Uncovering Novel Signaling Interactions in Plant Metabolic Networks

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The factors that regulate composition in plants provide a key to utilization of crops for production of improved and novel constituents. Starch, an easily accessible and energy-cheap storage of reduced carbon, is formed via photosynthesis- that is, using solar power. However, little is known about the molecular mechanisms of this process. This research focuses on expanding the understanding of the molecular processes, or network that controls the amount of starch in plants.The objective of this research is to identify new genes and mechanisms that impact starch content in Arabidopsis leaves. The hypothesis is that an as-yet-unidentified gene set interacts with a novel signaling mechanism that affects starch biosynthesis. The aim is to broaden the starch regulatory network by identifying functions for a group of previously uncharacterized proteins that impact this network. The specific aims of this project are:Aim 1. Analyze genes that are candidates in the starch network. By examining the starch content and other constituents in mutants for genes provides an approach to determine the role of each gene. Aim 2. Refine and expand the starch transcriptional network. Data from experiments of Aim 1 will be analyzed by statistical methods and a novel combination of network analysis and genetic algorithms in the context of the known starch network. These studies will reveal how selected perturbations in the starch network effect the accumulation of starch and the health of the plant, and will generate experimentally-testable hypotheses about which genes participate in the network. Aim 3. Identify proteins that interact with known or candidate proteins of the starch network. Much regulation of the composition in a living organism is achieved by formation of complexes among specific proteins. This can activate or deactivate particular processes. Computational methods will be used to predict from a protein?s sequence and structure what other proteins it might bind to. By using experimental methods, we will test these predictions. These data will expand and elaborate on potential interactions within the starch metabolic and regulatory network. Taken together, these studies will define novel factors that control starch accumulation in plants. This integrated research platform will also provide a prototype of how to study plant composition. In the long term, these results will help improve crops for food, industrial products, and fuels.Broader impactsThis project includes a comprehensive plan for hands-on high school and undergraduate research activities in bioinformatics and molecular genetics of plants, for integrating research and outreach activities among the postdoctoral researcher and graduate students, and for postdoctoral mentoring. The multidisciplinary approaches in the research will strengthen the experience, broadening the understanding of young scientists. It will also create a new puzzle-like module on biological networks within the MetaBlast game. MetaBlast is a 3D interactive cellular world (http://metablast.org) populated with organelles and proteins. It can be run in an immersive environment or on a laptop computer, thus it can be used in classrooms and at home. The MetaBlast team includes faculty, teachers, and students in biology, art, computer science, music, and game design. The biological network module will be designed to illustrate the complexities and layers of biological networks. The mission for the student player will be to engineer interrelated parts of the (simplified) starch metabolic and regulatory network such that they function to regulate starch metabolism. The unit will be implemented in two undergraduate biology courses. Educational activities will strongly consider the underprivileged and underrepresented in science. This effort will include the integration of students from five programs at Iowa State University targeting underrepresented undergraduate and high school students.