Coevolutionary Epidemiology of Hosts and Their Infectious Pathogens

宿主及其传染性病原体的共同进化流行病学

• 批准号: RGPIN-2022-03113
• 负责人: MacPherson, Ailene
• 金额: $ 2.11万
• 依托单位: Simon Fraser University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=758544
• 关键词: Coevolutionary; Epidemiology; Hosts; Their; Infectious

My new research program addresses fundamental questions at the intersection of evolution, ecology, and epidemiology. Inspired by the Red Queen hypothesis and the putative importance of biotic interactions in shaping diversity, the long-term goal of my research program is to characterize the emergent consequences of coevolution between hosts and their infectious pathogens. Over the next 5 years, my team will develop and apply mathematical and statistical models to support the study of infectious pathogens as model systems of coevolution via two short-term objectives: 1) Develop phylogenetic methods to characterize epidemiological mechanisms of infectious diseases, and 2) Develop population genetic models and inference methods to characterize host-pathogen coevolution in spatially structured environments. To reassess the Red Queen hypothesis in the context of directly-transmitted diseases, my team will employ complementary genomic and genetic approaches to understand feedbacks between evolutionary, epidemiological, and ecological (E3) processes. In Objective 1 we will develop a new class of methods that will allow us to characterize epidemiological mechanisms from the evolutionary relationship between pathogen genome sequences. We will then optimize these methods to infer coinfection and coevolution. Finally, we will apply these methods to cytomegalovirus, to quantify coinfection in the multimammate rat, and hence its suitability as a vector for a transmissible vaccine. In Objective 2 we will use population genetic models to understand the emergent evolutionary consequences of coevolution in spatially structured environments. Local adaptation is a powerful metric connecting theoretical and empirical understandings of coevolution. By first adapting the measurement of local adaptation for coevolution between hosts and their infectious pathogens, we will use population genetic models to assess the consequences of disease on spatial diversity. We will then use these models to develop an inferential method for identifying the strength of trade-offs between epidemiological traits, knowledge which is essential for predicting disease evolution. Finally, we will adapt this inferential framework to design and test the robustness of genomic conservation strategies for rescuing species at risk of extinction from disease. We are faced with numerous existential crises at the E3 intersection: from the unprecedented loss of biodiversity from anthropogenic environmental change and the control of zoonotic pathogens. The outcomes of the proposed research will advance genomic epidemiology and provide a theoretical framework for developing evolutionarily robust conservation strategies for wildlife populations threatened by infectious disease. My research program applies mathematical and statistical approaches to both address fundamental questions in evolution and will contribute scientific knowledge and methods to address these crises for the benefit of Canadians.

我的新研究计划解决了进化，生态学和流行病学交集的基本问题。受到红皇后假设的启发以及生物相互作用在塑造多样性中的推定重要性，我的研究计划的长期目标是表征宿主与其感染性病原体之间共同进化的新兴后果。在接下来的5年中，我的团队将开发和应用数学和统计模型，以通过两个短期目标来支持传染病的研究作为协同进化的模型：1）开发系统发育方法，以表征传染病的流行病学机制，以及2）发展宿主遗传学模型和突发性遗传模型的表征宿主遗传学的方法，使宿主构成了稳固的环境。为了在直接传播疾病的背景下重新评估红色女王假设，我的团队将采用互补的基因组和遗传方法来了解进化，流行病学和生态学（E3）过程之间的反馈。在目标1中，我们将开发一类新的方法，使我们能够从病原体基因组序列之间的进化关系来表征流行病学机制。然后，我们将优化这些方法来推断共感染和共同进化。最后，我们将将这些方法应用于巨细胞病毒，以量化多模拟大鼠的共同感染，从而作为媒介作为传播疫苗的适用性。在目标2中，我们将使用人群遗传模型来了解在空间结构化环境中共同进化的新兴进化后果。局部适应是一个有力的指标，可以将理论和经验理解相连。首先，通过调整局部适应性的测量宿主与传染病之间的共同进化，我们将使用人群遗传模型来评估疾病对空间多样性的后果。然后，我们将使用这些模型来开发一种推论方法来确定流行病学特征之间权衡的强度，这对于预测疾病进化至关重要。最后，我们将适应这个推论框架，以设计和测试基因组保护策略的鲁棒性，以拯救有灭绝疾病风险的物种。 我们在E3交集处面临着许多存在的危机：从人为环境变化和人畜共患病原体的控制中，生物多样性的前所未有的丧失。拟议的研究的结果将推动基因组流行病学，并为制定进化强大的保护策略，为受感染性疾病威胁的野生动植物种群提供了一个理论框架。我的研究计划将数学和统计方法应用于进化中的基本问题，并将为解决这些危机的科学知识和方法来解决加拿大人的利益。