Biosystems Data Analysis, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands.
Preventive Dentistry, Academic Centre for Dentistry, Vrije Universiteit Amsterdam and University of Amsterdam, Amsterdam, The Netherlands.
NPJ Biofilms Microbiomes. 2024 Sep 19;10(1):89. doi: 10.1038/s41522-024-00565-x.
Gingivitis-the inflammation of the gums-is a reversible stage of periodontal disease. It is caused by dental plaque formation due to poor oral hygiene. However, gingivitis susceptibility involves a complex set of interactions between the oral microbiome, oral metabolome and the host. In this study, we investigated the dynamics of the oral microbiome and its interactions with the salivary metabolome during experimental gingivitis in a cohort of 41 systemically healthy participants. We use Parallel Factor Analysis (PARAFAC), which is a multi-way generalization of Principal Component Analysis (PCA) that can model the variability in the response due to subjects, variables and time. Using the modelled responses, we identified microbial subcommunities with similar dynamics that connect to the magnitude of the gingivitis response. By performing high level integration of the predicted metabolic functions of the microbiome and salivary metabolome, we identified pathways of interest that describe the changing proportions of Gram-positive and Gram-negative microbiota, variation in anaerobic bacteria, biofilm formation and virulence.
牙龈炎——即牙龈炎症——是牙周病的一个可逆阶段。它是由于口腔卫生不良导致牙菌斑形成而引起的。然而,牙龈炎易感性涉及口腔微生物组、口腔代谢组和宿主之间复杂的相互作用。在这项研究中,我们在一个由 41 名系统性健康参与者组成的队列中,研究了实验性牙龈炎期间口腔微生物组的动态及其与唾液代谢组的相互作用。我们使用平行因子分析(PARAFAC),这是主成分分析(PCA)的一种多维推广,可以对由于个体、变量和时间而导致的响应中的可变性进行建模。使用建模后的响应,我们确定了与牙龈炎反应幅度相关的具有相似动态的微生物亚群落。通过对微生物组和唾液代谢组的预测代谢功能进行高水平的综合分析,我们确定了描述革兰氏阳性和革兰氏阴性菌群变化比例、厌氧菌变化、生物膜形成和毒力变化的相关途径。