Connecting Single-Cell Signaling Dynamics to Multicellular Decision Making

将单细胞信号动力学与多细胞决策联系起来

• 批准号: 10001585
• 负责人: Allyson E Sgro
• 金额: $ 41.25万
• 依托单位: BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10001585
• 关键词: Address; Affect; Amoeba genus; Animal Model; Automobile Driving; Award; Behavior; Behavior Control; Biochemical; Biomimetics; Cells; Communication; Cues; Decision Making; Dictyostelium discoideum; Disease; Environment; Goals; Health; Hour; Human; Injury; Link; Malignant Neoplasms; Mechanics; Microbial Biofilms; Mission; Modeling; Neurons; Organ; Population; Research; Signal Transduction; System; Techniques; United States National Institutes of Health; Visualization; Work; Wound models; fundamental research; new technology; programs; social; tool; treatment strategy; tumor

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.

摘要 许多疾病和伤害的治愈仍然难以捉摸，因为它们影响的系统是 高度适应性的多细胞集合体，利用生化通信重新编程以 绕过我们的治疗策略。我的研究项目的目标是确定单个细胞如何解释 它们的环境并调节它们的行为来控制这些多细胞决定。我们目前的情况 由于概念和技术上的挑战，对这种联系的理解一直有限 通过将单个细胞内部的小规模、快速动态与展开的更大规模的行为联系起来 在蜂窝种群中持续数小时和数天。在这个奖项中，我们将应对这些挑战，并将重点放在 解决我们理解中的几个关键差距，特别是(1)确定单细胞调控机制 用于调节整个种群的行为，以及(2)阐明信号和信号之间的相互作用 机械学驱使细胞群体共同努力，重塑自己。使我们能够直接链接 从单细胞动力学到全人口决策，我们正在开发和实施新的 同时定量显示和控制细胞内和细胞间生化的技术 推动这些决策的动力。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--社会变形虫--盘基网硬毛虫以及 仿生伤口愈合模型，我们可以直接将细胞内信号与机械环境联系起来 暗示。我们在这些系统中开发的将信号动态与种群行为联系起来的工具也将 使我们能够审问这些行为，并开发具有真正预测能力的这些行为的模型。 我们对单细胞动力学的新的预测性理解用于协调集体和 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 这些行为为变革性的新疾病和伤害治疗创造了条件。