Coarse-grained Stochastic Model of Myosin-Driven Vesicles into Dendritic Spines

TL;DR

This paper develops a coarse-grained stochastic model of myosin-driven vesicle transport into dendritic spines, capturing bistability and translocation dynamics, with analytical and numerical insights into vesicle movement.

Contribution

It introduces a coarse-grained, agent-based stochastic model for vesicle transport that captures key experimental features and reformulates the problem as a mean first passage time analysis.

Findings

Model reproduces bistability in vesicle velocity.

Coarse-graining accurately captures waiting-time distributions.

Analytical calculations of vesicle translocation times.

Abstract

We study the dynamics of membrane vesicle motor transport into dendritic spines, which are bulbous intracellular compartments in neurons that play a key role in transmitting signals between neurons. We consider the stochastic analog of the vesicle transport model in [Park and Fai, The Dynamics of Vesicles Driven Into Closed Constrictions by Molecular Motors. Bull. Math. Biol. 82, 141 (2020)]. The stochastic version, which may be considered as an agent-based model, relies mostly on the action of individual myosin motors to produce vesicle motion. To aid in our analysis, we coarse-grain this agent-based model using a master equation combined with a partial differential equation describing the probability of local motor positions. We confirm through convergence studies that the coarse-graining captures the essential features of bistability in velocity (observed in experiments) and waiting-time distributions to switch between steady-state velocities. Interestingly, these results allow us to reformulate the translocation problem in terms of the mean first passage time for a run-and-tumble particle moving on a finite domain with absorbing boundaries at the two ends. We conclude by presenting numerical and analytical calculations of vesicle translocation.