Physiological effects of nitrogen starvation in an anaerobic batch culture of Saccharomyces cerevisiae

Coarse-Grained Modeling Elucidates Differential Metabolism of Saccharomyces cerevisiae under Varied Nutrient Limitations

Microorganisms such as Saccharomyces cerevisiae have a native ability to adapt their metabolism to varying nutrient conditions. Understanding their responses to nutrient limitations is critical for decoding cellular physiology and designing strategies for metabolic engineering. While the influence of carbon availability on yeast metabolism has been extensively studied, the role of nitrogen availability remains relatively underexplored. In this study, we utilized a coarse-grained kinetic model to systematically analyze and compare the effects of carbon and nitrogen limitations on yeast metabolism. Our model successfully revealed the differential metabolic characteristics of S. cerevisiae under carbon- and nitrogen-limited chemostat conditions. It also highlighted the significance of protein activity regulation at varying carbon-to-nitrogen ratios, and elucidated distinct strategies employed to maintain ATP homeostasis. This study provides a computational tool for investigating yeast physiology under nutrient limitations and offers quantitative and mechanistic insights into yeast metabolism.

An integrated multiphase dynamic genome-scale model explains batch fermentations led by species of the Saccharomyces genus

During batch fermentation, a variety of compounds are synthesized, as microorganisms undergo distinct growth phases: lag, exponential, growth-no-growth transition, stationary, and decay. A detailed understanding of the metabolic pathways involved in these phases is crucial for optimizing the production of target compounds. Dynamic flux balance analysis (dFBA) offers insight into the dynamics of metabolic pathways. However, explaining secondary metabolism remains a challenge. A multiphase and multi-objective dFBA scheme (MPMO model) has been proposed for this purpose. However, its formulation is discontinuous, changing from phase to phase; its accuracy in predicting intracellular fluxes is hampered by the lack of a mechanistic link between phases; and its simulation requires considerable computational effort. To address these limitations, we combine a novel model with a genome-scale model to predict the distribution of intracellular fluxes throughout batch fermentation. This integrated multiphase continuous model (IMC) has a unique formulation over time, and it incorporates empirical regulatory descriptions to automatically identify phase transitions and incorporates the hypotheses that yeasts might vary their cellular objective over time to adapt to the changing environment. We validated the predictive capacity of the IMC model by comparing its predictions with intracellular metabolomics data for Saccharomyces uvarum during batch fermentation. The model aligns well with the data, confirming its predictive capabilities. Notably, the IMC model accurately predicts trehalose accumulation, which was enforced in the MPMO model. We further demonstrate the generalizability of the IMC model, explaining the dynamics of primary and secondary metabolism of three Saccharomyces species. The model provides biological insights consistent with the literature and metabolomics data, establishing it as a valuable tool for exploring the dynamics of novel fermentation processes.IMPORTANCEThis work presents an integrated multiphase continuous dynamic genome-scale model (IMC model) for batch fermentation, a crucial process widely used in industry to produce biofuels, enzymes, pharmaceuticals, and food products or ingredients. The IMC model integrates a continuous kinetic model with a genome-scale model to address the critical limitations of existing dynamic flux balance analysis schemes, such as the difficulty of explaining secondary metabolism, the lack of mechanistic links between growth phases, or the high computational demands. The model also introduces the hypothesis that cells adapt the FBA objective over time. The IMC improves the accuracy of intracellular flux predictions and simplifies the implementation process with a unique dFBA formulation over time. Its ability to predict both primary and secondary metabolism dynamics in different Saccharomyces species underscores its versatility and robustness. Furthermore, its alignment with empirical metabolomics data validates its predictive power, offering valuable insights into metabolic processes during batch fermentation. These advances pave the way for optimizing fermentation processes, potentially leading to more efficient production of target compounds and novel biotechnological applications.

Parallel proteomics and phosphoproteomics defines starvation signal specific processes in cell quiescence

Cells arrest growth and enter a quiescent state upon nutrient deprivation. However, the molecular processes by which cells respond to different starvation signals to regulate exit from the cell division cycle and initiation of quiescence remains poorly understood. To study the role of protein expression and signaling in quiescence we combined temporal profiling of the proteome and phosphoproteome using stable isotope labeling with amino acids in cell culture (SILAC) in Saccharomyces cerevisiae (budding yeast). We find that carbon and phosphorus starvation signals activate quiescence through largely distinct remodeling of the proteome and phosphoproteome. However, increased expression of mitochondrial proteins is associated with quiescence establishment in response to both starvation signals. Deletion of the putative quiescence regulator RIM15, which encodes a serine-threonine kinase, results in reduced survival of cells starved for phosphorus and nitrogen, but not carbon. However, we identified common protein phosphorylation roles for RIM15 in quiescence that are enriched for RNA metabolism and translation. We also find evidence for RIM15-mediated phosphorylation of some targets, including IGO1, prior to starvation consistent with a functional role for RIM15 in proliferative cells. Finally, our results reveal widespread catabolism of amino acids in response to nitrogen starvation, indicating widespread amino acid recycling via salvage pathways in conditions lacking environmental nitrogen. Our study defines an expanded quiescent proteome and phosphoproteome in yeast, and highlights the multiple coordinated molecular processes at the level of protein expression and phosphorylation that are required for quiescence.

Parameter Estimation of Dynamic Beer Fermentation Models

In this study, two dynamic models of beer fermentation are proposed, and their parameters are estimated using experimental data collected during several batch experiments initiated with different sugar concentrations. Biomass, sugar, ethanol, and vicinal diketone concentrations are measured off-line with an analytical system while two on-line immersed probes deliver temperature, ethanol concentration, and carbon dioxide exhaust rate measurements. Before proceeding to the estimation of the unknown model parameters, a structural identifiability analysis is carried out to investigate the measurement configuration and the kinetic model structure. The model predictive capability is investigated in cross-validation, in view of opening up new perspectives for monitoring and control purposes. For instance, the dynamic model could be used as a predictor in receding-horizon observers and controllers.

Consideration of Maintenance in Wine Fermentation Modeling

We show that a simple model with a maintenance term can satisfactorily reproduce the simulations of several existing models of wine fermentation from the literature, as well as experimental data. The maintenance describes a consumption of the nitrogen that is not entirely converted into biomass. We show also that considering a maintenance term in the model is equivalent to writing a model with a variable yield that can be estimated from data.

A Multiphase Multiobjective Dynamic Genome-Scale Model Shows Different Redox Balancing among Yeast Species of the Saccharomyces Genus in Fermentation

Yeasts constitute over 1,500 species with great potential for biotechnology. Still, the yeast Saccharomyces cerevisiae dominates industrial applications, and many alternative physiological capabilities of lesser-known yeasts are not being fully exploited. While comparative genomics receives substantial attention, little is known about yeasts’ metabolic specificity in batch cultures. Here, we propose a multiphase multiobjective dynamic genome-scale model of yeast batch cultures that describes the uptake of carbon and nitrogen sources and the production of primary and secondary metabolites. The model integrates a specific metabolic reconstruction, based on the consensus Yeast8, and a kinetic model describing the time-varying culture environment. In addition, we proposed a multiphase multiobjective flux balance analysis to compute the dynamics of intracellular fluxes. We then compared the metabolism of S. cerevisiae and Saccharomyces uvarum strains in a rich medium fermentation. The model successfully explained the experimental data and brought novel insights into how cryotolerant strains achieve redox balance. The proposed model (along with the corresponding code) provides a comprehensive picture of the main steps occurring inside the cell during batch cultures and offers a systematic approach to prospect or metabolically engineering novel yeast cell factories.

IMPORTANCE Nonconventional yeast species hold the promise to provide novel metabolic routes to produce industrially relevant compounds and tolerate specific stressors, such as cold temperatures. This work validated the first multiphase multiobjective genome-scale dynamic model to describe carbon and nitrogen metabolism throughout batch fermentation. To test and illustrate its performance, we considered the comparative metabolism of three yeast strains of the Saccharomyces genus in rich medium fermentation. The study revealed that cryotolerant Saccharomyces species might use the γ-aminobutyric acid (GABA) shunt and the production of reducing equivalents as alternative routes to achieve redox balance, a novel biological insight worth being explored further. The proposed model (along with the provided code) can be applied to a wide range of batch processes started with different yeast species and media, offering a systematic and rational approach to prospect nonconventional yeast species metabolism and engineering novel cell factories.

Comparative uptake of exogenous thiamine and subsequent metabolic footprint in Saccharomyces cerevisiae and Kluyveromyces marxianus under simulated oenological conditions

Managed inoculation of non-Saccharomyces yeast species is regarded as a practical way to introduce new characteristics to wine. However, these yeasts struggle to survive until fermentation is complete. Kluyveromyces marxianus IWBT Y885 is one such yeast. Although it displays interesting oenological properties, a longer persistence during alcoholic fermentation would warranty a stronger impact on wine composition. A key factor for survival, growth and sustained metabolic activity of all yeasts is their nutrient requirements. Thus, identifying nutrients that are essential for maximising fermentation performance, and subsequently ensuring adequate levels of nutrients, is a means to ensure significant contribution of yeasts to wine properties. This study aimed to identify essential nutrients, other than previously studied sugars and nitrogen, for maximum impact of K. marxianus Y885, as well as to characterise the outcomes of their utilisation. A multifactorial experimental design was employed to investigate the impact of nutrient concentrations on fermentation performance with K. marxianus Y885 in synthetic must. B-complex vitamins most significantly impacted fermentation performance of K. marxianus Y885 compared to other nutrient groups investigated. Considering the well-established role of the vitamin, thiamine, for maximum fermentation performance during winemaking and the fact that it may be supplemented to wine fermentations legally, the responses to specifically exogenous thiamine concentration for K. marxianus Y885 and Saccharomyces cerevisiae EC1118 were compared in terms of population viability, fermentation rate, total sugars utilised, thiamine assimilation kinetics, and final wine composition. A saturation effect for initial thiamine concentration of K. marxianus Y885 fermentations was characterised, with a maximum fermentation rate and over 90% of available sugars utilisation obtained at 0.25 mg/L. An appreciably larger comparative increase in exponential cell growth rate, maximum population, fermentation rate and total CO₂ production for K. marxianus Y885 compared to S. cerevisiae EC1118 revealed a greater necessity for thiamine to ensure maximum fermentation performance. A delayed uptake of thiamine at higher concentrations for K. marxianus Y885 suggested differential regulation of thiamine uptake compared to S. cerevisiae EC1118. In addition, different trends in metabolites produced between species suggest that thiamine concentration impacts the carbon metabolic flux differently in these two yeasts, potentially impacting final wine properties.

A fattening factor to quantify the accumulation ability of microorganisms under N-starvation

Many microorganisms can accumulate biomass in the form of lipids and polysaccharides, which can be used for biofuels, bioplastics, food and feed. Some innovative bioprocesses exploit the competitive advantage provided by such accumulation ability, mainly under N-starvation, to select high-accumulating strains against biological contaminants, by using uncoupled nutrient feeding. However, there is no general and easily comparable parameter available to compare biomass accumulation ability among different microbial strains, which could measure the competitive advantage. Here, a parameter termed "fattening factor" (η_x) is described to quantify such strain-specific biomass accumulation ability in bacteria, yeasts and microalgae. This parameter measures how many fold a microbial population can increase its biomass just as the result of accumulation. It is derived from considerations about the main metabolic aspects of cells' response to N-starvation, which induces variations in cell cycle, biomass production and biochemical composition. The fattening factor described here should be easily estimatable in N-starvation for every culturable microbial strain, by measuring the amount of accumulated biomass.

Cultivation processes to select microorganisms with high accumulation ability

The microbial ability to accumulate biomolecules is fundamental for different biotechnological applications aiming at the production of biofuels, food and bioplastics. However, high accumulation is a selective advantage only under certain stressful conditions, such as nutrient depletion, characterized by lower growth rate. Conventional bioprocesses maintain an optimal and stable environment for large part of the cultivation, that doesn't reward cells for their accumulation ability, raising the risk of selection of contaminant strains with higher growth rate, but lower accumulation of products. Here in this work the physiological responses of different microorganisms (microalgae, bacteria, yeasts) under N-starvation and energy starvation are reviewed, with the aim to furnish relevant insights exploitable to develop tailored bioprocesses to select specific strains for their higher accumulation ability. Microorganism responses to starvation are reviewed focusing on cell cycle, biomass production and variations in biochemical composition. Then, the work describes different innovative bioprocess configurations exploiting uncoupled nutrient feeding strategies (feast-famine), tailored to maintain a selective pressure to reward the strains with higher accumulation ability in mixed microbial populations. Finally, the main models developed in recent studies to describe and predict microbial growth and intracellular accumulation upon N-starvation and feast-famine conditions have been reviewed.

Screening of Saccharomyces strains for the capacity to produce desirable fermentative compounds under the influence of different nitrogen sources in synthetic wine fermentations

A collection of 33 Saccharomyces yeasts were used for wine fermentation with a sole nitrogen source: ammonium and four individual aroma-inducing amino acids. The fermentation performance and chemical wine composition were evaluated. The most valuable nitrogen sources were valine as a fermentation promoter on non-cerevisiae strains, phenylalanine as fruity aromas enhancer whereas the ethanol yield was lessened by leucine and isoleucine. S. cerevisiae SC03 and S. kudriavzevii SK02 strains showed to be the greatest producers of fruity ethyl esters while S. kudriavzevii strains SK06 and SK07 by shortening the fermentation duration. S. uvarum strains produced the greatest succinic acid amounts and, together with S. eubayanus, they reached the highest production of 2-phenylethanol and its acetate ester; whereas S. kudriavzevii strains were found to be positively related to high glycerol production.

Cellular quiescence in budding yeast

Cellular quiescence, the temporary and reversible exit from proliferative growth, is the predominant state of all cells. However, our understanding of the biological processes and molecular mechanisms that underlie cell quiescence remains incomplete. As with the mitotic cell cycle, budding and fission yeast are preeminent model systems for studying cellular quiescence owing to their rich experimental toolboxes and the evolutionary conservation across eukaryotes of pathways and processes that control quiescence. Here, we review current knowledge of cell quiescence in budding yeast and how it pertains to cellular quiescence in other organisms, including multicellular animals. Quiescence entails large-scale remodeling of virtually every cellular process, organelle, gene expression, and metabolic state that is executed dynamically as cells undergo the initiation, maintenance, and exit from quiescence. We review these major transitions, our current understanding of their molecular bases, and highlight unresolved questions. We summarize the primary methods employed for quiescence studies in yeast and discuss their relative merits. Understanding cell quiescence has important consequences for human disease as quiescent single-celled microbes are notoriously difficult to kill and quiescent human cells play important roles in diseases such as cancer. We argue that research on cellular quiescence will be accelerated through the adoption of common criteria, and methods, for defining cell quiescence. An integrated approach to studying cell quiescence, and a focus on the behavior of individual cells, will yield new insights into the pathways and processes that underlie cell quiescence leading to a more complete understanding of the life cycle of cells. TAKE AWAY: Quiescent cells are viable cells that have reversibly exited the cell cycle Quiescence is induced in response to a variety of nutrient starvation signals Quiescence is executed dynamically through three phases: initiation, maintenance, and exit Quiescence entails large-scale remodeling of gene expression, organelles, and metabolism Single-cell approaches are required to address heterogeneity among quiescent cells.

ATPase-based implementation of enforced ATP wasting in Saccharomyces cerevisiae for improved ethanol production

BACKGROUND

Enforced ATP wasting has been recognized as a promising metabolic engineering strategy to enhance the microbial production of metabolites that are coupled to ATP generation. It also appears to be a suitable approach to improve production of ethanol by Saccharomyces cerevisiae. In the present study, we constructed different S. cerevisiae strains with heterologous expression of genes of the ATP-hydrolyzing F₁-part of the ATPase enzyme to induce enforced ATP wasting and quantify the resulting effect on biomass and ethanol formation.

RESULTS

In contrast to genomic integration, we found that episomal expression of the αβγ subunits of the F₁-ATPase genes of Escherichia coli in S. cerevisiae resulted in significantly increased ATPase activity, while neither genomic integration nor episomal expression of the β subunit from Trichoderma reesei could enhance ATPase activity. When grown in minimal medium under anaerobic growth-coupled conditions, the strains expressing E. coli's F₁-ATPase genes showed significantly improved ethanol yield (increase of 10% compared to the control strain). However, elevated product formation reduces biomass formation and, therefore, volumetric productivity. We demonstrate that this negative effect can be overcome under growth-decoupled (nitrogen-starved) operation with high and constant biomass concentration. Under these conditions, which mimic the second (production) phase of a two-stage fermentation process, the ATPase-expressing strains showed significant improvement in volumetric productivity (up to 111%) compared to the control strain.

CONCLUSIONS

Our study shows that expression of genes of the F₁-portion of E. coli's ATPase induces ATPase activity in S. cerevisiae and can be a promising way to improve ethanol production. This ATP-wasting strategy can be easily applied to other metabolites of interest, whose formation is coupled to ATP generation.

Genetic interaction profiles of regulatory kinases differ between environmental conditions and cellular states

Cell growth and quiescence in eukaryotic cells is controlled by an evolutionarily conserved network of signaling pathways. Signal transduction networks operate to modulate a wide range of cellular processes and physiological properties when cells exit proliferative growth and initiate a quiescent state. How signaling networks function to respond to diverse signals that result in cell cycle exit and establishment of a quiescent state is poorly understood. Here, we studied the function of signaling pathways in quiescent cells using global genetic interaction mapping in the model eukaryotic cell, Saccharomyces cerevisiae (budding yeast). We performed pooled analysis of genotypes using molecular barcode sequencing (Bar-seq) to test the role of ~4,000 gene deletion mutants and ~12,000 pairwise interactions between all non-essential genes and the protein kinase genes TOR1, RIM15, and PHO85 in three different nutrient-restricted conditions in both proliferative and quiescent cells. We detect up to 10-fold more genetic interactions in quiescent cells than proliferative cells. We find that both individual gene effects and genetic interaction profiles vary depending on the specific pro-quiescence signal. The master regulator of quiescence, RIM15, shows distinct genetic interaction profiles in response to different starvation signals. However, vacuole-related functions show consistent genetic interactions with RIM15 in response to different starvation signals, suggesting that RIM15 integrates diverse signals to maintain protein homeostasis in quiescent cells. Our study expands genome-wide genetic interaction profiling to additional conditions, and phenotypes, and highlights the conditional dependence of epistasis.

Global analysis of protein homomerization in Saccharomyces cerevisiae

In vivo analyses of the occurrence, subcellular localization, and dynamics of protein–protein interactions (PPIs) are important issues in functional proteomic studies. The bimolecular fluorescence complementation (BiFC) assay has many advantages in that it provides a reliable way to detect PPIs in living cells with minimal perturbation of the structure and function of the target proteins. Previously, to facilitate the application of the BiFC assay to genome-wide analysis of PPIs, we generated a collection of yeast strains expressing full-length proteins tagged with the N-terminal fragment of Venus (VN), a yellow fluorescent protein variant, from their own native promoters. In the present study, we constructed a VC (the C-terminal fragment of Venus) fusion library consisting of 5671 MATα strains expressing C-terminally VC-tagged proteins (representing ∼91% of the yeast proteome). For genome-wide analysis of protein homomer formation, we mated each strain in the VC fusion library with its cognate strain in the VN fusion library and performed the BiFC assay. From this analysis, we identified 186 homomer candidates. We further investigated the functional relevance of the homomerization of Pln1, a yeast perilipin. Our data set provides a useful resource for understanding the physiological roles of protein homomerization. Furthermore, the VC fusion library together with the VN fusion library will provide a valuable platform to systematically analyze PPIs in the natural cellular context.

Achieving Metabolic Flux Analysis for S. cerevisiae at a Genome-Scale: Challenges, Requirements, and Considerations

Recent advances in 13C-Metabolic flux analysis (13C-MFA) have increased its capability to accurately resolve fluxes using a genome-scale model with narrow confidence intervals without pre-judging the activity or inactivity of alternate metabolic pathways. However, the necessary precautions, computational challenges, and minimum data requirements for successful analysis remain poorly established. This review aims to establish the necessary guidelines for performing 13C-MFA at the genome-scale for a compartmentalized eukaryotic system such as yeast in terms of model and data requirements, while addressing key issues such as statistical analysis and network complexity. We describe the various approaches used to simplify the genome-scale model in the absence of sufficient experimental flux measurements, the availability and generation of reaction atom mapping information, and the experimental flux and metabolite labeling distribution measurements to ensure statistical validity of the obtained flux distribution. Organism-specific challenges such as the impact of compartmentalization of metabolism, variability of biomass composition, and the cell-cycle dependence of metabolism are discussed. Identification of errors arising from incorrect gene annotation and suggested alternate routes using MFA are also highlighted.

Metabolic flux analysis during the exponential growth phase of Saccharomyces cerevisiae in wine fermentations

As a consequence of the increase in global average temperature, grapes with the adequate phenolic and aromatic maturity tend to be overripe by the time of harvest, resulting in increased sugar concentrations and imbalanced C/N ratios in fermenting musts. This fact sets obvious additional hurdles in the challenge of obtaining wines with reduced alcohols levels, a new trend in consumer demands. It would therefore be interesting to understand Saccharomyces cerevisiae physiology during the fermentation of must with these altered characteristics. The present study aims to determine the distribution of metabolic fluxes during the yeast exponential growth phase, when both carbon and nitrogen sources are in excess, using continuous cultures. Two different sugar concentrations were studied under two different winemaking temperature conditions. Although consumption and production rates for key metabolites were severely affected by the different experimental conditions studied, the general distribution of fluxes in central carbon metabolism was basically conserved in all cases. It was also observed that temperature and sugar concentration exerted a higher effect on the pentose phosphate pathway and glycerol formation than on glycolysis and ethanol production. Additionally, nitrogen uptake, both quantitatively and qualitatively, was strongly influenced by environmental conditions. This work provides the most complete stoichiometric model used for Metabolic Flux Analysis of S. cerevisiae in wine fermentations employed so far, including the synthesis and release of relevant aroma compounds and could be used in the design of optimal nitrogen supplementation of wine fermentations.

Effect of oxygen and lipid supplementation on the volatile composition of chemically defined medium and Chardonnay wine fermented with Saccharomyces cerevisiae

Oxygen or lipids are required to complete stressful alcoholic fermentation. Lack of these nutrients can inhibit sugar uptake and growth, which leads to incomplete or 'stuck' fermentation. Oxygen or lipids supplementation not only restores yeast fermentative activity and also affects formation of yeast volatile metabolites. To clarify the effect of oxygen and lipid supplementation on the formation of flavour active metabolites during wine fermentation, we evaluated the addition of these two nutrients to chemically defined grape juice and filter clarified Chardonnay must. Lipid addition increased the concentration of esters, higher alcohols and volatile acids, whereas oxygen increased the concentration of higher alcohols and altered the proportion of acetate to ethyl esters and the proportion of branch-chain acids to medium-chain fatty acids. Combined addition of lipids and oxygen showed an additive effect on concentration of higher alcohols whereas oxygen suppressed the enhancing effect of lipids on formation of esters and volatile acids. Our results demonstrate the potential of lipid and oxygen supplementation for the manipulation of wine aroma in white wine fermentation.

Detection of transcriptional triggers in the dynamics of microbial growth: application to the respiratorily versatile bacterium Shewanella oneidensis

The capacity of microorganisms to respond to variable external conditions requires a coordination of environment-sensing mechanisms and decision-making regulatory circuits. Here, we seek to understand the interplay between these two processes by combining high-throughput measurement of time-dependent mRNA profiles with a novel computational approach that searches for key genetic triggers of transcriptional changes. Our approach helped us understand the regulatory strategies of a respiratorily versatile bacterium with promising bioenergy and bioremediation applications, Shewanella oneidensis, in minimal and rich media. By comparing expression profiles across these two conditions, we unveiled components of the transcriptional program that depend mainly on the growth phase. Conversely, by integrating our time-dependent data with a previously available large compendium of static perturbation responses, we identified transcriptional changes that cannot be explained solely by internal network dynamics, but are rather triggered by specific genes acting as key mediators of an environment-dependent response. These transcriptional triggers include known and novel regulators that respond to carbon, nitrogen and oxygen limitation. Our analysis suggests a sequence of physiological responses, including a coupling between nitrogen depletion and glycogen storage, partially recapitulated through dynamic flux balance analysis, and experimentally confirmed by metabolite measurements. Our approach is broadly applicable to other systems.

Different selective pressures lead to different genomic outcomes as newly-formed hybrid yeasts evolve

BACKGROUND

Interspecific hybridization occurs in every eukaryotic kingdom. While hybrid progeny are frequently at a selective disadvantage, in some instances their increased genome size and complexity may result in greater stress resistance than their ancestors, which can be adaptively advantageous at the edges of their ancestors' ranges. While this phenomenon has been repeatedly documented in the field, the response of hybrid populations to long-term selection has not often been explored in the lab. To fill this knowledge gap we crossed the two most distantly related members of the Saccharomyces sensu stricto group, S. cerevisiae and S. uvarum, and established a mixed population of homoploid and aneuploid hybrids to study how different types of selection impact hybrid genome structure.

RESULTS

As temperature was raised incrementally from 31°C to 46.5°C over 500 generations of continuous culture, selection favored loss of the S. uvarum genome, although the kinetics of genome loss differed among independent replicates. Temperature-selected isolates exhibited greater inherent and induced thermal tolerance than parental species and founding hybrids, and also exhibited ethanol resistance. In contrast, as exogenous ethanol was increased from 0% to 14% over 500 generations of continuous culture, selection favored euploid S. cerevisiae x S. uvarum hybrids. Ethanol-selected isolates were more ethanol tolerant than S. uvarum and one of the founding hybrids, but did not exhibit resistance to temperature stress. Relative to parental and founding hybrids, temperature-selected strains showed heritable differences in cell wall structure in the forms of increased resistance to zymolyase digestion and Micafungin, which targets cell wall biosynthesis.

CONCLUSIONS

This is the first study to show experimentally that the genomic fate of newly-formed interspecific hybrids depends on the type of selection they encounter during the course of evolution, underscoring the importance of the ecological theatre in determining the outcome of the evolutionary play.

Comparative secretome investigation of Magnaporthe oryzae proteins responsive to nitrogen starvation

Magnaporthe oryzae is a fungal pathogen that causes blast disease in rice. During its early infection process, during which starvation of nutrients, including nitrogen, prevails before establishment of successful infection, the fungally secreted proteins play an important role in the pathogenicity and stress response. In this study, M. oryzae-secreted proteins were investigated in an N-deficient minimal medium using two-dimensional gel electrophoresis (2-DGE) coupled with mass spectrometry analysis (MALDI-TOF-MS and μLC-ESI-MS/MS). The 2-DGE analysis of secreted proteins detected 89 differentially expressed protein spots (14 downregulated and 75 upregulated) responsive to N starvation. Eighty five of the protein spots were identified by mass spectrometry analyses. Identified proteins were mainly cell wall hydrolase enzymes (22.4%), protein and lipid hydrolases (24.7%), reactive oxygen species detoxifying proteins (22.4%), and proteins with unknown function (14.1%), suggesting early production of prerequisite proteins for successful infection of the host. SignalP analysis predicted the presence of signal peptides in 67% of the identified proteins, suggesting that in addition to the classical Golgi/endoplasmic reticulum secretory pathway, M. oryzae might possess other, as yet undefined, secretory pathways. Those nonclassical or leaderless secretion proteins accounted for 25.9% of the total identified proteins by TatP and SecretomeP predictions. Semiquantitative reverse transcriptase polymerase chain reaction of seven randomly selected N-responsive secreted proteins also revealed a good correlation between RNA and protein levels. Taken together, the establishment of the M. oryzae secretome that is responsive to N starvation provides the first evidence of the secretion of 60 unreported and 25 previously known proteins. This developed protein inventory could be exploited to improve our understanding of the secretory mechanisms of M. oryzae and its invasive growth process in rice tissue.

Continuous Fermentation of Undetoxified Dilute Acid Lignocellulose Hydrolysate by Saccharomycescerevisiae ATCC 96581 Using Cell Recirculation

Saccharomyces cerevisiae ATCC 96581 was cultivated in a chemostat reactor with undetoxified dilute acid softwood hydrolysate as the only carbon and energy source. The effects of nutrient addition, dilution rate, cell recirculation, and microaerobicity were investigated. Fermentation of unsupplemented dilute acid lignocellulose hydrolysate at D = 0.10 h(-1) in an anaerobic continuous reactor led to washout. Addition of ammonium sulfate or yeast extract was insufficient for obtaining steady state. In contrast, dilute acid lignocellulose hydrolysate supplemented with complete mineral medium, except for the carbon and energy source, was fermentable under anaerobic steady-state conditions at dilution rates up to 0.14 h(-1). Under these conditions, washout occurred at D = 0.15 h(-1). This was preceded by a drop in fermentative capacity and a very high specific ethanol production rate. Growth at all different dilution rates tested resulted in residual sugar in the chemostat. Cell recirculation (90%), achieved by cross-flow filtration, increased the sugar conversion rate from 92% to 99% at D = 0.10 h(-1). Nutrient addition clearly improved the long-term ethanol productivity in the recirculation cultures. Application of microaerobic conditions on the nutrient-supplemented recirculation cultures resulted in a higher production of biomass, a higher cellular protein content, and improved fermentative capacity, which further improves the robustness of fermentation of undetoxified lignocellulose hydrolysate.

Starvation response of Saccharomyces cerevisiae grown in anaerobic nitrogen- or carbon-limited chemostat cultures

Anaerobic starvation conditions are frequent in industrial fermentation and can affect the performance of the cells. In this study, the anaerobic carbon or nitrogen starvation response of Saccharomyces cerevisiae was investigated for cells grown in anaerobic carbon or nitrogen-limited chemostat cultures at a dilution rate of 0.1 h(-1) at pH 3.25 or 5. Lactic or benzoic acid was present in the growth medium at different concentrations, resulting in 16 different growth conditions. At steady state, cells were harvested and then starved for either carbon or nitrogen for 24 h under anaerobic conditions. We measured fermentative capacity, glucose uptake capacity, intracellular ATP content, and reserve carbohydrates and found that the carbon, but not the nitrogen, starvation response was dependent upon the previous growth conditions. All cells subjected to nitrogen starvation retained a large portion of their initial fermentative capacity, independently of previous growth conditions. However, nitrogen-limited cells that were starved for carbon lost almost all their fermentative capacity, while carbon-limited cells managed to preserve a larger portion of their fermentative capacity during carbon starvation. There was a positive correlation between the amount of glycogen before carbon starvation and the fermentative capacity and ATP content of the cells after carbon starvation. Fermentative capacity and glucose uptake capacity were not correlated under any of the conditions tested. Thus, the successful adaptation to sudden carbon starvation requires energy and, under anaerobic conditions, fermentable endogenous resources. In an industrial setting, carbon starvation in anaerobic fermentations should be avoided to maintain a productive yeast population.

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.

Metabolic flux analysis of RQ-controlled microaerobic ethanol production by Saccharomyces cerevisiae

Microaerobic ethanol production by Saccharomyces cerevisiae CBS 8066 was investigated at different growth rates in respiratory quotient (RQ)-controlled continuous culture. The RQ was controlled by changing the inlet gas composition by a feedback controller while keeping other parameters constant. The ethanol yield increased slightly from the anaerobic values with decreasing RQ, reaching a broad maximum at RQ 20 to 12. There was little or no glycerol production at RQ values below 17 over a wide range of dilution rates. Metabolic flux analysis revealed that a decrease in the ethanol yield at RQ 6 coincided with the cyclic, oxidative operation of the TCA cycle reactions. The model indicated that respiratory dissimilation of glucose only occurs when the oxygen uptake rate is high enough to completely substitute for glycerol formation. The cytosolic and the mitochondrial NADH balances were important for determining the flux distributions. The smallest deviations between estimated and measured product yields were obtained when the unknown co-factor requirements of a limited number of biosynthetic reactions were chosen so that the amount of excess NADH formed in biosynthesis was minimized. The biomass yield was positively correlated with the net amount of NADH reoxidized in respiration and glycerol formation, indicating that the turnover of excess NADH from biosynthesis is an important factor influencing the biomass yield under oxygen-limiting conditions.

Dimerization of Rhizobium meliloti NifH protein in Saccharomyces cerevisiae cells requires simultaneous expression of NifM protein

Compared to free living diazotrophs, the nitrogenase system of symbiotic microorganisms, like Rhizobium (Synorhizobium) meliloti, was poorly studied. The aim of our research was to investigate whether (by analogy with Klebsiella pneumoniae) the NifM product is required and sufficient to obtain active R. meliloti Fe-protein. We cloned nifH gene of R. meliloti and nifM gene of K. pneumoniae in suitable yeast vectors. When introduced into Saccharomyces cerevisiae cells, both genes were effectively expressed to proteins similar to the native products in its immunoreactivity and apparent molecular mass. The association of R. meliloti NifH protein into dimer structure required co-expression of NifM that also conferred stability of NifH polypeptide. However, the NifH protein synthesized in yeast did not show enzyme activity, suggesting that the NifM of K. pneumoniae is incapable of activating the NifH protein of R. meliloti.

Large-scale prediction of phenotype: concept

The capability to gather organism wide data has far outstripped the ability to understand it. Transforming large-scale data into a "better" cell requires tools that integrate physiology with its environment. One such tool is large-scale mathematical models that marry stoichiometry and kinetics with metabolic regulation and control. It is straightforward to determine stoichiometry (at least for central pathways), and kinetics can be roughly approximated where need be. However, the molecular details of the "metabolic wiring" managing the cell are often missing. Presented here is a surrogate for these missing details based on a simple premise; over evolutionary time, biological systems have developed objective-based programs that frugally manage gene expression and enzyme activity. Mathematically, this notion can be represented as sets of nonlinear control or "management" problems which, when solved in parallel with the model balances, offer a prediction of how gene expression and enzyme activity are modulated, in the absence of specific mechanistic details. We present a model of Escherichia coli central carbon metabolism, describing batch aerobic growth on glucose, in which transcription, translation, and activity of the gene products of 45 genes is "managed" using this approach. The model consists of 122 species (metabolites, enzymes, mRNA pools, and biomass) and describes 46 reactions (17 reversible). The model is identified (kinetic parameters as well as management structure) from metabolic flux ratio (METAFoR) analysis and physiological measurements. Simulations of a pyruvate kinase knockout strain are compared with experiments and it is shown the model is capable of accurately capturing the metabolic reprogramming resulting from the deletion. Analysis of the mRNA expression pattern, translational pattern and enzyme activity pattern of the wild-type versus mutant indicates a combination of expression and specific activity shifts are responsible for observed differences. While being only a first step toward large-scale physiological modeling, this work is important in two ways. First, it strengthens the hypothesis that unknown mechanism can be reasonably approximated using objective-based management criteria. Second, it provides a dynamic means to couple large-scale analysis technologies with physiology at the single-gene, single-protein level.

Can yeast glycolysis be understood in terms of in vitro kinetics of the constituent enzymes? Testing biochemistry

This paper examines whether the in vivo behavior of yeast glycolysis can be understood in terms of the in vitro kinetic properties of the constituent enzymes. In nongrowing, anaerobic, compressed Saccharomyces cerevisiae the values of the kinetic parameters of most glycolytic enzymes were determined. For the other enzymes appropriate literature values were collected. By inserting these values into a kinetic model for glycolysis, fluxes and metabolites were calculated. Under the same conditions fluxes and metabolite levels were measured. In our first model, branch reactions were ignored. This model failed to reach the stable steady state that was observed in the experimental flux measurements. Introduction of branches towards trehalose, glycogen, glycerol and succinate did allow such a steady state. The predictions of this branched model were compared with the empirical behavior. Half of the enzymes matched their predicted flux in vivo within a factor of 2. For the other enzymes it was calculated what deviation between in vivo and in vitro kinetic characteristics could explain the discrepancy between in vitro rate and in vivo flux.

The metabolic network of Lactococcus lactis: distribution of (14)C-labeled substrates between catabolic and anabolic pathways

Lactococcus lactis NCDO 2118 was grown in a simple synthetic medium containing only six essential amino acids and glucose as carbon substrates to determine qualitatively and quantitatively the carbon fluxes into the metabolic network. The specific rates of substrate consumption, product formation, and biomass synthesis, calculated during the exponential growth phase, represented the carbon fluxes within the catabolic and anabolic pathways. The macromolecular composition of the biomass was measured to distribute the global anabolic flux into the specific anabolic pathways. Finally, the distribution of radiolabeled substrates, both into the excreted fermentation end products and into the different macromolecular fractions of biomass, was monitored. The classical end products of lactic acid metabolism (lactate, formate, and acetate) were labeled with glucose, which did not label other excreted products, and to a lesser extent with serine, which was deaminated to pyruvate and represented approximately 10% of the pyruvate flux. Other minor products, keto and hydroxy acids, were produced from glutamate and branched-chain amino acids via deamination and subsequent decarboxylation and/or reduction. Glucose labeled all biomass fractions and accounted for 66% of the cellular carbon, although this represented only 5% of the consumed glucose.

Glycolytic flux is conditionally correlated with ATP concentration in Saccharomyces cerevisiae: a chemostat study under carbon- or nitrogen-limiting conditions

Anaerobic and aerobic chemostat cultures of Saccharomyces cerevisiae were performed at a constant dilution rate of 0.10 h(-1). The glucose concentration was kept constant, whereas the nitrogen concentration was gradually decreasing; i.e., the conditions were changed from glucose and energy limitation to nitrogen limitation and energy excess. This experimental setup enabled the glycolytic rate to be separated from the growth rate. There was an extensive uncoupling between anabolic energy requirements and catabolic energy production when the energy source was present in excess both aerobically and anaerobically. To increase the catabolic activity even further, experiments were carried out in the presence of 5 mM acetic acid or benzoic acid. However, there was almost no effect with acetate addition, whereas both respiratory (aerobically) and fermentative activities were elevated in the presence of benzoic acid. There was a strong negative correlation between glycolytic flux and intracellular ATP content; i.e., the higher the ATP content, the lower the rate of glycolysis. No correlation could be found with the other nucleotides tested (ADP, GTP, and UTP) or with the ATP/ADP ratio. Furthermore, a higher rate of glycolysis was not accompanied by an increasing level of glycolytic enzymes. On the contrary, the glycolytic enzymes decreased with increasing flux. The most pronounced reduction was obtained for HXK2 and ENO1. There was also a correlation between the extent of carbohydrate accumulation and glycolytic flux. A high accumulation was obtained at low glycolytic rates under glucose limitation, whereas nitrogen limitation during conditions of excess carbon and energy resulted in more or less complete depletion of intracellular storage carbohydrates irrespective of anaerobic or aerobic conditions. However, there was one difference in that glycogen dominated anaerobically whereas under aerobic conditions, trehalose was the major carbohydrate accumulated. Possible mechanisms which may explain the strong correlation between glycolytic flux, storage carbohydrate accumulation, and ATP concentrations are discussed.