A stochastic model of ion channel cluster formation in the plasma membrane

Abstract

Ion channels are often found arranged into dense clusters in the plasma membranes of excitable cells, but the mechanisms underlying the formation and maintenance of these functional aggregates are unknown. Here, we tested the hypothesis that channel clustering is the consequence of a stochastic self-assembly process and propose a model by which channel clusters are formed and regulated in size. Our hypothesis is based on statistical analyses of the size distributions of the channel clusters we measured in neurons, ventricular myocytes, arterial smooth muscle, and heterologous cells, which in all cases were described by exponential functions, indicative of a Poisson process (i.e., clusters form in a continuous, independent, and memory-less fashion). We were able to reproduce the observed cluster distributions of five different types of channels in the membrane of excitable and tsA-201 cells in simulations using a computer model in which channels are “delivered” to the membrane at randomly assigned locations. The model’s three parameters represent channel cluster nucleation, growth, and removal probabilities, the values of which were estimated based on our experimental measurements. We also determined the time course of cluster formation and membrane dwell time for CaV1.2 and TRPV4 channels expressed in tsA-201 cells to constrain our model. In addition, we elaborated a more complex version of our model that incorporated a self-regulating feedback mechanism to shape channel cluster formation. The strong inference we make from our results is that CaV1.2, CaV1.3, BK, and TRPV4 proteins are all randomly inserted into the plasma membranes of excitable cells and that they form homogeneous clusters that increase in size until they reach a steady state. Further, it appears likely that cluster size for a diverse set of membrane-bound proteins and a wide range of cell types is regulated by a common feedback mechanism.

Nanoscale coupling of junctophilin-2 and ryanodine receptors regulates vascular smooth muscle cell contractility

“…S3 A and B ). This observation is consistent with a model suggesting that membrane-associated protein clusters (including RyR2 and JPH2) are formed by stochastic self-assembly and their size is maintained by a relatively rapid rate of turnover (22). Using object-based analysis (23) to identify protein clusters that are juxtaposed within the limit of resolution of our GSDIM system (<40 nm; SI Appendix , Fig.…”

Kv2.1 channels play opposing roles in regulating membrane potential, Ca 2+ channel function, and myogenic tone in arterial smooth muscle

“…Our recent paper describes a potential mechanism by which Kv2.1 could increase Ca V 1.2 channel clustering in arterial smooth muscle (8). In these cells, Ca V 1.2 cluster formation is determined by a stochastic self-assembly process in which cluster size is determined by 3 distinct biological probabilities: cluster nucleation (P n ), removal (P R ), and growth (P g ).…”

“…A salient property of Ca V 1.2 channels is their intrinsic ability to form clusters via a stochastic self-assembly mechanism (8). Channels within these clusters undergo functional coupling in response to local elevations in [Ca 2+ ] i (9)(10)(11).…”

β-adrenergic control of sarcolemmal CaV1.2 abundance by small GTPase Rab proteins

“…Activation of βARs was observed to increase the probability of channel insertion while activation of AngII receptors increased the probability of channel removal. These very scenarios were predicted in a recently published computer model designed to test the hypothesis that ion channel clustering occurs via a stochastic self-assembly process (45).…”