Department of Preventive Dentistry, Academic Centre for Dentistry Amsterdam, University of Amsterdam and Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
School of Engineering, Faculty of Science, Agriculture and Engineering, Newcastle University, Newcastle upon Tyne, UK.
Br Dent J. 2020 Dec;229(12):769-773. doi: 10.1038/s41415-020-2407-8. Epub 2020 Dec 18.
The oral ecosystem is shaped by complex interactions between systemic health disease and the resident oral microbiota. Research in the last two decades has produced datasets describing the genetics and physiology of the host and the oral microbiome in health and disease. There are inter-individual differences in the ability to tolerate oral disease-promoting challenges. Identification of the key factors that drive a healthy and resilient oral ecosystem is urgently needed. So far, progress is being made towards replicating the host-microbiota interplay in vitro. Clinical studies may shed light on the mechanisms of oral health resilience. However, most clinical studies are cross-sectional and are insufficient for understanding resilience or for identifying biomarkers that correlate with the point of transition from oral health to dysbiosis. Mathematical and computational models, including artificial intelligence approaches, offer an opportunity to inform the design of clinical studies by identifying key biomarkers and interaction networks in complex datasets and predicting important parameters. This paper discusses some of the challenges and opportunities for understanding the biological basis of resilience of the oral ecosystem. It discusses the current status and challenges, and proposes a way forward to better understand resilience towards oral diseases.
口腔生态系统是由全身健康疾病和常驻口腔微生物群之间的复杂相互作用所塑造的。在过去的二十年中,研究产生了描述宿主和口腔微生物组在健康和疾病中的遗传学和生理学的数据集。个体之间在耐受口腔疾病促进因素的能力方面存在差异。迫切需要确定驱动健康和有弹性的口腔生态系统的关键因素。到目前为止,在体外复制宿主-微生物群相互作用方面正在取得进展。临床研究可能揭示口腔健康弹性的机制。然而,大多数临床研究是横断面的,不足以了解弹性或确定与从口腔健康到生态失调的转变点相关的生物标志物。数学和计算模型,包括人工智能方法,通过在复杂数据集中识别关键生物标志物和相互作用网络以及预测重要参数,为设计临床研究提供了机会。本文讨论了理解口腔生态系统弹性的生物学基础的一些挑战和机遇。它讨论了当前的现状和挑战,并提出了一种前进的方法,以更好地理解对口腔疾病的弹性。