Systems Biology of Plasmodium falciparum: Building and Exploring Network Models

描述(由申请人提供)：由于疟原虫对现有药物的抗药性日益增强，迫切需要新的抗疟疾干预措施。我们研究的长期目标是使用一种高效和具有成本效益的数据挖掘方法来确定潜在的药物或疫苗目标。这项拟议的研究旨在识别生物网络，作为从系统层面理解寄生虫生物学的第一步。与功能基因组学相比，功能基因组学需要关于靶标身份或功能的先验信息，而对寄生虫生物学的系统水平理解将使我们能够根据靶标在网络中的关键作用来识别靶标。具体目标1集中于收集与三个基因家族相关的数据：蛋白酶、转运蛋白和转录因子，它们是寄生虫生长和感染的细胞网络中的重要组成部分。我们的项目将包括基因组数据、表达数据以及来自其他高通量实验和生物信息学和统计分析的数据。具体目标2侧重于以网络模型的形式集成和封装这些数据。这些模型将使用从工程领域提取的概率图形方法来推断。具体目标3侧重于探索这些模型，特别是根据湿法实验室基因图谱和耐药性实验的数据。我们的“生物图谱”将使推动寄生虫表型变化的进化力量可视化，并使我们能够识别寄生虫中的网络设计弱点--可能导致新的疟疾控制策略的潜在弱点。

DESCRIPTION (provided by applicant): There is an urgent need for novel anti-malaria interventions, due to the growing resistance of Plasmodium parasites to available drugs. The long-term objective of our research is to identify potential drug or vaccine targets using an efficient and cost-effective data-mining approach. This proposed study is aimed at the identification of biological networks as the first step toward a systems-level understanding of parasite biology. Compared to functional genomics, which requires a priori information about the identity or function of targets, a systems-level understanding of parasite biology will allow us to identify targets based on their key roles in networks. Specific aim 1 focuses on the harvest of data relevant to three gene families: the proteases, transporters, and transcription factors that are essential components in cellular networks for parasite growth and infection. Our project will encompass genomic data, expression data, and data derived from other high throughput experiments and bioinformatic and statistical analyses. Specific aim 2 focuses on the integration and encapsulation of these data in the form of network models. The models will be inferred using probabilistic graphical methods drawn from the field of engineering. Specific aim 3 focuses on the exploration of these models, particularly in the light of data from wet lab gene mapping and drug resistance experiments. Our "biological maps" will enable the visualization of evolutionary forces driving changes in the parasite's phenotype and should allow us to identify network design weaknesses in the parasite--potential vulnerabilities that could result in new malarial control strategies.