Geometry aware predictive models for exocytosis

TL;DR

This paper introduces a geometry-aware analytical model for exocytosis that predicts key parameters based on vesicle and pore geometry, supported by numerical simulations, aiding experimental data analysis.

Contribution

The paper presents a novel analytical model linking exocytosis dynamics to vesicle and pore geometry, validated by numerical simulations.

Findings

Analytical model accurately predicts exocytosis parameters.

Model aligns well with numerical simulation results.

Potential to extract geometrical info from experimental data.

Abstract

Inter neuron communication happens through the exchange of neurotransmitters at the synapse by a process known as exocytosis. This makes exocytosis a fundamental process of information exchange in the body. The exocytosis process has a distinct geometry as it involves a vesicle that attaches to the cell membrane and then releases the neurotransmitters through a pore. Significant recent research, both experimental and numerical, attempt to understand the time dynamics of exocytosis. In this manuscript, we share an analytical model that predicts the key output parameters of exocytosis based on the geometry of the vesicle and pore. Our analytical predictions are well supported by detailed numerical simulations. This model could help extract geometrical parameters from experimental data and hence could be of broad interest.