High-throughput identification of viral termini and packaging mechanisms in virome datasets using PhageTermVirome

Abstract Viruses that infect bacteria (phages) are increasingly recognized for their importance in diverse ecosystems but identifying and annotating them in large-scale sequence datasets is still challenging. Although efficient scalable virus identification tools are emerging, defining the exact end...

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Autores principales:	Julian R. Garneau, Véronique Legrand, Martial Marbouty, Maximilian O. Press, Dean R. Vik, Louis-Charles Fortier, Matthew B. Sullivan, David Bikard, Marc Monot
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/7415601f7f3444748212a6542a24a5c2
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spelling	oai:doaj.org-article:7415601f7f3444748212a6542a24a5c22021-12-02T18:02:14ZHigh-throughput identification of viral termini and packaging mechanisms in virome datasets using PhageTermVirome10.1038/s41598-021-97867-32045-2322https://doaj.org/article/7415601f7f3444748212a6542a24a5c22021-09-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-97867-3https://doaj.org/toc/2045-2322Abstract Viruses that infect bacteria (phages) are increasingly recognized for their importance in diverse ecosystems but identifying and annotating them in large-scale sequence datasets is still challenging. Although efficient scalable virus identification tools are emerging, defining the exact ends (termini) of phage genomes is still particularly difficult. The proper identification of termini is crucial, as it helps in characterizing the packaging mechanism of bacteriophages and provides information on various aspects of phage biology. Here, we introduce PhageTermVirome (PTV) as a tool for the easy and rapid high-throughput determination of phage termini and packaging mechanisms using modern large-scale metagenomics datasets. We successfully tested the PTV algorithm on a mock virome dataset and then used it on two real virome datasets to achieve the rapid identification of more than 100 phage termini and packaging mechanisms, with just a few hours of computing time. Because PTV allows the identification of free fully formed viral particles (by recognition of termini present only in encapsidated DNA), it can also complement other virus identification softwares to predict the true viral origin of contigs in viral metagenomics datasets. PTV is a novel and unique tool for high-throughput characterization of phage genomes, including phage termini identification and characterization of genome packaging mechanisms. This software should help researchers better visualize, map and study the virosphere. PTV is freely available for downloading and installation at https://gitlab.pasteur.fr/vlegrand/ptv .Julian R. GarneauVéronique LegrandMartial MarboutyMaximilian O. PressDean R. VikLouis-Charles FortierMatthew B. SullivanDavid BikardMarc MonotNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Julian R. Garneau Véronique Legrand Martial Marbouty Maximilian O. Press Dean R. Vik Louis-Charles Fortier Matthew B. Sullivan David Bikard Marc Monot High-throughput identification of viral termini and packaging mechanisms in virome datasets using PhageTermVirome
description	Abstract Viruses that infect bacteria (phages) are increasingly recognized for their importance in diverse ecosystems but identifying and annotating them in large-scale sequence datasets is still challenging. Although efficient scalable virus identification tools are emerging, defining the exact ends (termini) of phage genomes is still particularly difficult. The proper identification of termini is crucial, as it helps in characterizing the packaging mechanism of bacteriophages and provides information on various aspects of phage biology. Here, we introduce PhageTermVirome (PTV) as a tool for the easy and rapid high-throughput determination of phage termini and packaging mechanisms using modern large-scale metagenomics datasets. We successfully tested the PTV algorithm on a mock virome dataset and then used it on two real virome datasets to achieve the rapid identification of more than 100 phage termini and packaging mechanisms, with just a few hours of computing time. Because PTV allows the identification of free fully formed viral particles (by recognition of termini present only in encapsidated DNA), it can also complement other virus identification softwares to predict the true viral origin of contigs in viral metagenomics datasets. PTV is a novel and unique tool for high-throughput characterization of phage genomes, including phage termini identification and characterization of genome packaging mechanisms. This software should help researchers better visualize, map and study the virosphere. PTV is freely available for downloading and installation at https://gitlab.pasteur.fr/vlegrand/ptv .
format	article
author	Julian R. Garneau Véronique Legrand Martial Marbouty Maximilian O. Press Dean R. Vik Louis-Charles Fortier Matthew B. Sullivan David Bikard Marc Monot
author_facet	Julian R. Garneau Véronique Legrand Martial Marbouty Maximilian O. Press Dean R. Vik Louis-Charles Fortier Matthew B. Sullivan David Bikard Marc Monot
author_sort	Julian R. Garneau
title	High-throughput identification of viral termini and packaging mechanisms in virome datasets using PhageTermVirome
title_short	High-throughput identification of viral termini and packaging mechanisms in virome datasets using PhageTermVirome
title_full	High-throughput identification of viral termini and packaging mechanisms in virome datasets using PhageTermVirome
title_fullStr	High-throughput identification of viral termini and packaging mechanisms in virome datasets using PhageTermVirome
title_full_unstemmed	High-throughput identification of viral termini and packaging mechanisms in virome datasets using PhageTermVirome
title_sort	high-throughput identification of viral termini and packaging mechanisms in virome datasets using phagetermvirome
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/7415601f7f3444748212a6542a24a5c2
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High-throughput identification of viral termini and packaging mechanisms in virome datasets using PhageTermVirome

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