Network Topology in Cell Signaling

细胞信号传导中的网络拓扑

• 批准号: 7393767
• 负责人: NORBERT PERRIMON
• 金额: $ 26.9万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-04-15 至 2009-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7393767
• 关键词: Algorithms; Animals; Applications Grants; Back; Biochemical; Biological; Biological Assay; Case Study; Cell Line; Cell Nucleus; Cell physiology; Cell surface; Cells; Classification; Co-Immunoprecipitations; Complementary DNA; Complex; Cues; Custom; Data; Development; Diabetes Mellitus; Disease; Disruption; Doctor of Philosophy; Double-Stranded RNA; Drosophila genus; Drug Delivery Systems; EGF gene; Enhancers; Epidermal Growth Factor Receptor; Event; Gene Expression; Gene Expression Profiling; Gene Silencing; Genes; Genetic; Goals; In Vitro; Insulin; Insulin Resistance; Internet; Knowledge; Ligands; Link; Liquid substance; Maps; Mass Spectrum Analysis; Measures; Mediating; Methodology; Methods; Modeling; Molecular; Molecular Profiling; Nature; Numbers; Pathway interactions; Phosphoric Monoester Hydrolases; Phosphorylation; Phosphotransferases; Physiological; Physiology; Plant Roots; Probability; Process; Protein Dephosphorylation; Protein Kinase; Proteins; Purpose; RNA Interference; Regulation; Reproducibility; Research Personnel; Rest; Score; Signal Pathway; Signal Transduction; Signal Transduction Pathway; Specificity; Structure; System; Thinking; Time; Tissues; Transgenic Organisms; Validation; Whole Organism; base; cell type; computational network modeling; computerized tools; feeding; gain of function; in vivo; insight; insulin signaling; interest; loss of function; mutant; network models; novel; novel strategies; programs; protein protein interaction; response; tissue/cell culture; tool

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.

描述(申请人提供)：信号通路通常被认为是可分离的模块，沿着线性通道传输信号，导致对离散细胞功能的调节。事实上，对动物发育的研究经常考虑如何处理来自独立信号通路的贡献，以创造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是独立的、相互作用最小的“模块”，仍然是一个有争议的问题。支持这一拨款提议的假设是，信号通路比之前认为的更相互联系，并嵌入复杂的网络中。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，以产生一个全面的连接组件网络，该网络基于与RNA干扰(RNAi)减少这些组件相关的转录反应。对于我们来说，胰岛素信号系统是一个理想的案例研究。胰岛素抵抗是迟发性糖尿病的根本原因，可能是由于胰岛素信号转导不完全依赖于某些成分而引起的。因此，破译胰岛素信号网络以及胰岛素途径与其他途径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网络的蛋白激酶和磷酸酶(PPase)成分上，这些成分在生物化学上相关，并作为药物靶标引起了极大的兴趣。这个网络将通过使用基因特异性dsRNA连续干扰在果蝇SL2细胞系中表达的261个Kinase和PPase来构建。在静息状态下或在胰岛素或EGF(Spitz)刺激之后，将使用微阵列表达谱来确定转录签名。计算网络建模算法将被用于将基因表达谱转换为网络连通性。新连接的分子性质将在体内得到验证，并使用生化分析进行表征。总之，这些研究将极大地促进我们对信号网络及其在信号转导过程中的组织的了解。