ArticlePloS one2012
On ribosome load, codon bias and protein abundance.
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 39 citations in OpenAlex.
- Codon usage bias in yeasts and its correlation with gene expression, growth temperature, and protein structure.Frontiers in microbiology · 2024Article
- The active free-living bathypelagic microbiome is largely dominated by rare surface taxa.ISME communications · 2024Article
- Stochastic dynamics and ribosome-RNAP interactions in transcription-translation coupling.Biophysical journal · 2023Article
- Environment-specificity and universality of the microbial growth law.Communications biology · 2022Article
- Variation in upstream open reading frames contributes to allelic diversity in maize protein abundance.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Quantitative Control for Stoichiometric Protein Synthesis.Annual review of microbiology · 2021Article
- High-throughput microbioreactor provides a capable tool for early stage bioprocess development.Scientific reports · 2021Article
- Algorithms for ribosome traffic engineering and their potential in improving host cells' titer and growth rate.Scientific reports · 2020Article
- Translational Selection for Speed Is Not Sufficient to Explain Variation in Bacterial Codon Usage Bias.Genome biology and evolution · 2018Article
- Making life difficult for Clostridium difficile: augmenting the pathogen's metabolic model with transcriptomic and codon usage data for better therapeutic target characterization.BMC systems biology · 2017Article
- Growth rates and rRNA content of four marine bacteria in pure cultures and in the Delaware estuary.The ISME journal · 2016Article
- Predictive analytics of environmental adaptability in multi-omic network models.Scientific reports · 2015Article
- A portable expression resource for engineering cross-species genetic circuits and pathways.Nature communications · 2015Article
- Codon usage and codon context bias in Xanthophyllomyces dendrorhous.BMC genomics · 2015Article
- How do bacteria tune translation efficiency?Current opinion in microbiology · 2015Review
- A critical analysis of codon optimization in human therapeutics.Trends in molecular medicine · 2014Review
- Molecular crowding limits translation and cell growth.Proceedings of the National Academy of Sciences of the United States of America · 2013Article
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Authors and funding
3 authors at 3 institutions in 2 countries.
Funding
Abstract
Different codons encoding the same amino acid are not used equally in protein-coding sequences. In bacteria, there is a bias towards codons with high translation rates. This bias is most pronounced in highly expressed proteins, but a recent study of synthetic GFP-coding sequences did not find a correlation between codon usage and GFP expression, suggesting that such correlation in natural sequences is not a simple property of translational mechanisms. Here, we investigate the effect of evolutionary forces on codon usage. The relation between codon bias and protein abundance is quantitatively analyzed based on the hypothesis that codon bias evolved to ensure the efficient usage of ribosomes, a precious commodity for fast growing cells. An explicit fitness landscape is formulated based on bacterial growth laws to relate protein abundance and ribosomal load. The model leads to a quantitative relation between codon bias and protein abundance, which accounts for a substantial part of the observed bias for E. coli. Moreover, by providing an evolutionary link, the ribosome load model resolves the apparent conflict between the observed relation of protein abundance and codon bias in natural sequences and the lack of such dependence in a synthetic gfp library. Finally, we show that the relation between codon usage and protein abundance can be used to predict protein abundance from genomic sequence data alone without adjustable parameters.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.