ArticlePNAS nexus2023
Optimization of ribosome utilization in
Article in PNAS nexus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
8 citing papers in PubMed.
- Article
- Bacterial gene 5' ends have unusual mutation rates that can mislead tests of selection.PLoS biology · 2025Article
- Article
- Sucrose-driven carbon redox rebalancing eliminates the Crabtree effect and boosts energy metabolism in yeast.Nature communications · 2025Article
- Why AGG is associated with high transgene output: passenger effects and their implications for transgene design.NAR genomics and bioinformatics · 2025Article
- Understanding the regulation of protein synthesis under stress conditions.Biophysical journal · 2024Article
- Decoding stoichiometric protein synthesis inBiophysical reports · 2023Article
- Genes for highly abundant proteins in Escherichia coli avoid 5' codons that promote ribosomal initiation.PLoS computational biology · 2023Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Resource optimization in protein synthesis is often looked at from the perspective of translation efficiency-the rate at which proteins are synthesized from a single transcript. The higher the rate of protein synthesis, the more efficiently a transcript is translated. However, the production of a ribosome consumes significantly more cellular resources than an mRNA molecule. Therefore, there should be a stronger selection pressure for optimizing ribosome usage than translation efficiency. This paper reports strong evidence of such optimization which becomes more prominent in highly expressed transcripts that consume a significant amount of cellular resources. The ribosome usage is optimized by the biases in codon usage and translation initiation rates. This optimization significantly reduces the ribosome requirement in
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Registered trials
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