A biologically inspired two-species exclusion model: effects of RNA polymerase motor traffic on simultaneous DNA replication

TL;DR

This paper presents a biologically inspired exclusion model simulating the interaction between RNA polymerase traffic and DNA replication forks, revealing possible conflict outcomes based on particle dynamics and phase behavior.

Contribution

It introduces a novel two-species exclusion model capturing RNAP and replication fork interactions with analytical and simulation insights.

Findings

Predicted conflict outcomes depend on TASEP phase.

Identified three pathways for resolving particle encounters.

Model can be adapted for experimental data comparison.

Abstract

We introduce a two-species exclusion model to describe the key features of the conflict between the RNA polymerase (RNAP) motor traffic, engaged in the transcription of a segment of DNA, concomitant with the progress of two DNA replication forks on the same DNA segment. One of the species of particles ($P$) represents RNAP motors while the other ($R$) represents replication forks. Motivated by the biological phenomena that this model is intended to capture, a maximum of only two $R$ particles are allowed to enter the lattice from two opposite ends whereas the unrestricted number of $P$ particles constitute a totally asymmetric simple exclusion process (TASEP) in a segment in the middle of the lattice. Consequently, the lattice consists of three segments; the encounters of the $P$ particles with the $R$ particles are confined within the middle segment (segment $2$) whereas only the $R$ particles can occupy the sites in the segments $1$ and $3$. The model captures three distinct pathways for resolving the co-directional as well as head-collision between the $P$ and $R$ particles. Using Monte Carlo simulations and heuristic analytical arguments that combine exact results for the TASEP with mean-field approximations, we predict the possible outcomes of the conflict between the traffic of RNAP motors ($P$ particles engaged in transcription) and the replication forks ($R$ particles). The outcomes, of course, depend on the dynamical phase of the TASEP of $P$ particles. In principle, the model can be adapted to the experimental conditions to account for the data quantitatively.