Structure and Function of Oral Microbial Community in Periodontitis Based on Integrated Data

Area of Science:

• Oral microbiology
• Periodontal disease research
• Bioinformatics

Background:

• Microorganisms are crucial in periodontal disease development.
• Identifying specific microbial biomarkers aids in diagnosis and treatment monitoring.
• Integrating large datasets can reveal common patterns in periodontitis.

Purpose of the Study:

• To screen and merge high-quality periodontitis-related sequence datasets.
• To comprehensively analyze merged data for potential biomarkers and microbial characteristics.
• To establish a novel method for integrating similar sequence data.

Main Methods:

• Included 943 subgingival samples from nine publications.
• Utilized QIIME2 for sequence data cleaning and merging.
• Analyzed microbial structure, biomarkers, and correlation networks.
• Predicted microbial functions and metabolic pathways using PICRUSt.

Main Results:

• Significant differences in microbial communities and functions between periodontitis and healthy individuals.
• Identified specific bacterial biomarkers for periodontitis (e.g., Treponema, Bacteroides) and healthy periodontium (e.g., Veillonella, Neisseria).
• Observed shifts in microbial proportions with increasing pocket depth and synergistic relationships among pathobionts.

Conclusions:

• Integrated analysis reveals distinct oral microbial communities and metabolic pathways in periodontitis.
• Provides potential biomarkers for periodontitis diagnosis and monitoring.
• Demonstrates a new method for integrating sequence data applicable to other microbial studies.