Diversity of flux distribution in central carbon metabolism of S. cerevisiae strains from diverse environments

Strategies to Maintain Redox Homeostasis in Yeast Cells with Impaired Fermentation-Dependent NADPH Generation

Redox homeostasis is the balance between oxidation and reduction reactions. Its maintenance depends on glutathione, including its reduced and oxidized form, GSH/GSSG, which is the main intracellular redox buffer, but also on the nicotinamide adenine dinucleotide phosphate, including its reduced and oxidized form, NADPH/NADP+. Under conditions that enable yeast cells to undergo fermentative metabolism, the main source of NADPH is the pentose phosphate pathway. The lack of enzymes responsible for the production of NADPH has a significant impact on yeast cells. However, cells may compensate in different ways for impairments in NADPH synthesis, and the choice of compensation strategy has several consequences for cell functioning. The present study of this issue was based on isogenic mutants: Δzwf1, Δgnd1, Δald6, and the wild strain, as well as a comprehensive panel of molecular analyses such as the level of gene expression, protein content, and enzyme activity. The obtained results indicate that yeast cells compensate for the lack of enzymes responsible for the production of cytosolic NADPH by changing the content of selected proteins and/or their enzymatic activity. In turn, the cellular strategy used to compensate for them may affect cellular efficiency, and thus, the ability to grow or sensitivity to environmental acidification.

Insights into intraspecific diversity of central carbon metabolites in Saccharomyces cerevisiae during wine fermentation

Saccharomyces cerevisiae is a major actor in winemaking that converts sugars from the grape must into ethanol and CO2 with outstanding efficiency. Primary metabolites produced during fermentation have a great importance in wine. While ethanol content contributes to the overall profile, other metabolites like glycerol, succinate, acetate or lactate also have significant impacts, even when present in lower concentrations. S. cerevisiae is known for its great genetic diversity that is related to its natural or technological environment. However, the variation range of metabolic diversity which can be exploited to enhance wine quality depends on the pathway considered. Our experiment assessed the diversity of primary metabolites production in a set of 51 S. cerevisiae strains from various genetic backgrounds. Results pointed out great yield differences depending on the metabolite considered, with ethanol having the lowest variation. A negative correlation between ethanol and glycerol was observed, confirming glycerol synthesis as a suitable lever to reduce ethanol yield. Genetic groups were linked to specific yields, such as the wine group and high α-ketoglutarate and low acetate yields. This research highlights the potential of using natural yeast diversity in winemaking. It also provides a detailed data set on production of well known (ethanol, glycerol, acetate) or little-known (lactate) primary metabolites.

Virtually identical does not mean exactly identical: Discrepancy in energy metabolism between glucose and fructose fermentation influences the reproductive potential of yeast cells

The physiological efficiency of cells largely depends on the possibility of metabolic adaptations to changing conditions, especially on the availability of nutrients. Central carbon metabolism has an essential role in cellular function. In most cells is based on glucose, which is the primary energy source, provides the carbon skeleton for the biosynthesis of important cell macromolecules, and acts as a signaling molecule. The metabolic flux between pathways of carbon metabolism such as glycolysis, pentose phosphate pathway, and mitochondrial oxidative phosphorylation is dynamically adjusted by specific cellular economics responding to extracellular conditions and intracellular demands. Using Saccharomyces cerevisiae yeast cells and potentially similar fermentable carbon sources i.e. glucose and fructose we analyzed the parameters concerning the metabolic status of the cells and connected with them alteration in cell reproductive potential. Those parameters were related to the specific metabolic network: the hexose uptake - glycolysis and activity of the cAMP/PKA pathway - pentose phosphate pathway and biosynthetic capacities - the oxidative respiration and energy generation. The results showed that yeast cells growing in a fructose medium slightly increased metabolism redirection toward respiratory activity, which decreased pentose phosphate pathway activity and cellular biosynthetic capabilities. These differences between the fermentative metabolism of glucose and fructose, lead to long-term effects, manifested by changes in the maximum reproductive potential of cells.

Production of D-glucaric acid with phosphoglucose isomerase-deficient Saccharomyces cerevisiae

D-Glucaric acid is a potential biobased platform chemical. Previously mainly Escherichia coli, but also the yeast Saccharomyces cerevisiae, and Pichia pastoris, have been engineered for conversion of D-glucose to D-glucaric acid via myo-inositol. One reason for low yields from the yeast strains is the strong flux towards glycolysis. Thus, to decrease the flux of D-glucose to biomass, and to increase D-glucaric acid yield, the four step D-glucaric acid pathway was introduced into a phosphoglucose isomerase deficient (Pgi1p-deficient) Saccharomyces cerevisiae strain. High D-glucose concentrations are toxic to the Pgi1p-deficient strains, so various feeding strategies and use of polymeric substrates were studied. Uniformly labelled 13C-glucose confirmed conversion of D-glucose to D-glucaric acid. In batch bioreactor cultures with pulsed D-fructose and ethanol provision 1.3 g D-glucaric acid L-1 was produced. The D-glucaric acid titer (0.71 g D-glucaric acid L-1) was lower in nitrogen limited conditions, but the yield, 0.23 g D-glucaric acid [g D-glucose consumed]-1, was among the highest that has so far been reported from yeast. Accumulation of myo-inositol indicated that myo-inositol oxygenase activity was limiting, and that there would be potential to even higher yield. The Pgi1p-deficiency in S. cerevisiae provides an approach that in combination with other reported modifications and bioprocess strategies would promote the development of high yield D-glucaric acid yeast strains.

Endo metabolomic profiling of flor and wine yeasts reveals a positive correlation between intracellular metabolite load and the specific glycolytic flux during wine fermentation

This study explored the intracellular metabolic variations between 17 strains of Saccharomyces cerevisiae belonging to two different genetic populations: flor and wine yeasts, in the context of alcoholic fermentation. These two populations are closely related as they share the same ecological niche but display distinct genetic characteristics. A protocol was developed for intracellular metabolites extraction and 1H-NMR analysis. This methodology allowed us to identify and quantify 21 intracellular metabolites at two different fermentation steps: the exponential and stationary phases. This work provided evidence of significant differences in the abundance of intracellular metabolites, which are strain- and time-dependent, thus revealing complex interactions. Moreover, the differences in abundance appeared to be correlated with life-history traits such as average cell size and specific glycolytic flux, which revealed unsuspected phenotypic correlations between metabolite load and fermentation activity.

Elucidating yeast glycolytic dynamics at steady state growth and glucose pulses through kinetic metabolic modeling

Microbial cell factories face changing environments during industrial fermentations. Kinetic metabolic models enable the simulation of the dynamic metabolic response to these perturbations, but their development is challenging due to model complexity and experimental data requirements. An example of this is the well-established microbial cell factory Saccharomyces cerevisiae, for which no consensus kinetic model of central metabolism has been developed and implemented in industry. Here, we aim to bring the academic and industrial communities closer to this consensus model. We developed a physiology informed kinetic model of yeast glycolysis connected to central carbon metabolism by including the effect of anabolic reactions precursors, mitochondria and the trehalose cycle. To parametrize such a large model, a parameter estimation pipeline was developed, consisting of a divide and conquer approach, supplemented with regularization and global optimization. Additionally, we show how this first mechanistic description of a growing yeast cell captures experimental dynamics at different growth rates and under a strong glucose perturbation, is robust to parametric uncertainty and explains the contribution of the different pathways in the network. Such a comprehensive model could not have been developed without using steady state and glucose perturbation data sets. The resulting metabolic reconstruction and parameter estimation pipeline can be applied in the future to study other industrially-relevant scenarios. We show this by generating a hybrid CFD-metabolic model to explore intracellular glycolytic dynamics for the first time. The model suggests that all intracellular metabolites oscillate within a physiological range, except carbon storage metabolism, which is sensitive to the extracellular environment.

Data integration uncovers the metabolic bases of phenotypic variation in yeast

The relationship between different levels of integration is a key feature for understanding the genotype-phenotype map. Here, we describe a novel method of integrated data analysis that incorporates protein abundance data into constraint-based modeling to elucidate the biological mechanisms underlying phenotypic variation. Specifically, we studied yeast genetic diversity at three levels of phenotypic complexity in a population of yeast obtained by pairwise crosses of eleven strains belonging to two species, Saccharomyces cerevisiae and S. uvarum. The data included protein abundances, integrated traits (life-history/fermentation) and computational estimates of metabolic fluxes. Results highlighted that the negative correlation between production traits such as population carrying capacity (K) and traits associated with growth and fermentation rates (J_max) is explained by a differential usage of energy production pathways: a high K was associated with high TCA fluxes, while a high J_max was associated with high glycolytic fluxes. Enrichment analysis of protein sets confirmed our results.

This powerful approach allowed us to identify the molecular and metabolic bases of integrated trait variation, and therefore has a broad applicability domain.

The integration of data at different levels of cellular organization is an important goal in computational biology for understanding the way the genotypic variation translates into phenotypic variation. Novel profiling technologies and accurate high-throughput phenotyping now allows genomic, transcriptomic, metabolic and proteomic characterization of a large number of individuals under various environmental conditions. However, the metabolic fluxes remain difficult to measure. In this work, we take advantage of recent advances in genome-scale functional annotation and constraint-based metabolic modeling to provide a mathematical framework that allows to estimate internal cellular fluxes from protein abundances and elucidate the biological mechanisms underlying phenotypic variation. Applied to yeast as a model system, this approach highlights that the negative correlation between production traits such as maximum population size and growth and fermentation traits is explained by a differential usage of energy production pathways. The ability to identify molecular and metabolic bases of the variation of integrated traits through population studies has a broad applicability domain.

Metabolic differences between a wild and a wine strain of Saccharomyces cerevisiae during fermentation unveiled by multi-omic analysis

Saccharomyces cerevisiae, a widespread yeast present both in the wild and in fermentative processes, like winemaking. During the colonization of these human-associated fermentative environments, certain strains of S. cerevisiae acquired differential adaptive traits that enhanced their physiological properties to cope with the challenges imposed by these new ecological niches. The advent of omics technologies allowed unveiling some details of the molecular bases responsible for the peculiar traits of S. cerevisiae wine strains. However, the metabolic diversity within yeasts remained poorly explored, in particular that existing between wine and wild strains of S. cerevisiae. For this purpose, we performed a dual transcriptomic and metabolomic comparative analysis between a wild and a wine S. cerevisiae strains during wine fermentations performed at high and low temperatures. By using this approach, we could correlate the differential expression of genes involved in metabolic pathways, such as sulfur, arginine and thiamine metabolisms, with differences in the amounts of key metabolites that can explain some important differences in the fermentation performance between the wine and wild strains.

A Distance-Based Framework for the Characterization of Metabolic Heterogeneity in Large Sets of Genome-Scale Metabolic Models

Gene expression and protein abundance data of cells or tissues belonging to healthy and diseased individuals can be integrated and mapped onto genome-scale metabolic networks to produce patient-derived models. As the number of available and newly developed genome-scale metabolic models increases, new methods are needed to objectively analyze large sets of models and to identify the determinants of metabolic heterogeneity. We developed a distance-based workflow that combines consensus machine learning and metabolic modeling techniques and used it to apply pattern recognition algorithms to collections of genome-scale metabolic models, both microbial and human. Model composition, network topology and flux distribution provide complementary aspects of metabolic heterogeneity in patient-specific genome-scale models of skeletal muscle. Using consensus clustering analysis we identified the metabolic processes involved in the individual responses to endurance training in older adults.

Mitochondrial respiration is required to provide amino acids during fermentative proliferation of fission yeast

When glucose is available, many organisms repress mitochondrial respiration in favour of aerobic glycolysis, or fermentation in yeast, that suffices for ATP production. Fission yeast cells, however, rely partially on respiration for rapid proliferation under fermentative conditions. Here, we determined the limiting factors that require respiratory function during fermentation. When inhibiting the electron transport chain, supplementation with arginine was necessary and sufficient to restore rapid proliferation. Accordingly, a systematic screen for mutants growing poorly without arginine identified mutants defective in mitochondrial oxidative metabolism. Genetic or pharmacological inhibition of respiration triggered a drop in intracellular levels of arginine and amino acids derived from the Krebs cycle metabolite alpha‐ketoglutarate: glutamine, lysine and glutamic acid. Conversion of arginine into these amino acids was required for rapid proliferation when blocking the respiratory chain. The respiratory block triggered an immediate gene expression response diagnostic of TOR inhibition, which was muted by arginine supplementation or without the AMPK‐activating kinase Ssp1. The TOR‐controlled proteins featured biased composition of amino acids reflecting their shortage after respiratory inhibition. We conclude that respiration supports rapid proliferation in fermenting fission yeast cells by boosting the supply of Krebs cycle‐derived amino acids.

Cuminal Inhibits Trichothecium roseum Growth by Triggering Cell Starvation: Transcriptome and Proteome Analysis

Trichothecium roseum is a harmful postharvest fungus causing serious damage, together with the secretion of insidious mycotoxins, on apples, melons, and other important fruits. Cuminal, a predominant component of Cuminum cyminum essential oil has proven to successfully inhibit the growth of T. roseum in vitro and in vivo. Electron microscopic observations revealed cuminal exposure impaired the fungal morphology and ultrastructure, particularly the plasmalemma. Transcriptome and proteome analysis was used to investigate the responses of T. roseum to exposure of cuminal. In total, 2825 differentially expressed transcripts (1516 up and 1309 down) and 225 differentially expressed proteins (90 up and 135 down) were determined. Overall, notable parts of these differentially expressed genes functionally belong to subcellular localities of the membrane system and cytosol, along with ribosomes, mitochondria and peroxisomes. According to the localization analysis and the biological annotation of these genes, carbohydrate and lipids metabolism, redox homeostasis, and asexual reproduction were among the most enriched gene ontology (GO) terms. Biological pathway enrichment analysis showed that lipids and amino acid degradation, ATP-binding cassette transporters, membrane reconstitution, mRNA surveillance pathway and peroxisome were elevated, whereas secondary metabolite biosynthesis, cell cycle, and glycolysis/gluconeogenesis were down regulated. Further integrated omics analysis showed that cuminal exposure first impaired the polarity of the cytoplasmic membrane and then triggered the reconstitution and dysfunction of fungal plasmalemma, resulting in handicapped nutrient procurement of the cells. Consequently, fungal cells showed starvation stress with limited carbohydrate metabolism, resulting a metabolic shift to catabolism of the cell's own components in response to the stress. Additionally, these predicaments brought about oxidative stress, which, in collaboration with the starvation, damaged certain critical organelles such as mitochondria. Such degeneration, accompanied by energy deficiency, suppressed the biosynthesis of essential proteins and inhibited fungal growth.

QTL mapping of modelled metabolic fluxes reveals gene variants impacting yeast central carbon metabolism

The yeast Saccharomyces cerevisiae is an attractive industrial microorganism for the production of foods and beverages as well as for various bulk and fine chemicals, such as biofuels or fragrances. Building blocks for these biosyntheses are intermediates of yeast central carbon metabolism (CCM), whose intracellular availability depends on balanced single reactions that form metabolic fluxes. Therefore, efficient product biosynthesis is influenced by the distribution of these fluxes. We recently demonstrated great variations in CCM fluxes between yeast strains of different origins. However, we have limited understanding of flux modulation and the genetic basis of flux variations. In this study, we investigated the potential of quantitative trait locus (QTL) mapping to elucidate genetic variations responsible for differences in metabolic flux distributions (fQTL). Intracellular metabolic fluxes were estimated by constraint-based modelling and used as quantitative phenotypes, and differences in fluxes were linked to genomic variations. Using this approach, we detected four fQTLs that influence metabolic pathways. The molecular dissection of these QTLs revealed two allelic gene variants, PDB1 and VID30, contributing to flux distribution. The elucidation of genetic determinants influencing metabolic fluxes, as reported here for the first time, creates new opportunities for the development of strains with optimized metabolite profiles for various applications.

Adaptation of S. cerevisiae to Fermented Food Environments Reveals Remarkable Genome Plasticity and the Footprints of Domestication

The budding yeast Saccharomyces cerevisiae can be found in the wild and is also frequently associated with human activities. Despite recent insights into the phylogeny of this species, much is still unknown about how evolutionary processes related to anthropogenic niches have shaped the genomes and phenotypes of S. cerevisiae. To address this question, we performed population-level sequencing of 82 S. cerevisiae strains from wine, flor, rum, dairy products, bakeries, and the natural environment (oak trees). These genomic data enabled us to delineate specific genetic groups corresponding to the different ecological niches and revealed high genome content variation across the groups. Most of these strains, compared with the reference genome, possessed additional genetic elements acquired by introgression or horizontal transfer, several of which were population-specific. In addition, several genomic regions in each population showed evidence of nonneutral evolution, as shown by high differentiation, or of selective sweeps including genes with key functions in these environments (e.g., amino acid transport for wine yeast). Linking genetics to lifestyle differences and metabolite traits has enabled us to elucidate the genetic basis of several niche-specific population traits, such as growth on galactose for cheese strains. These data indicate that yeast has been subjected to various divergent selective pressures depending on its niche, requiring the development of customized genomes for better survival in these environments. These striking genome dynamics associated with local adaptation and domestication reveal the remarkable plasticity of the S. cerevisiae genome, revealing this species to be an amazing complex of specialized populations.

Disorders in NADPH generation via pentose phosphate pathway influence the reproductive potential of the Saccharomyces cerevisiae yeast due to changes in redox status

Intermediary metabolites have a crucial impact on basic cell functions. There is a relationship between cellular metabolism and redox balance. To maintain redox homoeostasis, the cooperation of both glutathione and nicotine adenine dinucleotides is necessary. Availability of nicotinamide adenine dinucleotide phosphate (NADPH) as a major electron donor is critical for many intracellular redox reactions. The activity of glucose-6-phosphate dehydrogenase (Zwf1p) and 6-phosphogluconate dehydrogenase (Gnd1p and Gnd2p) is responsible for NADPH formation in a pentose phosphate (PP) pathway. In this study, we examine the impact of redox homoeostasis on cellular physiology and proliferation. We have noted that the Δzwf1 mutant lacking the rate-limiting enzyme of the PP pathway shows changes in the cellular redox status caused by disorders in NADPH generation. This leads to a decrease in reproductive potential but without affecting the total lifespan of the cell. The results presented in this paper show that nicotine adenine dinucleotides play a central role in cellular physiology.

Less is more or more is less: Implications of glucose metabolism in the regulation of the reproductive potential and total lifespan of the Saccharomyces cerevisiae yeast

Carbohydrates are dietary nutrients that have an influence on cells physiology, cell reproductive capacity and, consequently, the lifespan of organisms. They are used in cellular processes after conversion to glucose, which is the primary source of energy and carbon skeleton for biosynthetic processes. Studies of the influence of glucose on cellular parameters and lifespan of organisms are primarily concerned with the effect of low glucose concentration defined as calorie restriction conditions. However, the effect of high glucose concentration on cell physiology is also very important. Thus, a comparative analysis of the effects of low and high glucose concentration conditions on cell efficiency was proposed with regard to reproductive capacity and total lifespan of the cell. Glucose concentration determines the type of metabolism and biosynthetic capabilities, which in turn, through the regulation on the cell size, may affect the reproductive capacity of cells. This study was conducted on yeast cells of wild-type and mutant strains Δgpa2 and Δgpr1 with glucose signalling pathway impairment. Such an experimental model enabled testing both the role of glucose concentration in the regulation of metabolic changes and the extent to which these changes depend on the extracellular or intracellular glucose concentrations. It has been shown here that calorie/glucose excess connected with changes in cell metabolic fluxes increases biosynthetic capabilities of yeast cells. This leads to an increase in cell dry weight accompanied by the increase in cell size and a simultaneous decrease in the reproductive potential and the overall length of cell life.

John PC, Crowley MF, Bomble YJ. Prediction of reaction knockouts to maximize succinate production by Actinobacillus succinogenes

Succinate is a precursor of multiple commodity chemicals and bio-based succinate production is an active area of industrial bioengineering research. One of the most important microbial strains for bio-based production of succinate is the capnophilic gram-negative bacterium Actinobacillus succinogenes, which naturally produces succinate by a mixed-acid fermentative pathway. To engineer A. succinogenes to improve succinate yields during mixed acid fermentation, it is important to have a detailed understanding of the metabolic flux distribution in A. succinogenes when grown in suitable media. To this end, we have developed a detailed stoichiometric model of the A. succinogenes central metabolism that includes the biosynthetic pathways for the main components of biomass-namely glycogen, amino acids, DNA, RNA, lipids and UDP-N-Acetyl-α-D-glucosamine. We have validated our model by comparing model predictions generated via flux balance analysis with experimental results on mixed acid fermentation. Moreover, we have used the model to predict single and double reaction knockouts to maximize succinate production while maintaining growth viability. According to our model, succinate production can be maximized by knocking out either of the reactions catalyzed by the PTA (phosphate acetyltransferase) and ACK (acetyl kinase) enzymes, whereas the double knockouts of PEPCK (phosphoenolpyruvate carboxykinase) and PTA or PEPCK and ACK enzymes are the most effective in increasing succinate production.

Genome-scale modeling of yeast: chronology, applications and critical perspectives

Over the last 15 years, several genome-scale metabolic models (GSMMs) were developed for different yeast species, aiding both the elucidation of new biological processes and the shift toward a bio-based economy, through the design of in silico inspired cell factories. Here, an historical perspective of the GSMMs built over time for several yeast species is presented and the main inheritance patterns among the metabolic reconstructions are highlighted. We additionally provide a critical perspective on the overall genome-scale modeling procedure, underlining incomplete model validation and evaluation approaches and the quest for the integration of regulatory and kinetic information into yeast GSMMs. A summary of experimentally validated model-based metabolic engineering applications of yeast species is further emphasized, while the main challenges and future perspectives for the field are finally addressed.

Beyond topology: coevolution of structure and flux in metabolic networks

Interactions between the structure of a metabolic network and its functional properties underlie its evolutionary diversification, but the mechanism by which such interactions arise remains elusive. Particularly unclear is whether metabolic fluxes that determine the concentrations of compounds produced by a metabolic network, are causally linked to a network's structure or emerge independently of it. A direct empirical study of populations where both structural and functional properties vary among individuals' metabolic networks is required to establish whether changes in structure affect the distribution of metabolic flux. In a population of house finches (Haemorhous mexicanus), we reconstructed full carotenoid metabolic networks for 442 individuals and uncovered 11 structural variants of this network with different compounds and reactions. We examined the consequences of this structural diversity for the concentrations of plumage-bound carotenoids produced by flux in these networks. We found that concentrations of metabolically derived, but not dietary carotenoids, depended on network structure. Flux was partitioned similarly among compounds in individuals of the same network structure: within each network, compound concentrations were closely correlated. The highest among-individual variation in flux occurred in networks with the strongest among-compound correlations, suggesting that changes in the magnitude, but not the distribution of flux, underlie individual differences in compound concentrations on a static network structure. These findings indicate that the distribution of flux in carotenoid metabolism closely follows network structure. Thus, evolutionary diversification and local adaptations in carotenoid metabolism may depend more on the gain or loss of enzymatic reactions than on changes in flux within a network structure.

Metabolic systems modeling for cell factories improvement

Techniques for modeling microbial bioproduction systems have evolved over many decades. Here, we survey recent literature and focus on modeling approaches for improving bioproduction. These techniques from systems biology are based on different methodologies, starting from stoichiometry only to various stoichiometry with kinetics approaches that address different issues in metabolic systems. Techniques to overcome unknown kinetic parameters using random sampling have emerged to address meaningful questions. Among those questions, pathway robustness seems to be an important issue for metabolic engineering. We also discuss the increasing significance of databases in biology and their potential impact for biotechnology.

Saccharomyces cerevisiae metabolism in ecological context

The architecture and regulation of Saccharomyces cerevisiae metabolic network are among the best studied owing to its widespread use in both basic research and industry. Yet, several recent studies have revealed notable limitations in explaining genotype-metabolic phenotype relations in this yeast, especially when concerning multiple genetic/environmental perturbations. Apparently unexpected genotype-phenotype relations may originate in the evolutionarily shaped cellular operating principles being hidden in common laboratory conditions. Predecessors of laboratory S. cerevisiae strains, the wild and the domesticated yeasts, have been evolutionarily shaped by highly variable environments, very distinct from laboratory conditions, and most interestingly by social life within microbial communities. Here we present a brief review of the genotypic and phenotypic peculiarities of S. cerevisiae in the context of its social lifestyle beyond laboratory environments. Accounting for this ecological context and the origin of the laboratory strains in experimental design and data analysis would be essential in improving the understanding of genotype-environment-phenotype relationships.