Non-Lethal Control of the Cariogenic Potential of an Agent-Based Model for Dental Plaque

Dental caries or tooth decay is a prevalent global disease whose causative agent is the oral biofilm known as plaque. According to the ecological plaque hypothesis, this biofilm becomes pathogenic when external challenges drive it towards a state with a high proportion of acid-producing bacteria. Determining which factors control biofilm composition is therefore desirable when developing novel clinical treatments to combat caries, but is also challenging due to the system complexity and the existence of multiple bacterial species performing similar functions. Here we employ agent-based mathematical modelling to simulate a biofilm consisting of two competing, distinct types of bacterial populations, each parameterised by their nutrient uptake and aciduricity, periodically subjected to an acid challenge resulting from the metabolism of dietary carbohydrates. It was found that one population was progressively eliminated from the system to give either a benign or a pathogenic biofilm, with a tipping point between these two fates depending on a multiplicity of factors relating to microbial physiology and biofilm geometry. Parameter sensitivity was quantified by individually varying the model parameters against putative experimental measures, suggesting non-lethal interventions that can favourably modulate biofilm composition. We discuss how the same parameter sensitivity data can be used to guide the design of validation experiments, and argue for the benefits of in silico modelling in providing an additional predictive capability upstream from in vitro experiments.

龋齿（Dental caries）又称蛀牙，是一种全球性高发疾病，其致病因子为被称为牙菌斑（plaque）的口腔生物膜（oral biofilm）。根据生态菌斑假说（ecological plaque hypothesis），当外界压力促使该生物膜转向产酸菌（acid-producing bacteria）占比过高的状态时，其便会获得致病性。明确调控生物膜群落组成的关键因素，对于开发对抗龋齿的新型临床治疗方案具有重要意义，但由于系统复杂性以及功能冗余的多种细菌类群的存在，该问题极具挑战性。本研究采用基于智能体的数学建模（agent-based mathematical modelling），模拟由两类相互竞争的独特细菌种群构成的生物膜；两类种群均以营养摄取能力与耐酸性（aciduricity）作为参数进行设定，并周期性地承受由膳食碳水化合物代谢所引发的酸性压力。研究结果显示，其中一类细菌种群会被系统逐步淘汰，最终使生物膜呈现良性或致病性两种状态；二者之间的临界转折点取决于与微生物生理学及生物膜几何结构相关的多种因素。通过针对假定的实验测量指标逐一调整模型参数，我们对参数敏感性进行了量化分析，据此提出了可正向调控生物膜群落组成的非致死性干预策略。本研究还探讨了如何利用相同的参数敏感性数据指导验证实验的设计，并论证了计算机模拟建模（in silico modelling）可在体外实验（in vitro experiments）之前提供额外的预测能力，具备显著应用价值。