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QTL dissection of Lag phase in wine fermentation reveals a new translocation responsible for Saccharomyces cerevisiae adaptation to sulfite.

ABSTRACT: Quantitative genetics and QTL mapping are efficient strategies for deciphering the genetic polymorphisms that explain the phenotypic differences of individuals within the same species. Since a decade, this approach has been applied to eukaryotic microbes such as Saccharomyces cerevisiae in order to find natural genetic variations conferring adaptation of individuals to their environment. In this work, a QTL responsible for lag phase duration in the alcoholic fermentation of grape juice was dissected by reciprocal hemizygosity analysis. After invalidating the effect of some candidate genes, a chromosomal translocation affecting the lag phase was brought to light using de novo assembly of parental genomes. This newly described translocation (XV-t-XVI) involves the promoter region of ADH1 and the gene SSU1 and confers an increased expression of the sulfite pump during the first hours of alcoholic fermentation. This translocation constitutes another adaptation route of wine yeast to sulfites in addition to the translocation VIII-t-XVI previously described. A population survey of both translocation forms in a panel of domesticated yeast strains suggests that the translocation XV-t-XVI has been empirically selected by human activity.

SUBMITTER: Zimmer A

PROVIDER: S-EPMC3904918 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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QTL dissection of Lag phase in wine fermentation reveals a new translocation responsible for Saccharomyces cerevisiae adaptation to sulfite.

Zimmer Adrien A Durand Cécile C Loira Nicolás N Durrens Pascal P Sherman David James DJ Marullo Philippe P

PloS one 20140128 1

Quantitative genetics and QTL mapping are efficient strategies for deciphering the genetic polymorphisms that explain the phenotypic differences of individuals within the same species. Since a decade, this approach has been applied to eukaryotic microbes such as Saccharomyces cerevisiae in order to find natural genetic variations conferring adaptation of individuals to their environment. In this work, a QTL responsible for lag phase duration in the alcoholic fermentation of grape juice was disse ...[more]

PMID: 24489712

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Project description: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.

Project description:BackgroundThe volatile metabolites produced by Saccharomyces cerevisiae during alcoholic fermentation, which are mainly esters, higher alcohols and organic acids, play a vital role in the quality and perception of fermented beverages, such as wine. Although the metabolic pathways and genes behind yeast fermentative aroma formation are well described, little is known about the genetic mechanisms underlying variations between strains in the production of these aroma compounds. To increase our knowledge about the links between genetic variation and volatile production, we performed quantitative trait locus (QTL) mapping using 130 F2-meiotic segregants from two S. cerevisiae wine strains. The segregants were individually genotyped by next-generation sequencing and separately phenotyped during wine fermentation.ResultsUsing different QTL mapping strategies, we were able to identify 65 QTLs in the genome, including 55 that influence the formation of 30 volatile secondary metabolites, 14 with an effect on sugar consumption and central carbon metabolite production, and 7 influencing fermentation parameters. For ethyl lactate, ethyl octanoate and propanol formation, we discovered 2 interacting QTLs each. Within 9 of the detected regions, we validated the contribution of 13 genes in the observed phenotypic variation by reciprocal hemizygosity analysis. These genes are involved in nitrogen uptake and metabolism (AGP1, ALP1, ILV6, LEU9), central carbon metabolism (HXT3, MAE1), fatty acid synthesis (FAS1) and regulation (AGP2, IXR1, NRG1, RGS2, RGT1, SIR2) and explain variations in the production of characteristic sensorial esters (e.g., 2-phenylethyl acetate, 2-metyhlpropyl acetate and ethyl hexanoate), higher alcohols and fatty acids.ConclusionsThe detection of QTLs and their interactions emphasizes the complexity of yeast fermentative aroma formation. The validation of underlying allelic variants increases knowledge about genetic variation impacting metabolic pathways that lead to the synthesis of sensorial important compounds. As a result, this work lays the foundation for tailoring S. cerevisiae strains with optimized volatile metabolite production for fermented beverages and other biotechnological applications.

Project description:Wineries face unprecedented challenges due to new market demands and climate change effects on wine quality. New yeast starters including non-conventional Saccharomyces species, such as S. kudriavzevii, may contribute to deal with some of these challenges. The design of new fermentations using non-conventional yeasts requires an improved understanding of the physiology and metabolism of these cells. Dynamic modeling brings the potential of exploring the most relevant mechanisms and designing optimal processes more systematically. In this work we explore mechanisms by means of a model selection, reduction and cross-validation pipeline which enables to dissect the most relevant fermentation features for the species under consideration, Saccharomyces cerevisiae T73 and Saccharomyces kudriavzevii CR85. The pipeline involved the comparison of a collection of models which incorporate several alternative mechanisms with emphasis on the inhibitory effects due to temperature and ethanol. We focused on defining a minimal model with the minimum number of parameters, to maximize the identifiability and the quality of cross-validation. The selected model was then used to highlight differences in behavior between species. The analysis of model parameters would indicate that the specific growth rate and the transport of hexoses at initial times are higher for S. cervisiae T73 while S. kudriavzevii CR85 diverts more flux for glycerol production and cellular maintenance. As a result, the fermentations with S. kudriavzevii CR85 are typically slower; produce less ethanol but higher glycerol. Finally, we also explored optimal initial inoculation and process temperature to find the best compromise between final product characteristics and fermentation duration. Results reveal that the production of glycerol is distinctive in S. kudriavzevii CR85, it was not possible to achieve the same production of glycerol with S. cervisiae T73 in any of the conditions tested. This result brings the idea that the optimal design of mixed cultures may have an enormous potential for the improvement of final wine quality.

Dataset Information

QTL dissection of Lag phase in wine fermentation reveals a new translocation responsible for Saccharomyces cerevisiae adaptation to sulfite.

Publications

QTL dissection of Lag phase in wine fermentation reveals a new translocation responsible for Saccharomyces cerevisiae adaptation to sulfite.

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