Linking genetic, metabolic, and phenotypic diversity among Saccharomyces cerevisiae strains using multi-omics associations
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/1822/59873 |
Resumo: | 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. |
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Linking genetic, metabolic, and phenotypic diversity among Saccharomyces cerevisiae strains using multi-omics associationsgeno-to-phenotype associationmulti-omic studyplatform strainSaccharomyces cerevisiaestress resistanceScience & TechnologyThe 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.G.P. would like to thank Deutsche Forschungsgemeinschaft (DFG) CRC/Transregio 124 “Pathogenic fungi and their human host: Networks of interaction,” subproject B5. B.B., L.D., M.J.H., and J.F. thank the Novo Nordisk Foundation for financial support.info:eu-repo/semantics/publishedVersionOxford University PressUniversidade do MinhoKang, KangBergdahl, BastiMachado, DanielDato, LauraHan, Ting-LiLi, JunVillas-Boas, SilasHerrgård, Markus J.Förster, JochenPanagiotou, Gianni20192019-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/59873engKang, 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. GigaScience, 8(4), giz015, 20192047-217X10.1093/gigascience/giz01530715293https://academic.oup.com/gigascienceinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:41:55ZPortal AgregadorONG |
dc.title.none.fl_str_mv |
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 |
spellingShingle |
Linking genetic, metabolic, and phenotypic diversity among Saccharomyces cerevisiae strains using multi-omics associations Kang, Kang geno-to-phenotype association multi-omic study platform strain Saccharomyces cerevisiae stress resistance Science & Technology |
title_short |
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_sort |
Linking genetic, metabolic, and phenotypic diversity among Saccharomyces cerevisiae strains using multi-omics associations |
author |
Kang, Kang |
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_role |
author |
author2 |
Bergdahl, Basti Machado, Daniel Dato, Laura Han, Ting-Li Li, Jun Villas-Boas, Silas Herrgård, Markus J. Förster, Jochen Panagiotou, Gianni |
author2_role |
author author author author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Kang, Kang Bergdahl, Basti Machado, Daniel Dato, Laura Han, Ting-Li Li, Jun Villas-Boas, Silas Herrgård, Markus J. Förster, Jochen Panagiotou, Gianni |
dc.subject.por.fl_str_mv |
geno-to-phenotype association multi-omic study platform strain Saccharomyces cerevisiae stress resistance Science & Technology |
topic |
geno-to-phenotype association multi-omic study platform strain Saccharomyces cerevisiae stress resistance Science & Technology |
description |
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. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019 2019-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/1822/59873 |
url |
http://hdl.handle.net/1822/59873 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
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. GigaScience, 8(4), giz015, 2019 2047-217X 10.1093/gigascience/giz015 30715293 https://academic.oup.com/gigascience |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Oxford University Press |
publisher.none.fl_str_mv |
Oxford University Press |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
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repository.mail.fl_str_mv |
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1777303821302628352 |