A systems genetics approach to determine factors regulating Plasmodium falciparum sporozoite infectivity

根除疟疾是一项全球卫生优先事项，需要在多个层面采取干预措施。子孢子 传播阶段感染肝脏，是干预的重要目标，因为很少有寄生虫成功地 开始感染哺乳动物宿主。感染的早期阶段通常使用啮齿动物进行研究 疟疾模型，并且对感染性相关基因的搜索一直局限于基于候选人的研究。 接近。最近开发的肝脏嵌合人源化小鼠模型产生了巨大的影响 在现场，现在使子孢子传播和肝脏阶段的研究恶性疟原虫和 基因杂交的实施。因此，我们建议利用遗传杂交， 肝嵌合人源化小鼠（FRG huHep），以产生后代的重组作图群体 具有不同水平的子孢子感染性的寄生虫。这种寄生虫种群可以用来 使用系统遗传学表征感染性的转录调控网络。我们 初步数据显示，来自遗传杂交的两个克隆重组后代表现出较高的子孢子 感染性水平高于亲本NF 54实验室菌株。我们将从这一点来描述剩余的寄生虫 交叉以确定最具传染性的克隆系，并使用这种寄生虫在 FRG huHep小鼠。我们将使用以下方法识别与测量的表型相关的遗传变异： 数量性状基因座（QTL）作图。因为QTL作图将识别大的DNA连锁块， 包含几十个可能与感染性相关的基因，我们将使用表达QTL（eQTL） 映射、共表达网络分析和贝叶斯网络构建，系统地描述了 转录网络调节传染性。本研究将为进一步研究P. 恶性疟原虫子孢子在一个前所未有的水平，定义的分子过程，管理子孢子 全球范围内的传染性。子孢子感染性相关通路的剖析及其调控 网络可用于鉴定特异性干预子孢子的药物和疫苗靶标 感染

Malaria eradication is a global health priority that will require interventions on multiple scales. The sporozoite transmission stages infect the liver and are important targets for intervention as very few parasites successfully initiate infection of the mammalian host. Early stages of infection have typically been studied using the rodent models of malaria, and the search for infectivity-associated genes has been restricted to candidate-based approaches. The recent development of liver-chimeric humanized mouse models has made a dramatic impact on the field, now enabling sporozoite transmission and liver stage studies of Plasmodium falciparum and the implementation of genetic crosses. Therefore we propose to utilize a genetic cross, conducted in the liver-chimeric humanized mouse (FRG huHep), to create a recombinant mapping population of progeny parasites that have varying levels of sporozoite infectivity. This parasite population can be used to characterize the transcriptional regulatory network underlying infectivity using systems genetics. Our preliminary data show that two clonal recombinant progeny from a genetic cross, exhibited higher sporozoite infectivity levels than the parent NF54 laboratory strain. We will characterize the remaining parasites from this cross to determine the clonal line that is most infectious, and use this parasite to perform a back cross in the FRG huHep mouse. We will identify genetic variation associated with the measured phenotypes using quantitative trait loci (QTL) mapping. Because QTL mapping will identify large linkage blocks of DNA that contain several dozen genes that may be associated with infectivity, we will then use expression QTL (eQTL) mapping, co-expression network analysis and Bayesian network construction to systematically describe the transcriptional network regulating infectivity. This study will provide genetic and transcriptional analysis of P. falciparum sporozoites on an unprecedented level, defining the molecular processes that govern sporozoite infectivity on a global scale. Dissection of the sporozoite-infectivity associated pathways and regulatory networks can be used to identify drug and vaccine targets which specifically intervene against sporozoite infection.