Connecting Single-Cell Signaling Dynamics to Multicellular Decision Making

总结 许多疾病和伤害的治愈方法仍然难以捉摸，因为它们影响的系统是 高度适应性的多细胞群体，利用生化通讯来重新编程， 规避我们的治疗策略我的研究项目的目标是确定单细胞如何解释 并调节它们的行为来控制这些多细胞决定。我们目前 由于概念和技术上的挑战，对这种联系的理解是有限的 通过将单个细胞内的小规模快速动态与更大规模的行为展开联系起来， 在细胞群中持续数小时和数天。在此次颁奖期间，我们将应对这些挑战，并专注于 解决我们理解中的几个关键差距，特别是（1）确定单细胞调节机制 用于调节群体范围内的行为，以及（2）阐明信号传导和 力学驱使细胞群体一起工作来重塑自己。使我们能够直接连接 单细胞动力学到全人群决策，我们正在开发和实施新的 细胞内和细胞间生物化学的同时定量可视化和控制技术 推动这些决定的动力。这些技术与定量建模相结合，将使我们能够 在细胞内信号和多细胞行为之间建立因果联系。我们的工作将在一个 集体行为的经典模式生物，社会性变形虫盘基网柄阿米巴，以及一种 仿生伤口愈合模型，我们可以直接将细胞内信号传导与机械环境 线索我们在这些系统中开发的将信号动态与群体行为联系起来的工具也将 使我们能够询问这些行为并开发具有真实的预测能力的这些行为的模型。 随着我们对用于协调集体的单细胞动力学的新预测理解， 证明我们可以自己控制这些行为，我们将为重新编程奠定基础。 这些行为用于变革性的新疾病和损伤治疗。

SUMMARY Cures for many diseases and injuries have remained elusive because the systems they affect are highly adaptable multicellular collectives that harness biochemical communication to reprogram themselves to circumvent our treatment strategies. The goal of my research program is to identify how single cells interpret their environments and modulate their behaviors to control these multicellular decisions. Our current understanding of this connection has been limited due to the conceptual and technological challenges presented by connecting the small-scale, fast dynamics inside single cells to larger-scale behaviors unfolding over hours and days in cellular populations. During this award, we will address these challenges and focus on resolving several key gaps in our understanding, specifically (1) identifying single-cell regulatory mechanisms for modulating population-wide behaviors and (2) elucidating how the interplay between signaling and mechanics drives cellular populations to work together to remodel themselves. To enable us to directly link single-cell dynamics to population-wide decision making, we are developing and implementing new technologies for simultaneous quantitative visualization and control of intra- and intercellular biochemical dynamics driving these decisions. These techniques, in combination with quantitative modeling, will allow us to make causal links between intracellular signaling and multicellular behaviors. Our work will be performed in a classic model organism for collective behaviors, the social amoeba Dictyostelium discoideum, as well as a biomimetic wound healing model where we can directly link intracellular signaling to mechanical environmental cues. The tools we develop in these systems to link signaling dynamics to population behaviors will also enable us to interrogate these behaviors and develop models of these behaviors with real predictive power. With our new predictive understanding of the single-cell dynamics used to coordinate collectives and by demonstrating we can control these behaviors ourselves, we will be laying the groundwork for reprogramming these behaviors for transformative new disease and injury treatments.