Metabolomics-based prediction models of yeast strains for screening of metabolites contributing to ethanol stress tolerance

International Conference on Chemical and Bioprocess Engineering

地球科学;化学;生物科学

Hashim, Z.^1 ; Fukusaki, E.^2

Department of Bioprocess Engineering, Faculty of Chemical Engineering, Universiti Teknologi Malaysia, Skudai, Johor

81310, Malaysia^1

Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Osaka, Suita

565-0871, Japan^2

关键词: Biofuel production;    Ethanol production;    Ethanol tolerance;    Microbial system;    Multivariate models;    Prediction model;    Production yield;    Strain improvement;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/36/1/012046/pdf
DOI  :  10.1088/1755-1315/36/1/012046

学科分类：生物科学（综合）

来源: IOP

【 摘 要 】

The increased demand for clean, sustainable and renewable energy resources has driven the development of various microbial systems to produce biofuels. One of such systems is the ethanol-producing yeast. Although yeast produces ethanol naturally using its native pathways, production yield is low and requires improvement for commercial biofuel production. Moreover, ethanol is toxic to yeast and thus ethanol tolerance should be improved to further enhance ethanol production. In this study, we employed metabolomics-based strategy using 30 single-gene deleted yeast strains to construct multivariate models for ethanol tolerance and screen metabolites that relate to ethanol sensitivity/tolerance. The information obtained from this study can be used as an input for strain improvement via metabolic engineering.