Role of spatial structure in shaping viral population diversity and evolution

总结 病毒进化使得新型病毒病原体在人类中出现。的演变 甲型流感病毒对于宿主免疫中季节性谱系的维持也至关重要。 进化可以是选择的结果，导致适应度的增加，也可以是随机过程的结果，通常会减少 健身。因此，选择力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。基于进化理论，我们假设随机效应的大小 病毒进化过程受到表征病毒在宿主内传播的空间结构的强烈影响。在 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， 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 因此，预计宿主环境的表型、宿主反应和物理特征 影响病毒遗传多样性和进化。我们的首要假设是，调节病毒的特征 病毒的空间结构也调节病毒的多样性和进化。我们将测试流感的这一假设 一种使用模拟建模和实验方法的良好集成组合的病毒。在目标 1 中，我们 将使用计算、细胞培养和雪貂模型来检查空间结构化传播的后果 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的病毒 条形码可以对病毒多样性进行可靠的量化。这样，随机效应的程度 主导病毒动力学将在一系列条件下进行检查。在目标 2 中，我们将评估 空间结构传播对净化和积极选择的影响。计算方法 将用于提出关于病毒传播距离有多远影响从头有益的能力的假设 和有害的突变以达到统治地位。然后将使用实验来测试这些模型预测 常见与罕见的长距离扩散条件下的进化。这样我们就可以测试理论 与空间结构相关的随机效应阻碍自然选择发挥作用的能力的概念 不断扩大的人口。总而言之，这两个目标提出的研究将揭示以下内容的重要性： 空间结构到病毒种群生物学和进化，加深我们对力量的基本理解 塑造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.