Transcriptional Regulation and the Diversification of Metabolism in Wine Yeast Strains
Author(s) -
Debra Rossouw,
Dan Jacobson,
Florian F. Bauer
Publication year - 2011
Publication title -
genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.792
H-Index - 246
eISSN - 1943-2631
pISSN - 0016-6731
DOI - 10.1534/genetics.111.132720
Subject(s) - biology , winemaking , yeast in winemaking , wine , saccharomyces cerevisiae , transcription factor , yeast , genetics , gene , gene expression , phenotype , gene regulatory network , regulation of gene expression , transcription (linguistics) , fermentation in winemaking , computational biology , food science , linguistics , philosophy
Transcription factors and their binding sites have been proposed as primary targets of evolutionary adaptation because changes to single transcription factors can lead to far-reaching changes in gene expression patterns. Nevertheless, there is very little concrete evidence for such evolutionary changes. Industrial wine yeast strains, of the species Saccharomyces cerevisiae, are a geno- and phenotypically diverse group of organisms that have adapted to the ecological niches of industrial winemaking environments and have been selected to produce specific styles of wine. Variation in transcriptional regulation among wine yeast strains may be responsible for many of the observed differences and specific adaptations to different fermentative conditions in the context of commercial winemaking. We analyzed gene expression profiles of wine yeast strains to assess the impact of transcription factor expression on metabolic networks. The data provide new insights into the molecular basis of variations in gene expression in industrial strains and their consequent effects on metabolic networks important to wine fermentation. We show that the metabolic phenotype of a strain can be shifted in a relatively predictable manner by changing expression levels of individual transcription factors, opening opportunities to modify transcription networks to achieve desirable outcomes.
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