Queuing model of axonal transport

TL;DR

This paper models axonal transport of vesicles using queuing theory, revealing how stochastic transport leads to resource fluctuations at synapses and identifying factors influencing these fluctuations.

Contribution

It introduces a stochastic queuing model for vesicular transport in axons, analyzing resource fluctuations and their dependence on cargo load and injection rate.

Findings

Discrete transport causes non-Poissonian fluctuations in synaptic resources.

Fano factors increase with cargo load, indicating higher variability.

Fluctuations can be mitigated by increasing injection rate and reducing cargo per vesicle.

Abstract

The motor-driven intracellular transport of vesicles to synaptic targets in the axons and dendrites of neurons plays a crucial role in normal cell function. Moreover, stimulus-dependent regulation of active transport is an important component of long-term synaptic plasticity, whereas the disruption of vesicular transport can lead to the onset of various neurodegenerative diseases. In this paper we investigate how the discrete and stochastic nature of vesicular transport in axons contributes to fluctuations in the accumulation of resources within synaptic targets. We begin by solving the first passage time problem of a single motor-cargo complex (particle) searching for synaptic targets distributed along a one-dimensional axonal cable. We then use queuing theory to analyze the accumulation of synaptic resources under the combined effects of multiple search-and-capture events and degradation. In particular, we determine the steady-state mean and variance of the distribution of synaptic resources along the axon in response to the periodic insertion of particles. The mean distribution recovers the spatially decaying distribution of resources familiar from deterministic population models. However, the discrete nature of vesicular transport can lead to Fano factors that are greater than unity (non-Poissonian) across the array of synapses, resulting in significant fluctuation bursts. We also find that each synaptic Fano factor is independent of the rate of particle insertion but increases monotonically with the amount of protein cargo in each vesicle. This implies that fluctuations can be reduced by increasing the injection rate while decreasing the cargo load of each vesicle.