A temporal view of the Plasmodium-red blood cell interactome

描述（由申请人提供）：细胞蛋白质与其他蛋白质形成复杂的相互作用网络。虽然很明显，这些网络是动态的结构，随着环境信号的变化而变化，并在疾病状态下发生变化，但我们评估网络时间变化的能力仍处于早期阶段。疟疾感染的红细胞是一种简单的模型，可以用来研究蛋白质相互作用网络随时间的变化。红细胞是高度分化的细胞，缺乏细胞器，含有有限的蛋白质。在感染过程中，疟原虫将蛋白质输出到红细胞中，从而显著改变宿主细胞的特性。由于红细胞缺乏细胞核，因此不能通过改变其蛋白质含量来对寄生虫感染作出反应，因此红细胞表型中发生的变化必须是由于输出到红细胞中的约300种疟疾蛋白。输出的疟疾蛋白被认为与RBC蛋白结合，并以这种方式作为引起细胞蛋白相互作用网络扰动的病变。由于关于大多数疟疾基因表达时间的详细信息已经存在，我们可以模拟细胞蛋白质相互作用网络随时间的变化，并将疟疾-RBC相互作用组中的这些时间变化与细胞特性的变化相关联。然而，这些疟疾蛋白的功能信息是稀缺的，只有非常有限的数量之间的相互作用输出疟疾蛋白和RBC蛋白已被报道。本研究的总体目标是阐明，验证和时间模型的蛋白质-蛋白质之间的相互作用的疟疾寄生虫恶性疟原虫和RBC蛋白质的网络。新的酵母菌株，改进的酵母双杂交筛选方法和两种互补的酵母双杂交筛选方法的组合将用于创建高质量的疟疾-RBC蛋白相互作用网络。相互作用将通过GST唐斯和分裂荧光素酶试验进行验证，我们在本项目中开发了高通量分析酵母中蛋白质-蛋白质相互作用的方法。从这些数据中，我们将为每个交互制定一个置信度评分。然后将疟疾-RBC蛋白质相互作用与现有的基因表达数据整合，以开发疟疾-RBC相互作用组的时间依赖性视图。使用我们的模型的结果作为指导，我们将调查时间上不同的疟疾红细胞蛋白相互作用的功能，使用重新密封的红细胞鬼和ektacytometry。该项目在研究疟疾-RBC蛋白相互作用网络的技术应用和开发方面具有创新性。该项目产生的数据不仅与我们对相互作用组动力学的理解有关，而且还与了解疟疾寄生虫如何引起疾病有关。

DESCRIPTION (provided by applicant): Cellular proteins form complex networks of interactions with other proteins. Although it is clear that these networks are dynamic structures that change in response to environmental signals and that are altered in disease states, our ability to assess the temporal changes in the networks is still at an early stage. Malaria-infected RBCs are a simple model in which to study changes in protein interaction networks over time. RBCs are highly differentiated cells that lack organelles and that contain a limited set of proteins. During infection, malaria parasites export proteins into the RBC that dramatically alter the properties of the host cell. Because RBCs lack nuclei, and thus cannot respond to parasite infection by altering their protein content, the changes that occur in the RBC phenotype must be due to the approximately 300 malaria proteins that are exported into the RBC. The exported malaria proteins are thought to bind to RBC proteins and, in this way, act as lesions that cause perturbations in the cellular protein interaction network. Since detailed information about the timing of expression of most malaria genes is already available, we can model changes in the cellular protein interaction network over time and correlate those temporal changes in the malaria-RBC interactome with changes in cellular properties. However, functional information about these malaria proteins is scarce and only a very limited number of interactions between exported malaria proteins and RBC proteins have been reported. The overall goal of this research is to elucidate, validate, and temporally model the network of protein-protein interactions between the malaria parasite Plasmodium falciparum and RBC proteins. A combination of new yeast strains, improved yeast two-hybrid screening methodology, and two complementary yeast two-hybrid screening approaches will be used to create a high-quality malaria-RBC protein interaction network. Interactions will be validated by GST pull downs and the split-luciferase assay, which we develop in this project for high-throughput analysis of protein-protein interactions in yeast. From this data we will develop a confidence score for each interaction. The malaria-RBC protein interactions will then be integrated with existing gene expression data to develop a time-dependent view of the malaria-RBC interactome. Using the results of our model as a guide, we will investigate the function of temporally distinct malaria-RBC protein interactions using the resealed RBC ghosts and ektacytometry. This project is innovative in its application and development of technologies to study the malaria-RBC protein interaction network. The data generated from this project is relevant not only to our understanding of interactome dynamics but also for understanding how malaria parasites cause disease.