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Meta-SourceTracker: application of Bayesian source tracking to shotgun metagenomics.
McGhee, Jordan J; Rawson, Nick; Bailey, Barbara A; Fernandez-Guerra, Antonio; Sisk-Hackworth, Laura; Kelley, Scott T.
Afiliación
  • McGhee JJ; Bioinformatics and Medical Informatics Program, San Diego State University, San Diego, CA, United States of America.
  • Rawson N; Department of Mathematics and Statistics, San Diego State University, San Diego, CA, United States of America.
  • Bailey BA; Department of Mathematics and Statistics, San Diego State University, San Diego, CA, United States of America.
  • Fernandez-Guerra A; Microbial Genomics and Bioinformatics Research Group, Max Planck Institute for Marine Microbiology, Bremen, Germany.
  • Sisk-Hackworth L; Current affiliation: Lundbeck Foundation GeoGenetics Centre, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark.
  • Kelley ST; Department of Biology, San Diego State University, San Diego, CA, United States of America.
PeerJ ; 8: e8783, 2020.
Article en En | MEDLINE | ID: mdl-32231882
ABSTRACT

BACKGROUND:

Microbial source tracking methods are used to determine the origin of contaminating bacteria and other microorganisms, particularly in contaminated water systems. The Bayesian SourceTracker approach uses deep-sequencing marker gene libraries (16S ribosomal RNA) to determine the proportional contributions of bacteria from many potential source environments to a given sink environment simultaneously. Since its development, SourceTracker has been applied to an extensive diversity of studies, from beach contamination to human behavior.

METHODS:

Here, we demonstrate a novel application of SourceTracker to work with metagenomic datasets and tested this approach using sink samples from a study of coastal marine environments. Source environment metagenomes were obtained from metagenomics studies of gut, freshwater, marine, sand and soil environments. As part of this effort, we implemented features for determining the stability of source proportion estimates, including precision visualizations for performance optimization, and performed domain-specific source-tracking analyses (i.e., Bacteria, Archaea, Eukaryota and viruses). We also applied SourceTracker to metagenomic libraries generated from samples collected from the International Space Station (ISS).

RESULTS:

SourceTracker proved highly effective at predicting the composition of known sources using shotgun metagenomic libraries. In addition, we showed that different taxonomic domains sometimes presented highly divergent pictures of environmental source origins for both the coastal marine and ISS samples. These findings indicated that applying SourceTracker to separate domains may provide a deeper understanding of the microbial origins of complex, mixed-source environments, and further suggested that certain domains may be preferable for tracking specific sources of contamination.
Palabras clave

Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: PeerJ Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: PeerJ Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos