Chemogenomic Analysis of E. coli Response to NO species

描述（由申请人提供）：本申请的目标是开发用于重建细菌中的信号传导和转录网络的化学基因组分析方法。特别是，大肠杆菌反应活性氮氧化物物种（RNOS），如一氧化氮和S-亚硝基硫醇，将被用作模型系统。而不是仅仅依赖于关联关系，这并不揭示信号传导机制的化学细节，拟议的研究将开发一个范式，将化学反应性信息纳入E.杆菌由此产生的网络将是机械可行的，并与基因表达数据一致。所提出的方法包括通过三个部分的迭代：转录组测量，网络成分分析（NCA），和化学信息分析。本研究从野生型E. coli对RNOS的反应和来自文献数据库的初始转录因子（TF）-启动子连接性，这对于感兴趣的条件是不完整的。NCA首先基于野生型微阵列数据推断TF在RNOS挑战下的活性。转录因子的活性，而不是表达水平，为推断化学机制和信号通路提供了关键信息。在受干扰的TF中，化学信息分析允许将受影响的TF分类为直接和间接靶标，并鉴定用于信号传导的潜在化学机制。然后使用染色体敲除技术删除受干扰的TF。进一步测试所得敲除菌株对RNOS的响应，并在NCA中分析转录组数据以推断修订的靶TF和转录网络。如果预测到新的TF目标，则迭代继续。此外，预测的网络使用遗传和生化实验进行验证。

DESCRIPTION (provided by applicant): The goal of this application is to develop a chemo genomic analysis methodology for reconstructing signaling and transcription networks in bacteria. In particular, Escherichia coli responses to reactive nitrogen oxide species (RNOS), such as nitric oxide and S-nitrosothiols, will be used as a model system. Instead of relying solely on association relationships, which does not reveal chemical details of signaling mechanisms, the proposed research will develop a paradigm to incorporate chemical reactivity information in the transcriptomic analysis of E. coli. The resulting network will be mechanistically feasible and consistent with gene expression data. The proposed approach consists of iteration through three components: transcriptome measurements, Network Component Analysis (NCA), and chemoinfomatic analysis. The investigation starts from micro array experiments of wild-type E. coli response to RNOS and the initial transcription factor (TF)-promoter connectivity from the literature database, which is incomplete for the conditions of interest. NCA first deduces the activities of TF upon RNOS challenge based on wild-type micro array data. The activities of TFs, rather than the expression levels, provide critical information for deducing chemical mechanisms and signaling pathways. Among the TFs perturbed, chemoinfomatic analysis allows the classification of affected TFs into direct and indirect targets and the identification of potential chemical mechanisms for signaling. The perturbed TFs are then deleted using chromosomal knockout techniques. The resulting knockout strains are further tested for responses to RNOS and the transcriptome data are analyzed in NCA to deduce revised target TFs and transcription networks. If hew TF targets are predicted, then the iteration continues. Otherwise, the predicted networks are verified using genetic and biochemical experiments.