Network Topology in Cell Signaling

描述（由申请人提供）：信号通路通常被认为是可分离的模块，沿着线性束传递信号，导致离散细胞功能的调节。事实上，动物发育研究经常考虑如何处理来自独立信号通路的贡献，以产生不同的细胞类型和组织。然而，信号通路在多大程度上实际上作为独立的最小相互作用的“模块”起作用仍然是一个有争议的问题。支持这项拨款提案的假设是，信号通路比以前认为的更加相互关联，并且嵌入在复杂的网络中。为了分析信号转导通路的独立性或“模块化”水平，我们建议将重点放在果蝇组织培养细胞中的胰岛素信号转导上，以基于RNA干扰（RNAi）减少这些成分的转录反应生成一个综合的连接成分网络。胰岛素信号系统是一个理想的研究案例。胰岛素抵抗是迟发性糖尿病的根本原因，它可能是由不完全与胰岛素信号有关的成分的失调引起的。因此，破译胰岛素信号网络以及胰岛素通路与其他通路之间的串扰性质对于理解胰岛素抵抗的病理生理学至关重要。我们选择将我们的分析限制在蛋白激酶和磷酸酶（PPase）网络的组成部分，它们是生物化学相关的，并且作为药物靶点非常有趣。该网络将通过使用基因特异性dsRNAs，依次干扰果蝇SL2细胞系中表达的261激酶和PPase来构建。转录特征将在静息状态或胰岛素或EGF （Spitz）刺激后使用微阵列表达谱来确定。计算网络建模算法将用于将基因表达谱转换为网络连接。新连接的分子性质将在体内验证并使用生化分析表征。总之，这些研究将大大提高我们对信号网络及其在信号转导过程中的组织的认识。

DESCRIPTION (provided by applicant): Signaling pathways are often thought of as separable modules, transmitting signals along linear tracts resulting in the regulation of discrete cell functions. Indeed, studies of animal development often consider how contributions from independent signaling pathways are processed to create distinct cell types and tissues. However, the extent to which signaling pathways actually function as independent minimally interacting "modules" is still a matter of debate. The hypothesis underpinning this grant proposal is that signaling pathways are much more interconnected than previously thought and are embedded in complex networks. To analyze the level of independence, or "modularity", of signal transduction pathways, we propose to focus on Insulin signaling in Drosophila tissue culture cells to generate a comprehensive network of connected components based on transcriptional responses associated with the reduction of those components by RNA interference (RNAi). The Insulin signaling system is an ideal case study for our purpose. Insulin resistance, the root cause of late onset diabetes, can be caused by deregulation of components that are not solely devoted to Insulin signaling. Thus, deciphering the Insulin signaling network and the nature of cross-talk between the Insulin pathway and other pathways will be critical to understanding the patho-physiology of Insulin resistance. We have chosen to restrict our analysis to the Protein Kinase and Phosphatase (PPase) components of the network, which are biochemically related and of great interest as drug targets. The network will be built by successively perturbing, using gene-specific dsRNAs, each of the 261 Kinase and PPase that are expressed in the Drosophila SL2 cell line. The transcriptional signature will be ascertained using microarray expression profiling either in the resting state or following Insulin or EGF (Spitz) stimulation. Computational network-modeling algorithms will be used to convert gene expression profiles into network connectivities. The molecular nature of novel connections will be validated in vivo and characterized using biochemical assays. Altogether, these studies will greatly advance our knowledge of signaling networks and their organization during signal transduction.