Deciphering the network structure of signaling dynamics

项目摘要/摘要 涉及RAS GTP酶及其下游效应因子的信号网络，特别是 PI3K和MAPK/ERK通路在不同的细胞过程中发挥重要作用，包括 增殖、新陈代谢、迁移和生存。信令网络导联的错位 到发育异常、代谢紊乱和癌症等疾病。尽管它的 临床重要性，以RAS信号网络为目标的疾病治疗 由于对其复杂的监管不完全理解，这是一个具有挑战性的问题。近几年来的研究成果 单细胞水平的RAS信号动力学显示了令人着迷的特性， 功能含义。特别是，我们演示了RAS信令网络显示 可兴奋系统的特征，如随机激活、行波和全有或全无 激活。Ras-PI3K-ERK信号网络的兴奋性在细胞内起着重要作用 调节细胞增殖的化学和机械刺激的运动和整合。 然而，编码可兴奋动态的RAS信令网络的整体结构 是未知的。本应用程序的目的是分析RAS信令的结构 通过系统地扰动单个节点并研究其对兴奋性的影响来构建网络 网络的动态。为此，我们将开发一种基于荧光活细胞的方法 成像以同时跟踪大量的信号活动。我们将使用此方法 要监测~30个信号活动的兴奋性反应，当每个活动 被药物抑制了。扰动的影响将提供对监管的洞察 信号活动之间的关系。我们还将对不同的公司进行网络分析 了解细胞类型对小分子抑制剂的不同反应的基础。这些 研究将为包含足够的网络细节的量化模型铺平道路 对细胞反应做出准确的预测。

Project Summary/Abstract The signaling network involving Ras GTPases and their downstream effectors, particularly the PI3K and MAPK/ERK pathways, plays important roles in diverse cellular processes including proliferation, metabolism, migration, and survival. Derangements of the signaling network leads to diseases such as developmental anomalies, metabolic disorders, and cancer. Despite its clinical importance, targeting the Ras signaling network for disease treatment has been challenging due to an incomplete understanding of its complex regulation. Recent studies of the Ras signaling dynamics at the single-cell level revealed fascinating properties with important functional implications. In particular, we demonstrated that the Ras signaling network displays hallmarks of excitable systems such as stochastic activation, traveling waves, and all-or-none activation. The excitability of the Ras-PI3K-ERK signaling network plays important roles in cell motility and integration of chemical and mechanical stimuli that regulate cell proliferation. However, the overall structure of the Ras signaling network that encodes the excitable dynamics is not known. The purpose of this application is to analyze the structure of the Ras signaling network by systematically perturbing individual nodes and studying the effects on the excitable dynamics of the network. To this end we will develop a method based on fluorescent live cell imaging to simultaneously track a large number of signaling activities. We will use this method to monitor the excitable responses of ~30 signaling activities when each activity is pharmacologically inhibited. The effects of perturbations will provide insight into the regulatory relationship between the signaling activities. We will also carry out network analysis on different cell types to understand the basis of their distinct responses to small molecule inhibitors. These studies will pave the way for quantitative models containing sufficient details of the network to make accurate predictions of cellular responses.