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Into the Dark: Exploring the Deep Ocean with Single-Virus Genomics

Single-virus genomics (SVGs) has been successfully applied to ocean surface samples allowing the discovery of widespread dominant viruses overlooked for years by metagenomics, such as the uncultured virus vSAG 37-F6 infecting the ubiquitous Pelagibacter spp. In SVGs, one uncultured virus at a time i...

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Autores principales: Martinez-Hernandez, Francisco, Fornas, Oscar, Martinez-Garcia, Manuel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9322844/
https://www.ncbi.nlm.nih.gov/pubmed/35891567
http://dx.doi.org/10.3390/v14071589
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author Martinez-Hernandez, Francisco
Fornas, Oscar
Martinez-Garcia, Manuel
author_facet Martinez-Hernandez, Francisco
Fornas, Oscar
Martinez-Garcia, Manuel
author_sort Martinez-Hernandez, Francisco
collection PubMed
description Single-virus genomics (SVGs) has been successfully applied to ocean surface samples allowing the discovery of widespread dominant viruses overlooked for years by metagenomics, such as the uncultured virus vSAG 37-F6 infecting the ubiquitous Pelagibacter spp. In SVGs, one uncultured virus at a time is sorted from the environmental sample, whole-genome amplified, and sequenced. Here, we have applied SVGs to deep-ocean samples (200–4000 m depth) from global Malaspina and MEDIMAX expeditions, demonstrating the feasibility of this method in deep-ocean samples. A total of 1328 virus-like particles were sorted from the North Atlantic Ocean, the deep Mediterranean Sea, and the Pacific Ocean oxygen minimum zone (OMZ). For this proof of concept, sixty single viruses were selected at random for sequencing. Genome annotation identified 27 of these genomes as bona fide viruses, and detected three auxiliary metabolic genes involved in nucleotide biosynthesis and sugar metabolism. Massive protein profile analysis confirmed that these viruses represented novel viral groups not present in databases. Although they were not previously assembled by viromics, global fragment recruitment analysis showed a conserved profile of relative abundance of these viruses in all analyzed samples spanning different oceans. Altogether, these results reveal the feasibility in using SVGs in this vast environment to unveil the genomes of relevant viruses.
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spelling pubmed-93228442022-07-27 Into the Dark: Exploring the Deep Ocean with Single-Virus Genomics Martinez-Hernandez, Francisco Fornas, Oscar Martinez-Garcia, Manuel Viruses Article Single-virus genomics (SVGs) has been successfully applied to ocean surface samples allowing the discovery of widespread dominant viruses overlooked for years by metagenomics, such as the uncultured virus vSAG 37-F6 infecting the ubiquitous Pelagibacter spp. In SVGs, one uncultured virus at a time is sorted from the environmental sample, whole-genome amplified, and sequenced. Here, we have applied SVGs to deep-ocean samples (200–4000 m depth) from global Malaspina and MEDIMAX expeditions, demonstrating the feasibility of this method in deep-ocean samples. A total of 1328 virus-like particles were sorted from the North Atlantic Ocean, the deep Mediterranean Sea, and the Pacific Ocean oxygen minimum zone (OMZ). For this proof of concept, sixty single viruses were selected at random for sequencing. Genome annotation identified 27 of these genomes as bona fide viruses, and detected three auxiliary metabolic genes involved in nucleotide biosynthesis and sugar metabolism. Massive protein profile analysis confirmed that these viruses represented novel viral groups not present in databases. Although they were not previously assembled by viromics, global fragment recruitment analysis showed a conserved profile of relative abundance of these viruses in all analyzed samples spanning different oceans. Altogether, these results reveal the feasibility in using SVGs in this vast environment to unveil the genomes of relevant viruses. MDPI 2022-07-21 /pmc/articles/PMC9322844/ /pubmed/35891567 http://dx.doi.org/10.3390/v14071589 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Martinez-Hernandez, Francisco
Fornas, Oscar
Martinez-Garcia, Manuel
Into the Dark: Exploring the Deep Ocean with Single-Virus Genomics
title Into the Dark: Exploring the Deep Ocean with Single-Virus Genomics
title_full Into the Dark: Exploring the Deep Ocean with Single-Virus Genomics
title_fullStr Into the Dark: Exploring the Deep Ocean with Single-Virus Genomics
title_full_unstemmed Into the Dark: Exploring the Deep Ocean with Single-Virus Genomics
title_short Into the Dark: Exploring the Deep Ocean with Single-Virus Genomics
title_sort into the dark: exploring the deep ocean with single-virus genomics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9322844/
https://www.ncbi.nlm.nih.gov/pubmed/35891567
http://dx.doi.org/10.3390/v14071589
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