Department of Mechanical Engineering, Birla Institute of Technology and Science, Pilani, Pilani 333031, India.
William H. Miller III Department of Physics & Astronomy, Johns Hopkins University, Baltimore, MD 21218.
Proc Natl Acad Sci U S A. 2022 Aug 2;119(31):e2121302119. doi: 10.1073/pnas.2121302119. Epub 2022 Jul 29.
Some dividing cells sense their shape by becoming polarized along their long axis. Cell polarity is controlled in part by polarity proteins, like Rho GTPases, cycling between active membrane-bound forms and inactive cytosolic forms, modeled as a "wave-pinning" reaction-diffusion process. Does shape sensing emerge from wave pinning? We show that wave pinning senses the cell's long axis. Simulating wave pinning on a curved surface, we find that high-activity domains migrate to peaks and troughs of the surface. For smooth surfaces, a simple rule of minimizing the domain perimeter while keeping its area fixed predicts the final position of the domain and its shape. However, when we introduce roughness to our surfaces, shape sensing can be disrupted, and high-activity domains can become localized to locations other than the global peaks and valleys of the surface. On rough surfaces, the domains of the wave-pinning model are more robust in finding the peaks and troughs than the minimization rule, although both can become trapped in steady states away from the peaks and valleys. We can control the robustness of shape sensing by altering the Rho GTPase diffusivity and the domain size. We also find that the shape-sensing properties of cell polarity models can explain how domains localize to curved regions of deformed cells. Our results help to understand the factors that allow cells to sense their shape-and the limits that membrane roughness can place on this process.
一些分裂细胞通过沿着长轴极化来感知自身形状。细胞极性部分受极性蛋白控制，如 Rho GTPases，它们在活性膜结合形式和非活性胞质形式之间循环，可被模拟为“波钉扎”反应-扩散过程。形状感知是否源自波钉扎？我们发现波钉扎可感知细胞的长轴。在曲面上模拟波钉扎，我们发现高活性域向表面的峰和谷迁移。对于光滑表面，通过最小化域周长而保持其面积固定的简单规则可以预测域的最终位置及其形状。然而，当我们在表面引入粗糙度时，形状感知可能会受到干扰，高活性域可能会定位于表面全局峰和谷以外的位置。在粗糙表面上，波钉扎模型的域比最小化规则更能找到峰和谷，尽管两者都可能被困在远离峰和谷的稳定状态。我们可以通过改变 Rho GTPase 扩散率和域大小来控制形状感知的稳健性。我们还发现，细胞极性模型的形状感知特性可以解释域如何定位于变形细胞的弯曲区域。我们的研究结果有助于理解细胞感知自身形状的因素，以及膜粗糙度对这一过程的限制。
