Uncovering Novel Signaling Interactions in Plant Metabolic Networks

调节植物成分的因素为利用作物生产改良的和新的成分提供了关键。淀粉是一种容易获得、能源廉价的还原碳储存方式，它是通过光合作用形成的，也就是使用太阳能。然而，人们对这一过程的分子机制知之甚少。这项研究的重点是扩大对控制植物淀粉含量的分子过程或网络的理解。本研究的目的是识别影响拟南芥叶片淀粉含量的新基因和新机制。假说是，一组尚未确定的基因与一种影响淀粉生物合成的新信号机制相互作用。其目的是通过确定影响淀粉调控网络的一组以前未确定的蛋白质的功能来扩大淀粉调控网络。本项目的具体目标是：目标1。分析淀粉网络中的候选基因。通过检查基因突变体中的淀粉含量和其他成分，提供了一种确定每个基因作用的方法。目的2.完善和扩大淀粉转录网络。目标1的实验数据将在已知淀粉网络的背景下，通过统计方法和网络分析与遗传算法的新组合进行分析。这些研究将揭示淀粉网络中选定的扰动如何影响淀粉的积累和植物的健康，并将产生关于哪些基因参与该网络的可实验验证的假说。目的3.确定与淀粉网络的已知或候选蛋白相互作用的蛋白质。在生物体中，对其组成的大部分调节是通过特定蛋白质之间形成复合体来实现的。这可以激活或停用特定的进程。计算方法将被用来根据蛋白质？S的序列和结构预测它可能与哪些其他蛋白质结合。通过使用实验方法，我们将检验这些预测。这些数据将扩展和详细说明淀粉代谢和调节网络中的潜在相互作用。综上所述，这些研究将确定控制植物中淀粉积累的新因素。这个综合研究平台还将为如何研究植物成分提供一个原型。从长远来看，这些成果将有助于改善用于食品、工业产品和燃料的作物。广泛的影响该项目包括一个全面的计划，包括在生物信息学和植物分子遗传学方面的高中和本科生实践研究活动，整合博士后研究人员和研究生之间的研究和推广活动，以及博士后指导。研究中的多学科方法将加强经验，拓宽年轻科学家的理解。它还将在MetaBlast游戏中的生物网络上创建一个新的类似益智的模块。MetaBlast是一个由细胞器和蛋白质组成的3D互动细胞世界(http://metablast.org))。它可以在身临其境的环境中运行，也可以在笔记本电脑上运行，因此可以在教室和家里使用。MetaBlast团队包括生物学、艺术、计算机科学、音乐和游戏设计方面的教职员工、教师和学生。生物网络模块将被设计来说明生物网络的复杂性和层次。学生玩家的任务将是设计(简化的)淀粉代谢和调节网络的相互关联的部分，以便它们能够调节淀粉新陈代谢。该单元将在两门本科生物学课程中实施。教育活动将强烈考虑在科学界处于不利地位和代表性不足的人。这项努力将包括整合爱荷华州立大学五个项目的学生，目标是代表人数不足的本科生和高中生。

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.