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. 2025 Aug 19;109(1):186.
doi: 10.1007/s00253-025-13574-3.

Signature of oral microbial dysbiosis in different periodontitis risk levels

Affiliations

Signature of oral microbial dysbiosis in different periodontitis risk levels

Yanan Xu et al. Appl Microbiol Biotechnol. .

Abstract

Individuals categorized into distinct periodontitis risk levels often demonstrate substantial disparities not only in the likelihood of developing periodontitis but also in the rate at which the disease progresses. However, the oral microbial communities and their functional characteristics corresponding to different periodontitis risk levels remain to be further explored. Therefore, 52 subjects with periodontitis were selected and categorized into different periodontitis risk groups based on the periodontal risk calculator (PRC). Unstimulated saliva was collected, and metagenomics sequencing was performed to compare microbial diversity, taxonomy, and functional annotation among groups. There was no significant difference in species richness and evenness between the very high risk group and the high risk group, but beta diversity increased in the former group. A higher abundance of Filifactor alocis, Streptococcus cristatus, Klebsiella pneumoniae, and Streptococcus anginosus was attributed to the very high risk group, while Pseudopropionibacterium propionicum and Abiotrophia defectiva were found in higher abundance in the high risk group. Functional annotation revealed that biosynthesis of amino acids (lysine biosynthesis; phenylalanine, tyrosine and tryptophan biosynthesis; valine, leucine, and isoleucine biosynthesis), citrate cycle (TCA cycle), carbon fixation pathways in prokaryotes, oxidative phosphorylation, lipopolysaccharide biosynthesis, fatty acid biosynthesis, ubiquinone and other terpenoid-quinone biosynthesis, pantothenate and CoA biosynthesis, and glutathione metabolism were enriched in the very high risk group. The combined results indicate that the periodontal pathogens associated with a higher risk of periodontitis and the regulation of their related functional pathways increase the risk and likelihood of periodontitis development. KEY POINTS : • There were differences in microbial diversity among different periodontitis risk-level groups. • Some previously overlooked species and pathogenic pathways were linked to periodontitis risk differences. • Combining PRC with metagenomic sequencing revealed more potential pathogens.

Keywords: Metagenomics; Microbiology; Periodontitis; Risk assessment.

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Conflict of interest statement

Declarations. Ethics approval: The Medical Ethics Committee of the Affiliated Stomatological Hospital of Kunming Medical University approved the study protocol (Ethics Approval No. KYKQ2022MEC008 and No. KYKQ2024MEC006). All patients signed a written informed consent prior to enrollment. Conflict of interest: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Oral microbial diversity in the very high risk group and the high risk group. a The species accumulation curves based on the number of species. b Alpha-diversity (Chao1 index, Simpson index, Shannon index). c Beta-diversity (Bray–Curtis distance). d Partial least squares discriminant analysis (PLS-DA) at the species level for the two groups. The confidence level of the elliptical confidence intervals of the scatterplot analyzed by PLS-DA is 95%. The two-sided Wilcoxon rank-sum test was used to determine significance, and p < 0.05 indicates statistical significance
Fig. 2
Fig. 2
Differences in the taxonomic composition between the very high risk group and the high-risk group. a The Venn diagram of the number of species in the very high risk group and the high-risk group. b Stacked diagram of identifies species that differ between the two groups. c Statistical analysis of metagenomic profiles (STAMP) analysis identifies species that differ significantly between the two groups. d Linear discriminant analysis effect size (LEfSe) analysis for differential taxa. The horizontal coordinate is the linear discriminant analysis (LDA) value. The larger the LDA value is, the more it contributes to the difference between the two groups. The picture only shows the taxa with an LDA value greater than 2
Fig. 3
Fig. 3
The performance of differential species in distinguishing risk levels. Receiver operating characteristic (ROC) curves and area under the curve (AUC) values of the top 30 differentially abundant bacteria between the very high risk group and the high risk group. When the AUC value is between 0.5 and 0.7, it indicates relatively low predictive accuracy, and when it is between 0.7 and 0.9, it indicates moderate predictive accuracy. FPR, false positive rate; TPR, true positive rate
Fig. 4
Fig. 4
The functional annotation analysis in the very high risk group and the high risk group. a The Venn diagram of the number of genes at the Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology (KO) level for the very high risk group and the high risk group. b Beta-diversity (Bray–Curtis distance). c Functional KEGG pathway enrichment analysis. The abscissa is the reporter score value (with a threshold of 1.65), and the ordinate is the pathway. Positive and negative values indicate the enrichment direction

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