Our long-term goal is to understand how plants sense and respond to nitrogen (N) and how N nutrient or metabolite signals interact with hormonal pathways to control plant growth and development. Understanding these processes offers opportunities for improving N use efficiency in plants, an important issue for health, agriculture, and human nutrition. The increasing demand for agricultural production by the growing world population and diversification of crop use have led to massive N-based fertilizer use worldwide. This immense use of N fertilizers results in both high costs for agriculture and, most importantly, major detrimental effects on the environment and human health. It is of paramount importance for modern agriculture to improve N use efficiency in crops.
Besides their nutritional role in plants, nitrate and other forms of N can also act as signals to regulate the expression of hundreds of genes, causing modulation of growth and developmental processes. Although the genes and processes affected by changes in external or internal N have been identified, the molecular mechanisms involved in N sensing and signaling are still poorly understood. In previous studies, we built the first integrative gene network model for Arabidopsis thaliana. We used this model to identify gene networks that are controlled by organic or inorganic N in Arabidopsis. Our model allowed us to identify novel regulatory network modules that control different aspects of plant physiology, growth, and development.
We now seek to understand the molecular mechanisms of nitrate responses with temporal and spatial resolution in Arabidopsis thaliana. We propose to take our systems biology efforts to the next level by integrating, interpreting, and modeling new high-quality data we generate with available public datasets to explore gene function in cells and in whole organisms over developmental time and after specific environmental perturbations.
Life exists in four dimensions. Despite this fundamental characteristic of our living world, experimental biology has typically evaluated time and space independently. However, the composite nature of the outputs measured (e.g., integration of various cell types and one time point) does not allow us to understand the spatiotemporal characteristics of the molecular regulatory networks controlling biological processes within multicellular organisms. We are developing new bioinformatics tools and obtaining new systematic experimental data to understand the dynamic and cell-specific properties of N regulatory gene networks in multicellular organisms over developmental time. Questions that interest us are related to understanding the molecular principles of how cells coherently interpret N signals and respond accordingly, providing the organism with its developmental and physiological attributes. Researchers around the world are seeking the answers to these questions, and they are inspired by the ever growing need for a deeper understanding of complex biological systems, arguably the only way to knowledgeably resolve issues in human health.
The Center for Genome Regulation (Fund for Advanced Research in Priority Areas Program), Millennium Nucleus Center for Plant Functional Genomics (Millennium Science Initiative), and a grant from National Commission for Technological and Scientific Research provided partial support for these projects.
As of January 17, 2012