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Non-invasive real time monitoring of yeast volatilome by PTR-ToF-MS
INTRODUCTION: Producing a wide range of volatile secondary metabolites Saccharomyces cerevisiae influences wine, beer, and bread sensory quality and hence selection of strains based on their volatilome becomes pivotal. A rapid on-line method for volatilome assessing of strains growing on standard so...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5579147/ https://www.ncbi.nlm.nih.gov/pubmed/28932179 http://dx.doi.org/10.1007/s11306-017-1259-y |
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author | Khomenko, Iuliia Stefanini, Irene Cappellin, Luca Cappelletti, Valentina Franceschi, Pietro Cavalieri, Duccio Märk, Tilmann D. Biasioli, Franco |
author_facet | Khomenko, Iuliia Stefanini, Irene Cappellin, Luca Cappelletti, Valentina Franceschi, Pietro Cavalieri, Duccio Märk, Tilmann D. Biasioli, Franco |
author_sort | Khomenko, Iuliia |
collection | PubMed |
description | INTRODUCTION: Producing a wide range of volatile secondary metabolites Saccharomyces cerevisiae influences wine, beer, and bread sensory quality and hence selection of strains based on their volatilome becomes pivotal. A rapid on-line method for volatilome assessing of strains growing on standard solid media is still missing. OBJECTIVES: Methodologically, the aim of this study was to demonstrate the automatic, real-time, direct, and non-invasive monitoring of yeast volatilome in order to rapidly produce a robust large data set encompassing measurements relative to many strains, replicates and time points. The fundamental scope was to differentiate volatilomes of genetically similar strains of oenological relevance during the whole growing process. METHOD: Six different S. cerevisiae strains (four meiotic segregants of a natural strain and two laboratory strains) inoculated onto a solid medium have been monitored on-line by Proton Transfer Reaction—Time-of-Flight—Mass Spectrometry for 11 days every 4 h (3540 time points). FastGC PTR-ToF-MS was performed during the stationary phase on the 5th day. RESULTS: More than 300 peaks have been extracted from the average spectra associated to each time point, 70 have been tentatively identified. Univariate and multivariate analyses have been performed on the data matrix (3640 measurements × 70 peaks) highlighting the volatilome evolution and strain-specific features. Laboratory strains with opposite mating type, and meiotic segregants of the same natural strain showed significantly different profiles. CONCLUSIONS: The described set-up allows the on-line high-throughput screening of yeast volatilome of S. cerevisiae strains and the identification of strain specific features and new metabolic pathways, discriminating also genetically similar strains, thus revealing a novel method for strain phenotyping, identification, and quality control. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-017-1259-y) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5579147 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-55791472017-09-18 Non-invasive real time monitoring of yeast volatilome by PTR-ToF-MS Khomenko, Iuliia Stefanini, Irene Cappellin, Luca Cappelletti, Valentina Franceschi, Pietro Cavalieri, Duccio Märk, Tilmann D. Biasioli, Franco Metabolomics Original Article INTRODUCTION: Producing a wide range of volatile secondary metabolites Saccharomyces cerevisiae influences wine, beer, and bread sensory quality and hence selection of strains based on their volatilome becomes pivotal. A rapid on-line method for volatilome assessing of strains growing on standard solid media is still missing. OBJECTIVES: Methodologically, the aim of this study was to demonstrate the automatic, real-time, direct, and non-invasive monitoring of yeast volatilome in order to rapidly produce a robust large data set encompassing measurements relative to many strains, replicates and time points. The fundamental scope was to differentiate volatilomes of genetically similar strains of oenological relevance during the whole growing process. METHOD: Six different S. cerevisiae strains (four meiotic segregants of a natural strain and two laboratory strains) inoculated onto a solid medium have been monitored on-line by Proton Transfer Reaction—Time-of-Flight—Mass Spectrometry for 11 days every 4 h (3540 time points). FastGC PTR-ToF-MS was performed during the stationary phase on the 5th day. RESULTS: More than 300 peaks have been extracted from the average spectra associated to each time point, 70 have been tentatively identified. Univariate and multivariate analyses have been performed on the data matrix (3640 measurements × 70 peaks) highlighting the volatilome evolution and strain-specific features. Laboratory strains with opposite mating type, and meiotic segregants of the same natural strain showed significantly different profiles. CONCLUSIONS: The described set-up allows the on-line high-throughput screening of yeast volatilome of S. cerevisiae strains and the identification of strain specific features and new metabolic pathways, discriminating also genetically similar strains, thus revealing a novel method for strain phenotyping, identification, and quality control. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-017-1259-y) contains supplementary material, which is available to authorized users. Springer US 2017-08-31 2017 /pmc/articles/PMC5579147/ /pubmed/28932179 http://dx.doi.org/10.1007/s11306-017-1259-y Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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. |
spellingShingle | Original Article Khomenko, Iuliia Stefanini, Irene Cappellin, Luca Cappelletti, Valentina Franceschi, Pietro Cavalieri, Duccio Märk, Tilmann D. Biasioli, Franco Non-invasive real time monitoring of yeast volatilome by PTR-ToF-MS |
title | Non-invasive real time monitoring of yeast volatilome by PTR-ToF-MS |
title_full | Non-invasive real time monitoring of yeast volatilome by PTR-ToF-MS |
title_fullStr | Non-invasive real time monitoring of yeast volatilome by PTR-ToF-MS |
title_full_unstemmed | Non-invasive real time monitoring of yeast volatilome by PTR-ToF-MS |
title_short | Non-invasive real time monitoring of yeast volatilome by PTR-ToF-MS |
title_sort | non-invasive real time monitoring of yeast volatilome by ptr-tof-ms |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5579147/ https://www.ncbi.nlm.nih.gov/pubmed/28932179 http://dx.doi.org/10.1007/s11306-017-1259-y |
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