Table_6_Structure and Function of Oral Microbial Community in Periodontitis Based on Integrated Data.docx

ObjectiveMicroorganisms play a key role in the initiation and progression of periodontal disease. Research studies have focused on seeking specific microorganisms for diagnosing and monitoring the outcome of periodontitis treatment. Large samples may help to discover novel potential biomarkers and capture the common characteristics among different periodontitis patients. This study examines how to screen and merge high-quality periodontitis-related sequence datasets from several similar projects to analyze and mine the potential information comprehensively. MethodsIn all, 943 subgingival samples from nine publications were included based on predetermined screening criteria. A uniform pipeline (QIIME2) was applied to clean the raw sequence datasets and merge them together. Microbial structure, biomarkers, and correlation network were explored between periodontitis and healthy individuals. The microbiota patterns at different periodontal pocket depths were described. Additionally, potential microbial functions and metabolic pathways were predicted using PICRUSt to assess the differences between health and periodontitis. ResultsThe subgingival microbial communities and functions in subjects with periodontitis were significantly different from those in healthy subjects. Treponema, TG5, Desulfobulbus, Catonella, Bacteroides, Aggregatibacter, Peptostreptococcus, and Eikenella were periodontitis biomarkers, while Veillonella, Corynebacterium, Neisseria, Rothia, Paludibacter, Capnocytophaga, and Kingella were signature of healthy periodontium. With the variation of pocket depth from shallow to deep pocket, the proportion of Spirochaetes, Bacteroidetes, TM7, and Fusobacteria increased, whereas that of Proteobacteria and Actinobacteria decreased. Synergistic relationships were observed among different pathobionts and negative relationships were noted between periodontal pathobionts and healthy microbiota. ConclusionThis study shows significant differences in the oral microbial community and potential metabolic pathways between the periodontitis and healthy groups. Our integrated analysis provides potential biomarkers and directions for in-depth research. Moreover, a new method for integrating similar sequence data is shown here that can be applied to other microbial-related areas.研究目的 微生物在牙周病（periodontal disease）的发生与进展中发挥关键作用。现有研究多聚焦于筛选特异性微生物，以辅助牙周炎的诊断及治疗效果监测。大样本量研究有助于发现潜在新型生物标志物，并捕捉不同牙周炎患者间的共性特征。本研究旨在探索如何从多个同类项目中筛选并整合高质量牙周炎相关序列数据集，实现对潜在信息的全面分析与挖掘。 研究方法 本研究基于预先设定的筛选标准，共纳入9项已发表研究的943份龈下（subgingival）样本。采用统一分析流程（QIIME2）对原始序列数据集进行质控清洗与合并。随后对比分析牙周炎患者与健康人群的微生物群落结构、生物标志物及关联网络，并描述不同牙周袋深度下的微生物组特征。此外，本研究通过PICRUSt预测潜在微生物功能与代谢通路，以评估健康状态与牙周炎间的功能差异。 研究结果 牙周炎患者的龈下微生物群落及其功能与健康人群存在显著差异。鉴定出的牙周炎特异性生物标志物包括密螺旋体属（Treponema）、TG5、脱硫弧菌属（Desulfobulbus）、卡顿氏菌属（Catonella）、拟杆菌属（Bacteroides）、聚集杆菌属（Aggregatibacter）、消化链球菌属（Peptostreptococcus）以及艾肯菌属（Eikenella）；而韦荣球菌属（Veillonella）、棒状杆菌属（Corynebacterium）、奈瑟菌属（Neisseria）、罗氏菌属（Rothia）、帕鲁德杆菌属（Paludibacter）、噬二氧化碳细胞菌属（Capnocytophaga）以及金氏菌属（Kingella）为健康牙周组织的特征性微生物。随着牙周袋深度从浅至深，螺旋体门（Spirochaetes）、拟杆菌门（Bacteroidetes）、TM7及梭杆菌门（Fusobacteria）的相对丰度逐渐升高，而变形菌门（Proteobacteria）与放线菌门（Actinobacteria）的相对丰度则呈下降趋势。不同牙周致病菌间呈现协同关联，而牙周致病菌与健康微生物群之间则存在负相关关系。 研究结论 本研究证实，牙周炎组与健康对照组的口腔微生物群落及潜在代谢通路存在显著差异。本整合分析为后续深入研究提供了潜在生物标志物与研究方向。此外，本研究提出了一种整合同类序列数据的新方法，该方法可推广应用于其他微生物相关研究领域。