Abstract

Objective: To profile the salivary microbiomes of a Hong Kong Chinese cohort at a species-level resolution and determine species that discriminated clinically resolved periodontitis from periodontally healthy cases.Methods: Salivary microbiomes of 35 Hong Kong Chinese subjects' under routine supportive dental care were analyzed. All subjects had been treated for any dental caries or periodontal disease with all restorative treatment completed at least 1 year ago and had ≤3 residual pockets. They were categorized based on a past diagnosis of chronic periodontitis into “healthy” (H) or “periodontitis” (P) categories. Unstimulated whole saliva was collected, genomic DNA was isolated, and high throughput Illumina MiSeq sequencing of 16S rRNA (V3-V4) gene amplicons was performed. The sequences were assigned taxonomy at the species level by using a BLASTN based algorithm that used a combined reference database of HOMD RefSeqV14.51, HOMD RefSeqExtended V1.1 and GreenGeneGold. Species-level OTUs were subjected to downstream analysis in QIIME and R. For P and H group comparisons, community diversity measures were compared, differentially abundant species were determined using DESeq2, and disease indicator species were determined using multi-level pattern analysis within the R package “indicspecies.”Results: P subjects were significantly older than H subjects (p = 0.003) but not significantly different in their BOP scores (p = 0.82). No significant differences were noted in alpha diversity measures after adjusting for age, gender, and BOP or in the beta diversity estimates. Four species; Treponema sp. oral taxon 237, TM7 sp. Oral Taxon A56, Prevotella sp. oral taxon 314, Prevotella sp. oral taxon 304, and Capnocytophaga leadbetteri were significantly more abundant in P than in the H group. Indicator species analysis showed 7 significant indicators species of P group. Fusobacterium sp oral taxon 370 was the sole positive indicator of P group (positive predictive value = 0.9, p = 0.04). Significant indicators of the H category were Leptotrichia buccalis, Corynebacterium matruchotii, Leptotrichia hofstadii, and Streptococcus intermedius.Conclusion: This exploratory study showed salivary microbial species could discriminate treated, well-maintained chronic periodontitis from healthy controls with similar gingival inflammation levels. The findings suggest that certain salivary microbiome features may identify periodontitis-susceptible individuals despite clinical disease resolution.

Highlights

  • Salivary microbiomes show temporal stability in health (Belstrøm et al, 2016)

  • Salivary microbiomes of 35 subjects were analyzed after 4 subjects were excluded due to having

  • We conducted an exploratory investigation to assess the salivary microbiome in P and H subjects within a Hong Kong Chinese cohort

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Summary

Introduction

Salivary microbiomes show temporal stability in health (Belstrøm et al, 2016). Discernible microbial community patterns at baseline are shown to predict increased risk of inflammatory disease onset in a skin model (van Rensburg et al, 2015). Whether some microbial “traits” in the oral microbiome are associated with past disease experience or future risk is not established. The salivary microbiome composition has been found comparable to pooled subgingival plaque in terms of its “representativeness” of the subgingival microbiota (Belstrøm et al, 2017). The host-microbiome link is bi-directional, and as inherent features of oral microbiota affect immune programming (Madhwani and McBain, 2016), they may associate with susceptibility to infection. Plaque biofilm accumulation and its consequent compositional shift to a dysbiotic state is key to the initiation of periodontitis-associated inflammation in susceptible individuals. Inherent microbial susceptibility “traits” may be reflected in states of clinically resolved periodontal disease. Salivary microbiome differences between well-treated periodontitis and healthy subjects with comparable periodontal health could potentially reflect stable ecological patterns that predict past or future periodontal disease

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