bioRxiv preprint doi: https://doi.org/10.1101/2021.04.02.438287; this version posted April 4, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. First-principles model of optimal translation factors stoichiometry Jean-Benoît Lalanne1;2;# and Gene-Wei Li1;y 1Department of Biology, and 2Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. #Present address: Department of Genome Sciences, University of Washington, Seattle, WA 98105, USA. yCorresponding author:
[email protected] Abstract Enzymatic pathways have evolved uniquely preferred protein expression stoichiometry in living cells, but our ability to predict the optimal abundances from basic properties remains underdeveloped. Here we report a biophysical, first-principles model of growth optimization for core mRNA transla- tion, a multi-enzyme system that involves proteins with a broadly conserved stoichiometry spanning two orders of magnitude. We show that a parsimonious flux model constrained by proteome allocation is sufficient to predict the conserved ratios of translation factors through maximization of ribosome usage The analytical solutions, without free parameters, provide an interpretable framework for the observed hierarchy of expression levels based on simple biophysical properties, such as diffusion con- stants and protein sizes. Our results provide an intuitive and quantitative understanding for the construction of a central process of life, as well as a path toward rational design of pathway-specific enzyme expression stoichiometry. 1 bioRxiv preprint doi: https://doi.org/10.1101/2021.04.02.438287; this version posted April 4, 2021.