Profiling microbial strains in urban environments using metagenomic sequencing data

Abstract Background The microbial communities populating human and natural environments have been extensively characterized with shotgun metagenomics, which provides an in-depth representation of the microbial diversity within a sample. Microbes thriving in urban environments may be crucially import...

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Main Authors: Moreno Zolfo, Francesco Asnicar, Paolo Manghi, Edoardo Pasolli, Adrian Tett, Nicola Segata
Format: Article
Language:English
Published: BMC 2018-05-01
Series:Biology Direct
Subjects:
Online Access:http://link.springer.com/article/10.1186/s13062-018-0211-z
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spelling doaj-66ef45ac31c442209136bea380858f242020-11-24T21:11:26ZengBMCBiology Direct1745-61502018-05-0113111310.1186/s13062-018-0211-zProfiling microbial strains in urban environments using metagenomic sequencing dataMoreno Zolfo0Francesco Asnicar1Paolo Manghi2Edoardo Pasolli3Adrian Tett4Nicola Segata5Centre for Integrative Biology, University of TrentoCentre for Integrative Biology, University of TrentoCentre for Integrative Biology, University of TrentoCentre for Integrative Biology, University of TrentoCentre for Integrative Biology, University of TrentoCentre for Integrative Biology, University of TrentoAbstract Background The microbial communities populating human and natural environments have been extensively characterized with shotgun metagenomics, which provides an in-depth representation of the microbial diversity within a sample. Microbes thriving in urban environments may be crucially important for human health, but have received less attention than those of other environments. Ongoing efforts started to target urban microbiomes at a large scale, but the most recent computational methods to profile these metagenomes have never been applied in this context. It is thus currently unclear whether such methods, that have proven successful at distinguishing even closely related strains in human microbiomes, are also effective in urban settings for tasks such as cultivation-free pathogen detection and microbial surveillance. Here, we aimed at a) testing the currently available metagenomic profiling tools on urban metagenomics; b) characterizing the organisms in urban environment at the resolution of single strain and c) discussing the biological insights that can be inferred from such methods. Results We applied three complementary methods on the 1614 metagenomes of the CAMDA 2017 challenge. With MetaMLST we identified 121 known sequence-types from 15 species of clinical relevance. For instance, we identified several Acinetobacter strains that were close to the nosocomial opportunistic pathogen A. nosocomialis. With StrainPhlAn, a generalized version of the MetaMLST approach, we inferred the phylogenetic structure of Pseudomonas stutzeri strains and suggested that the strain-level heterogeneity in environmental samples is higher than in the human microbiome. Finally, we also probed the functional potential of the different strains with PanPhlAn. We further showed that SNV-based and pangenome-based profiling provide complementary information that can be combined to investigate the evolutionary trajectories of microbes and to identify specific genetic determinants of virulence and antibiotic resistances within closely related strains. Conclusion We show that strain-level methods developed primarily for the analysis of human microbiomes can be effective for city-associated microbiomes. In fact, (opportunistic) pathogens can be tracked and monitored across many hundreds of urban metagenomes. However, while more effort is needed to profile strains of currently uncharacterized species, this work poses the basis for high-resolution analyses of microbiomes sampled in city and mass transportation environments. Reviewers This article was reviewed by Alexandra Bettina Graf, Daniel Huson and Trevor Cickovski.http://link.springer.com/article/10.1186/s13062-018-0211-zMetagenomicsStrain-level microbial genomicsUrban microbiome
collection DOAJ
language English
format Article
sources DOAJ
author Moreno Zolfo
Francesco Asnicar
Paolo Manghi
Edoardo Pasolli
Adrian Tett
Nicola Segata
spellingShingle Moreno Zolfo
Francesco Asnicar
Paolo Manghi
Edoardo Pasolli
Adrian Tett
Nicola Segata
Profiling microbial strains in urban environments using metagenomic sequencing data
Biology Direct
Metagenomics
Strain-level microbial genomics
Urban microbiome
author_facet Moreno Zolfo
Francesco Asnicar
Paolo Manghi
Edoardo Pasolli
Adrian Tett
Nicola Segata
author_sort Moreno Zolfo
title Profiling microbial strains in urban environments using metagenomic sequencing data
title_short Profiling microbial strains in urban environments using metagenomic sequencing data
title_full Profiling microbial strains in urban environments using metagenomic sequencing data
title_fullStr Profiling microbial strains in urban environments using metagenomic sequencing data
title_full_unstemmed Profiling microbial strains in urban environments using metagenomic sequencing data
title_sort profiling microbial strains in urban environments using metagenomic sequencing data
publisher BMC
series Biology Direct
issn 1745-6150
publishDate 2018-05-01
description Abstract Background The microbial communities populating human and natural environments have been extensively characterized with shotgun metagenomics, which provides an in-depth representation of the microbial diversity within a sample. Microbes thriving in urban environments may be crucially important for human health, but have received less attention than those of other environments. Ongoing efforts started to target urban microbiomes at a large scale, but the most recent computational methods to profile these metagenomes have never been applied in this context. It is thus currently unclear whether such methods, that have proven successful at distinguishing even closely related strains in human microbiomes, are also effective in urban settings for tasks such as cultivation-free pathogen detection and microbial surveillance. Here, we aimed at a) testing the currently available metagenomic profiling tools on urban metagenomics; b) characterizing the organisms in urban environment at the resolution of single strain and c) discussing the biological insights that can be inferred from such methods. Results We applied three complementary methods on the 1614 metagenomes of the CAMDA 2017 challenge. With MetaMLST we identified 121 known sequence-types from 15 species of clinical relevance. For instance, we identified several Acinetobacter strains that were close to the nosocomial opportunistic pathogen A. nosocomialis. With StrainPhlAn, a generalized version of the MetaMLST approach, we inferred the phylogenetic structure of Pseudomonas stutzeri strains and suggested that the strain-level heterogeneity in environmental samples is higher than in the human microbiome. Finally, we also probed the functional potential of the different strains with PanPhlAn. We further showed that SNV-based and pangenome-based profiling provide complementary information that can be combined to investigate the evolutionary trajectories of microbes and to identify specific genetic determinants of virulence and antibiotic resistances within closely related strains. Conclusion We show that strain-level methods developed primarily for the analysis of human microbiomes can be effective for city-associated microbiomes. In fact, (opportunistic) pathogens can be tracked and monitored across many hundreds of urban metagenomes. However, while more effort is needed to profile strains of currently uncharacterized species, this work poses the basis for high-resolution analyses of microbiomes sampled in city and mass transportation environments. Reviewers This article was reviewed by Alexandra Bettina Graf, Daniel Huson and Trevor Cickovski.
topic Metagenomics
Strain-level microbial genomics
Urban microbiome
url http://link.springer.com/article/10.1186/s13062-018-0211-z
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