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A system based network approach to ethanol tolerance in Saccharomyces cerevisiae

BACKGROUND: Saccharomyces cerevisiae has been widely used for bio-ethanol production and development of rational genetic engineering strategies leading both to the improvement of productivity and ethanol tolerance is very important for cost-effective bio-ethanol production. Studies on the identifica...

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Autores principales: Kasavi, Ceyda, Eraslan, Serpil, Arga, Kazim Yalcin, Oner, Ebru Toksoy, Kirdar, Betul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4236716/
https://www.ncbi.nlm.nih.gov/pubmed/25103914
http://dx.doi.org/10.1186/s12918-014-0090-6
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author Kasavi, Ceyda
Eraslan, Serpil
Arga, Kazim Yalcin
Oner, Ebru Toksoy
Kirdar, Betul
author_facet Kasavi, Ceyda
Eraslan, Serpil
Arga, Kazim Yalcin
Oner, Ebru Toksoy
Kirdar, Betul
author_sort Kasavi, Ceyda
collection PubMed
description BACKGROUND: Saccharomyces cerevisiae has been widely used for bio-ethanol production and development of rational genetic engineering strategies leading both to the improvement of productivity and ethanol tolerance is very important for cost-effective bio-ethanol production. Studies on the identification of the genes that are up- or down-regulated in the presence of ethanol indicated that the genes may be involved to protect the cells against ethanol stress, but not necessarily required for ethanol tolerance. RESULTS: In the present study, a novel network based approach was developed to identify candidate genes involved in ethanol tolerance. Protein-protein interaction (PPI) network associated with ethanol tolerance (tETN) was reconstructed by integrating PPI data with Gene Ontology (GO) terms. Modular analysis of the constructed networks revealed genes with no previously reported experimental evidence related to ethanol tolerance and resulted in the identification of 17 genes with previously unknown biological functions. We have randomly selected four of these genes and deletion strains of two genes (YDR307W and YHL042W) were found to exhibit improved tolerance to ethanol when compared to wild type strain. The genome-wide transcriptomic response of yeast cells to the deletions of YDR307W and YHL042W in the absence of ethanol revealed that the deletion of YDR307W and YHL042W genes resulted in the transcriptional re-programming of the metabolism resulting from a mis-perception of the nutritional environment. Yeast cells perceived an excess amount of glucose and a deficiency of methionine or sulfur in the absence of YDR307W and YHL042W, respectively, possibly resulting from a defect in the nutritional sensing and signaling or transport mechanisms. Mutations leading to an increase in ribosome biogenesis were found to be important for the improvement of ethanol tolerance. Modulations of chronological life span were also identified to contribute to ethanol tolerance in yeast. CONCLUSIONS: The system based network approach developed allows the identification of novel gene targets for improved ethanol tolerance and supports the highly complex nature of ethanol tolerance in yeast.
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spelling pubmed-42367162014-11-20 A system based network approach to ethanol tolerance in Saccharomyces cerevisiae Kasavi, Ceyda Eraslan, Serpil Arga, Kazim Yalcin Oner, Ebru Toksoy Kirdar, Betul BMC Syst Biol Research Article BACKGROUND: Saccharomyces cerevisiae has been widely used for bio-ethanol production and development of rational genetic engineering strategies leading both to the improvement of productivity and ethanol tolerance is very important for cost-effective bio-ethanol production. Studies on the identification of the genes that are up- or down-regulated in the presence of ethanol indicated that the genes may be involved to protect the cells against ethanol stress, but not necessarily required for ethanol tolerance. RESULTS: In the present study, a novel network based approach was developed to identify candidate genes involved in ethanol tolerance. Protein-protein interaction (PPI) network associated with ethanol tolerance (tETN) was reconstructed by integrating PPI data with Gene Ontology (GO) terms. Modular analysis of the constructed networks revealed genes with no previously reported experimental evidence related to ethanol tolerance and resulted in the identification of 17 genes with previously unknown biological functions. We have randomly selected four of these genes and deletion strains of two genes (YDR307W and YHL042W) were found to exhibit improved tolerance to ethanol when compared to wild type strain. The genome-wide transcriptomic response of yeast cells to the deletions of YDR307W and YHL042W in the absence of ethanol revealed that the deletion of YDR307W and YHL042W genes resulted in the transcriptional re-programming of the metabolism resulting from a mis-perception of the nutritional environment. Yeast cells perceived an excess amount of glucose and a deficiency of methionine or sulfur in the absence of YDR307W and YHL042W, respectively, possibly resulting from a defect in the nutritional sensing and signaling or transport mechanisms. Mutations leading to an increase in ribosome biogenesis were found to be important for the improvement of ethanol tolerance. Modulations of chronological life span were also identified to contribute to ethanol tolerance in yeast. CONCLUSIONS: The system based network approach developed allows the identification of novel gene targets for improved ethanol tolerance and supports the highly complex nature of ethanol tolerance in yeast. BioMed Central 2014-08-08 /pmc/articles/PMC4236716/ /pubmed/25103914 http://dx.doi.org/10.1186/s12918-014-0090-6 Text en Copyright © 2014 Kasavi et al.; licensee BioMed Central 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 use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Kasavi, Ceyda
Eraslan, Serpil
Arga, Kazim Yalcin
Oner, Ebru Toksoy
Kirdar, Betul
A system based network approach to ethanol tolerance in Saccharomyces cerevisiae
title A system based network approach to ethanol tolerance in Saccharomyces cerevisiae
title_full A system based network approach to ethanol tolerance in Saccharomyces cerevisiae
title_fullStr A system based network approach to ethanol tolerance in Saccharomyces cerevisiae
title_full_unstemmed A system based network approach to ethanol tolerance in Saccharomyces cerevisiae
title_short A system based network approach to ethanol tolerance in Saccharomyces cerevisiae
title_sort system based network approach to ethanol tolerance in saccharomyces cerevisiae
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4236716/
https://www.ncbi.nlm.nih.gov/pubmed/25103914
http://dx.doi.org/10.1186/s12918-014-0090-6
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