Metabolomics

Dataset Information

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Linking genetic, metabolic and phenotypic diversity 1 among S. cerevisiae strains using multi-omics associations


ABSTRACT: The selection of bioengineering platform strains and engineering strategies to improve the stress resistance of Saccharomyces cerevisiae remains a pressing need in bio-based chemical production. Thus, a systematic effort to exploit the genotypic and phenotypic diversity to boost yeast’s industrial value is still urgently needed. Here, we analyzed 5400 growth curves obtained from 36 S. cerevisiae strains and comprehensively profiled their resistances against 13 industrially relevant stresses. We observed that bioethanol and brewing strains exhibit higher resistance against acidic conditions, however, plant isolates tend to have wider range of resistance, which may be associated with their metabolome and fluxome signatures in TCA cycle and fatty acid metabolism. By deep genomic sequencing we found that industrial strains have more genomic duplications especially affecting transcription factors, presenting disparate evolutionary paths in comparison to the environmental strains which have more InDels, gene deletions and strain-specific genes. Genome-wide association studies coupled with protein-protein interaction networks uncovered novel genetic determinants of stress resistances. These resistance-related engineering targets and strain rankings provide a valuable source for engineering significantly improved industrial platform strains.

This metabolomic study of 36 yeast strains measured intra- and extracellular metabolome under standard glucose medium, profiled by GS-MS. This is part of a multi-omic study on yeast strain collection.

INSTRUMENT(S): Gas Chromatography MS - Positive (GC-MS (Positive))

SUBMITTER: Kang Kang 

PROVIDER: MTBLS780 | MetaboLights | 2019-01-16

REPOSITORIES: MetaboLights

Dataset's files

Source:
Action DRS
MTBLS780 Other
FILES Other
a_MTBLS780_EXTRA_cfb_yeast_metabolite_profiling_mass_spectrometry.txt Txt
a_MTBLS780_INTRA_cfb_yeast_metabolite_profiling_mass_spectrometry.txt Txt
i_Investigation.txt Txt
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