Functional causality in regulating cell morphogenesis

形态发生是广泛的细胞功能中的一个基本过程，因此是最好的 学习。因此，大多数起作用的成分过程及其大部分分子部分 都是已知的。更不了解的是，许多底层组件流程是如何集成到 全力以赴。这种整合是由化学和机械途径系统调节的，i)高 非线性程度；二)高度冗余；三)因果的空间和时间分离 组件进程之间。这种通路配置的关键结果是任何 组件可以导致广泛和快速的适应。因此，表型变化主要反映了 系统的重新配置，而不一定是受干扰目标的功能。这项挑战具有 困扰着细胞形态发生中的分子功能的询问，并导致了许多争议 这可能与实验设计上的细微差异有关，从而触发了不同的适应过程。至 绕过这些限制，我的实验室在过去10年里开发出了定量活细胞 揭示时空分布分子间功能相互作用的成像方法 过程，如细胞骨架聚合物动力学、力和化学信号，基于 它们在未受扰动的系统中的自发激活涨落。建立在细胞关键发现的基础上 形态控制机制，这需要使用一种无扰动的方法，而不是更 传统的实验范式，我们在这里提出了这个研究计划的扩展，它将 引入严格的统计框架来推断分子过程的因果耦合 瀑布。这包括从波动时间序列直接识别反馈交互作用的算法 在可变细胞条件下过程之间和因果级联的动态重新布线 条件。这些计算发展将与实验系统的创新相平行 多达8个并发过程的多光谱活细胞成像和用于分析细胞形态发生 3D中的自然组织环境。这些研究将集中在高度协调的系统上。 促进肌动蛋白介导的细胞形态改变的冗余肌动蛋白调控因子及其相互作用 该系统具有调控RhoGTPase信号的系统。这项工作的影响将远远超出 我们将对这些途径系统的调控获得新的见解。这项工作将解决臭名昭著的 复杂分子系统的适应反应，这是普遍存在的，也是阻碍人类健康发展的根本障碍 对细胞功能的系统查询。我们为解决其中一些问题而开发的工具将会 可作为广泛采用的方法来分析细胞调节过程。

Morphogenesis is a fundamental process in a wide range of cell functions and therefore one of the best studied. Consequently, most of the contributing component processes and the majority of their molecular parts are known. Much less understood is how the many underlying component processes are integrated into a working whole. This integration is regulated by a system of chemical and mechanical pathways with i) a high level of non-linearity; ii) a high level of redundancy; and iii) a separation in space and time of cause and effect between component processes. A key consequence of such a pathway configuration is that perturbation of any component can lead to wide-ranging and fast adaptation. Hence, phenotypic changes primarily reflect a reconfiguration of the system and not necessarily the function of the perturbed target. This challenge has plagued the interrogation of molecular functions in cell morphogenesis, and has led to numerous controversies that likely relate to slight differences in experimental designs triggering divergent adaptation processes. To circumvent some of these limitations, my lab has developed over the past 10 years quantitative live cell imaging methods that reveal the functional interplay between spatially and temporally distributed molecular processes, such as cytoskeleton polymer dynamics, forces, and chemical signals, based on the coupling of their spontaneous activation fluctuations in unperturbed systems. Building on key discoveries of cell morphogenic control mechanisms, which required the use of a perturbation-free approach rather than a more conventional experimental paradigm, we propose here an extension of this research program that will introduce a rigorous statistical framework to infer the coupling of molecular processes in cause and effect cascades. This includes algorithms to identify directly, from fluctuation time series, feedback interactions between processes and the dynamic rewiring of the cause and effect cascades under variable cellular conditions. These computational developments will be paralleled by innovation in experimental systems for multispectral live cell imaging of up to 8 concurrent processes and for the analysis of cell morphogenesis in native tissue environments in 3D. The studies will be focused on the coordination of the system of highly redundant actin modulating factors in promoting actin mediated cell shape changes and the interactions of this system with the regulatory system of RhoGTPase signals. The impact of this work will reach far beyond the new insights we will gain of the regulation of these pathway systems. The work will address the notorious adaptation responses of complex molecular systems, which are generic and a fundamental impediment to the systematic inquiry of cell functions. The tools we develop to overcome some of these problems will be made available as widely-adoptable approaches to the analysis of cell regulatory processes.