Population Structure of Schistosomes and Host Snails

描述（由申请方提供）：寄生虫体与其蜗牛宿主之间的相互作用在宿主和寄生虫遗传系统的进化发展中起着重要作用。基因流动、遗传漂变和选择都可能作用于这些系统，驱动共同进化轨迹并决定疾病动态。评估宿主和寄生虫遗传异质性的程度和结构是预测传染病流行病学的重要第一步。曼氏血吸虫和光滑双脐吸虫的等位基因微卫星标记的最新特征为我们提供了一个机会，在当地的空间尺度上研究寄生虫和宿主的种群结构。该项目的具体目标包括： 1)根据来自微卫星的等位基因数据，确定螺体和蜗牛种群细分的相对性质，并评估遗传变异在空间和时间尺度上的变化; 2)将微卫星等位基因异质性与生物标志物相关联，以评估遗传变异与流行病学重要表型表达之间的关系。了解宿主和寄生虫遗传多样性在个体宿主内和个体宿主之间以及种群内和种群之间的分布，将使我们能够估计寄生虫基因流，评估多个寄生虫基因型对寄生虫毒力的重要性，并开始了解驱动疾病动态的微进化力量之间的相互作用。结果将产生进化的流行病学过程的见解，有助于确定控制策略的遗传后果，并补充并发的免疫流行病学研究的人在巴西流行的社区。

DESCRIPTION (provided by the applicant): Interactions between schistosomes and their snail hosts play an important role in the evolutionary development of host and parasite genetic systems. Gene flow, genetic drift and selection all potentially act on these systems, driving co-evolutionary trajectories and dictating disease dynamics. Assessing the degree and structure of genetic heterogeneity of both hosts and parasites is an essential first step in predicting the epidemiology of infectious diseases. The recent characterization of allelic microsatellite markers for Schistosoma mansoni and Biomphalaria glabrata provides us with an opportunity to study population structure of both parasite and host on a local spatial scale. Specific aims of this project include: 1) Determining the relative nature of population subdivision for schistosomes and snails based on allelic data from microsatellites, and assessing how that genetic variation changes on both spatial and temporal scales; and 2) Correlating microsatellite allelic heterogeneity with biomarkers for schistosome virulence and snail resistance to assess relationships between genetic variation and phenotypic expressions of epidemiological importance. Knowledge of the distribution of host and parasite genetic diversity within and among individual hosts, and within and among populations, will allow us to estimate parasite gene flow, assess the importance of multiple parasite genotypes on schistosome virulence, and begin to understand the interplay among micro-evolutionary forces that drive disease dynamics. Results will yield evolutionary insights into the epidemiological process, help to identify genetic consequences of control strategies, and complement concurrent immuno-epidemiology studies of humans in endemic Brazilian communities.