A temporal view of the Plasmodium-red blood cell interactome

疟原虫-红细胞相互作用组的时间视图

• 批准号: 8282783
• 负责人: Douglas J. LaCount
• 金额: $ 28.39万
• 依托单位: PURDUE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-06-15 至 2014-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8282783
• 关键词: Address; Binding; Biological Assay; Biology; Bone Marrow; Cell Nucleus; Cell membrane; Cell physiology; Cells; Complex; Computer Simulation; Cytoplasm; Cytoskeletal Proteins; Cytoskeleton; Data; Development; Disease; Erythrocytes; Escherichia coli; Gene Expression; Gene Proteins; Genes; Glutathione S-Transferase; Goals; Human; Infection; Lesion; Libraries; Life Cycle Stages; Luciferases; Malaria; Methodology; Modeling; Morphology; Organelles; Parasites; Phenotype; Plasmodium; Plasmodium falciparum; Property; Protein Dynamics; Protein Export Pathway; Proteins; Proteome; RNA Interference; Reporting; Research; Screening procedure; Series; Set protein; Signal Transduction; Source; Staging; Structure; System; Testing; Time; Yeasts; experience; high throughput analysis; improved; innovation; link protein; network models; physical property; protein protein interaction; public health relevance; research study; response; technology development; tool; vector; yeast two hybrid system

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. PUBLIC HEALTH RELEVANCE: Proteins are linked to each other by a complex network of interactions. To better understand how these networks change over time and in disease states, we will develop a temporal model of protein- protein interactions in malaria-infected red blood cells. This data is generally relevant to our understanding of cellular processes and specifically relevant to how malaria parasites cause disease.

描述（由申请人提供）：细胞蛋白质形成与其他蛋白质相互作用的复杂网络。虽然很明显，这些网络是动态结构，会根据环境信号发生变化，并在疾病状态下发生改变，但我们评估网络中时间变化的能力仍处于早期阶段。疟疾感染的红细胞是一个简单的模型，用于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，含有一组有限的蛋白质。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，因此红细胞表型发生的变化一定是由于大约300种疟疾蛋白输出到红细胞中。输出的疟疾蛋白被认为与红细胞蛋白结合，并以这种方式作为损害，引起细胞蛋白相互作用网络的扰动。由于大多数疟疾基因表达时间的详细信息已经获得，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-红细胞相互作用组的这些时间变化与细胞特性的变化联系起来。然而，关于这些疟疾蛋白的功能信息很少，只有非常有限数量的输出疟疾蛋白和红细胞蛋白之间的相互作用被报道。本研究的总体目标是阐明、验证和暂时模拟疟疾寄生虫恶性疟原虫和红细胞蛋白之间的蛋白-蛋白相互作用网络。结合新的酵母菌株，改进的酵母双杂交筛选方法，以及两种互补的酵母双杂交筛选方法，将用于创建一个高质量的疟疾-红细胞蛋白相互作用网络。相互作用将通过GST拉下和分裂荧光素酶实验来验证，我们在这个项目中开发了用于酵母中蛋白质-蛋白质相互作用的高通量分析。根据这些数据，我们将为每个交互建立一个置信度评分。然后，疟疾-红细胞蛋白相互作用将与现有的基因表达数据相结合，以开发疟疾-红细胞相互作用组的时间依赖性视图。以我们的模型结果为指导，我们将使用重新密封的红细胞幽灵和细胞计数法研究时间上不同的疟疾-红细胞蛋白相互作用的功能。本项目在研究疟疾-红细胞蛋白相互作用网络的应用和技术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动力学的理解有关，而且与了解疟疾寄生虫如何引起疾病有关。