Ana Duran-Pinedo, O Solbiati Jose, Flavia Teles, Zhang Yanping, Jorge Frias-Lopez
Department of Oral Biology, University of Florida, College of Dentistry, 1395 Center Drive Gainesville, Gainesville, FL, 32610 - 0424, USA.
Department of Basic & Translational Sciences, University of Pennsylvania, School of Dental Medicine, 240 South 40 Street, Philadelphia, PA, 19104 - 6030, USA.
Microbiome. 2025 May 14;13(1):119. doi: 10.1186/s40168-025-02108-8.
In periodontitis, the interplay between the host and microbiome generates a self-perpetuating cycle of inflammation of tooth-supporting tissues, potentially leading to tooth loss. Despite increasing knowledge of the phylogenetic compositional changes of the periodontal microbiome, the current understanding of in situ activities of the oral microbiome and the interactions among community members and with the host is still limited. Prior studies on the subgingival plaque metatranscriptome have been cross-sectional, allowing for only a snapshot of a highly variable microbiome, and do not include the transcriptome profiles from the host, a critical element in the progression of the disease.
To identify the host-microbiome interactions in the subgingival milieu that lead to periodontitis progression, we conducted a longitudinal analysis of the host-microbiome metatranscriptome from clinically stable and progressing sites in 15 participants over 1 year. Our research uncovered a distinct timeline of activities of microbial and host responses linked to disease progression, revealing a significant clinical and metabolic change point (the moment in time when the statistical properties of a time series change) at the 6-month mark of the study, with 1722 genes differentially expressed (DE) in the host and 111,705 in the subgingival microbiome. Genes associated with immune response, especially antigen presentation genes, were highly up-regulated in stable sites before the 6-month change point but not in the progressing sites. Activation of cobalamin, porphyrin, and motility in the microbiome contribute to the progression of the disease. Conversely, inhibition of lipopolysaccharide and glycosphingolipid biosynthesis in stable sites coincided with increased immune response. Correlation delay analysis revealed that the positive feedback loop of activities leading to progression consists of immune regulation and response activation in the host that leads to an increase in potassium ion transport and cobalamin biosynthesis in the microbiome, which in turn induces the immune response. Causality analysis identified two clusters of microbiome genes whose progression can accurately predict the outcomes at specific sites with high confidence (AUC = 0.98095 and 0.97619).
A specific timeline of host-microbiome activities characterizes the progression of the disease. The metabolic activities of the dysbiotic microbiome and the host are responsible for the positive feedback loop of reciprocally reinforced interactions leading to progression and tissue destruction. Video Abstract.
在牙周炎中，宿主与微生物群之间的相互作用会引发牙齿支持组织炎症的自我延续循环，可能导致牙齿脱落。尽管对牙周微生物群的系统发育组成变化的了解日益增加，但目前对口腔微生物群的原位活性以及群落成员之间及其与宿主的相互作用的认识仍然有限。先前关于龈下菌斑宏转录组的研究是横断面研究，只能提供高度可变的微生物群的一个快照，并且不包括宿主的转录组谱，而宿主转录组谱是疾病进展的关键因素。
为了确定龈下环境中导致牙周炎进展的宿主-微生物群相互作用，我们对15名参与者临床稳定和进展部位的宿主-微生物群宏转录组进行了为期1年的纵向分析。我们的研究揭示了与疾病进展相关的微生物和宿主反应活动的独特时间线，在研究的6个月时发现了一个显著的临床和代谢变化点（时间序列的统计特性发生变化的时刻），宿主中有1722个基因差异表达（DE），龈下微生物群中有111705个基因差异表达。与免疫反应相关的基因，尤其是抗原呈递基因，在6个月变化点之前在稳定部位高度上调，但在进展部位则不然。微生物群中钴胺素、卟啉和运动性的激活促进了疾病的进展。相反在稳定部位脂多糖和糖鞘脂生物合成的抑制与免疫反应增加同时发生。相关性延迟分析表明导致疾病进展的活动的正反馈回路包括宿主中的免疫调节和反应激活，这导致微生物群中钾离子转运和钴胺素生物合成增加，进而诱导免疫反应。因果关系分析确定了两组微生物群基因，其进展可以高度准确地预测特定部位的结果（AUC = 0.98095和0.97619）。
宿主-微生物群活动的特定时间线表征了疾病的进展。功能失调的微生物群和宿主的代谢活动是导致疾病进展和组织破坏的相互增强的相互作用的正反馈回路的原因。视频摘要。
