School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Zhejiang, China.
Department of Stomatology, Tongde Hospital of Zhejiang Province, Zhejiang, China.
Microb Pathog. 2023 Dec;185:106390. doi: 10.1016/j.micpath.2023.106390. Epub 2023 Oct 17.
Dental caries is a result of the ecological dysfunction of the polymicrobial community on the tooth surface, which evolves through microbial interactions. In this study, we conducted a thorough analysis of the dental plaque microbiome to comprehend its multi-microbial aetiology.
In this study, plaque was collected from healthy tooth surfaces, shallow carious teeth and deep carious teeth, and bacterial composition and abundance were assessed using 16S rRNA high-throughput sequencing. Random forest and LEfSe were used to profile various microorganisms at each stage. Additionally, we developed a molecular ecological network (MEN) based on random matrix theory (RMT) to examine microbial interactions for the first time.
Our results reveal that Scardovia wiggsiae, Streptococcus mutans, and Propionibacterium acidifaciens may be associated with initial caries, and Propionibacterium acidifaciens differentiates between shallow and deep caries. As caries progressed, the alpha diversity index declined, indicating a decrease in microbial variety. The network topological indices such as centralization betweenness revealed that the caries network had become more complex, involving more microbial interactions. The shallow network revealed a high negative correlation ratio across nodes, indicating that microbes competed heavily. In contrast, the positive correlation ratio of deep network nodes was high, and microorganisms transitioned from a competitive to a synergistic state.
This study suggests that microbial diversity and interactions are critical to caries progression and that future caries research should give greater consideration to the role of microbial interaction factors in caries progression.
龋齿是牙齿表面多微生物群落生态功能失调的结果，其通过微生物相互作用而发展。在本研究中，我们对牙菌斑微生物组进行了全面分析，以了解其多微生物病因。
本研究从健康牙面、浅龋和深龋中采集牙菌斑，采用 16S rRNA 高通量测序评估细菌组成和丰度。随机森林和 LEfSe 用于分析各阶段的各种微生物。此外，我们首次基于随机矩阵理论 (RMT) 开发了分子生态网络 (MEN)，以检查微生物相互作用。
我们的结果表明，Scardovia wiggsiae、Streptococcus mutans 和 Propionibacterium acidifaciens 可能与初期龋齿有关，而 Propionibacterium acidifaciens 则可区分浅龋和深龋。随着龋齿的进展，alpha 多样性指数下降，表明微生物种类减少。网络拓扑指数，如中心化介数，表明龋齿网络变得更加复杂，涉及更多的微生物相互作用。浅龋网络的节点间呈现出高负相关比，表明微生物间竞争激烈。相比之下，深龋网络节点的正相关比较高，微生物从竞争状态向协同状态转变。
本研究表明，微生物多样性和相互作用对龋齿进展至关重要，未来的龋齿研究应更多地考虑微生物相互作用因素在龋齿进展中的作用。
