Protein translocation without specific quality control in a computational model of the Tat system

TL;DR

This paper presents a stochastic computational model of the Tat translocation system that predicts cluster size distributions and translocation rates without relying on specific quality control mechanisms, aligning with experimental data.

Contribution

It introduces a novel model of Tat translocation that accounts for NT substrates and predicts cluster dynamics and translocation rates without explicit quality control.

Findings

Larger TatA clusters depend on NT substrate fraction

Translocation rate is optimized by substrate unbinding rate

Model aligns with in vitro Tat translocation data

Abstract

The twin-arginine translocation (Tat) system transports folded proteins of various sizes across both bacterial and plant thylakoid membranes. The membrane-associated TatA protein is an essential component of the Tat translocon, and a broad distribution of different sized TatA-clusters is observed in bacterial membranes. We assume that the size dynamics of TatA clusters are affected by substrate binding, unbinding, and translocation to associated TatBC clusters, where clusters with bound translocation substrates favour growth and those without associated substrates favour shrinkage. With a stochastic model of substrate binding and cluster dynamics, we numerically determine the TatA cluster size distribution. We include a proportion of targeted but non-translocatable (NT) substrates, with the simplifying hypothesis that the substrate translocatability does not directly affect cluster dynamical rate constants or substrate binding or unbinding rates. This amounts to a translocation model without specific quality control. Nevertheless, NT substrates will remain associated with TatA clusters until unbound and so will affect cluster sizes and translocation rates. We find that the number of larger TatA clusters depends on the NT fraction $f$. The translocation rate can be optimized by tuning the rate of spontaneous substrate unbinding, $\Gamma_U$. We present an analytically solvable three-state model of substrate translocation without cluster size dynamics that follows our computed translocation rates, and that is consistent with {\em in vitro} Tat-translocation data in the presence of NT substrates.