Background: The salivary microbiota is a potential diagnostic indicator of several diseases. Culture-independent techniques are required to study the salivary microbial community since many of its members have not been cultivated.
Methods: We explored the bacterial community composition in the saliva sample using metagenomic whole genome shotgun (WGS) sequencing, the extraction of 16S rRNA gene fragments from metagenomic sequences (16S-WGS) and high-throughput sequencing of PCR-amplified bacterial 16S rDNA gene (16S-HTS) regions V1 and V3.
Results: The hierarchical clustering of data based on the relative abundance of bacterial genera revealed that distances between 16S-HTS datasets for V1 and V3 regions were greater than those obtained for the same V region with different numbers of PCR cycles. Datasets generated by 16S-HTS and 16S-WGS were even more distant. Finally, comparison of WGS and 16S-based datasets revealed the highest dissimilarity.The analysis of the 16S-HTS, WGS and 16S-WGS datasets revealed 206, 56 and 39 bacterial genera, respectively, 124 of which have not been previously identified in salivary microbiomes. A large fraction of DNA extracted from saliva corresponded to human DNA. Based on sequence similarity search against completely sequenced genomes, bacterial and viral sequences represented 0.73% and 0.0036% of the salivary metagenome, respectively. Several sequence reads were identified as parts of the human herpesvirus 7.
Conclusions: Analysis of the salivary metagenome may have implications in diagnostics e.g. in detection of microorganisms and viruses without designing specific tests for each pathogen.