Dynamics of the SHR-SCR Network Controlling Asymmetric Cell Division

描述（由申请人提供）：了解基因调控网络（grn）如何协调关键的发育事件，如组织模式，细胞分裂和命运规范，是生物学中一个主要的悬而未决的问题。传统上，grn被表示为由边和节点组成的静态模型。然而，这些模型未能捕捉到通过网络的动态信息流，而信息流最终决定了网络的发展输出。数学建模为描述网络动力学提供了可能。然而，模型需要参数化，而实验数据往往缺失。成像领域的最新发展提供了工具，使观察活生物体中的网络动力学和实验确定建模其行为所需的重要参数成为可能。在拟南芥根系中，由转录因子SHORT-ROOT （SHR）和稻草人（SCR）调控的一个小基因网络控制着地面组织干细胞直系后代的形成分裂。这些分裂是不对称的，因为子细胞继续产生不同的细胞系，皮层和内胚层。20多年来的遗传研究已经阐明了该网络的拓扑结构，但对网络组件如何动态地共同作用以影响细胞分裂和命运规范知之甚少。在这里，我建议使用前沿成像技术来实验确定SHR-SCR网络的重要动力学参数，并使用这些来模拟其功能。具体来说，我将使用双光子光板显微镜来实时测量野生型植物细胞分裂时网络组分蛋白表达变化的时间和水平，以及对SHR诱导的响应（目的1）。然后，我将使用一种来自相关光谱学领域的新技术，即“数量与亮度”（目标2），确定细胞分裂前后在细胞环境中形成的特定的shrr - scr复合物。最后，我将使用这些实验确定的参数和相互作用来模拟shrr - scr网络的行为（目标3）。这项工作将揭示该网络如何动态控制细胞分裂和细胞命运的规范在拟南芥根。它还将探索理解基因网络功能的新方法，这些方法可能普遍适用于所有生物体。

DESCRIPTION (provided by applicant): Understanding how gene regulatory networks (GRNs) orchestrate key developmental events such as tissue patterning, cell division and fate specification, is a major outstanding question in biology. GRNs are traditionally represented as static models comprised of edges and nodes. However, these models fail to capture the dynamic flow of information through the network that ultimately determines its developmental output. Mathematical modeling offers the potential for describing network dynamics. However, models require parameterization for which experimental data is often missing. Recent developments in the field of imaging have provided the tools to enable the observation of network dynamics in living organisms and the experimental determination of important parameters necessary for modeling their behavior. In Arabidopsis roots, a small network of genes regulated by the transcription factors SHORT-ROOT (SHR) and SCARECROW (SCR) controls the formative division of the immediate progeny of the ground tissue stem cells. These divisions are asymmetric, in that the daughter cells go on to produce distinct cell lineages, the cortex and endodermis. Over 20 years of genetic research have elucidated the topology of this network, yet little is known about how network components act together dynamically to effect cell division and fate specification. Here, I propose to use leading edge imaging techniques to experimentally determine important kinetic parameters of the SHR-SCR network and use these to model its function. Specifically, I will use two-photon light sheet microscopy to measure in real-time the timing and levels of changes in protein expression of network components as cells divide in wild-type plants and in response to SHR induction (Aim 1). I will then determine the specific SHR-SCR complexes formed in their cellular context both before and after cell division using a new technique from the field of correlation spectroscopy called Number and Brightness (Aim 2). And finally, I will use these experimentally determined parameters and interactions to model the behavior of the SHR-SCR network (Aim 3). This work will shed light on how this network dynamically controls cell division and the specification of cell fate in the Arabidopsis root. It will also explore new methods for understanding gene network function that may be generally applicable to all organisms.