Elucidating distinct ion channel populations on the surface of hippocampal neurons via single-particle tracking recurrence analysis

Abstract

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.

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• Machine Learning Analysis of Anomalous Diffusion
• Objective comparison of methods to decode anomalous diffusion
• Preface: Characterisation of Physical Processes from Anomalous Diffusion Data
• Evaluating Gaussianity of heterogeneous fractional Brownian motion
• Recurrent neural network analysis of single trajectories switching between anomalous diffusion states
• Two-dimensional fractional Brownian motion: Analysis in time and frequency domains