Gale Paul
59 Fairway Avenue, Tilehurst, Reading, Berkshire, UK.
Microb Risk Anal. 2018 Apr;8:1-13. doi: 10.1016/j.mran.2018.01.002. Epub 2018 Jan 4.
Assessing the risk of infection from emerging viruses or of existing viruses jumping the species barrier into novel hosts is limited by the lack of dose response data. The initial stages of the infection of a host by a virus involve a series of specific contact interactions between molecules in the host and on the virus surface. The strength of the interaction is quantified in the literature by the dissociation constant (K) which is determined experimentally and is specific for a given virus molecule/host molecule combination. Here, two stages of the initial infection process of host intestinal cells are modelled, namely escape of the virus in the oral challenge dose from the innate host defenses (e.g. mucin proteins in mucus) and the subsequent binding of any surviving virus to receptor molecules on the surface of the host epithelial cells. The strength of virus binding to host cells and to mucins may be quantified by the association constants, K and K, respectively. Here, a mechanistic dose-response model for the probability of infection of a host by a given virus dose is constructed using K and K which may be derived from published K values taking into account the number of specific molecular interactions. It is shown that the effectiveness of the mucus barrier is determined not only by the amount of mucin but also by the magnitude of K. At very high K values, slight excesses of mucin over virus are sufficient to remove all the virus according to the model. At lower K values, high numbers of virus may escape even with large excesses of mucin. The output from the mechanistic model is the probability (p) of infection by a single virion which is the parameter used in conventional dose-response models to predict the risk of infection of the host from the ingested dose. It is shown here how differences in K (due to molecular differences in an emerging virus strain or new host) affect p, and how these differences in K may be quantified in terms of two thermodynamic parameters, namely enthalpy and entropy. This provides the theoretical link between sequencing data and risk of infection. Lack of data on entropy is a limitation at present and may also affect our interpretation of K in terms of infectivity. It is concluded that thermodynamic approaches have a major contribution to make in developing dose-response models for emerging viruses.
由于缺乏剂量反应数据，评估新兴病毒或现有病毒跨越物种屏障感染新宿主的风险受到限制。病毒感染宿主的初始阶段涉及宿主和病毒表面分子之间一系列特定的接触相互作用。文献中通过解离常数（K）对相互作用强度进行量化，该常数通过实验确定，并且对于给定的病毒分子/宿主分子组合是特定的。在此，对宿主肠道细胞初始感染过程的两个阶段进行建模，即口服挑战剂量中的病毒从宿主固有防御（如黏液中的黏蛋白）中逃逸，以及任何存活病毒随后与宿主上皮细胞表面受体分子的结合。病毒与宿主细胞和黏蛋白结合的强度可分别通过结合常数K和K进行量化。在此，使用K和K构建了一个关于给定病毒剂量感染宿主概率的机械剂量反应模型，K和K可从已发表的K值中推导得出，并考虑了特定分子相互作用的数量。结果表明，黏液屏障的有效性不仅取决于黏蛋白的量，还取决于K的大小。根据模型，在K值非常高时，黏蛋白略微过量于病毒就足以清除所有病毒。在较低的K值下，即使黏蛋白大量过量，大量病毒仍可能逃逸。机械模型的输出是单个病毒粒子感染的概率（p），这是传统剂量反应模型中用于根据摄入剂量预测宿主感染风险的参数。此处展示了K的差异（由于新兴病毒株或新宿主中的分子差异）如何影响p，以及这些K的差异如何根据两个热力学参数，即焓和熵进行量化。这提供了测序数据与感染风险之间的理论联系。目前缺乏关于熵的数据是一个限制因素，也可能影响我们对K与感染性之间关系的解释。结论是，热力学方法在为新兴病毒开发剂量反应模型方面有重大贡献。
