Deciphering the network structure of signaling dynamics

项目总结/摘要 涉及Ras GTP酶及其下游效应物的信号网络，特别是 PI 3 K和MAPK/ERK通路在多种细胞过程中发挥重要作用，包括 增殖、代谢、迁移和存活。信号网络引线的紊乱 发育异常、代谢紊乱和癌症等疾病。尽管 临床上的重要性，靶向Ras信号网络用于疾病治疗一直是 由于对其复杂规则的不完全理解而具有挑战性。最近的研究 Ras信号在单细胞水平的动力学揭示了迷人的特性， 功能影响。特别是，我们证明了Ras信号网络显示 可激发系统的特征，如随机激活、行波和全有或全无 activation. Ras-PI 3 K-ERK信号网络的兴奋性在细胞内的信号转导中起着重要作用， 调节细胞增殖的化学和机械刺激的运动性和整合。 然而，编码可兴奋动力学的Ras信号网络的整体结构 不知道。本申请的目的是分析Ras信号的结构 通过系统地扰动单个节点并研究对可兴奋网络的影响， 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信号传导活动。我们将使用这种方法 监测约30个信号活动的兴奋反应，当每个活动是 很压抑。扰动的影响将提供对监管的洞察力 信号活动之间的关系。我们还将对不同的 细胞类型，以了解它们对小分子抑制剂的不同反应的基础。这些 研究将为包含网络足够细节的定量模型铺平道路， 准确预测细胞反应。

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.