Cell-free prediction of protein expression costs for growing cells

Abstract

Translating heterologous proteins places significant burden on host cells, consuming expression resources leading to slower cell growth and productivity. Yet predicting the cost of protein production for any gene is a major challenge, as multiple processes and factors determine translation efficiency. Here, to enable prediction of the cost of gene expression in bacteria, we describe a standard cell-free lysate assay that determines the relationship betweenin vivoand cell-free measurements and γ, a relative measure of the resource consumption when a given protein is expressed. When combined with a computational model of translation, this enables prediction of thein vivoburden placed on growingE. colicells for a variety of proteins of different functions and lengths. Using this approach, we can predict the burden of expressing multigene operons of different designs and differentiate between the fraction of burden related to gene expression compared to action of a metabolic pathway.