Intraindividual Variation and Personal Specificity of Salivary Microbiota

Abstract
Salivary microbiota is a typical habitat of the human microbiome. This study intended to use salivary microbiota as a model aiming to systematically address the influence of collection methods and temporal dynamics on the human microbiota compared to personal specificity. We carried out a supervised short-term longitudinal study to evaluate the influence of the change of collection methods and sampling time point on salivary microbiota in 10 systemically and orally healthy individuals with certain confounding factors (sex, oral and general health state, medication history, physical exercise, diet, and oral hygiene behavior) controlled before and during the sampling period. The microbial profiles were analyzed by 16S rDNA V3 to V4 hypervariable region amplicon sequencing. The taxonomic structure represented by the dominant species and the weighted UniFrac distance algorithm were used to demonstrate the individual specificity and the intraindividual variation introduced by the change of collection method and sampling time point. The findings suggested individual specificity existed in salivary microbiota from individuals with similar oral and general health status. The intraindividual variation brought by the change of collection method or sampling time point might introduce remarkable perturbation with the personal specificity. Insights into the intraindividual variation and personal specificity of salivary microbiota will enhance our understanding in salivary microbiota-related research. We recommend keeping collection conditions consistent within a study to avoid interference brought by the sampling. The strategy of repeated sampling at multiple time points as representative samples, as well as thorough interpretation of the complex relationships and causality between microbiome composition and disease without the interference of temporal dynamics, is optimal for research exploring the relationship between the salivary microbiome and disease.
Funding Information
  • Ministry of Science and Technology of the People’s Republic of China (2018FY101005)
  • National Natural Science Foundation of China (81801037)
  • Beijing Municipal Science and Technology Commission (Z181100001618015)