Metabolic responses to ethanol in Saccharomyces cerevisiae using a gas chromatography tandem mass spectrometry-based metabolomics approach

During the fermentation process, Saccharomyces cerevisiae cells are often inhibited by the accumulated ethanol, and the mechanism of the S. cerevisiae response to ethanol is not fully understood. In the current study, a systematic analytical approach was used to investigate the changes in the S. cerevisiae cell metabolome that were elicited by treatment with various concentrations of ethanol. Gas chromatography-mass spectrometry and a multivariate analysis were employed to investigate the ethanol-associated intracellular biochemical changes in S. cerevisiae. The intracellular metabolite profiles that were found upon treatment of the cells with different concentrations of ethanol were unique and could be distinguished with the aid of principal component analysis. Furthermore, partial least-squares-discriminant analysis revealed a group classification and pairwise discrimination between the control without ethanol and ethanol treated groups, and 29 differential metabolites with variable importance in the projection value greater than 1 were identified, which was also confirmed by the subsequent hierarchical cluster analysis. The metabolic relevance of these compounds in the response of S. cerevisiae to ethanol stress was investigated. Under ethanol stress, the glycolysis was inhibited and the use of carbon sources for fermentation was diminished, which might account for the growth inhibition of S. cerevisiae cells. It was suggested that S. cerevisiae cells change the levels of fatty acids, e.g., hexadecanoic, octadecanoic and palmitelaidic acids, to maintain the integrity of their plasma membrane through decreasing membrane fluidity in the medium containing ethanol. Moreover, the increased levels of some amino acids idemtified in the cells of ethanol-treated experimental group might also confer ethanol tolerance to S. cerevisiae. These results reveal that the metabolomics strategy is a powerful tool to gain insight into the molecular mechanism of a microorganism's cellular response to environmental stress factors.