Genetic Analysis of Salmonella Typhimurium Virulence

描述(由申请人提供)：使RPG能够利用NCRR中心和类似中心的计划(非-OD-09-058恢复法案资金用于竞争性修订申请)。这项拟议研究的目标是开始了解巨噬细胞如何对沙门氏菌感染做出反应，以及沙门氏菌毒力因子如何改变这种反应。我们将用亲本14028和同基因衍生物感染细胞，要么缺少特定的毒力调节因子，要么完全缺少III型分泌，并比较感染细胞的转录组、蛋白质组和磷蛋白质组的差异。一般来说，调控突变体表达与亲本相同的病原菌相关分子模式，但在分泌的蛋白质和其他毒力因子方面有所不同，其中一些尚未确定。三重突变体Spi-1/Spi-2/flgB不表达III型分泌效应物。这项实验将使对病原体相关分子模式的反应与改变或破坏巨噬细胞信号转导途径表达的毒力因子的表达之间有明显的区别。我们将使用一种新的交联和亲和纯化方法来鉴定特定分泌型效应器的目标蛋白。我们将使用生物信息学进行解释，包括在基因表达数据中寻找因果影响模式的网络推理算法，以及为重建哺乳动物细胞中的基因调控网络而开发的算法(MarGolin等人，2006年)。将包括来自几个来源的路径信息(例如，NCI-自然路径互动数据库(Schaefer等人，2009年))。这一分析将有助于确定沙门氏菌如何通过颠覆特定的宿主功能在宿主内生存。 公共卫生相关性：这项应用的目标是开始了解宿主细胞如何对感染做出反应。人体对感染的反应是由所有细菌上的分子模式决定的，这些细菌是由身体的天然免疫系统感知的。反过来，细菌通过产生毒力因子来阻止宿主的防御机制来保护自己。缺少特定毒力因子的沙门氏菌突变将被用来通过比较宿主细胞在多个水平上的变化来评估这些相同的毒力因子如何改变宿主反应。

DESCRIPTION (provided by applicant): Enabling RPGs to Leverage NCRR Center and Center-like Programs (NOT-OD-09-058 Recovery Act Funds for Competitive Revision Applications). The goal of this proposed research is to begin to understand how a macrophage responds to Salmonella infection and how Salmonella virulence factors alter that response. We will infect cells with the parent 14028 and isogenic derivatives either missing specific virulence regulators or missing type III secretion altogether and compare differences in the transcriptome, proteome and phosphoproteome of the infected cell. In general the regulator mutants will express the same pathogen associated molecular patterns as the parent but differ in the proteins secreted as well as other virulence factors some of which are not yet defined. The triple mutant SPI-1/SPI-2/flgB will express no type III secreted effectors. This experiment will allow a clear distinction to be made between response to pathogen associated molecular patterns and expression of virulence factors that modify or disrupt expression of macrophage signal transduction pathways. We will use a new cross-linking and affinity purification approach to identify the target protein of a given secreted effector. We will use bioinformatics for interpretation including network inference algorithms to look for patterns of causal influence in gene expression data and an algorithm developed for the reconstruction of gene regulatory networks in mammalian cells (Margolin et al., 2006). Pathway information from several sources will be included (e.g. NCI-Nature Pathway Interaction Database (Schaefer et al., 2009). This analysis will help define how Salmonella is able to survive within the host by subverting particular host functions. PUBLIC HEALTH RELEVANCE: The goal of this application is to begin to understand how a host cell responds to infection. Response of the body to infection is determined by molecular patterns on all bacteria that are sensed by the body's innate immune system. In turn, the bacteria defends itself by producing virulence factors to block host defense mechanisms. Salmonella mutations that are missing specific virulence factors will be used to assess how these same virulence factors alter host response by comparing changes in the host cell at multiple levels.