Molecular analysis of oral microbial communities in three Asian cohorts : links to periodontal, periimplant and systemic inflammatory status

Abstract

Molecular methods have revolutionized our understanding of the human microbiota. Studies included in this thesis explored oral microbial ecology in relation to periodontal, peri-implant diseases and covert pro-inflammatory burden with a focus on Asian cohorts. A combination of cluster analyses and supervised learning methods were used to explore relevant patterns.

In study I, we asked if salivary ‘red-complex’ periodontal pathogens and proinflammatory cytokine; interleukin-1 beta (IL-1β) quantities could predict the local pro-inflammatory (IL-1β) response in peri-implant mucositis. Two groups of maintenance patients having differing periodontal disease susceptibilities were examined in a multicenter study comprising two Asian populations (Hong Kong Chinese and Indian). Salivary pathogen and IL-1β burden correctly predicted the highest quartile of periimplant IL-1β responders only among the nonsusceptible subjects, implying that periodontal background could impact how these salivary biomarkers reflected the local inflammatory response to periimplant microbial challenges. However, no differences emerged in the total salivary ‘red complex’ periodontal pathogen burden between the periodontally susceptible and nonsusceptible subjects implying a need to explore salivary microbial ecology using open-ended tools.

In study II, we asked how salivary microbial communities of these subjects were shaped by their geography, covert inflammation as represented by salivary IL-1β and periodontal disease phenotype. High-throughput, ‘next-generation’ Illumina 16 S rRNA gene amplicon MiSeq sequencing of salivary DNA was performed. Community profiles of the 2 populations were compared to each other and with data from the Human Microbiome Project (HMP). A robust effect of geography on microbial composition was evident. Greatest alpha diversity was evident in the Indian cohort compared to HMP subjects, concurrent with reports of post-industrialized lifestyle and geographical impact on microbiome patterning. Next, patterns of community variance with periodontal background and salivary proinflammatory IL-1β load were each explored. Enterotyping-like cluster analysis revealed distinct dysbiotic microbiome patterns linked to highest IL-1β responder quartile within each population cohort. Enrichment of several Proteobacteria, Bacilli and markedly lower Clostridia were common features of high IL-1β associated clusters in both. Population-specific indicator species of periodontal disease phenotype were also determined.

In study III, we explored using similar high-throughput sequencing and data mining approaches, the subgingival plaque microbiomes of a classical Sri-Lankan tea worker cohort and its relation with over 40 year clinical follow-up of their periodontal health status. High diversity and large number of taxa previously undocumented in human oral cavity were evident in this rural living cohort. Associations between long-term periodontitis related tooth loss and subgingival microbial patterning were explored. Cluster analyses indicated severe periodontal disease sufferers as significantly overrepresented in a microbiome based cluster enriched with multiple Proteobacteria, Chlamydiae, Flavobacteriia, Bacilli and Treponema and markedly lower total Firmicutes, Clostridiales, Bifidobacteriales species. Several low-abundance genera typically not detected in oral microbiota emerged as significant predictors of periodontitis related tooth loss categories.

Overall, our findings demonstrate that multiple configurations of oral microbiota, are linked to periodontal phenotypes and inflammatory profiles, across different population groups. They also highlight the need to transition from reductionist to integrative perspectives to address the host-oral microbiome relationship.