Search

Oral microbial dysbiosis has been associated with periodontitis in studies using 16S rRNA gene sequencing analysis. However, this technology is not sufficient to consistently separate the bacterial species to species level, and reproducible oral microbiome signatures are scarce. Obtaining these signatures would significantly enhance our understanding of the underlying pathophysiological processes of this condition and foster the development of improved therapeutic strategies, potentially personalized to individual patients. Here, we sequenced newly collected samples from 24 patients with periodontitis, and we collected available oral microbiome data from 24 samples in patients with periodontitis and from 214 samples in healthy individuals ( n = 262). Data were harmonized, and we performed a pooled analysis of individual patient data. By metagenomic sequencing of the plaque microbiome, we found microbial signatures for periodontitis and defined a periodontitis-related complex, composed by the most discriminative bacteria. A simple two-factor decision tree, based on Tannerella forsythia and Fretibacterium fastidiosum , was associated with periodontitis with high accuracy (area under the curve: 0.94). Altogether, we defined robust oral microbiome signatures relevant to the pathophysiology of periodontitis that can help define promising targets for microbiome therapeutic modulation when caring for patients with periodontitis., Importance: Oral microbial dysbiosis has been associated with periodontitis in studies using 16S rRNA gene sequencing analysis. However, this technology is not sufficient to consistently separate the bacterial species to species level, and reproducible oral microbiome signatures are scarce. Here, using ultra-deep metagenomic sequencing and machine learning tools, we defined a simple two-factor decision tree, based on Tannerella forsythia and Fretibacterium fastidiosum , that was highly associated with periodontitis. Altogether, we defined robust oral microbiome signatures relevant to the pathophysiology of periodontitis that can help define promising targets for microbiome therapeutic modulation when caring for patients with periodontitis., Competing Interests: The authors declare no conflict of interest.

Periodontitis is a common condition characterized by an exacerbated pro-inflammatory response, which leads to tissue destruction and, ultimately, alveolar bone loss. In this pilot study, we assess the microbiota composition and cytokine profile changes in patients with stage III/IV, grade B/C periodontitis, specifically by comparing healthy and diseased sites in the same oral cavity. Overall, we found that microbiota architecture was significantly disrupted between diseased and healthy sites, and that the clustering was driven, in part, by the increased relative abundances of Synergistetes in diseased sites, as well as the increased abundances of Firmicutes in healthy sites. We also observed that diseased sites were enriched in Synergistetes, TM7, SR1, Spirochaetes, Bacteroidetes and Fusobacteria, and depleted in Firmicutes, Proteobacteria, Tenericutes and Actinobacteria compared to healthy sites. We found that Interleukin-1b, Interleukin-4, Interleukin-10, and Interleukin-17A were significantly overexpressed in diseased sites, whereas Interleukin-6 and TNF-alpha do not differ significantly between healthy and diseased sites. Here, we observed concomitant changes in the subgingival plaque microbiota and cytokines profile, suggesting that this combined alteration could contribute to the pathobiology of periodontitis.