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A combined meta-barcoding and shotgun metagenomic analysis of spontaneous wine fermentation

Wine is a complex beverage, comprising hundreds of metabolites produced through the action of yeasts and bacteria in fermenting grape must. Commercially, there is now a growing trend away from using wine yeast (Saccharomyces) starter cultures, toward the historic practice of uninoculated or “wild” f...

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Autores principales: Sternes, Peter R., Lee, Danna, Kutyna, Dariusz R., Borneman, Anthony R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5570097/
https://www.ncbi.nlm.nih.gov/pubmed/28595314
http://dx.doi.org/10.1093/gigascience/gix040
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author Sternes, Peter R.
Lee, Danna
Kutyna, Dariusz R.
Borneman, Anthony R.
author_facet Sternes, Peter R.
Lee, Danna
Kutyna, Dariusz R.
Borneman, Anthony R.
author_sort Sternes, Peter R.
collection PubMed
description Wine is a complex beverage, comprising hundreds of metabolites produced through the action of yeasts and bacteria in fermenting grape must. Commercially, there is now a growing trend away from using wine yeast (Saccharomyces) starter cultures, toward the historic practice of uninoculated or “wild” fermentation, where the yeasts and bacteria associated with the grapes and/or winery perform the fermentation. It is the varied metabolic contributions of these numerous non-Saccharomyces species that are thought to impart complexity and desirable taste and aroma attributes to wild ferments in comparison to their inoculated counterparts. To map the microflora of spontaneous fermentation, metagenomic techniques were employed to characterize and monitor the progression of fungal species in 5 different wild fermentations. Both amplicon-based ribosomal DNA internal transcribed spacer (ITS) phylotyping and shotgun metagenomics were used to assess community structure across different stages of fermentation. While providing a sensitive and highly accurate means of characterizing the wine microbiome, the shotgun metagenomic data also uncovered a significant overabundance bias in the ITS phylotyping abundance estimations for the common non-Saccharomyces wine yeast genus Metschnikowia. By identifying biases such as that observed for Metschnikowia, abundance measurements from future ITS phylotyping datasets can be corrected to provide more accurate species representation. Ultimately, as more shotgun metagenomic and single-strain de novo assemblies for key wine species become available, the accuracy of both ITS-amplicon and shotgun studies will greatly increase, providing a powerful methodology for deciphering the influence of the microbial community on the wine flavor and aroma.
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spelling pubmed-55700972017-08-29 A combined meta-barcoding and shotgun metagenomic analysis of spontaneous wine fermentation Sternes, Peter R. Lee, Danna Kutyna, Dariusz R. Borneman, Anthony R. Gigascience Research Wine is a complex beverage, comprising hundreds of metabolites produced through the action of yeasts and bacteria in fermenting grape must. Commercially, there is now a growing trend away from using wine yeast (Saccharomyces) starter cultures, toward the historic practice of uninoculated or “wild” fermentation, where the yeasts and bacteria associated with the grapes and/or winery perform the fermentation. It is the varied metabolic contributions of these numerous non-Saccharomyces species that are thought to impart complexity and desirable taste and aroma attributes to wild ferments in comparison to their inoculated counterparts. To map the microflora of spontaneous fermentation, metagenomic techniques were employed to characterize and monitor the progression of fungal species in 5 different wild fermentations. Both amplicon-based ribosomal DNA internal transcribed spacer (ITS) phylotyping and shotgun metagenomics were used to assess community structure across different stages of fermentation. While providing a sensitive and highly accurate means of characterizing the wine microbiome, the shotgun metagenomic data also uncovered a significant overabundance bias in the ITS phylotyping abundance estimations for the common non-Saccharomyces wine yeast genus Metschnikowia. By identifying biases such as that observed for Metschnikowia, abundance measurements from future ITS phylotyping datasets can be corrected to provide more accurate species representation. Ultimately, as more shotgun metagenomic and single-strain de novo assemblies for key wine species become available, the accuracy of both ITS-amplicon and shotgun studies will greatly increase, providing a powerful methodology for deciphering the influence of the microbial community on the wine flavor and aroma. Oxford University Press 2017-06-08 /pmc/articles/PMC5570097/ /pubmed/28595314 http://dx.doi.org/10.1093/gigascience/gix040 Text en © The Authors 2017. Published by Oxford University Press. 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Sternes, Peter R.
Lee, Danna
Kutyna, Dariusz R.
Borneman, Anthony R.
A combined meta-barcoding and shotgun metagenomic analysis of spontaneous wine fermentation
title A combined meta-barcoding and shotgun metagenomic analysis of spontaneous wine fermentation
title_full A combined meta-barcoding and shotgun metagenomic analysis of spontaneous wine fermentation
title_fullStr A combined meta-barcoding and shotgun metagenomic analysis of spontaneous wine fermentation
title_full_unstemmed A combined meta-barcoding and shotgun metagenomic analysis of spontaneous wine fermentation
title_short A combined meta-barcoding and shotgun metagenomic analysis of spontaneous wine fermentation
title_sort combined meta-barcoding and shotgun metagenomic analysis of spontaneous wine fermentation
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5570097/
https://www.ncbi.nlm.nih.gov/pubmed/28595314
http://dx.doi.org/10.1093/gigascience/gix040
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