Mathematical Modeling of the Arabidopsis Defense Signaling Network

拟南芥防御信号网络的数学建模

• 批准号: 0918908
• 负责人: Fumiaki Katagiri
• 金额: $ 75.52万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2014-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0918908&HistoricalAwards=false
• 关键词: Mathematical; Modeling; Arabidopsis; Defense; Signaling

Many plant defense reactions against pathogens are inducible. Plant recognition mechanisms detect pathogens and initiate signaling mechanisms that in turn activate plant defenses. One mode of recognition detects molecules that are common to particular classes of pathogens (called microbe-associated molecular patterns, MAMPs). The signal triggered by a MAMP is relayed through a complex network of signaling molecules, many of which are proteins. The goal of this research is to elucidate how the signaling network is organized and how the signal flows through the network during MAMP-induced disease resistance. The response of Arabidopsis thaliana to a bacterial pathogen will be analyzed using a combination of 3 approaches: 1) experimental deletion of specific combinations of the network components; 2) the collection of information about the signaling process from many points of the network, and 3) computer modeling of the signaling network. This approach is designed to broaden our understanding about the behavior of complex signaling networks in general and also allow exploration of the conditions that can substantially change the behavior of the plant defense network.Broader impacts: This project will build an interdisciplinary research team working to model biological signaling networks. It will provide interdisciplinary training at the interface of biology and computer science to undergraduate students and to a post-doctoral fellow and a Ph.D. student. Outreach programs will engage faculty and students from undergraduate institutions to participate in the project. The project will also provide summer research experiences for high school teachers, through existing and newly-developed programs.

许多植物对病原体的防御反应是可诱导的。植物识别机制检测病原体并启动信号传导机制，进而激活植物防御。 一种识别模式检测特定类别病原体所共有的分子（称为微生物相关分子模式，MAMP）。 由MAMP触发的信号通过复杂的信号分子网络传递，其中许多是蛋白质。 本研究的目的是阐明MAMP诱导的抗病性过程中信号网络是如何组织的以及信号如何通过网络流动。拟南芥对细菌病原体的反应将使用3种方法的组合进行分析：1）实验删除网络组件的特定组合; 2）从网络的许多点收集有关信号传导过程的信息; 3）信号传导网络的计算机建模。 本研究的目的是拓宽我们对复杂信号网络行为的理解，并探索能够显著改变植物防御网络行为的条件。更广泛的影响：本研究将建立一个跨学科的研究团队，致力于模拟生物信号网络。 它将在生物学和计算机科学的界面上为本科生和一名博士后研究员和一名博士提供跨学科培训。学生. 外联方案将吸引本科院校的教师和学生参与该项目。 该项目还将通过现有和新开发的项目为高中教师提供暑期研究经验。