US-UK Collab.: Eco-evolutionary dynamics of infectious diseases in host population networks

该项目将通过研究感染加州东南部沙漠中的沙漠大角羊的病毒、细菌和其他致病寄生虫，来调查群体通过个体运动联系起来的方式如何影响疾病的传播。许多动物生活在栖息地斑块中，形成了一个由偶尔运动联系在一起的种群网络。了解人口连通性的变化如何影响疾病传播非常重要，因为地球仪许多地区的地貌正在迅速变化。生活在美国西部沙漠山顶的沙漠大角羊。这项研究将测量有多少羊被感染，以及它们在人群中移动的速度。他们会问，是否越是孤立的种群遗传多样性越少，就越有可能被感染。这项研究将培养本科生，研究生和博士后研究员，并将通过与K-12教师，野生动物管理机构和自然历史博物馆的合作来吸引公众。 研究人员将利用观察数据、实验和数学模型来研究相互关联的宿主种群之间的空间关系如何影响不同地区的感染风险，为宿主免疫防御的遗传适应奠定基础。宿主群体之间免疫反应的差异可能影响到这些群体对传染病的脆弱性。研究人员假设，网络拓扑结构将限制寄生虫物种在宿主种群中的分布，寄生虫相互作用将在单个宿主中构建寄生虫群落。他们预计，不同人群中寄生虫群落的差异介导了对免疫功能相关基因的差异选择，导致免疫反应和局部免疫遗传适应的变化。他们假设，这些生态和进化过程之间的反馈驱动了宿主种群网络中寄生虫群落的动态，导致了不同种群对新感染的脆弱性。来自粪便样本的宏基因组数据将用于发现三个集合种群的寄生虫水平的寄生虫群落模式。在一个莫哈韦沙漠集合种群，他们将联合收割机纵向观察数据和实验方法，以评估寄生虫的相互作用，在构建内宿主寄生虫群落的作用。绵羊的免疫应答和调查免疫遗传学概况将用于估计十四个大角牛种群之间免疫遗传学差异的选择压力。经验数据将用于参数化和测试数学网络模型，探索生态和宿主进化过程如何塑造特别是大角牛的疾病动态，以及整个人口网络。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。

This project will investigate how the way that groups are connected through the movement of individuals affects the spread of disease by studying viruses, bacteria, and other disease-causing parasites that infect desert bighorn sheep in southeastern California deserts. Many animals live in habitat patches, forming a network of populations that are linked by occasional movements. Understanding how changes in population connectivity affect disease transmission is important, as landscapes are changing rapidly in many regions around the globe. Desert bighorn sheep that live on mountain tops in the deserts of the American West. The study will measure how many of the sheep have been infected, and the rate at which they move among populations. They will ask whether more isolated populations have less genetic diversity and are more likely to be infected. This research will train of undergraduate students, graduate students, and postdoctoral fellows, and will engage the public through collaborations with K-12 teachers, wildlife management agencies, and natural history museums. The researchers will use observational data, experiments, and mathematical models to investigate how the spatial relationships between interconnected host populations shape infection risks in different locales, setting the stage for genetic adaptation of immune defenses in the hosts. Differences in immune responses among host populations are likely to affect the populations' vulnerability to infectious diseases. The investigators hypothesize that network topology will constrain parasite species distributions across host populations, and parasite interactions will structure parasite communities within individual hosts. They expect that differences in parasite communities across populations mediate differential selection on genes involved in immune function, resulting in variation in immune responses and local immunogenetic adaptation. They hypothesize that feedbacks between these ecological and evolutionary processes drive the dynamics of parasite communities in host population networks, resulting in differential vulnerability to emerging infections across populations. Metagenomic data from fecal samples will be used to discover landscape-level parasite community patterns across three metapopulations. In a Mojave Desert metapopulation, they will combine longitudinal observational data and experimental approaches to assess the role of parasite interactions in structuring within-host parasite communities. Immune responses and survey immunogenetic profiles of sheep will be used to estimate the selective pressure underlying immunogenetic differences across fourteen bighorn populations. The empirical data will be used to parameterize and test mathematical network models exploring how ecological and host evolutionary processes shape disease dynamics in bighorn in particular, and across population networks in general.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.