Using High Throughput Sequencing to Understand the Biodiversity of Oral Bacterial Communities

High throughput sequencing of 16S rRNA amplicons is a cost-effective method for evaluation of bacterial communities associated with oral diseases. However, before undertaking large-scale studies, it is necessary to understand the technique-associated limitations and intrinsic variability of the oral ecosystem, which may affect our ability to discover disease-associated biomarkers. In this work we evaluated bias in species representation using an in vitro-assembled mock community of oral bacteria. We then sequenced the salivary and buccal mucosa bacterial communities of five healthy subjects to investigate their diversity and differences within and between subjects. Mock community analysis revealed primer and DNA isolation biases and an overestimation of diversity that was reduced after eliminating singleton operational taxonomic units (OTUs). Sequencing of salivary and mucosal communities revealed 455 OTUs (0.3% dissimilarity) across all samples with only 78 of the OTUs present in all subjects. Salivary communities were more diverse, with 120-318 OTUs per subject, while in mucosa each subject had 63-136 OTUs. Total OTUs per subject estimated using CatchAll (an estimator that performed well in evenly distributed salivary and also in uneven mucosal communities), ranged from 145-369 for saliva and 111-377 for mucosa. Inter-subject variability in community structure was lower than site differences between salivary and mucosal communities within subjects. These differences were evident even at very low sequencing depths and were mainly explained by an over-representation of Streptococcus mitis and Gemella haemolysans in mucosa, while several taxa from the genera Neisseria, Porphyromonas, Prevotella, Fusobacterium, among others, showed higher affinity for saliva. In summary, we present an experimental and data analysis framework that will facilitate the design and interpretation of pyrosequencing-based studies of the oral flora. Despite challenges associated with this technique, we demonstrate its power for the evaluation of oral diversity and biogeography patterns.