Adaption of mechano-chemical self-organization at cellular membranes to extracellular stressors

质膜受到长度和幅度不等的连续变形的影响。为了响应这种瞬态膜变形，曲率敏感分子被动态地招募到这些位置。与此建议相关的是，这些蛋白质中的一些能够局部改变肌动蛋白聚合速率，从而改变施加在膜上的力。这反过来又创造了与受体无关的反馈回路。在最近的工作中，我们发现了这样一个曲率相关的模块，它可以在贴壁的单细胞中介导探索性搜索模式（Begemann等人，Nature Physics）。我们发现，这种自组织模块依赖于曲率敏感信号分子在前沿（LE）的动态招募来变形膜，改变了包括免疫细胞在内的多种单细胞模型系统的运动模式。然而，外部压力源对信号处理的影响，以及通过该模块的搜索模式，仍然是难以捉摸的。在这个项目中，我们的目标是研究这些输入如何影响信号传导和细胞运动。具体来说，我们将回答(i)温度如何改变曲率相关的细胞运动模式，以及（ii）基底刚度如何影响曲率相关的细胞运动模式。为了解决这些问题，我们将利用我们在实验室开发的最先进的细胞、生物物理和计算工具。总的来说，这些研究将使我们对自组织信号系统如何在不同的外部条件下适应运动模式的信号这一基本问题获得新的见解。

The plasma membrane is subject to continuous deformations that vary in length and amplitude. In response to such transient membrane deformations, curvature-sensitive molecules are dynamically recruited to these sites. Relevant for this proposal, some of these proteins are capable to locally change actin polymerization rates, and in consequence the force exerted to the membrane. This, in turn, creates receptor-independent feedback loops. In recent work, we identified such a curvature-dependent module that mediates exploratory search pattern in adherent single cells (Begemann et al., Nature Physics). We showed that this self-organizing module, which relies on dynamic recruitment of curvature-sensitive signaling molecules to deforming membranes at the leading edge (LE), alters motion pattern in a variety of single-cell model systems including immune cells. However, the consequences of external stressors on signal processing, and hence on search pattern via this module, have remained elusive. In this project, we aim to investigate how such inputs affect signaling and cell motion. Specifically, we will answer (i) how temperature alters curvature-dependent cellular motion pattern, and (ii) how substrate stiffness affects curvature-dependent cellular motion pattern. To address these questions, we will take advantage of state-of-the-art cellular, biophysical and computational tools that we developed in the lab. Collectively, these studies will allow us to gain novel insights into the fundamental question how a self-organizing signaling system adapts signaling for motion pattern under varying external conditions.