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.
Highlights
Large-scale characterization of the host’s microbiota has been enabled by recent innovations in sequencing technologies [1] and computational methods [2,3,4]
Many of the time-dependent microbial signatures discovered by our analyses are associated with key events in the host response to C. rodentium infection
Full regeneration of the mucus layer occurs some time after the pathogen’s clearance, providing a possible explanation for the observed delay in Mucispirillum’s recolonization of distal colon. This consensus signature groups (CSGs) could provide a marker for health of the surface mucus layer in distal colon, with potential application to other models of inflammatory colitis
Summary
Large-scale characterization of the host’s microbiota has been enabled by recent innovations in sequencing technologies [1] and computational methods [2,3,4] These developments have provided initial insights into the microbiota’s association with normal physiology and disease [5,6,7,8,9,10,11]. Longitudinal studies are valuable for unraveling causal interactions among the host and microbial inhabitants Studies of these ecosystems over time require new analytic approaches to fully explore their extraordinarily complex dynamics and identify signatures relevant to host outcomes [12,13]. The kinetics of these changes are neither known, nor characterized This experimental model provides a valuable system in which to discover the complex behaviors of the microbiota, across gut locations, and at different stages of host disease
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