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Longitudinal Metagenomic Analysis of Hospital Air Identifies Clinically Relevant Microbes

We describe the sampling of sixty-three uncultured hospital air samples collected over a six-month period and analysis using shotgun metagenomic sequencing. Our primary goals were to determine the longitudinal metagenomic variability of this environment, identify and characterize genomes of potentia...

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Autores principales: King, Paula, Pham, Long K., Waltz, Shannon, Sphar, Dan, Yamamoto, Robert T., Conrad, Douglas, Taplitz, Randy, Torriani, Francesca, Forsyth, R. Allyn
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4970769/
https://www.ncbi.nlm.nih.gov/pubmed/27482891
http://dx.doi.org/10.1371/journal.pone.0160124
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author King, Paula
Pham, Long K.
Waltz, Shannon
Sphar, Dan
Yamamoto, Robert T.
Conrad, Douglas
Taplitz, Randy
Torriani, Francesca
Forsyth, R. Allyn
author_facet King, Paula
Pham, Long K.
Waltz, Shannon
Sphar, Dan
Yamamoto, Robert T.
Conrad, Douglas
Taplitz, Randy
Torriani, Francesca
Forsyth, R. Allyn
author_sort King, Paula
collection PubMed
description We describe the sampling of sixty-three uncultured hospital air samples collected over a six-month period and analysis using shotgun metagenomic sequencing. Our primary goals were to determine the longitudinal metagenomic variability of this environment, identify and characterize genomes of potential pathogens and determine whether they are atypical to the hospital airborne metagenome. Air samples were collected from eight locations which included patient wards, the main lobby and outside. The resulting DNA libraries produced 972 million sequences representing 51 gigabases. Hierarchical clustering of samples by the most abundant 50 microbial orders generated three major nodes which primarily clustered by type of location. Because the indoor locations were longitudinally consistent, episodic relative increases in microbial genomic signatures related to the opportunistic pathogens Aspergillus, Penicillium and Stenotrophomonas were identified as outliers at specific locations. Further analysis of microbial reads specific for Stenotrophomonas maltophilia indicated homology to a sequenced multi-drug resistant clinical strain and we observed broad sequence coverage of resistance genes. We demonstrate that a shotgun metagenomic sequencing approach can be used to characterize the resistance determinants of pathogen genomes that are uncharacteristic for an otherwise consistent hospital air microbial metagenomic profile.
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spelling pubmed-49707692016-08-18 Longitudinal Metagenomic Analysis of Hospital Air Identifies Clinically Relevant Microbes King, Paula Pham, Long K. Waltz, Shannon Sphar, Dan Yamamoto, Robert T. Conrad, Douglas Taplitz, Randy Torriani, Francesca Forsyth, R. Allyn PLoS One Research Article We describe the sampling of sixty-three uncultured hospital air samples collected over a six-month period and analysis using shotgun metagenomic sequencing. Our primary goals were to determine the longitudinal metagenomic variability of this environment, identify and characterize genomes of potential pathogens and determine whether they are atypical to the hospital airborne metagenome. Air samples were collected from eight locations which included patient wards, the main lobby and outside. The resulting DNA libraries produced 972 million sequences representing 51 gigabases. Hierarchical clustering of samples by the most abundant 50 microbial orders generated three major nodes which primarily clustered by type of location. Because the indoor locations were longitudinally consistent, episodic relative increases in microbial genomic signatures related to the opportunistic pathogens Aspergillus, Penicillium and Stenotrophomonas were identified as outliers at specific locations. Further analysis of microbial reads specific for Stenotrophomonas maltophilia indicated homology to a sequenced multi-drug resistant clinical strain and we observed broad sequence coverage of resistance genes. We demonstrate that a shotgun metagenomic sequencing approach can be used to characterize the resistance determinants of pathogen genomes that are uncharacteristic for an otherwise consistent hospital air microbial metagenomic profile. Public Library of Science 2016-08-02 /pmc/articles/PMC4970769/ /pubmed/27482891 http://dx.doi.org/10.1371/journal.pone.0160124 Text en © 2016 King et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
King, Paula
Pham, Long K.
Waltz, Shannon
Sphar, Dan
Yamamoto, Robert T.
Conrad, Douglas
Taplitz, Randy
Torriani, Francesca
Forsyth, R. Allyn
Longitudinal Metagenomic Analysis of Hospital Air Identifies Clinically Relevant Microbes
title Longitudinal Metagenomic Analysis of Hospital Air Identifies Clinically Relevant Microbes
title_full Longitudinal Metagenomic Analysis of Hospital Air Identifies Clinically Relevant Microbes
title_fullStr Longitudinal Metagenomic Analysis of Hospital Air Identifies Clinically Relevant Microbes
title_full_unstemmed Longitudinal Metagenomic Analysis of Hospital Air Identifies Clinically Relevant Microbes
title_short Longitudinal Metagenomic Analysis of Hospital Air Identifies Clinically Relevant Microbes
title_sort longitudinal metagenomic analysis of hospital air identifies clinically relevant microbes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4970769/
https://www.ncbi.nlm.nih.gov/pubmed/27482891
http://dx.doi.org/10.1371/journal.pone.0160124
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