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Microbial strain-level population structure and genetic diversity from metagenomes

Among the human health conditions linked to microbial communities, phenotypes are often associated with only a subset of strains within causal microbial groups. Although it has been critical for decades in microbial physiology to characterize individual strains, this has been challenging when using...

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Detalles Bibliográficos
Autores principales: Truong, Duy Tin, Tett, Adrian, Pasolli, Edoardo, Huttenhower, Curtis, Segata, Nicola
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5378180/
https://www.ncbi.nlm.nih.gov/pubmed/28167665
http://dx.doi.org/10.1101/gr.216242.116
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author Truong, Duy Tin
Tett, Adrian
Pasolli, Edoardo
Huttenhower, Curtis
Segata, Nicola
author_facet Truong, Duy Tin
Tett, Adrian
Pasolli, Edoardo
Huttenhower, Curtis
Segata, Nicola
author_sort Truong, Duy Tin
collection PubMed
description Among the human health conditions linked to microbial communities, phenotypes are often associated with only a subset of strains within causal microbial groups. Although it has been critical for decades in microbial physiology to characterize individual strains, this has been challenging when using culture-independent high-throughput metagenomics. We introduce StrainPhlAn, a novel metagenomic strain identification approach, and apply it to characterize the genetic structure of thousands of strains from more than 125 species in more than 1500 gut metagenomes drawn from populations spanning North and South American, European, Asian, and African countries. The method relies on per-sample dominant sequence variant reconstruction within species-specific marker genes. It identified primarily subject-specific strain variants (<5% inter-subject strain sharing), and we determined that a single strain typically dominated each species and was retained over time (for >70% of species). Microbial population structure was correlated in several distinct ways with the geographic structure of the host population. In some cases, discrete subspecies (e.g., for Eubacterium rectale and Prevotella copri) or continuous microbial genetic variations (e.g., for Faecalibacterium prausnitzii) were associated with geographically distinct human populations, whereas few strains occurred in multiple unrelated cohorts. We further estimated the genetic variability of gut microbes, with Bacteroides species appearing remarkably consistent (0.45% median number of nucleotide variants between strains), whereas P. copri was among the most plastic gut colonizers. We thus characterize here the population genetics of previously inaccessible intestinal microbes, providing a comprehensive strain-level genetic overview of the gut microbial diversity.
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spelling pubmed-53781802017-04-12 Microbial strain-level population structure and genetic diversity from metagenomes Truong, Duy Tin Tett, Adrian Pasolli, Edoardo Huttenhower, Curtis Segata, Nicola Genome Res Method Among the human health conditions linked to microbial communities, phenotypes are often associated with only a subset of strains within causal microbial groups. Although it has been critical for decades in microbial physiology to characterize individual strains, this has been challenging when using culture-independent high-throughput metagenomics. We introduce StrainPhlAn, a novel metagenomic strain identification approach, and apply it to characterize the genetic structure of thousands of strains from more than 125 species in more than 1500 gut metagenomes drawn from populations spanning North and South American, European, Asian, and African countries. The method relies on per-sample dominant sequence variant reconstruction within species-specific marker genes. It identified primarily subject-specific strain variants (<5% inter-subject strain sharing), and we determined that a single strain typically dominated each species and was retained over time (for >70% of species). Microbial population structure was correlated in several distinct ways with the geographic structure of the host population. In some cases, discrete subspecies (e.g., for Eubacterium rectale and Prevotella copri) or continuous microbial genetic variations (e.g., for Faecalibacterium prausnitzii) were associated with geographically distinct human populations, whereas few strains occurred in multiple unrelated cohorts. We further estimated the genetic variability of gut microbes, with Bacteroides species appearing remarkably consistent (0.45% median number of nucleotide variants between strains), whereas P. copri was among the most plastic gut colonizers. We thus characterize here the population genetics of previously inaccessible intestinal microbes, providing a comprehensive strain-level genetic overview of the gut microbial diversity. Cold Spring Harbor Laboratory Press 2017-04 /pmc/articles/PMC5378180/ /pubmed/28167665 http://dx.doi.org/10.1101/gr.216242.116 Text en © 2017 Truong 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
Truong, Duy Tin
Tett, Adrian
Pasolli, Edoardo
Huttenhower, Curtis
Segata, Nicola
Microbial strain-level population structure and genetic diversity from metagenomes
title Microbial strain-level population structure and genetic diversity from metagenomes
title_full Microbial strain-level population structure and genetic diversity from metagenomes
title_fullStr Microbial strain-level population structure and genetic diversity from metagenomes
title_full_unstemmed Microbial strain-level population structure and genetic diversity from metagenomes
title_short Microbial strain-level population structure and genetic diversity from metagenomes
title_sort microbial strain-level population structure and genetic diversity from metagenomes
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5378180/
https://www.ncbi.nlm.nih.gov/pubmed/28167665
http://dx.doi.org/10.1101/gr.216242.116
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