Enzyme-constrained metabolic model and in silico metabolic engineering of Clostridium ljungdahlii for the development of sustainable production processes.

Constraint-based genome-scale models (GEMs) of microorganisms provide a powerful tool for predicting and analyzing microbial phenotypes as well as for understanding how these are affected by genetic and environmental perturbations. Recently, MATLAB and Python-based tools have been developed to incorporate enzymatic constraints into GEMs. These constraints enhance phenotype predictions by accounting for the enzyme cost of catalyzed model´s reactions, thereby reducing the space of possible metabolic flux distributions. In this study, enzymatic constraints were added to an existing GEM of Clostridium ljungdahlii, a model acetogenic bacterium, by including its enzyme turnover numbers (kcats) and molecular masses, using the Python-based AutoPACMEN approach. When compared to the metabolic model iHN637, the enzyme cost-constrained model (ec_iHN637) obtained in our study showed an improved predictive ability of growth rate and product profile. The model ec_iHN637 was then employed to perform in silico metabolic engineering of C. ljungdahlii, by using the OptKnock computational framework to identify knockouts to enhance the production of desired fermentation products. The in silico metabolic engineering was geared towards increasing the production of fermentation products by C. ljungdahlii, with a focus on the utilization of synthesis gas and CO2. This resulted in different engineering strategies for overproduction of valuable metabolites under different feeding conditions, without redundant knockouts for different products. Importantly, the results of the in silico engineering results indicated that the mixotrophic growth of C. ljungdahlii is a promising approach to coupling improved cell growth and acetate and ethanol productivity with net CO2 fixation.

Towards closed carbon loop fermentations: Cofeeding of Yarrowia lipolytica with glucose and formic acid.

A novel fermentation process was developed in which renewable electricity is indirectly used as an energy source in fermentation, synergistically decreasing both the consumption of sugar as a first generation carbon source and emission of the greenhouse gas CO2 . As an illustration, a glucose-based process is co-fed with formic acid, which can be generated by capturing CO2 from fermentation offgas followed by electrochemical reduction with renewable electricity. This "closed carbon loop" concept is demonstrated by a case study in which cofeeding formic acid is shown to significantly increase the yield of biomass on glucose of the industrially relevant yeast species Yarrowia lipolytica. First, the optimal feed ratio of formic acid to glucose is established using chemostat cultivations. Subsequently, guided by a dynamic fermentation process model, a fed-batch protocol is developed and demonstrated on laboratory scale. Finally, the developed fed-batch process is tested and proven to be scalable at pilot scale. Extensions of the concept are discussed to apply the concept to anaerobic fermentations, and to recycle the O2 that is co-generated with the formic acid to aerobic fermentation processes for intensification purposes.

A 9-pool metabolic structured kinetic model describing days to seconds dynamics of growth and product formation by Penicillium chrysogenum.

A powerful approach for the optimization of industrial bioprocesses is to perform detailed simulations integrating large-scale computational fluid dynamics (CFD) and cellular reaction dynamics (CRD). However, complex metabolic kinetic models containing a large number of equations pose formidable challenges in CFD-CRD coupling and computation time afterward. This necessitates to formulate a relatively simple but yet representative model structure. Such a kinetic model should be able to reproduce metabolic responses for short-term (mixing time scale of tens of seconds) and long-term (fed-batch cultivation of hours/days) dynamics in industrial bioprocesses. In this paper, we used Penicillium chrysogenum as a model system and developed a metabolically structured kinetic model for growth and production. By lumping the most important intracellular metabolites in 5 pools and 4 intracellular enzyme pools, linked by 10 reactions, we succeeded in maintaining the model structure relatively simple, while providing informative insight into the state of the organism. The performance of this 9-pool model was validated with a periodic glucose feast-famine cycle experiment at the minute time scale. Comparison of this model and a reported black box model for this strain shows the necessity of employing a structured model under feast-famine conditions. This proposed model provides deeper insight into the in vivo kinetics and, most importantly, can be straightforwardly integrated into a computational fluid dynamic framework for simulating complete fermentation performance and cell population dynamics in large scale and small scale fermentors. Biotechnol. Bioeng. 2017;114: 1733-1743. © 2017 Wiley Periodicals, Inc.

Proliferating bloodstream-form Trypanosoma brucei use a negligible part of consumed glucose for anabolic processes.

Our quantitative knowledge of carbon fluxes in the long slender bloodstream form (BSF) Trypanosoma brucei is mainly based on non-proliferating parasites, isolated from laboratory animals and kept in buffers. In this paper we present a carbon balance for exponentially growing bloodstream form trypanosomes. The cells grew with a doubling time of 5.3h, contained 46 µ mol of carbon (10(8) cells)(-1) and had a glucose consumption flux of 160 nmol min(-1) (10(8) cells)(-1). The molar ratio of pyruvate excreted versus glucose consumed was 2.1. Furthermore, analysis of the (13)C label distribution in pyruvate in (13)C-glucose incubations of exponentially growing trypanosomes showed that glucose was the sole substrate for pyruvate production. We conclude that the glucose metabolised in glycolysis was hardly, if at all, used for biosynthetic processes. Carbon flux through glycolysis in exponentially growing trypanosomes was 10 times higher than the incorporation of carbon into biomass. This biosynthetic carbon is derived from other precursors present in the nutrient rich growth medium. Furthermore, we found that the glycolytic flux was unaltered when the culture went into stationary phase, suggesting that most of the ATP produced in glycolysis is used for processes other than growth.

Identification of informative metabolic responses using a minibioreactor: a small step change in the glucose supply rate creates a large metabolic response in Saccharomyces cerevisiae.

In this study, a previously developed mini-bioreactor, the Biocurve, was used to identify an informative stimulus-response experiment. The identified stimulus-response experiment was a modest 50% shift-up in glucose uptake rate (qGLC) that unexpectedly resulted in a disproportionate transient metabolic response. The 50% shift-up in qGLC in the Biocurve resulted in a near tripling of the online measured oxygen uptake (qO2) and carbon dioxide production (qCO2) rates, suggesting a considerable mobilization of glycogen and trehalose. The 50% shift-up in qGLC was subsequently studied in detail in a conventional bioreactor (4 l working volume), which confirmed the results obtained with the Biocurve. Especially relevant is the observation that the 50% increase in glucose uptake rate led to a three-fold increase in glycolytic flux, due to mobilization of storage materials. This explains the unexpected ethanol and acetate secretion after the shift-up, in spite of the fact that after the shift-up the qGLC was far less than the critical value. Moreover, these results show that the correct in vivo fluxes in glucose pulse experiments cannot be obtained from the uptake and secretion rates only. Instead, the storage fluxes must also be accurately quantified. Finally, we speculate on the possible role that the transient increase in dissolved CO2 immediately after the 50% shift-up in qGLC could have played a part in triggering glycogen and trehalose mobilization.

Cytosolic NADPH balancing in Penicillium chrysogenum cultivated on mixtures of glucose and ethanol.

The in vivo flux through the oxidative branch of the pentose phosphate pathway (oxPPP) in Penicillium chrysogenum was determined during growth in glucose/ethanol carbon-limited chemostat cultures, at the same growth rate. Non-stationary (13)C flux analysis was used to measure the oxPPP flux. A nearly constant oxPPP flux was found for all glucose/ethanol ratios studied. This indicates that the cytosolic NADPH supply is independent of the amount of assimilated ethanol. The cofactor assignment in the model of van Gulik et al. (Biotechnol Bioeng 68(6):602-618, 2000) was supported using the published genome annotation of P. chrysogenum. Metabolic flux analysis showed that NADPH requirements in the cytosol remain nearly the same in these experiments due to constant biomass growth. Based on the cytosolic NADPH balance, it is known that the cytosolic aldehyde dehydrogenase in P. chrysogenum is NAD(+) dependent. Metabolic modeling shows that changing the NAD(+)-aldehyde dehydrogenase to NADP(+)-aldehyde dehydrogenase can increase the penicillin yield on substrate.

Fast dynamic response of the fermentative metabolism of Escherichia coli to aerobic and anaerobic glucose pulses.

The response of Escherichia coli cells to transient exposure (step increase) in substrate concentration and anaerobiosis leading to mixed-acid fermentation metabolism was studied in a two-compartment bioreactor system consisting of a stirred tank reactor (STR) connected to a mini-plug-flow reactor (PFR: BioScope, 3.5 mL volume). Such a system can mimic the situation often encountered in large-scale, fed-batch bioreactors. The STR represented the zones of a large-scale bioreactor that are far from the point of substrate addition and that can be considered as glucose limited, whereas the PFR simulated the region close to the point of substrate addition, where glucose concentration is much higher than in the rest of the bioreactor. In addition, oxygen-poor and glucose-rich regions can occur in large-scale bioreactors. The response of E. coli to these large-scale conditions was simulated by continuously pumping E. coli cells from a well stirred, glucose limited, aerated chemostat (D = 0.1 h(-1)) into the mini-PFR. A glucose pulse was added at the entrance of the PFR. In the PFR, a total of 11 samples were taken in a time frame of 92 s. In one case aerobicity in the PFR was maintained in order to evaluate the effects of glucose overflow independently of oxygen limitation. Accumulation of acetate and formate was detected after E. coli cells had been exposed for only 2 s to the glucose-rich (aerobic) region in the PFR. In the other case, the glucose pulse was also combined with anaerobiosis in the PFR. Glucose overflow combined with anaerobiosis caused the accumulation of formate, acetate, lactate, ethanol, and succinate, which were also detected as soon as 2 s after of exposure of E. coli cells to the glucose and O(2) gradients. This approach (STR-mini-PFR) is useful for a better understanding of the fast dynamic phenomena occurring in large-scale bioreactors and for the design of modified strains with an improved behavior under large-scale conditions.

Simultaneous quantification of free nucleotides in complex biological samples using ion pair reversed phase liquid chromatography isotope dilution tandem mass spectrometry.

A new sensitive and accurate analytical method has been developed for quantification of intracellular nucleotides in complex biological samples from cultured cells of different microorganisms such as Saccharomyces cerevisiae, Escherichia coli, and Penicillium chrysogenum. This method is based on ion pair reversed phase liquid chromatography electrospray ionization isotope dilution tandem mass spectrometry (IP-LC-ESI-ID-MS/MS. A good separation and low detection limits were observed for these compounds using dibutylamine as volatile ion pair reagent in the mobile phase of the LC. Uniformly (13)C-labeled isotopes of nucleotides were used as internal standards for both extraction and quantification of intracellular nucleotides. The method was validated by determining the linearity, sensitivity, and repeatability.

Dynamic 13C-tracer study of storage carbohydrate pools in aerobic glucose-limited Saccharomyces cerevisiae confirms a rapid steady-state turnover and fast mobilization during a modest stepup in the glucose uptake rate.

In this research, two dynamic (13)C-labeling experiments confirmed turnover and rapid mobilization of stored glycogen and trehalose in an aerobic glucose-limited chemostat (D=0.05 h(-1)) culture of Saccharomyces cerevisiae. In one experiment, the continuous feed to an aerobic glucose-limited chemostat culture of S. cerevisiae was instantaneously switched from naturally labeled to fully (13)C labeled while maintaining the same feed rate before and after the switch. The dynamic replacements of naturally labeled intracellular glycolytic intermediates and CO(2) (in the off-gas) with their (13)C-labeled equivalents were measured. The data of this experiment suggest that the continuous turnover of glycogen and trehalose is substantial (c. 1/3 of the glycolytic flux). The second experiment combined the medium switch with a shiftup in the glucose feeding rate (dilution rate shiftup from 0.05 to 0.10 h(-1)). This experiment triggered a strong but transient mobilization of storage carbon, that was channelled into glycolysis, causing a significant disruption in the dynamic labeling profile of glycolytic intermediates. The off-gas measurements in the shiftup experiment confirmed a considerable transient influx of (12)C-carbon into glycolysis after the combined medium switch and dilution rate shiftup. This study shows that for accurate in vivo kinetic interpretation of rapid pulse experiments, glycogen and trehalose metabolism must be taken into account.

Model reduction and a priori kinetic parameter identifiability analysis using metabolome time series for metabolic reaction networks with linlog kinetics.

In this work, we present a time-scale analysis based model reduction and parameter identifiability analysis method for metabolic reaction networks. The method uses the information obtained from short term chemostat perturbation experiments. We approximate the time constant of each metabolite pool by their turn-over time and classify the pools accordingly into two groups: fast and slow pools. We performed a priori model reduction, neglecting the dynamic term of the fast pools. By making use of the linlog approximative kinetics, we obtained a general explicit solution for the fast pools in terms of the slow pools by elaborating the degenerate algebraic system resulting from model reduction. The obtained relations yielded also analytical relations between a subset of kinetic parameters. These relations also allow to realize an analytical model reduction using lumped reaction kinetics. After solving these theoretical identifiability problems and performing model reduction, we carried out a Monte Carlo approach to study the practical identifiability problems. We illustrated the methodology on model reduction and theoretical/practical identifiability analysis on an example system representing the glycolysis in Saccharomyces cerevisiae cells.

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

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

Malic acid production by Saccharomyces cerevisiae: engineering of pyruvate carboxylation, oxaloacetate reduction, and malate export.

Malic acid is a potential biomass-derivable "building block" for chemical synthesis. Since wild-type Saccharomyces cerevisiae strains produce only low levels of malate, metabolic engineering is required to achieve efficient malate production with this yeast. A promising pathway for malate production from glucose proceeds via carboxylation of pyruvate, followed by reduction of oxaloacetate to malate. This redox- and ATP-neutral, CO(2)-fixing pathway has a theoretical maximum yield of 2 mol malate (mol glucose)(-1). A previously engineered glucose-tolerant, C(2)-independent pyruvate decarboxylase-negative S. cerevisiae strain was used as the platform to evaluate the impact of individual and combined introduction of three genetic modifications: (i) overexpression of the native pyruvate carboxylase encoded by PYC2, (ii) high-level expression of an allele of the MDH3 gene, of which the encoded malate dehydrogenase was retargeted to the cytosol by deletion of the C-terminal peroxisomal targeting sequence, and (iii) functional expression of the Schizosaccharomyces pombe malate transporter gene SpMAE1. While single or double modifications improved malate production, the highest malate yields and titers were obtained with the simultaneous introduction of all three modifications. In glucose-grown batch cultures, the resulting engineered strain produced malate at titers of up to 59 g liter(-1) at a malate yield of 0.42 mol (mol glucose)(-1). Metabolic flux analysis showed that metabolite labeling patterns observed upon nuclear magnetic resonance analyses of cultures grown on (13)C-labeled glucose were consistent with the envisaged nonoxidative, fermentative pathway for malate production. The engineered strains still produced substantial amounts of pyruvate, indicating that the pathway efficiency can be further improved.

Quantitative analysis of metabolites in complex biological samples using ion-pair reversed-phase liquid chromatography-isotope dilution tandem mass spectrometry.

A rapid, sensitive and selective ion-pair reversed-phase liquid chromatography-electrospray ionization isotope dilution tandem mass spectrometry (IP-LC-ESI-ID-MS/MS) was developed for quantitative analysis of free intracellular metabolites in cell cultures. As an application a group of compounds involved in penicillin biosynthesis pathway of Penicillium chrysogenum cells, such as penicillin G (PenG), 6-aminopenicillanic acid (6-APA), benzylpenicilloic acid (PIO), ortho-hydroxyphenyl acetic acid (o-OH-PAA), phenylacetic acid (PAA), 6-oxopipeidine-2-carboxylic acid (OPC), 8-hydroxypenicillic acid (8-HPA), L-alpha-(delta-aminoadipyl)-L-alpha-cystenyl-D-alpha-valine (ACV) and isopenicillin N (IPN) were chosen. (13)C-labeled analogs of the metabolites were added to the sample solutions as internal standards (I.S.). Sample mixtures were analyzed without any sample pretreatment. No extraction recovery check was needed because I.S. was added to the cell samples before extraction process. The method showed excellent precision (relative standard deviation (RSD)

13C-Labeled metabolic flux analysis of a fed-batch culture of elutriated Saccharomyces cerevisiae.

This study addresses the question of whether observable changes in fluxes in the primary carbon metabolism of Saccharomyces cerevisiae occur between the different phases of the cell division cycle. To detect such changes by metabolic flux analysis, a 13C-labeling experiment was performed with a fed-batch culture inoculated with a partially synchronized cell population obtained through centrifugal elutriation. Such a culture exhibits dynamic changes in the fractions of cells in different cell cycle phases over time. The mass isotopomer distributions of free intracellular metabolites in central carbon metabolism were measured by liquid chromatography-mass spectrometry. For four time points during the culture, these distributions were used to obtain the best estimates for the metabolic fluxes. The obtained flux fits suggested that the optimally fitted split ratio for the pentose phosphate pathway changed by almost a factor of 2 up and down around a value of 0.27 during the experiment. Statistical analysis revealed that some of the fitted flux distributions for different time points were significantly different from each other, indicating that cell cycle-dependent variations in cytosolic metabolic fluxes indeed occurred.

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

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

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.

A method for estimation of elasticities in metabolic networks using steady state and dynamic metabolomics data and linlog kinetics.

BACKGROUND: Dynamic modeling of metabolic reaction networks under in vivo conditions is a crucial step in order to obtain a better understanding of the (dis)functioning of living cells. So far dynamic metabolic models generally have been based on mechanistic rate equations which often contain so many parameters that their identifiability from experimental data forms a serious problem. Recently, approximative rate equations, based on the linear logarithmic (linlog) format have been proposed as a suitable alternative with fewer parameters. RESULTS: In this paper we present a method for estimation of the kinetic model parameters, which are equal to the elasticities defined in Metabolic Control Analysis, from metabolite data obtained from dynamic as well as steady state perturbations, using the linlog kinetic format. Additionally, we address the question of parameter identifiability from dynamic perturbation data in the presence of noise. The method is illustrated using metabolite data generated with a dynamic model of the glycolytic pathway of Saccharomyces cerevisiae based on mechanistic rate equations. Elasticities are estimated from the generated data, which define the complete linlog kinetic model of the glycolysis. The effect of data noise on the accuracy of the estimated elasticities is presented. Finally, identifiable subset of parameters is determined using information on the standard deviations of the estimated elasticities through Monte Carlo (MC) simulations. CONCLUSION: The parameter estimation within the linlog kinetic framework as presented here allows the determination of the elasticities directly from experimental data from typical dynamic and/or steady state experiments. These elasticities allow the reconstruction of the full kinetic model of Saccharomyces cerevisiae, and the determination of the control coefficients. MC simulations revealed that certain elasticities are potentially unidentifiable from dynamic data only. Addition of steady state perturbation of enzyme activities solved this problem.

Characterization of an experimental miniature bioreactor for cellular perturbation studies.

A mini bioreactor (3.0 mL volume) has been developed and shown to be a versatile tool for rapidly screening and quantifying the response of organisms on environmental perturbations. The mini bioreactor is essentially a plug flow device transformed into a well-mixed reactor by a recycle flow of the broth. The gas and liquid phases are separated by a silicone membrane. Dynamic mass transfer experiments were performed to determine the mass transfer capacities for oxygen and carbon dioxide. The mass transfer coefficients for oxygen and carbon dioxide were found to be 1.55 +/- 0.17 x 10(-5) m/s and 4.52 +/- 0.60 x 10(-6) m/s, respectively. Cultivation experiments with the 3.0 mL bioreactor show that (i) it can maintain biomass in the same physiological state as the 4.0 L lab scale bioreactor, (ii) reproducible perturbation experiments such as changing substrate uptake rate can be readily performed and the physiological response monitored quantitatively in terms of the O2 and CO2 uptake and production rates.

13C-labeled gluconate tracing as a direct and accurate method for determining the pentose phosphate pathway split ratio in Penicillium chrysogenum.

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

Short-term metabolome dynamics and carbon, electron, and ATP balances in chemostat-grown Saccharomyces cerevisiae CEN.PK 113-7D following a glucose pulse.

The in vivo kinetics in Saccharomyces cerevisiae CEN.PK 113-7D was evaluated during a 300-second transient period after applying a glucose pulse to an aerobic, carbon-limited chemostat culture. We quantified the responses of extracellular metabolites, intracellular intermediates in primary metabolism, intracellular free amino acids, and in vivo rates of O(2) uptake and CO(2) evolution. With these measurements, dynamic carbon, electron, and ATP balances were set up to identify major carbon, electron, and energy sinks during the postpulse period. There were three distinct metabolic phases during this time. In phase I (0 to 50 seconds after the pulse), the carbon/electron balances closed up to 85%. The accumulation of glycolytic and storage compounds accounted for 60% of the consumed glucose, caused an energy depletion, and may have led to a temporary decrease in the anabolic flux. In phase II (50 to 150 seconds), the fermentative metabolism gradually became the most important carbon/electron sink. In phase III (150 to 300 seconds), 29% of the carbon uptake was not identified in the measurements, and the ATP balance had a large surplus. These results indicate an increase in the anabolic flux, which is consistent with macroscopic balances of extracellular fluxes and the observed increase in CO(2) evolution associated with nonfermentative metabolism. The identified metabolic processes involving major carbon, electron, and energy sinks must be taken into account in in vivo kinetic models based on short-term dynamic metabolome responses.