Predicting Metabolic Adaptation Under Dynamic Substrate Conditions Using a Resource-Dependent Kinetic Model: A Case Study Using Saccharomyces cerevisiae.

Exposed to changes in their environment, microorganisms will adapt their phenotype, including metabolism, to ensure survival. To understand the adaptation principles, resource allocation-based approaches were successfully applied to predict an optimal proteome allocation under (quasi) steady-state conditions. Nevertheless, for a general, dynamic environment, enzyme kinetics will have to be taken into account which was not included in the linear resource allocation models. To this end, a resource-dependent kinetic model was developed and applied to the model organism Saccharomyces cerevisiae by combining published kinetic models and calibrating the model parameters to published proteomics and fluxomics datasets. Using this approach, we were able to predict specific proteomes at different dilution rates under chemostat conditions. Interestingly, the approach suggests that the occurrence of aerobic fermentation (Crabtree effect) in S. cerevisiae is not caused by space limitation in the total proteome but rather an effect of constraints on the mitochondria. When exposing the approach to repetitive, dynamic substrate conditions, the proteome space was allocated differently. Less space was predicted to be available for non-essential enzymes (reserve space). This could indicate that the perceived "overcapacity" present in experimentally measured proteomes may very likely serve a purpose in increasing the robustness of a cell to dynamic conditions, especially an increase of proteome space for the growth reaction as well as of the trehalose cycle that was shown to be essential in providing robustness upon stronger substrate perturbations. The model predictions of proteome adaptation to dynamic conditions were additionally evaluated against respective experimentally measured proteomes, which highlighted the model's ability to accurately predict major proteome adaptation trends. This proof of principle for the approach can be extended to production organisms and applied for both understanding metabolic adaptation and improving industrial process design.

NADH-driven poly-3-hydroxybutyrate accumulation in Escherichia coli: Data from enzymatic assays and oxygen-limited continuous cultures.

Biosynthesis of poly-3-hydroxybutyrate (PHB) as a fermentation product enables the coupling of growth and product generation. Moreover, the reduction of oxygen supply should reduce operative cost and increase product yield. Generation of PHB as a fermentation product depends on the in vivo activity of an NADH-preferring acetoacetyl-CoA reductase. Proof of this concept requires (i) quantification of the cofactor preference, in physiologically relevant conditions, of a putative NADH-preferring acetoacetyl-CoA reductase and (ii) verification of PHB accumulation using an NADH-preferring acetoacetyl-CoA reductase in a species naturally incapable of doing so, for example, Escherichia coli. This dataset contains kinetic data obtained by spectrophotometry and data from a continuous culture of an engineered E. coli strain accumulating PHB under oxygen-limiting conditions. In this dataset it is possible to find (1) enzyme stability assays; (2) initial rates and progress curves from reactions catalyzed by two acetoacetyl-CoA reductases; (3) estimations of the relative use of NADH and NADPH by two acetoacetyl-CoA reductases; (4) estimations of the flux capacity of the reaction catalyzed by an acetoacetyl-CoA reductase; (5) biomass composition of an engineered E. coli strain transformed with a plasmid; (6) calculation of reconciled specific rates of this engineered strain growing on sucrose as the sole carbon source under oxygen limitation and (7) metabolic fluxes distributions during the continuous growth of this engineered strain. Because a relatively small number of acetoacetyl-CoA reductases have been kinetically characterized, data and scripts here provided could be useful for further kinetic characterizations. Moreover, the procedure described to estimate biomass composition could be interesting to estimate plasmid and protein burden in other strains. Application of data reconciliation to fermentations should help to obtain specific rates consistent with the principle of mass and electron conservation. All the required data and scripts to perform these analyses are deposited in a Mendeley Data repository. This article was co-submitted with the manuscript entitled "An NADH preferring acetoacetyl-CoA reductase is engaged in poly-3-hydroxybutyrate accumulation in Escherichiasia. coli".

Metabolic engineering strategies for butanol production in Escherichia coli.

The global market of butanol is increasing due to its growing applications as solvent, flavoring agent, and chemical precursor of several other compounds. Recently, the superior properties of n-butanol as a biofuel over ethanol have stimulated even more interest. (Bio)butanol is natively produced together with ethanol and acetone by Clostridium species through acetone-butanol-ethanol fermentation, at noncompetitive, low titers compared to petrochemical production. Different butanol production pathways have been expressed in Escherichia coli, a more accessible host compared to Clostridium species, to improve butanol titers and rates. The bioproduction of butanol is here reviewed from a historical and theoretical perspective. All tested rational metabolic engineering strategies in E. coli to increase butanol titers are reviewed: manipulation of central carbon metabolism, elimination of competing pathways, cofactor balancing, development of new pathways, expression of homologous enzymes, consumption of different substrates, and molecular biology strategies. The progress in the field of metabolic modeling and pathway generation algorithms and their potential application to butanol production are also summarized here. The main goals are to gather all the strategies, evaluate the respective progress obtained, identify, and exploit the outstanding challenges.

Metabolic adjustment upon repetitive substrate perturbations using dynamic 13C-tracing in yeast.

BACKGROUND: Natural and industrial environments are dynamic with respect to substrate availability and other conditions like temperature and pH. Especially, metabolism is strongly affected by changes in the extracellular space. Here we study the dynamic flux of central carbon metabolism and storage carbohydrate metabolism under dynamic feast/famine conditions in Saccharomyces cerevisiae. RESULTS: The metabolic flux reacts fast and sensitive to cyclic perturbations in substrate availability. Compared to well-documented stimulus-response experiments using substrate pulses, different metabolic responses are observed. Especially, cells experiencing cyclic perturbations do not show a drop in ATP with the addition of glucose, but an immediate increase in energy charge. Although a high glycolytic flux of up to 5.4 mmol g DW-1  h-1 is observed, no overflow metabolites are detected. From famine to feast the glucose uptake rate increased from 170 to 4788 µmol g DW-1  h-1 in 24 s. Intracellularly, even more drastic changes were observed. Especially, the T6P synthesis rate increased more than 100-fold upon glucose addition. This response indicates that the storage metabolism is very sensitive to changes in glycolytic flux and counterbalances these rapid changes by diverting flux into large pools to prevent substrate accelerated death and potentially refill the central metabolism when substrates become scarce. Using 13C-tracer we found a dilution in the labeling of extracellular glucose, G6P, T6P and other metabolites, indicating an influx of unlabeled carbon. It is shown that glycogen and trehalose degradation via different routes could explain these observations. Based on the 13C labeling in average 15% of the carbon inflow is recycled via trehalose and glycogen. This average fraction is comparable to the steady-state turnover, but changes significantly during the cycle, indicating the relevance for dynamic regulation of the metabolic flux. CONCLUSIONS: Comparable to electric energy grids, metabolism seems to use storage units to buffer peaks and keep reserves to maintain a robust function. During the applied fast feast/famine conditions about 15% of the metabolized carbon were recycled in storage metabolism. Additionally, the resources were distributed different to steady-state conditions. Most remarkably is a fivefold increased flux towards PPP that generated a reversed flux of transaldolase and the F6P-producing transketolase reactions. Combined with slight changes in the biomass composition, the yield decrease of 5% can be explained.

In Vivo Analysis of NH4+ Transport and Central Nitrogen Metabolism in Saccharomyces cerevisiae during Aerobic Nitrogen-Limited Growth.

Ammonium is the most common N source for yeast fermentations. Although its transport and assimilation mechanisms are well documented, there have been only a few attempts to measure the in vivo intracellular concentration of ammonium and assess its impact on gene expression. Using an isotope dilution mass spectrometry (IDMS)-based method, we were able to measure the intracellular ammonium concentration in N-limited aerobic chemostat cultivations using three different N sources (ammonium, urea, and glutamate) at the same growth rate (0.05 h-1). The experimental results suggest that, at this growth rate, a similar concentration of intracellular (IC) ammonium, about 3.6 mmol NH4+/literIC, is required to supply the reactions in the central N metabolism, independent of the N source. Based on the experimental results and different assumptions, the vacuolar and cytosolic ammonium concentrations were estimated. Furthermore, we identified a futile cycle caused by NH3 leakage into the extracellular space, which can cost up to 30% of the ATP production of the cell under N-limited conditions, and a futile redox cycle between Gdh1 and Gdh2 reactions. Finally, using shotgun proteomics with protein expression determined relative to a labeled reference, differences between the various environmental conditions were identified and correlated with previously identified N compound-sensing mechanisms.IMPORTANCE In our work, we studied central N metabolism using quantitative approaches. First, intracellular ammonium was measured under different N sources. The results suggest that Saccharomyces cerevisiae cells maintain a constant NH4+ concentration (around 3 mmol NH4+/literIC), independent of the applied nitrogen source. We hypothesize that this amount of intracellular ammonium is required to obtain sufficient thermodynamic driving force. Furthermore, our calculations based on thermodynamic analysis of the transport mechanisms of ammonium suggest that ammonium is not equally distributed, indicating a high degree of compartmentalization in the vacuole. Additionally, metabolomic analysis results were used to calculate the thermodynamic driving forces in the central N metabolism reactions, revealing that the main reactions in the central N metabolism are far from equilibrium. Using proteomics approaches, we were able to identify major changes, not only in N metabolism, but also in C metabolism and regulation.

Excessive by-product formation: A key contributor to low isobutanol yields of engineered Saccharomyces cerevisiae strains.

It is theoretically possible to engineer Saccharomyces cerevisiae strains in which isobutanol is the predominant catabolic product and high-yielding isobutanol-producing strains are already reported by industry. Conversely, isobutanol yields of engineered S. cerevisiae strains reported in the scientific literature typically remain far below 10% of the theoretical maximum. This study explores possible reasons for these suboptimal yields by a mass-balancing approach. A cytosolically located, cofactor-balanced isobutanol pathway, consisting of a mosaic of bacterial enzymes whose in vivo functionality was confirmed by complementation of null mutations in branched-chain amino acid metabolism, was expressed in S. cerevisiae. Product formation by the engineered strain was analysed in shake flasks and bioreactors. In aerobic cultures, the pathway intermediate isobutyraldehyde was oxidized to isobutyrate rather than reduced to isobutanol. Moreover, significant concentrations of the pathway intermediates 2,3-dihydroxyisovalerate and α-ketoisovalerate, as well as diacetyl and acetoin, accumulated extracellularly. While the engineered strain could not grow anaerobically, micro-aerobic cultivation resulted in isobutanol formation at a yield of 0.018±0.003 mol/mol glucose. Simultaneously, 2,3-butanediol was produced at a yield of 0.649±0.067 mol/mol glucose. These results identify massive accumulation of pathway intermediates, as well as overflow metabolites derived from acetolactate, as an important, previously underestimated contributor to the suboptimal yields of 'academic' isobutanol strains. The observed patterns of by-product formation is consistent with the notion that in vivo activity of the iron-sulphur-cluster-requiring enzyme dihydroxyacid dehydratase is a key bottleneck in the present and previously described 'academic' isobutanol-producing yeast strains.

Interaction of storage carbohydrates and other cyclic fluxes with central metabolism: A quantitative approach by non-stationary 13C metabolic flux analysis.

13C labeling experiments in aerobic glucose limited cultures of Saccharomyces cerevisiae at four different growth rates (0.054; 0.101, 0.207, 0.307 h-1) are used for calculating fluxes that include intracellular cycles (e.g., storage carbohydrate cycles, exchange fluxes with amino acids), which are rearranged depending on the growth rate. At low growth rates the impact of the storage carbohydrate recycle is relatively more significant than at high growth rates due to a higher concentration of these materials in the cell (up to 560-fold) and higher fluxes relative to the glucose uptake rate (up to 16%). Experimental observations suggest that glucose can be exported to the extracellular space, and that its source is related to storage carbohydrates, most likely via the export and subsequent extracellular breakdown of trehalose. This hypothesis is strongly supported by 13C-labeling experimental data, measured extracellular trehalose, and the corresponding flux estimations.

An alternative, arginase-independent pathway for arginine metabolism in Kluyveromyces lactis involves guanidinobutyrase as a key enzyme.

Most available knowledge on fungal arginine metabolism is derived from studies on Saccharomyces cerevisiae, in which arginine catabolism is initiated by releasing urea via the arginase reaction. Orthologues of the S. cerevisiae genes encoding the first three enzymes in the arginase pathway were cloned from Kluyveromyces lactis and shown to functionally complement the corresponding deletion in S. cerevisiae. Surprisingly, deletion of the single K. lactis arginase gene KlCAR1 did not completely abolish growth on arginine as nitrogen source. Growth rate of the deletion mutant strongly increased during serial transfer in shake-flask cultures. A combination of RNAseq-based transcriptome analysis and (13)C-(15)N-based flux analysis was used to elucidate the arginase-independent pathway. Isotopic (13)C(15)N-enrichment in γ-aminobutyrate revealed succinate as the entry point in the TCA cycle of the alternative pathway. Transcript analysis combined with enzyme activity measurements indicated increased expression in the Klcar1Δ mutant of a guanidinobutyrase (EC.3.5.3.7), a key enzyme in a new pathway for arginine degradation. Expression of the K. lactis KLLA0F27995g (renamed KlGBU1) encoding guanidinobutyrase enabled S. cerevisiae to use guanidinobutyrate as sole nitrogen source and its deletion in K. lactis almost completely abolish growth on this nitrogen source. Phylogenetic analysis suggests that this enzyme activity is widespread in fungi.

Fatal attraction in glycolysis: how Saccharomyces cerevisiae manages sudden transitions to high glucose.

In the model eukaryote Saccharomyces cerevisiae, it has long been known that a functional trehalose pathway is indispensable for transitions to high glucose conditions. Upon addition of glucose, cells with a defect in trehalose 6-phosphate synthase (Tps1), the first committed step in the trehalose pathway, display what we have termed an imbalanced glycolytic state; in this state the flux through the upper part of glycolysis outpaces that through the lower part of glycolysis. As a consequence, the intermediate fructose 1,6-bisphosphate (FBP) accumulates at low concentrations of ATP and inorganic phosphate (Pi). Despite significant research efforts, a satisfactory understanding of the regulatory role that trehalose metabolism plays during such transitions has remained infamously unresolved. In a recent study, we demonstrate that the startup of glycolysis exhibits two dynamic fates: a proper, functional, steady state or the imbalanced state described above. Both states are stable, attracting states, and the probability distribution of initial states determines the fate of a yeast cell exposed to glucose. Trehalose metabolism steers the dynamics of glycolysis towards the proper functional state through its ATP hydrolysis activity; a mechanism that ensures that the demand and supply of ATP is balanced with Pi availability under dynamic conditions. [van Heerden et al. Science (2014), DOI: 10.1126/science.1245114.].

Unravelling the regulatory structure of biochemical networks using stimulus response experiments and large-scale model selection.

To unravel the complex in vivo regulatory interdependences of biochemical networks, experiments with the living organism are absolutely necessary. Stimulus response experiments (SREs) have become increasingly popular in recent years. The response of metabolite concentrations from all major parts of the central metabolism is monitored over time by modem analytical methods, producing several thousand data points. SREs are applied to determine enzyme kinetic parameters and to find unknown enzyme regulatory mechanisms. Owing to the complex regulatory structure of metabolic networks and the amount of measured data, the evaluation of an SRE has to be extensively supported by modelling. If the enzyme regulatory mechanisms are part of the investigation, a large number of models with different enzyme kinetics have to be tested for their ability to reproduce the observed behaviour. In this contribution, a systematic model-building process for data-driven exploratory modelling is introduced with the aim of discovering essential features of the biological system. The process is based on data pre-processing, correlation-based hypothesis generation, automatic model family generation, large-scale model selection and statistical analysis of the best-fitting models followed by an extraction of common features. It is illustrated by the example of the aromatic amino acid synthesis pathway in Escherichia coli.