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Hybridization capture reveals microbial diversity missed using current profiling methods

BACKGROUND: Microorganisms comprise the majority of living organisms on our planet. For many years, exploration of the composition of microbial communities has been performed through the PCR-based study of the small subunit rRNA gene due to its high conservation across the domains of life. The appli...

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Autores principales: Gasc, Cyrielle, Peyret, Pierre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5870382/
https://www.ncbi.nlm.nih.gov/pubmed/29587880
http://dx.doi.org/10.1186/s40168-018-0442-3
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author Gasc, Cyrielle
Peyret, Pierre
author_facet Gasc, Cyrielle
Peyret, Pierre
author_sort Gasc, Cyrielle
collection PubMed
description BACKGROUND: Microorganisms comprise the majority of living organisms on our planet. For many years, exploration of the composition of microbial communities has been performed through the PCR-based study of the small subunit rRNA gene due to its high conservation across the domains of life. The application of this method has resulted in the discovery of many unexpected evolutionary lineages. However, amplicon sequencing is subject to numerous biases, with some taxa being missed, and is limited by the read length of second-generation sequencing platforms, which drastically reduces the phylogenetic resolution. RESULTS: Here, we describe a hybridization capture strategy that allows the enrichment of 16S rRNA genes from metagenomic samples and enables an exhaustive identification and a complete reconstruction of the biomarker. Applying this approach to a microbial mock community and a soil sample, we demonstrated that hybridization capture is able to reveal greater microbial diversity than 16S rDNA amplicon sequencing and shotgun sequencing. The reconstruction of full-length 16S rRNA genes facilitated the improvement of phylogenetic resolution and the discovery of novel prokaryotic taxa. CONCLUSIONS: Our results demonstrate that hybridization capture can lead to major breakthroughs in our understanding of microbial diversity, overcoming the limitations of conventional 16S rRNA gene studies. If applied to a broad range of environmental samples, this innovative approach could reveal the undescribed diversity of the still underexplored microbial communities and could provide a better understanding of ecosystem function. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40168-018-0442-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-58703822018-03-29 Hybridization capture reveals microbial diversity missed using current profiling methods Gasc, Cyrielle Peyret, Pierre Microbiome Methodology BACKGROUND: Microorganisms comprise the majority of living organisms on our planet. For many years, exploration of the composition of microbial communities has been performed through the PCR-based study of the small subunit rRNA gene due to its high conservation across the domains of life. The application of this method has resulted in the discovery of many unexpected evolutionary lineages. However, amplicon sequencing is subject to numerous biases, with some taxa being missed, and is limited by the read length of second-generation sequencing platforms, which drastically reduces the phylogenetic resolution. RESULTS: Here, we describe a hybridization capture strategy that allows the enrichment of 16S rRNA genes from metagenomic samples and enables an exhaustive identification and a complete reconstruction of the biomarker. Applying this approach to a microbial mock community and a soil sample, we demonstrated that hybridization capture is able to reveal greater microbial diversity than 16S rDNA amplicon sequencing and shotgun sequencing. The reconstruction of full-length 16S rRNA genes facilitated the improvement of phylogenetic resolution and the discovery of novel prokaryotic taxa. CONCLUSIONS: Our results demonstrate that hybridization capture can lead to major breakthroughs in our understanding of microbial diversity, overcoming the limitations of conventional 16S rRNA gene studies. If applied to a broad range of environmental samples, this innovative approach could reveal the undescribed diversity of the still underexplored microbial communities and could provide a better understanding of ecosystem function. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40168-018-0442-3) contains supplementary material, which is available to authorized users. BioMed Central 2018-03-27 /pmc/articles/PMC5870382/ /pubmed/29587880 http://dx.doi.org/10.1186/s40168-018-0442-3 Text en © The Author(s). 2018 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. 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 Methodology
Gasc, Cyrielle
Peyret, Pierre
Hybridization capture reveals microbial diversity missed using current profiling methods
title Hybridization capture reveals microbial diversity missed using current profiling methods
title_full Hybridization capture reveals microbial diversity missed using current profiling methods
title_fullStr Hybridization capture reveals microbial diversity missed using current profiling methods
title_full_unstemmed Hybridization capture reveals microbial diversity missed using current profiling methods
title_short Hybridization capture reveals microbial diversity missed using current profiling methods
title_sort hybridization capture reveals microbial diversity missed using current profiling methods
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5870382/
https://www.ncbi.nlm.nih.gov/pubmed/29587880
http://dx.doi.org/10.1186/s40168-018-0442-3
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