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The evolutionary dynamics of receptor binding avidity in influenza A: a mathematical model for a new antigenic drift hypothesis

机译:甲型流感病毒受体结合亲和力的进化动力学:一种新的抗原漂移假说的数学模型

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摘要

The most salient feature of influenza evolution in humans is its antigenic drift. This process is characterized by structural changes in the virus's B-cell epitopes and ultimately results in the ability of the virus to evade immune recognition and thereby reinfect previously infected hosts. Until recently, amino acid substitutions in epitope regions of the viral haemagglutinin were thought to be positively selected for their ability to reduce antibody binding and therefore were thought to be responsible for driving antigenic drift. However, a recent hypothesis put forward by Hensley and co-workers posits that cellular receptor binding avidity is the dominant phenotype under selection, with antigenic drift being a side effect of these binding avidity changes. Here, we present a mathematical formulation of this new antigenic drift model and use it to show how rates of antigenic drift depend on epidemiological parameters. We further use the model to evaluate how two different vaccination strategies can impact antigenic drift rates and ultimately disease incidence levels. Finally, we discuss the assumptions present in the model formulation, predictions of the model, and future work that needs to be done to determine the consistency of this hypothesis with known patterns of influenza's genetic and antigenic evolution.
机译:人类流行性感冒发展的最显着特征是其抗原性漂移。此过程的特征在于病毒B细胞表位的结构变化,最终导致病毒逃避免疫识别并重新感染先前感染宿主的能力。直到最近,病毒血凝素的表位区域中的氨基酸取代由于其减少抗体结合的能力而被认为是积极选择的,因此被认为是驱动抗原漂移的原因。然而,Hensley及其同事最近提出的假设认为,细胞受体结合亲和力是选择下的主要表型,抗原漂移是这些结合亲和力改变的副作用。在这里,我们提出了这种新的抗原漂移模型的数学公式,并用它来说明抗原漂移的速率如何取决于流行病学参数。我们进一步使用该模型来评估两种不同的疫苗接种策略如何影响抗原漂移率并最终影响疾病发生率。最后,我们讨论了模型制定中存在的假设,模型的预测以及需要做的工作,以确定该假设与流感的遗传和抗原进化的已知模式的一致性。

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