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Autometa: automated extraction of microbial genomes from individual shotgun metagenomes

Shotgun metagenomics is a powerful, high-resolution technique enabling the study of microbial communities in situ. However, species-level resolution is only achieved after a process of ‘binning’ where contigs predicted to originate from the same genome are clustered. Such culture-independent sequenc...

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Autores principales: Miller, Ian J, Rees, Evan R, Ross, Jennifer, Miller, Izaak, Baxa, Jared, Lopera, Juan, Kerby, Robert L, Rey, Federico E, Kwan, Jason C
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6547426/
https://www.ncbi.nlm.nih.gov/pubmed/30838416
http://dx.doi.org/10.1093/nar/gkz148
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author Miller, Ian J
Rees, Evan R
Ross, Jennifer
Miller, Izaak
Baxa, Jared
Lopera, Juan
Kerby, Robert L
Rey, Federico E
Kwan, Jason C
author_facet Miller, Ian J
Rees, Evan R
Ross, Jennifer
Miller, Izaak
Baxa, Jared
Lopera, Juan
Kerby, Robert L
Rey, Federico E
Kwan, Jason C
author_sort Miller, Ian J
collection PubMed
description Shotgun metagenomics is a powerful, high-resolution technique enabling the study of microbial communities in situ. However, species-level resolution is only achieved after a process of ‘binning’ where contigs predicted to originate from the same genome are clustered. Such culture-independent sequencing frequently unearths novel microbes, and so various methods have been devised for reference-free binning. As novel microbiomes of increasing complexity are explored, sometimes associated with non-model hosts, robust automated binning methods are required. Existing methods struggle with eukaryotic contamination and cannot handle highly complex single metagenomes. We therefore developed an automated binning pipeline, termed ‘Autometa’, to address these issues. This command-line application integrates sequence homology, nucleotide composition, coverage and the presence of single-copy marker genes to separate microbial genomes from non-model host genomes and other eukaryotic contaminants, before deconvoluting individual genomes from single metagenomes. The method is able to effectively separate over 1000 genomes from a metagenome, allowing the study of previously intractably complex environments at the level of single species. Autometa is freely available at https://bitbucket.org/jason_c_kwan/autometa and as a docker image at https://hub.docker.com/r/jasonkwan/autometa under the GNU Affero General Public License 3 (AGPL 3).
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spelling pubmed-65474262019-06-13 Autometa: automated extraction of microbial genomes from individual shotgun metagenomes Miller, Ian J Rees, Evan R Ross, Jennifer Miller, Izaak Baxa, Jared Lopera, Juan Kerby, Robert L Rey, Federico E Kwan, Jason C Nucleic Acids Res Methods Online Shotgun metagenomics is a powerful, high-resolution technique enabling the study of microbial communities in situ. However, species-level resolution is only achieved after a process of ‘binning’ where contigs predicted to originate from the same genome are clustered. Such culture-independent sequencing frequently unearths novel microbes, and so various methods have been devised for reference-free binning. As novel microbiomes of increasing complexity are explored, sometimes associated with non-model hosts, robust automated binning methods are required. Existing methods struggle with eukaryotic contamination and cannot handle highly complex single metagenomes. We therefore developed an automated binning pipeline, termed ‘Autometa’, to address these issues. This command-line application integrates sequence homology, nucleotide composition, coverage and the presence of single-copy marker genes to separate microbial genomes from non-model host genomes and other eukaryotic contaminants, before deconvoluting individual genomes from single metagenomes. The method is able to effectively separate over 1000 genomes from a metagenome, allowing the study of previously intractably complex environments at the level of single species. Autometa is freely available at https://bitbucket.org/jason_c_kwan/autometa and as a docker image at https://hub.docker.com/r/jasonkwan/autometa under the GNU Affero General Public License 3 (AGPL 3). Oxford University Press 2019-06-04 2019-03-06 /pmc/articles/PMC6547426/ /pubmed/30838416 http://dx.doi.org/10.1093/nar/gkz148 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research. 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 Methods Online
Miller, Ian J
Rees, Evan R
Ross, Jennifer
Miller, Izaak
Baxa, Jared
Lopera, Juan
Kerby, Robert L
Rey, Federico E
Kwan, Jason C
Autometa: automated extraction of microbial genomes from individual shotgun metagenomes
title Autometa: automated extraction of microbial genomes from individual shotgun metagenomes
title_full Autometa: automated extraction of microbial genomes from individual shotgun metagenomes
title_fullStr Autometa: automated extraction of microbial genomes from individual shotgun metagenomes
title_full_unstemmed Autometa: automated extraction of microbial genomes from individual shotgun metagenomes
title_short Autometa: automated extraction of microbial genomes from individual shotgun metagenomes
title_sort autometa: automated extraction of microbial genomes from individual shotgun metagenomes
topic Methods Online
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6547426/
https://www.ncbi.nlm.nih.gov/pubmed/30838416
http://dx.doi.org/10.1093/nar/gkz148
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