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Linking genetic, metabolic, and phenotypic diversity among Saccharomyces cerevisiae strains using multi-omics associations
BACKGROUND: 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 genotypic and phenotypic diversity to boost yeast's...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6446221/ https://www.ncbi.nlm.nih.gov/pubmed/30715293 http://dx.doi.org/10.1093/gigascience/giz015 |
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author | Kang, Kang Bergdahl, Basti Machado, Daniel Dato, Laura Han, Ting-Li Li, Jun Villas-Boas, Silas Herrgård, Markus J Förster, Jochen Panagiotou, Gianni |
author_facet | Kang, Kang Bergdahl, Basti Machado, Daniel Dato, Laura Han, Ting-Li Li, Jun Villas-Boas, Silas Herrgård, Markus J Förster, Jochen Panagiotou, Gianni |
author_sort | Kang, Kang |
collection | PubMed |
description | BACKGROUND: 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 genotypic and phenotypic diversity to boost yeast's industrial value is still urgently needed. RESULTS: We analyzed 5,400 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 a wider range of resistance, which may be associated with their metabolome and fluxome signatures in the tricarboxylic acid cycle and fatty acid metabolism. By deep genomic sequencing, we found that industrial strains have more genomic duplications especially affecting transcription factors, showing that they result from disparate evolutionary paths in comparison with 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. CONCLUSIONS: These resistance-related engineering targets and strain rankings provide a valuable source for engineering significantly improved industrial platform strains. |
format | Online Article Text |
id | pubmed-6446221 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-64462212019-04-09 Linking genetic, metabolic, and phenotypic diversity among Saccharomyces cerevisiae strains using multi-omics associations Kang, Kang Bergdahl, Basti Machado, Daniel Dato, Laura Han, Ting-Li Li, Jun Villas-Boas, Silas Herrgård, Markus J Förster, Jochen Panagiotou, Gianni Gigascience Research BACKGROUND: 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 genotypic and phenotypic diversity to boost yeast's industrial value is still urgently needed. RESULTS: We analyzed 5,400 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 a wider range of resistance, which may be associated with their metabolome and fluxome signatures in the tricarboxylic acid cycle and fatty acid metabolism. By deep genomic sequencing, we found that industrial strains have more genomic duplications especially affecting transcription factors, showing that they result from disparate evolutionary paths in comparison with 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. CONCLUSIONS: These resistance-related engineering targets and strain rankings provide a valuable source for engineering significantly improved industrial platform strains. Oxford University Press 2019-01-31 /pmc/articles/PMC6446221/ /pubmed/30715293 http://dx.doi.org/10.1093/gigascience/giz015 Text en © The Author(s) 2019. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Kang, Kang Bergdahl, Basti Machado, Daniel Dato, Laura Han, Ting-Li Li, Jun Villas-Boas, Silas Herrgård, Markus J Förster, Jochen Panagiotou, Gianni Linking genetic, metabolic, and phenotypic diversity among Saccharomyces cerevisiae strains using multi-omics associations |
title | Linking genetic, metabolic, and phenotypic diversity among Saccharomyces cerevisiae strains using multi-omics associations |
title_full | Linking genetic, metabolic, and phenotypic diversity among Saccharomyces cerevisiae strains using multi-omics associations |
title_fullStr | Linking genetic, metabolic, and phenotypic diversity among Saccharomyces cerevisiae strains using multi-omics associations |
title_full_unstemmed | Linking genetic, metabolic, and phenotypic diversity among Saccharomyces cerevisiae strains using multi-omics associations |
title_short | Linking genetic, metabolic, and phenotypic diversity among Saccharomyces cerevisiae strains using multi-omics associations |
title_sort | linking genetic, metabolic, and phenotypic diversity among saccharomyces cerevisiae strains using multi-omics associations |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6446221/ https://www.ncbi.nlm.nih.gov/pubmed/30715293 http://dx.doi.org/10.1093/gigascience/giz015 |
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