Comparative 'omic' profiling of industrial wine yeast strains
Date
2009-12
Authors
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Publisher
Stellenbosch : Stellenbosch University
Abstract
The main goal of this project was to elucidate the underlying genetic factors responsible for the
different fermentation phenotypes and physiological adaptations of industrial wine yeast strains. To
address this problem an ‘omic’ approach was pursued: Five industrial wine yeast strains, namely
VIN13, EC1118, BM45, 285 and DV10, were subjected to transcriptional, proteomic and exometabolomic
profiling during alcoholic fermentation in simulated wine-making conditions. The aim
was to evaluate and integrate the various layers of data in order to obtain a clearer picture of the
genetic regulation and metabolism of wine yeast strains under anaerobic fermentative conditions.
The five strains were also characterized in terms of their adhesion/flocculation phenotypes,
tolerance to various stresses and survival under conditions of nutrient starvation.
Transcriptional profiles for the entire yeast genome were obtained for three crucial stages during
fermentation, namely the exponential growth phase (day 2), early stationary phase (day 5) and late
stationary phase (day 14). Analysis of changes in gene expression profiles during the course of
fermentation provided valuable insights into the genetic changes that occur as the yeast adapt to
changing conditions during fermentation. Comparison of differentially expressed transcripts
between strains also enabled the identification of genetic factors responsible for differences in the
metabolism of these strains, and paved the way for genetic engineering of strains with directed
modifications in key areas. In particular, the integration of exo-metabolite profiles and gene
expression data for the strains enabled the construction of statistical models with a strong predictive
capability which was validated experimentally.
Proteomic analysis enabled correlations to be made between relative transcript abundance and
protein levels for approximately 450 gene and protein pairs per analysis. The alignment of
transcriptome and proteome data was very accurate for interstrain comparisons. For intrastrain
comparisons, there was almost no correlation between trends in protein and transcript levels, except
in certain functional categories such as metabolism. The data also provide interesting insights into
molecular evolutionary mechanisms that underlie the phenotypic diversity of wine yeast strains.
Overall, the systems biology approach to the study of yeast metabolism during alcoholic
fermentation opened up new avenues for hypothesis-driven research and targeted engineering
strategies for the genetic enhancement/ modification of wine yeast for commercial applications.
Description
Thesis (PhD(Agric) Viticulture and Oenology. Wine Biotechnology))--University of Stellenbosch, 2009.
Keywords
Wine yeast, Transcriptomics, Agriculture