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（GRNs）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。GRN传统上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产出。数学建模提供了描述网络动态的潜力。然而，模型需要参数化，而实验数据往往缺失。最近在成像领域的发展提供了工具，使观察网络动态在活的生物体和实验测定的重要参数建模其行为所必需的。在拟南芥根中，由转录因子SHORT-ROOT（SHR）和SCARECROW（SCR）调控的基因的小网络控制基本组织干细胞的直接后代的形成性分裂。这些分裂是不对称的，因为子细胞继续产生不同的细胞谱系，皮层和内皮。超过20年的遗传学研究已经阐明了这个网络的拓扑结构，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，实验确定重要的动力学参数的SHR-SCR网络，并使用这些模型的功能。具体来说，我将使用双光子光片显微镜来实时测量网络组件的蛋白质表达的变化的时间和水平，因为细胞在野生型植物中分裂，并响应SHR诱导（目标1）。然后，我将使用一种名为“数量和亮度”（Aim 2）的相关光谱学领域的新技术来确定细胞分裂前后在细胞环境中形成的特定SHR-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SHR-SCR网络的行为（目标3）。这项工作将阐明该网络如何动态控制细胞分裂和拟南芥根细胞命运的规范。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.