Bilateral BBSRC NSF/ Bio - Modelling Cellular Differentiation in Plants

North Carolina State University, Raleigh NC

Investigators

Abstract

Plant growth and development are flexible and prone to changes in character depending on the immediate environment of the plant. The processes of growth and development in plants depend on stem cells that divide and differentiate, but little is known about the mechanisms that govern stem cell differentiation. Understanding the properties that govern stem cell differentiation into different cell types (termed the cell fate decision process) is important for understanding the transition from single stem cells into mature cells and ultimately tissues and plants. This project engages research teams from the US (North Carolina State University) and the UK (University of Cambridge) to address the complex signals and regulatory programs that orchestrate cell fate decisions. Iron is an essential plant micronutrient which when deficient affects plant developmental processes, and this project will develop mathematical models to predict the emergent behaviors that are seen in response to changing iron availability. This project will provide insights into biological mechanisms common to all organisms and has important implications for agriculture and food security in terms of increased crop yield in response to stress. The combined use of experimental and mathematical modeling approaches will provide new interdisciplinary educational opportunities in biomathematics and molecular biology, engaging students (including groups underrepresented in science) at levels from kindergarten through high school and including undergraduate and graduate students. This project integrates experimental and computational approaches to identify gene regulatory and signaling networks that govern the progression of plant stem cell differentiation. The project will employ computational modeling approaches to predict cellular responses to intrinsic and extrinsic cues related to iron availability and its impact on phloem sieve element differentiation. The termination stage of sieve element development is characterized by programmed nuclear degradation. Differentiation of the sieve element is a powerful model for this kind of study because of a relatively rapid progression. Ordinary differential equations will be developed to assess how gene expression dynamics affect the differentiation of sieve elements. These equations will be incorporated into an Agent Based Model to enable the simulation of multiple cells differentiating simultaneously. The iteration of experimentation and model refinement will be instrumental for understanding the genes and networks that govern this differentiation process. This collaborative US/UK project is supported by the US National Science Foundation and the UK Biotechnology and Biological Sciences Research Council.