Modelling cargo transport in crowded environments: effect of motor association to cargos

TL;DR

This paper models cargo transport in crowded environments, revealing how motor association and obstacle interactions influence run-length, with findings aligning with experimental data and highlighting the role of eigenvalues in the dynamics.

Contribution

It introduces a novel model capturing the effects of motor association and crowding on cargo transport, including the impact of obstacle dynamics and eigenvalue analysis.

Findings

Run-length peaks at optimal motor density.

Eigenvalue of transition matrix governs cargo dynamics.

Model aligns with experimental observations.

Abstract

In intracellular transports, motor proteins transport macromolecules as cargos to desired locations by moving on biopolymers such as microtubules. Recent experiments suggest that cargos that can associate motor proteins during their translocation have larger run-length, association time and can overcome the motor traffic on microtubule tracks. Here, we model the dynamics of a cargo that can associate at the most m free motors present on the track as obstacles to its motion. The proposed models display competing effects of association and crowding, leading to a peak in the run-length with the free motor density. This result is consistent with past experimental observations. For m=2 and 3, we show that this feature is governed by the largest eigenvalue of the transition matrix describing the cargo dynamics. In all the above cases, free motors are assumed to be present as stalled obstacles. We finally compare simulation results for the run-length for general scenarios where the free motors undergo processive motion in addition to binding and unbinding to or from the microtubule.