A universal multi-turnpike principle for optimal allocation of translational resources
Abstract
mRNA translation in the cell requires efficient allocation of shared and limited resources including free ribosomes, tRNA molecules, and initiation factors across multiple transcripts. Using a network of dynamic mathematical models for ribosome flow along the mRNA, we pose the problem of maximizing the total steady-state protein production rate in the cell under a shared and limited total budget for all translation rates in all the transcripts. We prove that the optimal solution of this resource...
Description / Details
mRNA translation in the cell requires efficient allocation of shared and limited resources including free ribosomes, tRNA molecules, and initiation factors across multiple transcripts. Using a network of dynamic mathematical models for ribosome flow along the mRNA, we pose the problem of maximizing the total steady-state protein production rate in the cell under a shared and limited total budget for all translation rates in all the transcripts. We prove that the optimal solution of this resource allocation problem admits a multi-turnpike structure: in each mRNA, the transition rates are high and nearly uniform along the bulk of the coding region, with lower and varying rates near the boundaries of the~mRNA. Our results are based on the emergence of hierarchical optimality: regardless of how resources are allocated among genes, every transcript should internally organize itself in essentially the same way. This suggests that to optimize the overall production rate it is sufficient to regulate the initiation and termination regions in each transcript. Remarkably, this universal turnpike structure holds for any number of transcripts, arbitrary transcript lengths, and various optimization criteria.This agrees with observed conserved translational phenomena, such as codon ramps and initiation-dominated regulation. Our findings may also provide guidelines for the rational design of intracellular circuits operating under translational control.
Source: arXiv:2607.25043v1 - http://arxiv.org/abs/2607.25043v1 PDF: https://arxiv.org/pdf/2607.25043v1 Original Link: http://arxiv.org/abs/2607.25043v1
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Jul 29, 2026
Biotechnology
Biology
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