Bilateral BBSRC NSF/ Bio - Modelling Cellular Differentiation in Plants

植物的生长和发育是灵活的，容易根据植物所处的直接环境而发生性状变化。植物的生长发育过程依赖于干细胞的分裂和分化，但对控制干细胞分化的机制知之甚少。了解控制干细胞分化为不同细胞类型的特性（称为细胞命运决定过程）对于理解从单个干细胞到成熟细胞以及最终的组织和植物的转变非常重要。该项目吸引了来自美国（北卡罗莱纳州立大学）和英国（剑桥大学）的研究团队，以解决协调细胞命运决定的复杂信号和调节程序。铁是一种必需的植物微量营养素，缺乏铁会影响植物的发育过程，该项目将建立数学模型来预测铁可用性变化的紧急行为。该项目将提供对所有生物体共同的生物学机制的见解，并在提高作物产量以应对压力方面对农业和粮食安全具有重要意义。实验和数学建模方法的结合使用将为生物数学和分子生物学提供新的跨学科教育机会，吸引从幼儿园到高中的学生（包括科学领域代表性不足的群体），包括本科生和研究生。该项目结合实验和计算方法来识别控制植物干细胞分化进程的基因调控和信号网络。该项目将采用计算建模方法来预测细胞对铁的可用性及其对韧皮部筛元素分化的影响的内在和外在线索的反应。筛元发育的终止阶段以程序核降解为特征。筛元的分化由于其发展相对较快而成为这类研究的有力模型。将开发常微分方程来评估基因表达动态如何影响筛选元素的分化。这些方程将被合并到一个基于Agent的模型中，以实现多个细胞同时分化的模拟。实验的迭代和模型的改进将有助于理解控制这种分化过程的基因和网络。这个英美合作项目由美国国家科学基金会和英国生物技术和生物科学研究委员会支持。

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.