Format

Send to

Choose Destination
PLoS One. 2014 Jul 11;9(7):e95534. doi: 10.1371/journal.pone.0095534. eCollection 2014.

Dynamics of the microbiota in response to host infection.

Author information

1
Department of Pathology, Brigham & Women's Hospital, Boston, Massachusetts, United States of America; Department of Pathology, Harvard Medical School, Boston, Massachusetts, United States of America.
2
Department of Pathology, Brigham & Women's Hospital, Boston, Massachusetts, United States of America; Department of Pathology, Harvard Medical School, Boston, Massachusetts, United States of America; Center for Clinical and Translational Metagenomics, Brigham & Women's Hospital, Harvard Digestive Diseases Center, Harvard Medical School, Boston, Massachusetts, United States of America.
3
Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America.
4
Department of Pathology, Brigham & Women's Hospital, Boston, Massachusetts, United States of America; Center for Clinical and Translational Metagenomics, Brigham & Women's Hospital, Harvard Digestive Diseases Center, Harvard Medical School, Boston, Massachusetts, United States of America.
5
Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, United States of America.

Abstract

Longitudinal studies of the microbiota are important for discovering changes in microbial communities that affect the host. The complexity of these ecosystems requires rigorous integrated experimental and computational methods to identify temporal signatures that promote physiologic or pathophysiologic responses in vivo. Employing a murine model of infectious colitis with the pathogen Citrobacter rodentium, we generated a 2-month time-series of 16S rDNA gene profiles, and quantitatively cultured commensals, from multiple intestinal sites in infected and uninfected mice. We developed a computational framework to discover time-varying signatures for individual taxa, and to automatically group signatures to identify microbial sub-communities within the larger gut ecosystem that demonstrate common behaviors. Application of this model to the 16S rDNA dataset revealed dynamic alterations in the microbiota at multiple levels of resolution, from effects on systems-level metrics to changes across anatomic sites for individual taxa and species. These analyses revealed unique, time-dependent microbial signatures associated with host responses at different stages of colitis. Signatures included a Mucispirillum OTU associated with early disruption of the colonic surface mucus layer, prior to the onset of symptomatic colitis, and members of the Clostridiales and Lactobacillales that increased with successful resolution of inflammation, after clearance of the pathogen. Quantitative culture data validated findings for predominant species, further refining and strengthening model predictions. These findings provide new insights into the complex behaviors found within host ecosystems, and define several time-dependent microbial signatures that may be leveraged in studies of other infectious or inflammatory conditions.

PMID:
25014551
PMCID:
PMC4094490
DOI:
10.1371/journal.pone.0095534
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Public Library of Science Icon for PubMed Central
Loading ...
Support Center