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Large-scale network analysis captures biological features of bacterial plasmids

Many bacteria can exchange genetic material through horizontal gene transfer (HGT) mediated by plasmids and plasmid-borne transposable elements. Here, we study the population structure and dynamics of over 10,000 bacterial plasmids, by quantifying their genetic similarities and reconstructing a netw...

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Autores principales: Acman, Mislav, van Dorp, Lucy, Santini, Joanne M., Balloux, Francois
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7229196/
https://www.ncbi.nlm.nih.gov/pubmed/32415210
http://dx.doi.org/10.1038/s41467-020-16282-w
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author Acman, Mislav
van Dorp, Lucy
Santini, Joanne M.
Balloux, Francois
author_facet Acman, Mislav
van Dorp, Lucy
Santini, Joanne M.
Balloux, Francois
author_sort Acman, Mislav
collection PubMed
description Many bacteria can exchange genetic material through horizontal gene transfer (HGT) mediated by plasmids and plasmid-borne transposable elements. Here, we study the population structure and dynamics of over 10,000 bacterial plasmids, by quantifying their genetic similarities and reconstructing a network based on their shared k-mer content. We use a community detection algorithm to assign plasmids into cliques, which correlate with plasmid gene content, bacterial host range, GC content, and existing classifications based on replicon and mobility (MOB) types. Further analysis of plasmid population structure allows us to uncover candidates for yet undescribed replicon genes, and to identify transposable elements as the main drivers of HGT at broad phylogenetic scales. Our work illustrates the potential of network-based analyses of the bacterial ‘mobilome’ and opens up the prospect of a natural, exhaustive classification framework for bacterial plasmids.
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spelling pubmed-72291962020-06-05 Large-scale network analysis captures biological features of bacterial plasmids Acman, Mislav van Dorp, Lucy Santini, Joanne M. Balloux, Francois Nat Commun Article Many bacteria can exchange genetic material through horizontal gene transfer (HGT) mediated by plasmids and plasmid-borne transposable elements. Here, we study the population structure and dynamics of over 10,000 bacterial plasmids, by quantifying their genetic similarities and reconstructing a network based on their shared k-mer content. We use a community detection algorithm to assign plasmids into cliques, which correlate with plasmid gene content, bacterial host range, GC content, and existing classifications based on replicon and mobility (MOB) types. Further analysis of plasmid population structure allows us to uncover candidates for yet undescribed replicon genes, and to identify transposable elements as the main drivers of HGT at broad phylogenetic scales. Our work illustrates the potential of network-based analyses of the bacterial ‘mobilome’ and opens up the prospect of a natural, exhaustive classification framework for bacterial plasmids. Nature Publishing Group UK 2020-05-15 /pmc/articles/PMC7229196/ /pubmed/32415210 http://dx.doi.org/10.1038/s41467-020-16282-w 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
Acman, Mislav
van Dorp, Lucy
Santini, Joanne M.
Balloux, Francois
Large-scale network analysis captures biological features of bacterial plasmids
title Large-scale network analysis captures biological features of bacterial plasmids
title_full Large-scale network analysis captures biological features of bacterial plasmids
title_fullStr Large-scale network analysis captures biological features of bacterial plasmids
title_full_unstemmed Large-scale network analysis captures biological features of bacterial plasmids
title_short Large-scale network analysis captures biological features of bacterial plasmids
title_sort large-scale network analysis captures biological features of bacterial plasmids
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7229196/
https://www.ncbi.nlm.nih.gov/pubmed/32415210
http://dx.doi.org/10.1038/s41467-020-16282-w
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