Combinatorial Exploration of Cellular Regulatory Network Design Principles

描述（申请人提供）：细胞调控网络设计原理的组合探索 系统生物学的一个主要目标是了解细胞如何使用分子电路来实现复杂的生理行为，以及这些行为如何在癌症等疾病状态下分解。虽然只有一小部分现有的网络已经得到了很好的表征，经常性的拓扑结构已经出现了各种生物功能，这表明任何特定的行为是由有限数量的网络结构编码。为了快速识别目标行为的结构“解决方案”，我们建议开发一种筛选分子电路组合库的合成生物（正向工程）方法。我的具体目标是：1）开发组装组合电路库的方法。 作为一个试验平台，我们将构建一个酵母交配途径中的合成正反馈环库，并筛选这些记忆行为。 2)开发一个屏幕为一个复杂的动态行为感官适应。 将开发一种基于重组的流式细胞仪测定法，以筛选可以对刺激产生瞬时反应，但随后尽管受到持续刺激仍自动重置输出的细胞。 功能电路架构的比较，预计将揭示全球的设计原则，关键的网络拓扑结构和参数，和强大的结构图案，提供一个定量的蓝图，核心电路家庭能够每个目标任务。这种分析应该为如何构建实现记忆和适应的复杂电路提供基本的见解。从长远来看，新兴的网络结构和功能相关地图将指导生物系统的解释、治疗干扰和合理合成。 公共卫生相关性：细胞使用由相互作用的蛋白质组成的分子通信网络来感知和响应其环境。包括癌症在内的许多疾病都是在信号蛋白的改变改变了网络的结构，导致新的细胞行为时发生的。我们的目标是生成一个网络结构和功能相关的地图，以指导对复杂生物系统的理解和治疗纠正。

DESCRIPTION (provided by applicant): Combinatorial Exploration of Cellular Regulatory Network Design Principles A major goal in systems biology is to understand how cells use molecular circuits to achieve complex physiological behaviors and how these behaviors break down in disease states like cancer. Although only a small fraction of existing networks have been well characterized, recurrent topologies have emerged for a variety of biological functions, suggesting that any particular behavior is encoded by a limited number of network structures. With the goal of rapidly identifying the structural 'solutions' for target behaviors, we propose to develop a synthetic biological (forward engineering) approach of screening combinatorial libraries of molecular circuits. My specific aims are to: 1) Develop methods to assemble combinatorial circuit libraries. As a testbed we will construct a library of synthetic positive feedback loops in the yeast mating pathway and screen these for memory behavior. 2) Develop a screen for a complex dynamic behavior-sensory adaptation. A recombination-based FACS assay will be developed to screen for cells that can transiently respond to a stimulus, but then automatically reset output despite sustained stimulus. Comparison of functional circuit architectures is expected to reveal global design principles-critical network topologies and parameters, and robust structural motifs-providing a quantitative blueprint for core circuit families capable of each target task. This analysis should provide fundamental insight into how complex circuits that achieve memory and adaptation can be built. In the long-term, the emerging map correlating network structure and function will guide the interpretation, therapeutic perturbation, and rational synthesis of biological systems. PUBLIC HEALTH RELEVANCE: Cells sense and respond to their environment using a molecular communication network composed of interacting proteins. Many diseases, including cancer, arise when alteration of a signaling protein changes the network's structure, resulting in a new cellular behavior. Our goal is to generate a map correlating network structure and function that will guide the understanding and therapeutic correction of complex biological systems.