactions, it is immensely important to elucidate them not only for an integrated understanding of physiology, but also for practical applications of using biological systems as cell factories. We present some of the recent "-omics" approaches that have expanded our understanding of regulation at the gene, protein, and metabolite level, followed by analysis of the impact of this progress on the advancement of metabolic engineering. Although this review is by no means exhaustive, we attempt to convey our ideology that combining global information from various levels of metabolic hierarchy is absolutely essential in understanding and subsequently predicting the relationship between changes in gene expression and the resulting phenotype. The ultimate aim of this review is to provide metabolic engineers with an overview of recent advances in complementary aspects of regulation at the gene, protein, and metabolite level and those involved in fundamental research with potential hurdles in the path to implementing their discoveries in practical applications.     

A general model for aerobic yeast growth: batch growth

A general model for aerobic yeast growth in batch culture is presented. It is based on the concept that the aerobic metabolism of all yeasts is determined by the relative sizes of the transport rate of sugar into the cell and the transport rate of respiratory intermediates into the mitochondrion. If the rate of sugar uptake rate exceeds the rate of transport of respiratory intermediates into the mitochondrion (as in Saccharomyces cerevisiae, S. uvarum, and S. pombe), the metabolism exhibits the features of ethanol excretion and limited specific oxygen uptake rate. If the rate of transport of respiratory intermediates into the mitochondrion is of the same order as the transport of sugar into the cell (as in Candida utilis), the metabolism is characterized by little or no ethanol excretion and a much higher specific oxygen uptake rate. Batch data from an extensive range of yeast and carbon sources is used to illustrate the use of this model. The ability of this model to fit such an extensive range of experimental data suggests that it can be used as a generalized model for aerobic yeast growth.     

Modeling threshold phenomena, metabolic pathways switches and signals in chemostat-cultivated cells: the Crabtree effect in Saccharomyces cerevisiae

The long-term Crabtree effect in Saccharomyces cerevisiae cultivated in aerobic chemostat at steady state has been studied for three different substrate concentrations in the feed of the bioreactor (data: J. Gen. Microbiol., 129 (1983) 653). We have shown that a model using two ways of transport/metabolization (T/M) of hyperbolic form, with high and low affinity for the substrate, allowed to represent correctly the main characteristics of the phenomenon. The model is based on an explicit form of the T/M kinetics when the bioreactor is considered as a polyphasic dispersed system (PDS). Mass balances analysis also allows to quantify the critical dilution rate value (threshold), Dc, of the transition between respiratory and respirofermentative mode, for which ethanol is produced. A good approximation for the threshold is Dc = V(S)0 Y(Xc, S) where Y(Xc,S) is the average yield coefficient before transition and V(S)0, the maximum specific rate of high affinity T/M pathway. The theoretical value is 0.3 h(-1), and is equal to the experimental value. We thus show in a quantitative way that the transition depends both on culture conditions (global characteristic of the system) and on strain properties (intrinsic characteristic of the microorganism as well). Using two different methods to calculate the residual substrate has carried out the comparison between the simulations end the experimental data. This allowed showing that the latter is not well represented by Monod's model and has confirmed that the affinity for the substrate varies according to the biomass. We have then shown how to calculate the most important specific rates (or metabolic flux) related to biomass, ethanol, oxygen, hydrogen, respiratory and fermentative CO(2) and H(2)O within the cellular phase. It has appeared that the oxygen uptake rate directly depends on high-affinity T/M pathway. This let us think that the regulation of the Crabtree effect in S. cerevisiae depends on the saturation of some glucose metabolization and transport pathways rather than on saturation of the respiratory chains. The specific rates analysis has also allowed us to show, at least in this case, that the metabolization rate (biosynthesis+fueling) had its maximum value on the whole dilution rates interval; metabolites excretion (ethanol and fermentative CO(2)) only intervenes to drain a "surplus" glucose flux. As a consequence, the transport capacity must be higher than the one of metabolization. Maximization of the metabolization specific rate could then be used as an optimization criterion in the stoichiometric calculation of metabolic flux (and not the specific growth rate maximization because growth is limited in a chemostat (mu = D)). We have also shown that the mass balances based on the T/M processes are in agreement with molar and elementary balances of the general stoichiometric equation for glucose respiration and fermentation under aerobic conditions. Thanks to the specific rates calculating the stoichiometric coefficients has done this. The total mass balance difference does not exceed 4%, which is compatible with the experimental carbon balance. Finally, we have emphasized that the ratio of biosynthesis flux and metabolization flux is constant before and after transition. This observation could be applied as soon as the free substrate concentration in the cellular phase is low. The paper succinctly describes the former theoretical results on which the model is built and sufficiently explains the algorithm for straightforward implementation.     

Towards dynamic metabolic flux analysis in CHO cell cultures

Chinese hamster ovary (CHO) cells are the most widely used mammalian cell line for biopharmaceutical production, with a total global market approaching $100 billion per year. In the pharmaceutical industry CHO cells are grown in fed-batch culture, where cellular metabolism is characterized by high glucose and glutamine uptake rates combined with high rates of ammonium and lactate secretion. The metabolism of CHO cells changes dramatically during a fed-batch culture as the cells adapt to a changing environment and transition from exponential growth phase to stationary phase. Thus far, it has been challenging to study metabolic flux dynamics in CHO cell cultures using conventional metabolic flux analysis techniques that were developed for systems at metabolic steady state. In this paper we review progress on flux analysis in CHO cells and techniques for dynamic metabolic flux analysis. Application of these new tools may allow identification of intracellular metabolic bottlenecks at specific stages in CHO cell cultures and eventually lead to novel strategies for improving CHO cell metabolism and optimizing biopharmaceutical process performance.