The stochastic evolution of a protocell. The Gillespie algorithm in a dynamically varying volume

TL;DR

This paper introduces an improved Gillespie algorithm to simulate the stochastic evolution of protocells with growing volume, driven by molecule production, enabling better understanding of early cellular life.

Contribution

It presents a novel modification of the Gillespie algorithm for modeling stochastic chemical reactions in dynamically growing volumes, specifically applied to protocell evolution.

Findings

The improved algorithm accurately models protocell growth dynamics.

Stochastic models differ from deterministic predictions in protocell behavior.

Multiple protocell models were compared to assess stochastic effects.

Abstract

In the present paper we propose an improvement of the Gillespie algorithm allowing us to study the time evolution of an ensemble of chemical reactions occurring in a varying volume, whose growth is directly related to the amount of some specific molecules, belonging to the reactions set. This allows us to study the stochastic evolution of a protocell, whose volume increases because of the production of container molecules. Several protocells models are considered and compared with the deterministic models.