Nemoto Takashi, Shiba Takahiko, Komatsu Keiji, Watanabe Takayasu, Shimogishi Masahiro, Shibasaki Masaki, Koyanagi Tatsuro, Nagai Takahiko, Katagiri Sayaka, Takeuchi Yasuo, Iwata Takanori
Department of Periodontology, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University (TMDU)grid.265073.5, Tokyo, Japan.
Department of Chemistry, Nihon University School of Dentistry, Tokyo, Japan.
mSystems. 2021 Dec 21;6(6):e0088621. doi: 10.1128/mSystems.00886-21. Epub 2021 Oct 26.
Periodontal disease is an inflammatory condition caused by polymicrobial infection. The inflammation is initiated at the gingiva (gingivitis) and then extends to the alveolar bone, leading to tooth loss (periodontitis). Previous studies have shown differences in bacterial composition between periodontal healthy and diseased sites. However, bacterial metabolic activities during the health-to-periodontitis microbiome shift are still inadequately understood. This study was performed to investigate the bacterial characteristics of healthy, gingivitis, and periodontitis statuses through metatranscriptomic analysis. Subgingival plaque samples of healthy, gingivitis, and periodontitis sites in the same oral cavity were collected from 21 patients. Bacterial compositions were then determined based on 16S rRNA reads; taxonomic and functional profiles derived from genes based on mRNA reads were estimated. The results showed clear differences in bacterial compositions and functional profiles between healthy and periodontitis sites. Co-occurrence networks were constructed for each group by connecting two bacterial species if their mRNA abundances were positively correlated. The clustering coefficient values were 0.536 for healthy, 0.600 for gingivitis, and 0.371 for periodontitis sites; thus, network complexity increased during gingivitis development, whereas it decreased during progression to periodontitis. Taxa, including Eubacterium nodatum, Eubacterium saphenum, Filifactor alocis, and Fretibacterium fastidiosum, showed greater transcriptional activities than those of red complex bacteria, in conjunction with disease progression. These taxa were associated with periodontal disease progression, and the health-to-periodontitis microbiome shift was accompanied by alterations in bacterial network structure and complexity. The characteristics of the periodontal microbiome influence clinical periodontal status. Gingivitis involves reversible gingival inflammation without alveolar bone resorption. In contrast, periodontitis is an irreversible disease characterized by inflammatory destruction in both soft and hard tissues. An imbalance of the microbiome is present in both gingivitis and periodontitis. However, differences in microbiomes and their functional activities in the healthy, gingivitis, and periodontitis statuses are still inadequately understood. Furthermore, some inflamed gingival statuses do not consistently cause attachment loss. In this study, metatranscriptomic analyses were used to investigate the specific bacterial composition and gene expression patterns of the microbiomes of the healthy, gingivitis, and periodontitis statuses. In addition, co-occurrence network analysis revealed that the gingivitis site included features of networks observed in both the healthy and periodontitis sites. These results provide transcriptomic evidence to support gingivitis as an intermediate state between the healthy and periodontitis statuses.
牙周病是一种由多种微生物感染引起的炎症性疾病。炎症始于牙龈(牙龈炎),然后扩展到牙槽骨,导致牙齿脱落(牙周炎)。先前的研究表明,牙周健康部位和患病部位的细菌组成存在差异。然而,在从健康状态向牙周炎状态转变过程中细菌的代谢活动仍未得到充分了解。本研究旨在通过宏转录组分析来探究健康、牙龈炎和牙周炎状态下的细菌特征。从21名患者同一口腔内的健康、牙龈炎和牙周炎部位采集龈下菌斑样本。然后根据16S rRNA读数确定细菌组成;基于mRNA读数估算来自基因的分类学和功能概况。结果显示,健康部位和牙周炎部位在细菌组成和功能概况上存在明显差异。通过连接两个mRNA丰度呈正相关的细菌物种,为每组构建共现网络。健康部位的聚类系数值为0.536,牙龈炎部位为0.600,牙周炎部位为0.371;因此,在牙龈炎发展过程中网络复杂性增加,而在发展为牙周炎过程中网络复杂性降低。包括诺氏真杆菌、隐匿真杆菌、嗜栖纤毛菌和苛求密螺旋体在内的分类群,与红色复合体细菌相比,随着疾病进展显示出更高的转录活性。这些分类群与牙周病进展相关,从健康状态到牙周炎状态的微生物组转变伴随着细菌网络结构和复杂性的改变。牙周微生物组的特征影响临床牙周状态。牙龈炎涉及可逆的牙龈炎症,无牙槽骨吸收。相比之下,牙周炎是一种不可逆疾病,其特征是软硬组织均有炎症性破坏。牙龈炎和牙周炎中均存在微生物组失衡。然而,健康、牙龈炎和牙周炎状态下微生物组及其功能活动的差异仍未得到充分了解。此外,一些炎症性牙龈状态并不一定会持续导致附着丧失。在本研究中,宏转录组分析用于探究健康、牙龈炎和牙周炎状态下微生物组的特定细菌组成和基因表达模式。此外,共现网络分析表明,牙龈炎部位具有在健康部位和牙周炎部位观察到网络的特征。这些结果提供了转录组学证据,支持牙龈炎是健康状态和牙周炎状态之间的中间状态。