title: A metabolomics-based strategy for identification of gene targets for phenotype improvement and its application to 1-butanol tolerance in Saccharomyces cerevisiae.
abstract: BACKGROUND
  Traditional approaches to phenotype improvement include rational selection of genes for modification, and probability-driven processes such as laboratory evolution or random mutagenesis. A promising middle-ground approach is semi-rational engineering, where genetic modification targets are inferred from system-wide comparison of strains. Here, we have applied a metabolomics-based, semi-rational strategy of phenotype improvement to 1-butanol tolerance in Saccharomyces cerevisiae.
  
  
  RESULTS
  Nineteen yeast single-deletion mutant strains with varying growth rates under 1-butanol stress were subjected to non-targeted metabolome analysis by GC/MS, and a regression model was constructed using metabolite peak intensities as predictors and stress growth rates as the response. From this model, metabolites positively and negatively correlated with growth rate were identified including threonine and citric acid. Based on the assumption that these metabolites were linked to 1-butanol tolerance, new deletion strains accumulating higher threonine or lower citric acid were selected and subjected to tolerance measurement and metabolome analysis. The new strains exhibiting the predicted changes in metabolite levels also displayed significantly higher growth rate under stress over the control strain, thus validating the link between these metabolites and 1-butanol tolerance.
  
  
  CONCLUSIONS
  A strategy for semi-rational phenotype improvement using metabolomics was proposed and applied to the 1-butanol tolerance of S. cerevisiae. Metabolites correlated with growth rate under 1-butanol stress were identified, and new mutant strains showing higher growth rate under stress could be selected based on these metabolites. The results demonstrate the potential of metabolomics in semi-rational strain engineering.
authors.affiliation: Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871 Japan.
authors.forename: Shao Thing
authors.initials: ST
authors.lastname: Teoh
authors.affiliation: Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871 Japan.
authors.forename: Sastia
authors.initials: S
authors.lastname: Putri
authors.affiliation: Department of Bioscience, Nagahama Institute of Bio-Science and Technology, 1266 Tamura, Nagahama, Shiga 526-0829 Japan.
authors.forename: Yukio
authors.initials: Y
authors.lastname: Mukai
authors.affiliation: Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871 Japan.
authors.forename: Takeshi
authors.initials: T
authors.lastname: Bamba
authors.affiliation: Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871 Japan.
authors.forename: Eiichiro
authors.initials: E
authors.lastname: Fukusaki
keywords: 1-Butanol tolerance; Metabolomics; Orthogonal projections to latent structures; Phenotype improvement; Regression model; Saccharomyces cerevisiae; Semi-rational strain engineering