New integrative computational approaches unveil the Saccharomyces cerevisiae pheno-metabolomic fermentative profile and allow strain selection for winemaking
Autor(a) principal: | |
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Data de Publicação: | 2016 |
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/1822/41774 |
Resumo: | During must fermentation by Saccharomyces cerevisiae strains thousands of volatile aroma compounds are formed. The objective of the present work was to adapt computational approaches to analyze pheno-metabolomic diversity of a S. cerevisiae strain collection with different origins. Phenotypic and genetic characterization together with individual must fermentations were performed, and metabolites relevant to aromatic profiles were determined. Experimental results were projected onto a common coordinates system, revealing 17 statistical-relevant multi-dimensional modules, combining sets of most-correlated features of noteworthy biological importance. The present method allowed, as a breakthrough, to combine genetic, phenotypic and metabolomic data, which has not been possible so far due to difficulties in comparing different types of data. Therefore, the proposed computational approach revealed as successful to shed light into the holistic characterization of S. cerevisiae pheno-metabolome in must fermentative conditions. This will allow the identification of combined relevant features with application in selection of good winemaking strains. |
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New integrative computational approaches unveil the Saccharomyces cerevisiae pheno-metabolomic fermentative profile and allow strain selection for winemakingSaccharomyces cerevisiaeData-fusionWine yeastsMetabolomicsMatrix factorizationScience & TechnologyDuring must fermentation by Saccharomyces cerevisiae strains thousands of volatile aroma compounds are formed. The objective of the present work was to adapt computational approaches to analyze pheno-metabolomic diversity of a S. cerevisiae strain collection with different origins. Phenotypic and genetic characterization together with individual must fermentations were performed, and metabolites relevant to aromatic profiles were determined. Experimental results were projected onto a common coordinates system, revealing 17 statistical-relevant multi-dimensional modules, combining sets of most-correlated features of noteworthy biological importance. The present method allowed, as a breakthrough, to combine genetic, phenotypic and metabolomic data, which has not been possible so far due to difficulties in comparing different types of data. Therefore, the proposed computational approach revealed as successful to shed light into the holistic characterization of S. cerevisiae pheno-metabolome in must fermentative conditions. This will allow the identification of combined relevant features with application in selection of good winemaking strains.Ines Mendes was recipient of a fellowship from the Portuguese Science Foundation, FCT (SFRH/BD/74798/2010). This work was supported by FCT I.P. through the strategic funding UID/BIA/04050/2013, and the project PTDC/AGR-ALI/121062/2010.Elsevier B.V.Universidade do MinhoDuarte, Ricardo FrancoUmek, LanMendes, InêsCastro, C. C.Fonseca, NunoMartins, RosaFerreira, António C. SilvaSampaio, PaulaPais, CéliaSchuller, Dorit2016-11-152016-11-15T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/41774engFranco-Duarte, Ricardo; Umek, Lan; Mendes, Inês; Castro, C. C.; Fonseca, Nuno; Martins, Rosa; Silva-Ferreira, António C.; Sampaio, Paula; Pais, Célia; Schuller, Dorit, New integrative computational approaches unveil the Saccharomyces cerevisiae pheno-metabolomic fermentative profile and allow strain selection for winemaking. Food Chemistry, 211, 509-520, 20160308-81460308-814610.1016/j.foodchem.2016.05.08027283661http://www.elsevier.com/locate/issn/03088146info: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:RCAAP2023-07-21T12:22:21Zoai:repositorium.sdum.uminho.pt:1822/41774Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:15:49.660540Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
New integrative computational approaches unveil the Saccharomyces cerevisiae pheno-metabolomic fermentative profile and allow strain selection for winemaking |
title |
New integrative computational approaches unveil the Saccharomyces cerevisiae pheno-metabolomic fermentative profile and allow strain selection for winemaking |
spellingShingle |
New integrative computational approaches unveil the Saccharomyces cerevisiae pheno-metabolomic fermentative profile and allow strain selection for winemaking Duarte, Ricardo Franco Saccharomyces cerevisiae Data-fusion Wine yeasts Metabolomics Matrix factorization Science & Technology |
title_short |
New integrative computational approaches unveil the Saccharomyces cerevisiae pheno-metabolomic fermentative profile and allow strain selection for winemaking |
title_full |
New integrative computational approaches unveil the Saccharomyces cerevisiae pheno-metabolomic fermentative profile and allow strain selection for winemaking |
title_fullStr |
New integrative computational approaches unveil the Saccharomyces cerevisiae pheno-metabolomic fermentative profile and allow strain selection for winemaking |
title_full_unstemmed |
New integrative computational approaches unveil the Saccharomyces cerevisiae pheno-metabolomic fermentative profile and allow strain selection for winemaking |
title_sort |
New integrative computational approaches unveil the Saccharomyces cerevisiae pheno-metabolomic fermentative profile and allow strain selection for winemaking |
author |
Duarte, Ricardo Franco |
author_facet |
Duarte, Ricardo Franco Umek, Lan Mendes, Inês Castro, C. C. Fonseca, Nuno Martins, Rosa Ferreira, António C. Silva Sampaio, Paula Pais, Célia Schuller, Dorit |
author_role |
author |
author2 |
Umek, Lan Mendes, Inês Castro, C. C. Fonseca, Nuno Martins, Rosa Ferreira, António C. Silva Sampaio, Paula Pais, Célia Schuller, Dorit |
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 |
Duarte, Ricardo Franco Umek, Lan Mendes, Inês Castro, C. C. Fonseca, Nuno Martins, Rosa Ferreira, António C. Silva Sampaio, Paula Pais, Célia Schuller, Dorit |
dc.subject.por.fl_str_mv |
Saccharomyces cerevisiae Data-fusion Wine yeasts Metabolomics Matrix factorization Science & Technology |
topic |
Saccharomyces cerevisiae Data-fusion Wine yeasts Metabolomics Matrix factorization Science & Technology |
description |
During must fermentation by Saccharomyces cerevisiae strains thousands of volatile aroma compounds are formed. The objective of the present work was to adapt computational approaches to analyze pheno-metabolomic diversity of a S. cerevisiae strain collection with different origins. Phenotypic and genetic characterization together with individual must fermentations were performed, and metabolites relevant to aromatic profiles were determined. Experimental results were projected onto a common coordinates system, revealing 17 statistical-relevant multi-dimensional modules, combining sets of most-correlated features of noteworthy biological importance. The present method allowed, as a breakthrough, to combine genetic, phenotypic and metabolomic data, which has not been possible so far due to difficulties in comparing different types of data. Therefore, the proposed computational approach revealed as successful to shed light into the holistic characterization of S. cerevisiae pheno-metabolome in must fermentative conditions. This will allow the identification of combined relevant features with application in selection of good winemaking strains. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-11-15 2016-11-15T00:00:00Z |
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/1822/41774 |
url |
http://hdl.handle.net/1822/41774 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Franco-Duarte, Ricardo; Umek, Lan; Mendes, Inês; Castro, C. C.; Fonseca, Nuno; Martins, Rosa; Silva-Ferreira, António C.; Sampaio, Paula; Pais, Célia; Schuller, Dorit, New integrative computational approaches unveil the Saccharomyces cerevisiae pheno-metabolomic fermentative profile and allow strain selection for winemaking. Food Chemistry, 211, 509-520, 2016 0308-8146 0308-8146 10.1016/j.foodchem.2016.05.080 27283661 http://www.elsevier.com/locate/issn/03088146 |
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 |
Elsevier B.V. |
publisher.none.fl_str_mv |
Elsevier B.V. |
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 |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799132605458677760 |