# Optimal localization patterns in bacterial protein synthesis

## TL;DR

This paper explores how controlling the spatial localization and stoichiometry of mRNAs in bacteria can optimize protein synthesis rates without changing gene expression levels, based on physical principles.

## Contribution

It introduces a quantitative model showing how mRNA localization and polysome stoichiometry can be engineered to regulate protein synthesis in bacteria.

## Key findings

- Protein synthesis can be enhanced or inhibited by mRNA spatial localization.
- Colocalization of mRNAs and ribosomes is crucial for controlling synthesis rates.
- Physical mechanisms like excluded-volume effects influence protein production.

## Abstract

In $\textit{Escherichia coli}$ bacterium, the molecular compounds involved in protein synthesis, messenger RNAs (mRNAs) and ribosomes, show marked intracellular localization patterns. Yet a quantitative understanding of the physical principles which would allow one to control protein synthesis by designing, bioengineering, and optimizing these localization patterns is still lacking. In this study, we consider a scenario where a synthetic modification of mRNA reaction-diffusion properties allows for controlling the localization and stoichiometry of mRNAs and polysomes$\mathrm{-}$complexes of multiple ribosomes bound to mRNAs. Our analysis demonstrates that protein synthesis can be controlled, e.g., optimally enhanced or inhibited, by leveraging mRNA spatial localization and stoichiometry only, without resorting to alterations of mRNA expression levels. We identify the physical mechanisms that control the protein-synthesis rate, highlighting the importance of colocalization between mRNAs and freely diffusing ribosomes, and the interplay between polysome stoichiometry and excluded-volume effects due to the DNA nucleoid. The genome-wide, quantitative predictions of our work may allow for a direct verification and implementation in cell-biology experiments, where localization patterns and protein-synthesis rates may be monitored by fluorescence microscopy in single cells and populations.