Characterization of single-cell dynamics that lead to collective behaviors

描述(由申请人提供)：这项工作的目标是了解单细胞信号动力学如何有助于多细胞系统中集体行为的协调，例如社会变形虫Dictyostelialdiscoideum。在饥饿期间，阿米巴虫分泌信号分子cAMP，并将其作为细胞聚集成多细胞有机体的信号。在野生型和突变型细胞中，可以使用荧光传感器在单个阿米巴中测量这些信号分子动力学。通过将它们限制在微流体设备中，阿米巴可以暴露在空间和时间变化的微环境中，以测量这些变化如何影响信号传递。结合这些技术，这项建议的目标是(1)证明单个Dictyostelials细胞在发育过程中是可兴奋的系统，并开发其信号动力学的量化模型，准确地预测它们的行为，以及(2)识别单细胞cAMP信号网络中的反馈机制。从长远来看，这项拟议的工作将为描述基于单细胞动力学的集体行为协调的多细胞模型铺平道路。这样的模型将有助于确定解释生物系统如何协调集体行为并经历从单细胞控制的行为到多细胞控制的行为的转变的普遍原则。扩大我们对这些原则和反馈的理解，最终将使我们能够找到控制这些行为的新方法，潜在地揭示依赖集体行为来协调其进展的疾病的新药物和治疗目标。

DESCRIPTION (provided by applicant): The goal of this work is to understand how single-cell signaling dynamics contribute to the coordination of collective behaviors in multicellular systems such as the social amoeba Dictyostelium discoideum. During starvation, the amoebae secrete the signaling molecule cAMP and use it as a cue for the cells to aggregate into a multicellular organism. These signaling molecule dynamics can be measured in individual amoeba using fluorescent sensors in wild type and mutant cells. By confining them to microfluidic devices, the amoebae can be exposed to spatially and temporally varying microenvironments to measure how these changes influence signaling. Combining these techniques, this proposal's targets are (1) to show that single Dictyostelium cells during development are excitable systems, and to develop a quantitative model of their signaling dynamics that accurately predicts their behavior and (2) to identify feedback mechanisms in the single-cell cAMP signaling network. In the long term, the proposed work will pave the way for a multi-cellular model that describes the coordination of collective behavior based on single-cell dynamics. Such a model would aid in identifying universal principles that explain how biological systems coordinate collective behavior and undergo the transition from single- to multicellular-controlled behaviors. Expanding our understanding of these principles and feedbacks will ultimately allow us to find new ways to control these behaviors, potentially revealing new drug and treatment targets for diseases that rely on collective behavior to coordinate their progression.