The key parameters that govern translation efficiency

TL;DR

This paper models mRNA translation as a stochastic traffic flow, identifying key parameters that influence efficiency, and provides design principles for optimizing protein synthesis based on theoretical analysis and yeast data.

Contribution

It introduces a continuum limit analysis of the inhomogeneous $ ext{-}TASEP$ model to identify parameters affecting translation efficiency and offers practical design principles.

Findings

Closed-form expressions for translation current and ribosomal densities.

Characterization of phase transitions in translation dynamics.

Validation with yeast ribosome profiling data.

Abstract

Translation of mRNA into protein is a fundamental yet complex biological process with multiple factors that can potentially affect its efficiency. Here, we study a stochastic model describing the traffic flow of ribosomes along the mRNA (namely, the inhomogeneous $\ell$-TASEP), and identify the key parameters that govern the overall rate of protein synthesis, sensitivity to initiation rate changes, and efficiency of ribosome usage. By analyzing a continuum limit of the model, we obtain closed-form expressions for stationary currents and ribosomal densities, which agree well with Monte Carlo simulations. Furthermore, we completely characterize the phase transitions in the system, and by applying our theoretical results, we formulate design principles that detail how to tune the key parameters we identified to optimize translation efficiency. Using ribosome profiling data from S. cerevisiae, we shows that its translation system is generally consistent with these principles. Our theoretical results have implications for evolutionary biology, as well as synthetic biology.