Since elevated ethanol is a major stress during ethanol fermentation, yeast strains tolerant to ethanol are highly desirable for the industrial scale ethanol production. A technology called global transcriptional machinery engineering (gTME), which exploits a mutant library of SPT15 encoding the TATA-binding protein of Saccharomyces cerevisiae (Alper et al., 2006; Science 314: 1565-1568), seems to a powerful tool for creating ethanol-tolerant strains. However, the ability of created strains to tolerate high ethanol on rich media remains unproven. In this study, a similar strategy was used to obtain five strains with enhanced ethanol tolerance (ETS1-5) of S. cerevisiae. Comparing global transcriptional profiles of two selected strains ETS2 and ETS3 with that of the control identified 42 genes that were commonly regulated with twofold change. Out of 34 deletion mutants available from a gene knockout library, 18 were ethanol sensitive, suggesting that these genes were closely associated with ethanol tolerance. Eight of them were novel with most being functionally unknown. To establish a basis for future industrial applications, strains iETS2 and iETS3 were created by integrating the SPT15 mutant alleles of ETS2 and ETS3 into the chromosomes, which also exhibited enhanced ethanol tolerance and survival upon ethanol shock on a rich medium. Fermentation with 20% glucose for 24 h in a bioreactor revealed that iETS2 and iETS3 grew better and produced approximately 25% more ethanol than a control strain. The ethanol yield and productivity were also substantially enhanced: 0.31 g/g and 2.6 g/L/h, respectively, for control and 0.39 g/g and 3.2 g/L/h, respectively, for iETS2 and iETS3. Thus, our study demonstrates the utility of gTME in generating strains with enhanced ethanol tolerance that resulted in increase of ethanol production. Strains with enhanced tolerance to other stresses such as heat, fermentation inhibitors, osmotic pressure, and so on, may be further created by using gTME.

• PMID: 21437883
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Journal Article | Research Support, Non-U.S. Gov't

Authors

Yang J, Bae JY, Lee YM, Kwon H, Moon HY, Kang HA, Yee SB, Kim W, Choi W

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