Project 3.2.3

Defining the nutritional drivers of yeast performance and matching yeast to must

Project summary

From the AWRI’s extensive experience in the rescue of suboptimal fermentations, it has become increasingly clear that the ability to predict problematic fermentations, beyond an understanding of the impacts of sugar and nitrogen, is extremely poor. Work is therefore in progress to develop a greater understanding of the interactions of yeast strains with their environment. While currently over 200 yeast strains are available to the wine industry, there is limited detail available on how they perform in different contexts. This project aims to expand knowledge of yeast strain performance under a range of environmental conditions (i.e. in grape juices of widely varying composition as used for a range of wine styles) and inform winemakers about how they can reduce the risks of suboptimal fermentations though yeast strain choice.

Latest information

Defining yeast strain relationships through whole genome sequencing
Whole genome sequence data is now available for 200 wine yeast via the National Center for Biotechnology Information short read archive under the accession number SRP066835. This data archive contains genomic sequence information on wine, ale and cider yeasts of commercial and environmental origin, including species of Saccharomyces cerevisiae, Saccharomyces uvarum and hybrids of S. cerevisiae with non-cerevisiae Saccharomyces yeast including S. eubayanus, S. paradoxus and kudriazevii. The comparative analysis of this data has been published in the journal Genes|Genomes|Genetics.

Parallel phenotypic assessment using barcoded strains
A barcoded wine yeast collection developed in previous years is now being used to assess strain fitness in a variety of environments that reflect the natural compositional variation in winery-produced grape juice. Variables such as nitrogen, sugar, copper and vitamin concentrations and a range of temperatures and pH levels have been evaluated individually and in combination. Some individual factors were strong discriminants of yeast performance whereas combinations of difficult conditions had a levelling effect on competitive fitness rather than allowing the fittest to rise to dominance. Following the determination of individual yeast fitness profiles, more traditional genetic approaches, such as mating and phenotyping of progeny, are being used to identify the determinants of fitness in different environments.

Project Team

Markus Herderich
Simon Schmidt
Anthony Borneman
Angus Forgan
Paul Henschke
Radka Kolouchova