Comparative transcriptomic approach to investigate differences in wine yeast physiology and metabolism during fermentation.
Debra Rossouw, Roberto Olivares-Hernandes, Jens Nielsen, Florian F Bauer
文献索引：Appl. Environ. Microbiol. 75(20) , 6600-12, (2009)
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摘要
Commercial wine yeast strains of the species Saccharomyces cerevisiae have been selected to satisfy many different, and sometimes highly specific, oenological requirements. As a consequence, more than 200 different strains with significantly diverging phenotypic traits are produced globally. This genetic resource has been rather neglected by the scientific community because industrial strains are less easily manipulated than the limited number of laboratory strains that have been successfully employed to investigate fundamental aspects of cellular biology. However, laboratory strains are unsuitable for the study of many phenotypes that are of significant scientific and industrial interest. Here, we investigate whether a comparative transcriptomics and phenomics approach, based on the analysis of five phenotypically diverging industrial wine yeast strains, can provide insights into the molecular networks that are responsible for the expression of such phenotypes. For this purpose, some oenologically relevant phenotypes, including resistance to various stresses, cell wall properties, and metabolite production of these strains were evaluated and aligned with transcriptomic data collected during alcoholic fermentation. The data reveal significant differences in gene regulation between the five strains. While the genetic complexity underlying the various successive stress responses in a dynamic system such as wine fermentation reveals the limits of the approach, many of the relevant differences in gene expression can be linked to specific phenotypic differences between the strains. This is, in particular, the case for many aspects of metabolic regulation. The comparative approach therefore opens new possibilities to investigate complex phenotypic traits on a molecular level.