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Despite the high energetic cost of the reduction of sulfate to H 2 S, required for the synthesis of sulfur-containing amino acids, some wine Saccharomyces cerevisiae strains have been reported to produce excessive amounts of H 2 S during alcoholic fermentation, which is detrimental to wine quality. Surprisingly, in the presence of sulfite, used as a preservative, wine strains produce more H 2 S than wild (oak) or wine velum (flor) isolates during fermentation. Since copper resistance caused by the amplification of the sulfur rich protein Cup1p is a specific adaptation trait of wine strains, we analyzed the link between copper resistance mechanism, sulfur metabolism and H 2 S production. We show that a higher content of copper in the must increases the production of H 2 S, and that SO 2 increases the resistance to copper. Using a set of 51 strains we observed a positive and then negative relation between the number of copies of CUP1 and H 2 S production during fermentation. This complex pattern could be mimicked using a multicopy plasmid carrying CUP1, confirming the relation between copper resistance and H 2 S production. The massive use of copper for vine sanitary management has led to the selection of resistant strains at the cost of a metabolic tradeoff: the overproduction of H 2 S, resulting in a decrease in wine quality., (© 2024. The Author(s).)

The main goals and challenges for the life science communities in the Open Science framework are to increase reuse and sustainability of data resources, software tools, and workflows, especially in large-scale data-driven research and computational analyses. Here, we present key findings, procedures, effective measures and recommendations for generating and establishing sustainable life science resources based on the collaborative, cross-disciplinary work done within the EOSC-Life (European Open Science Cloud for Life Sciences) consortium. Bringing together 13 European life science research infrastructures, it has laid the foundation for an open, digital space to support biological and medical research. Using lessons learned from 27 selected projects, we describe the organisational, technical, financial and legal/ethical challenges that represent the main barriers to sustainability in the life sciences. We show how EOSC-Life provides a model for sustainable data management according to FAIR (findability, accessibility, interoperability, and reusability) principles, including solutions for sensitive- and industry-related resources, by means of cross-disciplinary training and best practices sharing. Finally, we illustrate how data harmonisation and collaborative work facilitate interoperability of tools, data, solutions and lead to a better understanding of concepts, semantics and functionalities in the life sciences., (© 2023 The Authors. Published under the terms of the CC BY 4.0 license.)

Saccharomyces cerevisiae is the main actor of wine fermentation but at present, still little is known about the factors impacting its distribution in the vineyards. In this study, 23 vineyards and 7 cellars were sampled over 2 consecutive years in the Bordeaux and Bergerac regions. The impact of geography and farming system and the relation between grape and vat populations were evaluated using a collection of 1374 S. cerevisiae merlot grape isolates and 289 vat isolates analyzed at 17 microsatellites loci. A very high genetic diversity of S. cerevisiae strains was obtained from grape samples, higher in conventional farming system than in organic one. The geographic appellation and the wine estate significantly impact the S. cerevisiae population structure, whereas the type of farming system has a weak global effect. When comparing cellar and vineyard populations, we evidenced the tight connection between the two compartments, based on the high proportion of grape isolates (25%) related to the commercial starters used in the cellar and on the estimation of bidirectional geneflows between the vineyard and the cellar compartments.

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.

Saccharomyces cerevisiae is a common yeast with several applications, among which the most ancient is winemaking. Because individuals belonging to this species show a wide genetic and phenotypic variability, the possibility to identify the strains driving fermentation is pivotal when aiming at stable and palatable products. Metagenomic sequencing is increasingly used to decipher the fungal populations present in complex samples such as musts. However, it does not provide information at the strain level. Microsatellites are commonly used to describe the genotype of single strains. Here we developed a population-level microsatellite profiling approach, SID (Saccharomyces cerevisiae IDentifier), to identify the strains present in complex environmental samples. We optimized and assessed the performances of the analytical procedure on patterns generated in silico by computationally pooling Saccharomyces cerevisiae microsatellite profiles, and on samples obtained by pooling DNA of different strains, proving its ability to characterize real samples of grape wine fermentations. SID showed clear differences among S. cerevisiae populations in grape fermentation samples, identifying strains that are likely composing the populations and highlighting the impact of the inoculation of selected exogenous strains on natural strains. This tool can be successfully exploited to identify S. cerevisiae strains in any kind of complex samples.