Hybrid Markov-mass action law for cell activation by rare binding events

TL;DR

This paper introduces a hybrid model combining mass-action laws and Markov chains to study rare molecular binding events in cell activation, specifically predicting vesicular release timing at neuronal synapses.

Contribution

It presents a novel multiscale stochastic model that integrates discrete binding events with continuum descriptions to analyze cellular processes.

Findings

The model predicts a bimodal distribution of vesicle release times.

Rare binding events can significantly influence the timing of cellular responses.

The approach enables studying complex cellular events across multiple time scales.

Abstract

The binding of molecules, ions or proteins to specific target sites is a generic step for cell activation. However, this step relies on rare events where stochastic particles located in a large bulk are searching for small and often hidden targets and thus remains difficult to study. We present here a hybrid discrete-continuum model where the large ensemble of particles is described by mass-action laws. The rare discrete binding events are modeled by a Markov chain for the encounter of a finite number of small targets by few Brownian particles, for which the arrival time is Poissonian. This model is applied for predicting the time distribution of vesicular release at neuronal synapses that remains elusive. This release is triggered by the binding of few calcium ions that can originate either from the synaptic bulk or from the transient entry through calcium channels. We report that the distribution of release time is bimodal although triggered by a single fast action potential: while the first peak follows a stimulation, the second corresponds to the random arrival over much longer time of ions located in the bulk to small binding targets. To conclude, the present multiscale stochastic chemical reaction modeling allows studying cellular events based on integrating discrete molecular events over various time scales.