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QTL mapping of modelled metabolic fluxes reveals gene variants impacting yeast central carbon metabolism

The yeast Saccharomyces cerevisiae is an attractive industrial microorganism for the production of foods and beverages as well as for various bulk and fine chemicals, such as biofuels or fragrances. Building blocks for these biosyntheses are intermediates of yeast central carbon metabolism (CCM), wh...

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Autores principales: Eder, Matthias, Nidelet, Thibault, Sanchez, Isabelle, Camarasa, Carole, Legras, Jean-Luc, Dequin, Sylvie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7005809/
https://www.ncbi.nlm.nih.gov/pubmed/32034164
http://dx.doi.org/10.1038/s41598-020-57857-3
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author Eder, Matthias
Nidelet, Thibault
Sanchez, Isabelle
Camarasa, Carole
Legras, Jean-Luc
Dequin, Sylvie
author_facet Eder, Matthias
Nidelet, Thibault
Sanchez, Isabelle
Camarasa, Carole
Legras, Jean-Luc
Dequin, Sylvie
author_sort Eder, Matthias
collection PubMed
description The yeast Saccharomyces cerevisiae is an attractive industrial microorganism for the production of foods and beverages as well as for various bulk and fine chemicals, such as biofuels or fragrances. Building blocks for these biosyntheses are intermediates of yeast central carbon metabolism (CCM), whose intracellular availability depends on balanced single reactions that form metabolic fluxes. Therefore, efficient product biosynthesis is influenced by the distribution of these fluxes. We recently demonstrated great variations in CCM fluxes between yeast strains of different origins. However, we have limited understanding of flux modulation and the genetic basis of flux variations. In this study, we investigated the potential of quantitative trait locus (QTL) mapping to elucidate genetic variations responsible for differences in metabolic flux distributions (fQTL). Intracellular metabolic fluxes were estimated by constraint-based modelling and used as quantitative phenotypes, and differences in fluxes were linked to genomic variations. Using this approach, we detected four fQTLs that influence metabolic pathways. The molecular dissection of these QTLs revealed two allelic gene variants, PDB1 and VID30, contributing to flux distribution. The elucidation of genetic determinants influencing metabolic fluxes, as reported here for the first time, creates new opportunities for the development of strains with optimized metabolite profiles for various applications.
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spelling pubmed-70058092020-02-18 QTL mapping of modelled metabolic fluxes reveals gene variants impacting yeast central carbon metabolism Eder, Matthias Nidelet, Thibault Sanchez, Isabelle Camarasa, Carole Legras, Jean-Luc Dequin, Sylvie Sci Rep Article The yeast Saccharomyces cerevisiae is an attractive industrial microorganism for the production of foods and beverages as well as for various bulk and fine chemicals, such as biofuels or fragrances. Building blocks for these biosyntheses are intermediates of yeast central carbon metabolism (CCM), whose intracellular availability depends on balanced single reactions that form metabolic fluxes. Therefore, efficient product biosynthesis is influenced by the distribution of these fluxes. We recently demonstrated great variations in CCM fluxes between yeast strains of different origins. However, we have limited understanding of flux modulation and the genetic basis of flux variations. In this study, we investigated the potential of quantitative trait locus (QTL) mapping to elucidate genetic variations responsible for differences in metabolic flux distributions (fQTL). Intracellular metabolic fluxes were estimated by constraint-based modelling and used as quantitative phenotypes, and differences in fluxes were linked to genomic variations. Using this approach, we detected four fQTLs that influence metabolic pathways. The molecular dissection of these QTLs revealed two allelic gene variants, PDB1 and VID30, contributing to flux distribution. The elucidation of genetic determinants influencing metabolic fluxes, as reported here for the first time, creates new opportunities for the development of strains with optimized metabolite profiles for various applications. Nature Publishing Group UK 2020-02-07 /pmc/articles/PMC7005809/ /pubmed/32034164 http://dx.doi.org/10.1038/s41598-020-57857-3 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Eder, Matthias
Nidelet, Thibault
Sanchez, Isabelle
Camarasa, Carole
Legras, Jean-Luc
Dequin, Sylvie
QTL mapping of modelled metabolic fluxes reveals gene variants impacting yeast central carbon metabolism
title QTL mapping of modelled metabolic fluxes reveals gene variants impacting yeast central carbon metabolism
title_full QTL mapping of modelled metabolic fluxes reveals gene variants impacting yeast central carbon metabolism
title_fullStr QTL mapping of modelled metabolic fluxes reveals gene variants impacting yeast central carbon metabolism
title_full_unstemmed QTL mapping of modelled metabolic fluxes reveals gene variants impacting yeast central carbon metabolism
title_short QTL mapping of modelled metabolic fluxes reveals gene variants impacting yeast central carbon metabolism
title_sort qtl mapping of modelled metabolic fluxes reveals gene variants impacting yeast central carbon metabolism
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7005809/
https://www.ncbi.nlm.nih.gov/pubmed/32034164
http://dx.doi.org/10.1038/s41598-020-57857-3
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