Mathematical Modeling of the Arabidopsis Defense Signaling Network

University Of Minnesota-Twin Cities, Minneapolis MN

Investigators

Abstract

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.