IADR Abstract Archives
A Large-Scale Meta-Omics Analysis of Plaque Microbiome for Periodontal Diagnosis
Objectives: To analyse the predictive capacity of supragingival and subgingival plaque microbiota at the ASV-level to discriminate different periodontal health conditions (periodontal health, gingivitis, and untreated and treated periodontitis).
Methods: A total of 120 patients (55 controls, 65 periodontitis) were selected for subgingival plaque collection in our setting. Sequencing of the V3-V4 16S rRNA gene region was performed in Illumina MiSeq. The obtained sequences and metadata were uploaded to the sequence read archive (SRA). Searches were performed in PubMed, Scopus, Embase, and the SRA to identify previously published Illumina V3-V4 sequencing studies on the supragingival and subgingival plaque microbiome in distinct periodontal conditions. Research that met the criteria for sequences and metadata were included in the meta-omics analysis, comprising a total of 2045 samples. Sequences were processed under the same bioinformatics protocol, which included the ASV-level classification and the use of an oral-specific database for taxonomic classification. The statistical analysis was conducted using the microbiome and mixOmics packages.
Results: The predictive models for supragingival microbiota had AUC values ranging from 0.818 to 0.996, representing, at most, 2.39% of the ASVs and 17.37% of the species detected, respectively. Conversely, the predictive models for subgingival microbiota had AUC values ranging from 0.796 to 0.902, representing 2.85% of the ASVs and 21.67% of the species, respectively.
Conclusions: Supragingival plaque microbiome was a better bacterial biomarker than the subgingival microbiome for discriminating periodontal health from untreated and treated periodontitis. The main health-predictor ASVs in both supragingival and subgingival plaque were: Rothia dentocariosa ASV2, Haemophilus parainfluenzae ASV3, ASV78, ASV45, and ASV46, Kingella oralis ASV66, Streptococcus vestibularis ASV27, and Actinomyces HMT 170 ASV119. The main periodontitis-predictor ASVs in dental plaque were: Tannerella forsythia ASV15, Filifactor alocis ASV19, Treponema denticola ASV38 and ASV150, Fretibacterium fastidiosum ASV97, Peptostreptococcaceae [XI][G-4] HMT369 ASV124, Streptococcus anginosus ASV142 and Peptostreptococcaceae [XI][G-6] nodatum ASV189.
Methods: A total of 120 patients (55 controls, 65 periodontitis) were selected for subgingival plaque collection in our setting. Sequencing of the V3-V4 16S rRNA gene region was performed in Illumina MiSeq. The obtained sequences and metadata were uploaded to the sequence read archive (SRA). Searches were performed in PubMed, Scopus, Embase, and the SRA to identify previously published Illumina V3-V4 sequencing studies on the supragingival and subgingival plaque microbiome in distinct periodontal conditions. Research that met the criteria for sequences and metadata were included in the meta-omics analysis, comprising a total of 2045 samples. Sequences were processed under the same bioinformatics protocol, which included the ASV-level classification and the use of an oral-specific database for taxonomic classification. The statistical analysis was conducted using the microbiome and mixOmics packages.
Results: The predictive models for supragingival microbiota had AUC values ranging from 0.818 to 0.996, representing, at most, 2.39% of the ASVs and 17.37% of the species detected, respectively. Conversely, the predictive models for subgingival microbiota had AUC values ranging from 0.796 to 0.902, representing 2.85% of the ASVs and 21.67% of the species, respectively.
Conclusions: Supragingival plaque microbiome was a better bacterial biomarker than the subgingival microbiome for discriminating periodontal health from untreated and treated periodontitis. The main health-predictor ASVs in both supragingival and subgingival plaque were: Rothia dentocariosa ASV2, Haemophilus parainfluenzae ASV3, ASV78, ASV45, and ASV46, Kingella oralis ASV66, Streptococcus vestibularis ASV27, and Actinomyces HMT 170 ASV119. The main periodontitis-predictor ASVs in dental plaque were: Tannerella forsythia ASV15, Filifactor alocis ASV19, Treponema denticola ASV38 and ASV150, Fretibacterium fastidiosum ASV97, Peptostreptococcaceae [XI][G-4] HMT369 ASV124, Streptococcus anginosus ASV142 and Peptostreptococcaceae [XI][G-6] nodatum ASV189.