Host-Pathogen Interaction Network Learning from In Vivo Gene Co-Expression

描述（由申请人提供）：第一阶段的目标是建立一个新的系统生物学软件工具的原型，用于从同时测量宿主-病原体基因表达的体内实验中识别可能的宿主-病原体蛋白质-蛋白质相互作用（PPI）关系和网络。识别这种相互作用的计算方法是一个重要的尚未解决的问题。同时测量宿主-病原体基因和蛋白质表达的新方法正在出现。这些方法产生了大量的数据，并且增加了无法手工处理的分析复杂性。新的系统生物学计算技术将是必不可少的，以帮助其分析。拥有鉴定宿主-病原体PPI关系的新工具将显著推进我们对免疫机制的理解，并对鉴定新的免疫治疗药物、佐剂和疫苗的潜在靶点/生物标志物具有重要意义。这对于NIAID A、B、C类重点病原体和其他高度关注的常见病来说是极其重要的知识。可行性将通过宿主和病原体微阵列以及受到伤寒沙门氏菌（野生型伤寒沙门氏菌）和等基因sipA， sopABDE2突变体攻击的牛动物模型的蛋白质组学数据进行验证。数据将由德克萨斯A&M国家外来动物和人畜共患疾病防御中心的合作者提供给Seralogix。公共卫生相关性：本文提出的新的系统生物学计算技术将有助于分析复杂的宿主-病原体相互作用。拥有鉴定宿主-病原体蛋白-蛋白关系的新工具将大大促进我们对免疫机制的理解，并对鉴定新的免疫治疗药物、佐剂和疫苗的潜在靶点/生物标志物具有重要意义。

DESCRIPTION (provided by applicant): The Phase I objective is to prototype a new systems biology software tool to identifying probable host-pathogen protein-protein interactive (PPI) relationships and networks from in vivo experiments where host-pathogen gene expressions are measured simultaneously. Computational methods for identifying such interactions are an important unsolved problem. New methods are emerging for simultaneous host-pathogen measurement of gene and protein expression. Tremendous amounts of data are generated from these methods and represent an increased analysis complexity that cannot be dealt with manually. New system biology computational techniques will be essential to aid in its analysis. Having new tools for identifying host-pathogen PPI relationships will significantly advance our understanding of immunologic mechanisms and has great implications in identifying potential targets/biomarkers for new immunotherapeutic drugs, adjuvants, and vaccines. This is extremely important knowledge for NIAID Category A, B and C priority pathogens and other common diseases of high concern. Proof-of-feasibility will be done using host and pathogen microarray and proteomic data from a bovine animal model challenged by Salmonella enterica Serovar Typhimurium (wild type S. Typhimurium) and an isogenic sipA, sopABDE2 mutant. Data will be provided to Seralogix by collaborators at Texas A&M National Center for Foreign Animal and Zoonotic Disease Defense. PUBLIC HEALTH RELEVANCE: The new system biology computational techniques, proposed herein, will be essential to aid in the analysis of complex host-pathogen interactions. Having new tools for identifying host-pathogen protein- protein relationships will significantly advance our understanding of immunologic mechanisms and has great implications in identifying potential targets/biomarkers for new immunotherapeutic drugs, adjuvants, and vaccines.