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Strain profiling and epidemiology of bacterial species from metagenomic sequencing.

ABSTRACT: Microbial communities are often composed by complex mixtures of multiple strains of the same species, characterized by a wide genomic and phenotypic variability. Computational methods able to identify, quantify and classify the different strains present in a sample are essential to fully exploit the potential of metagenomic sequencing in microbial ecology, with applications that range from the epidemiology of infectious diseases to the characterization of the dynamics of microbial colonization. Here we present a computational approach that uses the available genomic data to reconstruct complex strain profiles from metagenomic sequencing, quantifying the abundances of the different strains and cataloging them according to the population structure of the species. We validate the method on synthetic data sets and apply it to the characterization of the strain distribution of several important bacterial species in real samples, showing how its application provides novel insights on the structure and complexity of the microbiota.

SUBMITTER: Albanese D

PROVIDER: S-EPMC5741664 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Strain profiling and epidemiology of bacterial species from metagenomic sequencing.

Albanese Davide D Donati Claudio C

Nature communications 20171222 1

Microbial communities are often composed by complex mixtures of multiple strains of the same species, characterized by a wide genomic and phenotypic variability. Computational methods able to identify, quantify and classify the different strains present in a sample are essential to fully exploit the potential of metagenomic sequencing in microbial ecology, with applications that range from the epidemiology of infectious diseases to the characterization of the dynamics of microbial colonization. ...[more]

PMID: 29273717

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Project description:BackgroundThe 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.ResultsWe 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.ConclusionWe 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.ReviewersThis article was reviewed by Alexandra Bettina Graf, Daniel Huson and Trevor Cickovski.

Dataset Information

Strain profiling and epidemiology of bacterial species from metagenomic sequencing.

Publications

Strain profiling and epidemiology of bacterial species from metagenomic sequencing.

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