Abstract
The human mouth is an excellent system to study the dynamics of microbial communities and their interactions with their host. We employed oligotyping to analyze, with single-nucleotide resolution, oral microbial 16S ribosomal RNA (rRNA) gene sequence data from a time course sampled from the tongue of two individuals, and we interpret our results in the context of oligotypes that we previously identified in the oral data from the Human Microbiome Project. Our previous work established that many of these oligotypes had dramatically different distributions between individuals and across oral habitats, suggesting that they represented functionally different organisms. Here we demonstrate the presence of a consistent tongue microbiome but with rapidly fluctuating proportions of the characteristic taxa. In some cases closely related oligotypes representing strains or variants within a single species displayed fluctuating relative abundances over time, while in other cases an initially dominant oligotype was replaced by another oligotype of the same species. We use this high temporal and taxonomic level of resolution to detect correlated changes in oligotype abundance that could indicate which taxa likely interact synergistically or occupy similar habitats, and which likely interact antagonistically or prefer distinct habitats. For example, we found a strong correlation in abundance over time between two oligotypes from different families of Gamma Proteobacteria, suggesting a close functional or ecological relationship between them. In summary, the tongue is colonized by a microbial community of moderate complexity whose proportional abundance fluctuates widely on time scales of days. The drivers and functional consequences of these community dynamics are not known, but we expect they will prove tractable to future, targeted studies employing taxonomically resolved analysis of high-throughput sequencing data sampled at appropriate temporal intervals and spatial scales.
Highlights
Understanding microbial community dynamics requires knowledge of the time scale over which microbial communities adapt and change
Rapid decreases in the cost of DNA sequencing have made it possible to generate the large amounts of data required for studies of dynamics, but analysis methods limited to the genus or operational taxonomic units (OTUs) level have limited the opportunities for analyzing the dynamics within a single species or between closely related species
This study provides an example of the single-nucleotide taxonomic resolution of oligotyping which, in turn, enables analysis of microbial dynamics and associations that would otherwise not be possible if taxa were lumped into heterogeneous groups
Summary
Understanding microbial community dynamics requires knowledge of the time scale over which microbial communities adapt and change. Indications that changes of interest may occur over shorter time scales led to studies that sampled at daily intervals in a marine system and in the human microbiome (Dethlefsen and Relman, 2011; Caporaso et al, 2011; Koenig et al, 2011; Gajer et al, 2012; Martínez et al, 2013; Needham et al, 2013; David et al, 2014) These studies established that microbial communities are resilient, with episodic shifts in community composition followed by reversion to previous states. Our understanding of microbial community dynamics at the species level has heretofore been hindered by the use of analysis methods that cluster sequences into operational taxonomic units (OTUs) based on arbitrary similarity thresholds. It exploits all available informative data, reduces the effect of noise, and generates homogeneous groupings in the sense that www.frontiersin.org
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