Cargando…

SaccharomycesIDentifier, SID: strain-level analysis of Saccharomyces cerevisiae populations by using microsatellite meta-patterns

Saccharomyces cerevisiae is a common yeast with several applications, among which the most ancient is winemaking. Because individuals belonging to this species show a wide genetic and phenotypic variability, the possibility to identify the strains driving fermentation is pivotal when aiming at stabl...

Descripción completa

Detalles Bibliográficos
Autores principales: Stefanini, Irene, Albanese, Davide, Sordo, Maddalena, Legras, Jean-Luc, De Filippo, Carlotta, Cavalieri, Duccio, Donati, Claudio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5681646/
https://www.ncbi.nlm.nih.gov/pubmed/29127392
http://dx.doi.org/10.1038/s41598-017-15729-3
_version_ 1783277949034692608
author Stefanini, Irene
Albanese, Davide
Sordo, Maddalena
Legras, Jean-Luc
De Filippo, Carlotta
Cavalieri, Duccio
Donati, Claudio
author_facet Stefanini, Irene
Albanese, Davide
Sordo, Maddalena
Legras, Jean-Luc
De Filippo, Carlotta
Cavalieri, Duccio
Donati, Claudio
author_sort Stefanini, Irene
collection PubMed
description Saccharomyces cerevisiae is a common yeast with several applications, among which the most ancient is winemaking. Because individuals belonging to this species show a wide genetic and phenotypic variability, the possibility to identify the strains driving fermentation is pivotal when aiming at stable and palatable products. Metagenomic sequencing is increasingly used to decipher the fungal populations present in complex samples such as musts. However, it does not provide information at the strain level. Microsatellites are commonly used to describe the genotype of single strains. Here we developed a population-level microsatellite profiling approach, SID (Saccharomyces cerevisiae IDentifier), to identify the strains present in complex environmental samples. We optimized and assessed the performances of the analytical procedure on patterns generated in silico by computationally pooling Saccharomyces cerevisiae microsatellite profiles, and on samples obtained by pooling DNA of different strains, proving its ability to characterize real samples of grape wine fermentations. SID showed clear differences among S. cerevisiae populations in grape fermentation samples, identifying strains that are likely composing the populations and highlighting the impact of the inoculation of selected exogenous strains on natural strains. This tool can be successfully exploited to identify S. cerevisiae strains in any kind of complex samples.
format Online
Article
Text
id pubmed-5681646
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-56816462017-11-17 SaccharomycesIDentifier, SID: strain-level analysis of Saccharomyces cerevisiae populations by using microsatellite meta-patterns Stefanini, Irene Albanese, Davide Sordo, Maddalena Legras, Jean-Luc De Filippo, Carlotta Cavalieri, Duccio Donati, Claudio Sci Rep Article Saccharomyces cerevisiae is a common yeast with several applications, among which the most ancient is winemaking. Because individuals belonging to this species show a wide genetic and phenotypic variability, the possibility to identify the strains driving fermentation is pivotal when aiming at stable and palatable products. Metagenomic sequencing is increasingly used to decipher the fungal populations present in complex samples such as musts. However, it does not provide information at the strain level. Microsatellites are commonly used to describe the genotype of single strains. Here we developed a population-level microsatellite profiling approach, SID (Saccharomyces cerevisiae IDentifier), to identify the strains present in complex environmental samples. We optimized and assessed the performances of the analytical procedure on patterns generated in silico by computationally pooling Saccharomyces cerevisiae microsatellite profiles, and on samples obtained by pooling DNA of different strains, proving its ability to characterize real samples of grape wine fermentations. SID showed clear differences among S. cerevisiae populations in grape fermentation samples, identifying strains that are likely composing the populations and highlighting the impact of the inoculation of selected exogenous strains on natural strains. This tool can be successfully exploited to identify S. cerevisiae strains in any kind of complex samples. Nature Publishing Group UK 2017-11-10 /pmc/articles/PMC5681646/ /pubmed/29127392 http://dx.doi.org/10.1038/s41598-017-15729-3 Text en © The Author(s) 2017 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
Stefanini, Irene
Albanese, Davide
Sordo, Maddalena
Legras, Jean-Luc
De Filippo, Carlotta
Cavalieri, Duccio
Donati, Claudio
SaccharomycesIDentifier, SID: strain-level analysis of Saccharomyces cerevisiae populations by using microsatellite meta-patterns
title SaccharomycesIDentifier, SID: strain-level analysis of Saccharomyces cerevisiae populations by using microsatellite meta-patterns
title_full SaccharomycesIDentifier, SID: strain-level analysis of Saccharomyces cerevisiae populations by using microsatellite meta-patterns
title_fullStr SaccharomycesIDentifier, SID: strain-level analysis of Saccharomyces cerevisiae populations by using microsatellite meta-patterns
title_full_unstemmed SaccharomycesIDentifier, SID: strain-level analysis of Saccharomyces cerevisiae populations by using microsatellite meta-patterns
title_short SaccharomycesIDentifier, SID: strain-level analysis of Saccharomyces cerevisiae populations by using microsatellite meta-patterns
title_sort saccharomycesidentifier, sid: strain-level analysis of saccharomyces cerevisiae populations by using microsatellite meta-patterns
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5681646/
https://www.ncbi.nlm.nih.gov/pubmed/29127392
http://dx.doi.org/10.1038/s41598-017-15729-3
work_keys_str_mv AT stefaniniirene saccharomycesidentifiersidstrainlevelanalysisofsaccharomycescerevisiaepopulationsbyusingmicrosatellitemetapatterns
AT albanesedavide saccharomycesidentifiersidstrainlevelanalysisofsaccharomycescerevisiaepopulationsbyusingmicrosatellitemetapatterns
AT sordomaddalena saccharomycesidentifiersidstrainlevelanalysisofsaccharomycescerevisiaepopulationsbyusingmicrosatellitemetapatterns
AT legrasjeanluc saccharomycesidentifiersidstrainlevelanalysisofsaccharomycescerevisiaepopulationsbyusingmicrosatellitemetapatterns
AT defilippocarlotta saccharomycesidentifiersidstrainlevelanalysisofsaccharomycescerevisiaepopulationsbyusingmicrosatellitemetapatterns
AT cavalieriduccio saccharomycesidentifiersidstrainlevelanalysisofsaccharomycescerevisiaepopulationsbyusingmicrosatellitemetapatterns
AT donaticlaudio saccharomycesidentifiersidstrainlevelanalysisofsaccharomycescerevisiaepopulationsbyusingmicrosatellitemetapatterns