Department of Physics & Astronomy and Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles, California 90089, USA.
Phys Rev E. 2017 May;95(5-1):052406. doi: 10.1103/PhysRevE.95.052406. Epub 2017 May 16.
Neurotransmitter receptor molecules, concentrated in synaptic membrane domains along with scaffolds and other kinds of proteins, are crucial for signal transmission across chemical synapses. In common with other membrane protein domains, synaptic domains are characterized by low protein copy numbers and protein crowding, with rapid stochastic turnover of individual molecules. We study here in detail a stochastic lattice model of the receptor-scaffold reaction-diffusion dynamics at synaptic domains that was found previously to capture, at the mean-field level, the self-assembly, stability, and characteristic size of synaptic domains observed in experiments. We show that our stochastic lattice model yields quantitative agreement with mean-field models of nonlinear diffusion in crowded membranes. Through a combination of analytic and numerical solutions of the master equation governing the reaction dynamics at synaptic domains, together with kinetic Monte Carlo simulations, we find substantial discrepancies between mean-field and stochastic models for the reaction dynamics at synaptic domains. Based on the reaction and diffusion properties of synaptic receptors and scaffolds suggested by previous experiments and mean-field calculations, we show that the stochastic reaction-diffusion dynamics of synaptic receptors and scaffolds provide a simple physical mechanism for collective fluctuations in synaptic domains, the molecular turnover observed at synaptic domains, key features of the observed single-molecule trajectories, and spatial heterogeneity in the effective rates at which receptors and scaffolds are recycled at the cell membrane. Our work sheds light on the physical mechanisms and principles linking the collective properties of membrane protein domains to the stochastic dynamics that rule their molecular components.
神经递质受体分子集中在突触膜区域，与支架和其他类型的蛋白质一起，对于跨越化学突触的信号传递至关重要。与其他膜蛋白结构域一样，突触结构域的特点是蛋白质拷贝数低且蛋白质拥挤，单个分子的随机快速周转。我们在这里详细研究了先前发现的突触区域受体-支架反应扩散动力学的随机晶格模型，该模型在平均场水平上捕获了实验中观察到的突触区域的自组装、稳定性和特征尺寸。我们表明，我们的随机晶格模型与拥挤膜中非线性扩散的平均场模型产生了定量一致的结果。通过解析和数值求解支配突触区域反应动力学的主方程的组合，以及动力学蒙特卡罗模拟，我们发现突触区域反应动力学的平均场和随机模型之间存在很大差异。基于先前的实验和平均场计算对突触受体和支架的反应和扩散特性的研究，我们表明，突触受体和支架的随机反应扩散动力学为突触区域的集体波动、在突触区域观察到的分子周转率、观察到的单个分子轨迹的关键特征以及在细胞膜上受体和支架回收的有效速率的空间异质性提供了一个简单的物理机制。我们的工作阐明了将膜蛋白结构域的集体性质与支配其分子成分的随机动力学联系起来的物理机制和原则。
