Faculty of Pure and Applied Mathematics, Hugo Steinhaus Center, Wrocław University of Science and Technology, 50-370 Wrocław, Poland.
Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, Colorado 80523, USA.
Phys Rev E. 2017 Dec;96(6-1):062404. doi: 10.1103/PhysRevE.96.062404. Epub 2017 Dec 11.
Protein and lipid nanodomains are prevalent on the surface of mammalian cells. In particular, it has been recently recognized that ion channels assemble into surface nanoclusters in the soma of cultured neurons. However, the interactions of these molecules with surface nanodomains display a considerable degree of heterogeneity. Here, we investigate this heterogeneity and develop statistical tools based on the recurrence of individual trajectories to identify subpopulations within ion channels in the neuronal surface. We specifically study the dynamics of the K^{+} channel Kv1.4 and the Na^{+} channel Nav1.6 on the surface of cultured hippocampal neurons at the single-molecule level. We find that both these molecules are expressed in two different forms with distinct kinetics with regards to surface interactions, emphasizing the complex proteomic landscape of the neuronal surface. Further, the tools presented in this work provide new methods for the analysis of membrane nanodomains, transient confinement, and identification of populations within single-particle trajectories.
蛋白质和脂质纳米域普遍存在于哺乳动物细胞的表面。特别是,最近已经认识到,离子通道在培养神经元的胞体中组装成表面纳米簇。然而,这些分子与表面纳米域的相互作用表现出相当大的异质性。在这里,我们研究了这种异质性,并开发了基于个体轨迹重现的统计工具,以识别神经元表面离子通道中的亚群。我们专门在单细胞水平上研究了培养海马神经元表面 K^{+}通道 Kv1.4 和 Na^{+}通道 Nav1.6 的动力学。我们发现这两种分子都以两种不同的形式表达,其表面相互作用的动力学特征明显不同,这强调了神经元表面复杂的蛋白质组景观。此外,本文提出的工具为膜纳米域、瞬态限制以及单个粒子轨迹中群体的识别提供了新的分析方法。