Stochastic dynamics and ribosome-RNAP interactions in Transcription-Translation Coupling

TL;DR

This paper presents a stochastic model of transcription-translation coupling in prokaryotes, analyzing how molecular interactions influence the timing and protection of gene expression processes.

Contribution

It introduces a detailed mechanistic model incorporating ribosome and RNAP dynamics, providing new metrics to quantify coupling mechanisms and their effects.

Findings

Model predicts delay time distributions based on molecular features.

Proposes metrics for ribosome-RNAP binding probability and process protection.

Demonstrates conditions for acceleration, deceleration, and protection in transcription.

Abstract

Under certain cellular conditions, transcription and mRNA translation in prokaryotes appear to be "coupled," in which the formation of mRNA transcript and production of its associated protein are temporally correlated. Such transcription-translation coupling (TTC) has been evoked as a mechanism that speeds up the overall process, provides protection during the transcription, and/or regulates the timing of transcript and protein formation. What molecular mechanisms underlie ribosome-RNAP coupling and how they can perform these functions have not been explicitly modeled. We develop and analyze a continuous-time stochastic model that incorporates ribosome and RNAP elongation rates, initiation and termination rates, RNAP pausing, and direct ribosome and RNAP interactions (exclusion and binding). Our model predicts how distributions of delay times depend on these molecular features of transcription and translation. We also propose additional measures for TTC: a direct ribosome-RNAP binding probability and the fraction of time the translation-transcription process is "protected" from attack by transcription-terminating proteins. These metrics quantify different aspects of TTC and differentially depend on parameters of known molecular processes. We use our metrics to reveal how and when our model can exhibit either acceleration or deceleration of transcription, as well as protection from termination. Our detailed mechanistic model provides a basis for designing new experimental assays that can better elucidate the mechanisms of TTC.