Building a protein-interaction network to study Fusarium graminearum pathogenesis

Abstract

Protein interaction networks provide invaluable information on the complexity of biological pathways within organisms. They not only allow for key proteins to be identified within the network but also allow us to identify groups of closely associated proteins with common biological functions. These properties allow for a better understanding of the protein organization in a cell, and the specific interactions within individual biological processes provide a tool to predict functions of unknown proteins. Given the significant amount of time and cost associated with producing protein interaction networks, the majority of them have been generated for model organisms. For other organisms, protein interactions are predicted based on previously existing networks using Interolog and large-scale gene expression databases. Although these predicted networks are valuable, they can only provide information on proteins shared across species, such as those responsible for primary metabolism. As such, networks of unique secondary metabolism pathways, such as the biosynthesis of deoxynivalenol (DON) in Fusarium graminearum, cannot be extrapolated using existing resources in other organisms. Therefore, we propose a Fusarium Network of Trichothecene Associated Proteins (FuNTAP) based on yeast two-hybrid interactions of proteins that are differentially expressed under DON inducing conditions. FuNTAP should allow a characterization of the metabolic pathway by which this important metabolite is synthesized without recourse to predictions based on earlier model interactomes.