Integrative quantitative understanding of a dynamic protein interaction network

Plant growth strongly relies on the signalling molecule auxin, which regulates various developmental processes by controlling gene expression through a short pathway involving three dedicated protein families. While the function of individual response proteins is well understood, a major unanswered question is how interactions among those proteins generate a dynamic response system with diverse outputs. Thus far, auxin response has been studied mostly in Arabidopsis thaliana, particularly within the response protein families. Several members of these families have been studied in detail, however, there is little quantitative information of these response proteins and only a qualitative view of its dynamic system. In this project, we will generate the first integrative, quantitative view on the auxin response network. We will use the liverwort Marchantia polymorpha, an early diverging land plant that has the simplest possible complete auxin system. We will resolve all relevant quantitative parameters including concentrations of each response protein in the live organism, protein turnover rates and dissociation constants of all protein-protein interactions. We will use a combination of Marchantia genetics and advanced fluorescence spectroscopic methods and integrate all parameters into a mathematical model. This model will identify critical factors within the protein network that affect signal output. Subsequently, we will test model predictions by modifying protein levels or interaction affinities in Marchantia, and address effects on response output through quantification of RNA levels of specific target genes. We expect this project to reveal principles of dynamic auxin response, thus providing a quantitative framework for plant hormone biology.