Moving the wine yeast Saccharomyces cerevisiae up its adaptive peak in grape must – PEAKYEAST

During the first phase of the collection and identification of the microbial diversity of moutards in the Languedoc vineyards, we conducted parallel approaches to classical microbiology and metagenomics. This collection of microorganisms allowed us to begin the analysis of the diversity of two major species of the microbial community of the mout, through the analysis of genomes, in order to highlight the presence of events of horizontal transfers . In parallel, an experimental evolution approach will be set up to study the contribution of the genetic variability of yeast populations to adaptation to the mout. Finally, experimental horizontal transfers will be produced to evaluate the adaptive capacities offered by this type of evolution.

During the first step of the project, dedicated to the analysis of the microbial communities of two grapes varieties present in Languedoc vineyards : Viognier and Sauvignon, we have built a collection of grape must microorganisms (yeast and bacteria) which will be available from the collections: CIRM Levures and CIRM BIA respectively. The comparison of grape must microbial communities suggest inter-site differences, but the vintage appears to have had a major effect on microfloral composition. This set of grape must microorganisms allowed us to initiate the analysis of the diversity of two major species through the analysis of genomes. In parallel, recombinant populations with different levels of genetic diversity have been constructed. These populations will be used for forecoming experimental evolution of yeast in the grape must. Finally, libraries of T. microellipsoides in S. cerevisiae were constructed in order to model the adaptation allowed by horizontal transfers .

The genomic analyzes carried out on several yeast species found on grapes must, will enable us to detect horizontally transferred genes, between yeast species of the grapes microflore. These genes will allow us to identify functions possibly critical for growth in grape must. Moreover, experimental evolutions will allow us to answer the initial questions: evolve S. cerevisiae towards its adaptive peak in grape must. It will enable us to identify new possibilities for improving wine yeast from using genetic diversity. l

in preparation

Sustaining a growing population while preserving nature is challenging, especially when climates are increasingly unpredictable. Wine is one of the main commodities of the French economy, accounting for 1.3% of total exports in 2012 (5.6 billion euros of wine exports). In the context of global change and a highly competitive international market, maintaining high production levels of fine wine while limiting chemical inputs will require biological innovations. Such breakthroughs are likely to arise from experimenting with the grape must’s microbial community, a neglected actor of winemaking which impacts many wine characteristics. Much has yet to be learned about the main wine yeast, Saccharomyces cerevisiae, which can still fail to carry out alcoholic fermentation to fruition, despite modern microbiological techniques aimed at controlling fermentations. Although there is evidence that S. cerevisiae carries specific adaptations for growing in grape must, its overall level of adaptation to grape must is unknown. This matter can only be resolved with selection experiments, which assess the effect of new genetic variation on adaptation.

We propose to study the adaptive potential of S. cerevisiae in natural grape must, including their microbial communities. We will analyze the impact of i) different amount of standing genetic variation and ii) experimental horizontal gene transfers (HGT) on yeast adaptation to different biotic and abiotic environments. These two genetic mechanisms of adaptation (standing genetic variation and HGT) correspond to previously described modes of adaptation to grape must by S. cerevisiae. Specifically, adaptation in S. cerevisiae will be studied in a factorial selection experiment involving five microbial community treatments (T. delbrueckii, H. uvarum, both species, whole microbial community, or sterile grape must) and three recombinant populations of S. cerevisiae (wine strains alone, wine strains and closely related domesticated strains, or strains from all known S. cerevisiae sub-groups). The competitive fitness, fermentation traits, and genomics of adaptation will be studied in the evolved populations. The prevalence of HGT as a mechanism of adaptation to grape musts will be studied among non-Saccharomyces yeasts isolated from natural grape musts, as well as with experimental evolution in S. cerevisiae. Two strategies of experimental HGT will be implemented to test if new HGT can be beneficial for S. cerevisiae in grape must.

Our findings will be applicable to oenological research because all experiments will be performed in natural grape must using species and strains isolated from that environment, instead of using single-clones with undefined evolutionary history in standard laboratory media (typical for microbial evolutionary experiments). This innovative approach will allow us to test if previous laboratory studies are transposable to complex natural environments. Our work can impact wine starter technologies by providing new alleles, allele combinations for improving wine technological traits (i.e. fermentation completion). Better knowledge of the ecological niche of wine yeasts, including the effect of biotic interactions on S. cerevisiae growth and evolution, will help stabilize alcoholic fermentations. Moreover, experimental horizontal gene transfer (eHGT) has never been studied as extensively as in our project. Our results will increase dramatically our knowledge of the prevalence and functions of horizontal gene transfers. Sequencing genomes from species isolated from grape must’s microbial communities will fill a major gap in our knowledge of these communities, including the importance of HGT. The project will benefit from our broad consortium of experts because it requires the integration of new challenging approaches (eHGT, experimental evolution in complex environments) and advanced tools (phenomics robotic platform, genomics).