EAGER: Collaborative Research: Novel micromechanical and computational approaches to discover the mechanisms of symmetry breaking and polarized growth in dicot pavement cells

在植物中，叶表皮是一个重要的结构控制元素，它决定了下层组织的生长特性和器官的整体形式。叶子的大小和形状是农业生产中的重要特征，叶子的结构也是如此。因此，深入了解叶片发育的遗传和细胞调控是一个重要的研究目标。表皮的组织水平行为是由具有交错叶的锯齿状铺装细胞的极化生长驱动的。然而，这种重要的细胞形状控制途径的分子、细胞和机械控制机制尚不清楚。在开发出新的实验和计算方法之前，这种知识差距无法填补。该项目的目标是创建一套新的图像分析技术、机械设备和数学模型，从而能够从机制上理解组织水平的机械力如何与细胞内信号通路相互作用，从而控制形态发生的几何形状。我们的方法将包括开发新的图像分析和纳米级机械设备，这将使路面细胞生长机制的定量测试成为可能。我们将创建计算模型，使我们能够分析现有生长控制模型的合理性，并对机械力和细胞内重组如何相互作用来控制细胞形状做出新的预测。该研究将包括对研究团队的跨学科交叉培训，并有望在图像处理和分析方面产生技术进步，这些技术进步将通过与iPlant数据共享资源的合作向公众提供。该项目将产生广泛有用的计算模型，模拟植物细胞生长控制机制，并产生可通过实验验证的预测。该项目由综合生物系统学部植物、真菌和微生物发展项目以及分子和细胞生物科学学部网络、调控和细胞过程项目共同支持。

In plants, the leaf epidermis is an important architectural control element that defines the growth properties of underlying tissues and the overall form of the organ. The size and shape of leaves are important traits in agricultural production, as is the architecture of the leaf. Therefore, a deep understanding of the genetic and cellular control of leaf development is an important research goal. The tissue-level behavior of the epidermis is driven by the polarized growth of jig-saw-puzzle shaped pavement cells with interdigitating lobes. However, the molecular, cellular, and mechanical control mechanisms for this important cell shape control pathway are not known. This knowledge gap cannot be filled until new experimental and computational approaches are developed. The objective of this project is to create a new set of image analysis techniques, mechanical devices, and mathematical models that will enable a mechanistic understanding of how tissue-level mechanical forces interact with intracellular signaling pathways to control the geometry of morphogenesis. Our approach will include the development of new image analysis and nano-scale mechanical devices that will enable quantitative tests for the mechanisms of pavement cell growth. We will create computational models that will allow us to analyze the plausibility of existing growth control models, and make new predictions about how mechanical forces and intracellular reorganization interact to control cell shape. The research will include interdisciplinary cross-training of the research team, and is expected to generate technical advances in image processing and analysis that will be made publicly available through a collaboration with the iPlant data sharing resource. The project will generate broadly useful computational models that simulate plant cell growth control mechanisms and generate predictions that can be experimentally tested. This project is jointly supported by the Programs in Plant, Fungal and Microbial Development in the Division of Integrative Organismal Systems and by the Networks and Regulation and Cellular Processes Programs in the Division of Molecular and Cellular Biosciences.