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An integrated metagenomics pipeline for strain profiling reveals novel patterns of bacterial transmission and biogeography

We present the Metagenomic Intra-species Diversity Analysis System (MIDAS), which is an integrated computational pipeline for quantifying bacterial species abundance and strain-level genomic variation, including gene content and single-nucleotide polymorphisms (SNPs), from shotgun metagenomes. Our m...

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Autores principales: Nayfach, Stephen, Rodriguez-Mueller, Beltran, Garud, Nandita, Pollard, Katherine S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5088602/
https://www.ncbi.nlm.nih.gov/pubmed/27803195
http://dx.doi.org/10.1101/gr.201863.115
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author Nayfach, Stephen
Rodriguez-Mueller, Beltran
Garud, Nandita
Pollard, Katherine S.
author_facet Nayfach, Stephen
Rodriguez-Mueller, Beltran
Garud, Nandita
Pollard, Katherine S.
author_sort Nayfach, Stephen
collection PubMed
description We present the Metagenomic Intra-species Diversity Analysis System (MIDAS), which is an integrated computational pipeline for quantifying bacterial species abundance and strain-level genomic variation, including gene content and single-nucleotide polymorphisms (SNPs), from shotgun metagenomes. Our method leverages a database of more than 30,000 bacterial reference genomes that we clustered into species groups. These cover the majority of abundant species in the human microbiome but only a small proportion of microbes in other environments, including soil and seawater. We applied MIDAS to stool metagenomes from 98 Swedish mothers and their infants over one year and used rare SNPs to track strains between hosts. Using this approach, we found that although species compositions of mothers and infants converged over time, strain-level similarity diverged. Specifically, early colonizing bacteria were often transmitted from an infant’s mother, while late colonizing bacteria were often transmitted from other sources in the environment and were enriched for spore-formation genes. We also applied MIDAS to 198 globally distributed marine metagenomes and used gene content to show that many prevalent bacterial species have population structure that correlates with geographic location. Strain-level genetic variants present in metagenomes clearly reveal extensive structure and dynamics that are obscured when data are analyzed at a coarser taxonomic resolution.
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spelling pubmed-50886022016-11-15 An integrated metagenomics pipeline for strain profiling reveals novel patterns of bacterial transmission and biogeography Nayfach, Stephen Rodriguez-Mueller, Beltran Garud, Nandita Pollard, Katherine S. Genome Res Method We present the Metagenomic Intra-species Diversity Analysis System (MIDAS), which is an integrated computational pipeline for quantifying bacterial species abundance and strain-level genomic variation, including gene content and single-nucleotide polymorphisms (SNPs), from shotgun metagenomes. Our method leverages a database of more than 30,000 bacterial reference genomes that we clustered into species groups. These cover the majority of abundant species in the human microbiome but only a small proportion of microbes in other environments, including soil and seawater. We applied MIDAS to stool metagenomes from 98 Swedish mothers and their infants over one year and used rare SNPs to track strains between hosts. Using this approach, we found that although species compositions of mothers and infants converged over time, strain-level similarity diverged. Specifically, early colonizing bacteria were often transmitted from an infant’s mother, while late colonizing bacteria were often transmitted from other sources in the environment and were enriched for spore-formation genes. We also applied MIDAS to 198 globally distributed marine metagenomes and used gene content to show that many prevalent bacterial species have population structure that correlates with geographic location. Strain-level genetic variants present in metagenomes clearly reveal extensive structure and dynamics that are obscured when data are analyzed at a coarser taxonomic resolution. Cold Spring Harbor Laboratory Press 2016-11 /pmc/articles/PMC5088602/ /pubmed/27803195 http://dx.doi.org/10.1101/gr.201863.115 Text en © 2016 Nayfach et al.; Published by Cold Spring Harbor Laboratory Press http://creativecommons.org/licenses/by/4.0/ This article, published in Genome Research, is available under a Creative Commons License (Attribution 4.0 International), as described at http://creativecommons.org/licenses/by/4.0/.
spellingShingle Method
Nayfach, Stephen
Rodriguez-Mueller, Beltran
Garud, Nandita
Pollard, Katherine S.
An integrated metagenomics pipeline for strain profiling reveals novel patterns of bacterial transmission and biogeography
title An integrated metagenomics pipeline for strain profiling reveals novel patterns of bacterial transmission and biogeography
title_full An integrated metagenomics pipeline for strain profiling reveals novel patterns of bacterial transmission and biogeography
title_fullStr An integrated metagenomics pipeline for strain profiling reveals novel patterns of bacterial transmission and biogeography
title_full_unstemmed An integrated metagenomics pipeline for strain profiling reveals novel patterns of bacterial transmission and biogeography
title_short An integrated metagenomics pipeline for strain profiling reveals novel patterns of bacterial transmission and biogeography
title_sort integrated metagenomics pipeline for strain profiling reveals novel patterns of bacterial transmission and biogeography
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5088602/
https://www.ncbi.nlm.nih.gov/pubmed/27803195
http://dx.doi.org/10.1101/gr.201863.115
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