Expanding a dynamic flux balance model of yeast fermentation to genome-scale

Vargas, Fernando Silva; Pizarro, Francisco; Pérez-Correa, José Ricardo; Agosín, Eduardo

doi:10.1186/1752-0509-5-75

Cited by 64 publications

(74 citation statements)

References 94 publications

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“…On the other hand, dynamic flux balance analysis (dFBA) has emerged as a promising strategy to study batch cultures of several strains (Sainz et al, 2003; Hanly et al, 2012; Sánchez et al, 2014). Indeed, this methodology has been already applied to understand the behavior of industrial Saccharomyces cerevisiae strains in wine-like medium (Vargas et al, 2011). Therefore, a dFBA for O. oeni could be useful to simulate the kinetics of growth and industrial MLF extension.…”

Section: Discussionmentioning

confidence: 99%

Genome-Scale Reconstruction of the Metabolic Network in Oenococcus oeni to Assess Wine Malolactic Fermentation

et al. 2017

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Oenococcus oeni is the main responsible agent for malolactic fermentation in wine, an unpredictable and erratic process in winemaking. To address this, we have constructed and exhaustively curated the first genome-scale metabolic model of Oenococcus oeni, comprising 660 reactions, 536 metabolites and 454 genes. In silico experiments revealed that nutritional requirements are predicted with an accuracy of 93%, while 14 amino acids were found to be essential for the growth of this bacterial species. When the model was applied to determine the non-growth associated maintenance, results showed that O. oeni grown at 12% ethanol concentration spent 30 times more ATP to stay alive than in the absence of ethanol. Most of this ATP is employed for extruding protons outside of the cell. A positive relationship was also found between specific consumption rates of fructose, amino acids, oxygen, and malic acid and the specific production rates of erythritol, lactate, and acetate, according to the ethanol content of the medium. The metabolic model reconstructed here represents a unique tool to predict the successful completion of wine malolactic fermentation carried out either by different strains of Oenococcus oeni, as well as at any particular physico-chemical composition of wine. It will also allow the development of consortium metabolic models that could be applied to winemaking to simulate and understand the interactions between O. oeni and other microorganisms that share this ecological niche.

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Section: Discussionmentioning

confidence: 99%

Genome-Scale Reconstruction of the Metabolic Network in Oenococcus oeni to Assess Wine Malolactic Fermentation

et al. 2017

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“…Since the amounts of amino acids supplied in the medium were substantially lower than the anabolic demand, except for glutamine and arginine (44), we expected massive direct incorporation of exogenous amino acids into biomass through the activity of aminoacyl-tRNA synthases, which catalyze the initial step of protein biogenesis (45). This mode of operation is generally assumed, particularly in model-based quantitative analyses of yeast metabolic networks (46)(47)(48). In contrast to this assumption, our data revealed, as a general rule, partial use of most of the exogenous amino acids assimilated by yeast for direct protein synthesis, at a level independent of their availability.…”

Section: Discussionmentioning

confidence: 99%

Management of Multiple Nitrogen Sources during Wine Fermentation by Saccharomyces cerevisiae

Crépin

Truong

Bloem

et al. 2017

Appl Environ Microbiol

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During fermentative growth in natural and industrial environments, Saccharomyces cerevisiae must redistribute the available nitrogen from multiple exogenous sources to amino acids in order to suitably fulfill anabolic requirements. To exhaustively explore the management of this complex resource, we developed an advanced strategy based on the reconciliation of data from a set of stable isotope tracer experiments with labeled nitrogen sources. Thus, quantifying the partitioning of the N compounds through the metabolism network during fermentation, we demonstrated that, contrary to the generally accepted view, only a limited fraction of most of the consumed amino acids is directly incorporated into proteins. Moreover, substantial catabolism of these molecules allows for efficient redistribution of nitrogen, supporting the operative de novo synthesis of proteinogenic amino acids. In contrast, catabolism of consumed amino acids plays a minor role in the formation of volatile compounds. Another important feature is that the ␣-keto acid precursors required for the de novo syntheses originate mainly from the catabolism of sugars, with a limited contribution from the anabolism of consumed amino acids. This work provides a comprehensive view of the intracellular fate of consumed nitrogen sources and the metabolic origin of proteinogenic amino acids, highlighting a strategy of distribution of metabolic fluxes implemented by yeast as a means of adapting to environments with changing and scarce nitrogen resources. IMPORTANCE A current challenge for the wine industry, in view of the extensive competition in the worldwide market, is to meet consumer expectations regarding the sensory profile of the product while ensuring an efficient fermentation process. Understanding the intracellular fate of the nitrogen sources available in grape juice is essential to the achievement of these objectives, since nitrogen utilization affects both the fermentative activity of yeasts and the formation of flavor compounds. However, little is known about how the metabolism operates when nitrogen is provided as a composite mixture, as in grape must. Here we quantitatively describe the distribution through the yeast metabolic network of the N moieties and C backbones of these nitrogen sources. Knowledge about the management of a complex resource, which is devoted to improvement of the use of the scarce N nutrient for growth, will be useful for better control of the fermentation process and the sensory quality of wines.KEYWORDS complex nitrogen resource, metabolic network, metabolism, nitrogen, quantitative analysis, regulation, yeasts T he management of nutrients provided by the external environment, mainly carbon and nitrogen, and their redistribution inside the cells for the formation of biosynthetic precursors through the metabolic network are essential for all living organisms. The topology of the metabolic network of the yeast Saccharomyces cerevisiae is one of

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“…Varela et al [6] described the metabolic flux distribution of yeast during sluggish and normal fermentations using batch cultures. This group has further extended this approach by developing a genome-scale dynamic flux balance model that allows prediction of metabolite production in batch cultures [7]. In this context, Clement et al [8] studied the fermentation process in a “multistage bioreactor system”, where two or four fermenters, operating in continuous mode, were connected in tandem mimicking sequential stages of standard batch wine fermentations.…”

Section: Introductionmentioning

confidence: 99%

Metabolic Flux Analysis during the Exponential Growth Phase of Saccharomyces cerevisiae in Wine Fermentations

et al. 2013

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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.

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Expanding a dynamic flux balance model of yeast fermentation to genome-scale

Cited by 64 publications

References 94 publications

Genome-Scale Reconstruction of the Metabolic Network in Oenococcus oeni to Assess Wine Malolactic Fermentation

Genome-Scale Reconstruction of the Metabolic Network in Oenococcus oeni to Assess Wine Malolactic Fermentation

Management of Multiple Nitrogen Sources during Wine Fermentation by Saccharomyces cerevisiae

Metabolic Flux Analysis during the Exponential Growth Phase of Saccharomyces cerevisiae in Wine Fermentations

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