Role of spatial structure in shaping viral population diversity and evolution

摘要 病毒进化使人类群体中出现了新的病毒病原体。网络技术的演变 甲型流感病毒对维持宿主免疫方面的季节性血统也至关重要。 进化可以是选择的结果，导致适应度增加，或者是随机过程，通常会减少 健身。因此，选择性和随机力的相对效力是适应性的关键决定因素 人口的潜力。基于进化论，我们假设随机效应的大小 在病毒进化中，病毒在宿主内传播的空间结构强烈地影响着病毒的进化。在……里面 换句话说，病毒种群在太空中的扩张可能会引起随机的、宿主内的瓶颈和 创始人效应削弱了自然选择的效率。影响病毒传播的因素-包括病毒 表型、寄主反应和寄主环境的物理特征-因此预测 影响病毒遗传多样性和进化。我们的主要假设是，调节病毒特征的 病毒空间结构也调节病毒的多样性和进化。我们将针对流感检验这一假说 病毒采用了模拟、建模和实验方法的完美结合。在目标1中，我们 将使用计算、细胞培养和雪貂模型来研究空间结构扩散的后果 病毒种群的遗传多样性。在我们的实验中，我们将使用携带选择性中性病毒的病毒 条形码允许对病毒多样性进行可靠的量化。在这种情况下，随机效应的程度 将在一系列条件下检查主导病毒的动态。在目标2中，我们将评估 空间结构扩散对净化和正向选择的影响。计算方法 将被用来开发假设，即病毒传播的距离有多长会影响病毒的从头开始的能力 和有害的突变来达到统治地位。然后，这些模型预测将通过实验进行验证 常见与罕见长距离扩散条件下的演化。通过这种方式，我们将检验理论上的 与空间结构相关的随机效应阻碍自然选择发挥作用的概念 不断扩大的人口。总而言之，这两个目标中提出的研究将揭示 空间结构对病毒种群生物学和进化的影响，加深了我们对这些力量的基本认识 塑造了自然界中的病毒进化。

Summary Viral evolution enables the emergence of novel viral pathogens in the human population. The evolution of influenza A virus is also critical for the maintenance of seasonal lineages in the context of host immunity. Evolution can result from selection, leading to increased fitness, or stochastic processes that typically decrease fitness. The relative potency of selective and stochastic forces is therefore a critical determinant of the adaptive potential of a population. Based on evolutionary theory, we hypothesize that the magnitude of stochastic effects in viral evolution is strongly impacted by the spatial structure that characterizes viral spread within a host. In other words, the expansion of a virus population in space may give rise to random, within-host bottlenecks and founder effects that weaken the efficiency of natural selection. Factors that shape viral spread - including viral phenotypes, host responses and physical characteristics of the host environment - are therefore predicted to impact viral genetic diversity and evolution. Our overarching hypothesis is that viral features that modulate viral spatial structure also modulate viral diversity and evolution. We will test this hypothesis for influenza A virus using a well-integrated combination of simulation modeling and experimental approaches. In Aim 1, we will use computational, cell culture and ferret models to examine the consequences of spatially structured spread for genetic diversity of viral populations. For our experiments, we will use viruses carrying a selectively neutral barcode to allow robust quantification of viral diversity. In this way, the degree to which stochastic effects dominate viral dynamics will be examined under a range of conditions. In Aim 2, we will evaluate the consequences of spatially structured spread for both purifying and positive selection. Computational approaches will be used to develop hypotheses of how long distance virus dispersal impacts the ability of de novo beneficial and deleterious mutations to reach dominance. These model predictions will then be tested using experimental evolution under conditions of common vs. rare long distance dispersal. In this way, we will test the theoretical concept that stochastic effects associated with spatial structure impede the ability of natural selection to act on expanding populations. Taken together, the research proposed in these two aims will uncover the importance of spatial structure to viral population biology and evolution, deepening our fundamental understanding of the forces shaping viral evolution in nature.