Metagenomic Features of Oral Microbiome in Tibetan Dental Caries Patients: An Exploratory Study

This study aimed to preliminarily explore the composition and functional potential of oral bacteria in Tibetan patients with dental caries, and to explore potential associations between the observed functional features and the high-altitude living environment and dietary habits.

Saliva samples were collected from nine Tibetan individuals with dental caries. Sequencing was performed on an Illumina high-throughput sequencing platform. The obtained genomes were annotated and analyzed using the non-redundant protein (nr) database, Clusters of Orthologous Genes (COG) database, Kyoto Encyclopedia of Genes and Genomes (KEGG), Carbohydrate-Active Enzymes (CAZy) database, Comprehensive Antibiotic Resistance Database (CARD), and Virulence Factor Database (VFDB).

Across the nine samples, seven dominant phyla and ten dominant genera were identified. At the phylum level, Bacillota (44.06%) and Actinomycetota (26.2%) were predominant. At the genus level, Streptococcus (25.96%) predominated. Functional annotation showed that genes and pathways linked to cell wall/membrane biogenesis (32,623 genes) and carbohydrate metabolism (39,616 genes) accounted for a notable proportion of the total, thereby forming an efficient metabolic cascade encompassing carbohydrate uptake, metabolism, and acid production. Furthermore, multidrug resistance-related annotations represented the largest CARD category (53.05%), whereas immune modulation-related annotations predominated in VFDB annotation (52.48%).

This study provides a preliminary description of the community composition and functional annotation features of the oral microbiome in Tibetan patients with dental caries, showing prominent annotations related to carbohydrate metabolism and biofilm-associated functions, as well as resistance- and virulence-related annotations. These exploratory findings may serve as an initial reference for future studies on dental caries in Tibetan communities using larger cohorts and experimental validation.