ArticleeLife2017
Principles of cellular resource allocation revealed by condition-dependent proteome profiling.
Article in eLife, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 126 papers.
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Who cites it
126 citing papers in PubMed, 262 citations in OpenAlex.
- Bridging energy and proteome allocation models allows prediction of the resource cost of traits across environments.PLoS biology · 2026Article
- uORF-mediated translational control of CAK and Cdk activation in response to low nutrients in yeast.EMBO reports · 2026Article
- Peroxisomal Import Stress Drives Cellular Senescence through SCAF1-dependent Suppression of Mitoribosome Biogenesis.bioRxiv : the preprint server for biology · 2026Article
- The proportional scaling of mRNA and ribosome concentrations controls eukaryotic cell growth.Nature cell biology · 2026Article
- An adaptable, self-organizing, single-cell morphology circuit optimizes suctorian predatory trap structure.Current biology : CB · 2026Article
- Dynamic redistribution of eIF4F controls cap-dependent translation initiation.bioRxiv : the preprint server for biology · 2026Article
- Experimental evolution of cellular miniaturization reveals a putative mechanism for cell size evolution.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Energy-translation coupling limits anaerobic yeast growth.Nature communications · 2026Article
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- The return of metabolism: biochemistry and physiology of glycolysis.Biological reviews of the Cambridge Philosophical Society · 2026Review
- NMD-mediated control of Tor influences adaptation to nutrient and temperature conditions inbioRxiv : the preprint server for biology · 2026Article
- Whole-cell modeling predicts alternative proteome allocation strategies in the archaeon Methanococcus maripaludis.Scientific reports · 2026Article
- Probing the proteome.eLife · 2026Article
- Lipid accumulation in nitrogen and phosphorus-limited yeast is caused by less growth-related dilution.Metabolic engineering · 2026Article
- Fundamental errors in RNA velocity arising from the omission of cell growth.bioRxiv : the preprint server for biology · 2025Article
- A self-organizing single-cell morphology circuit optimizesbioRxiv : the preprint server for biology · 2025Article
- Non-canonical resource allocation in heterotrophically growing Thermoanaerobacter kivui.Nature communications · 2025Article
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- Article
- Diverse oncogenes use common mechanisms to drive growth of major forms of human cancer.Science advances · 2025Article
66 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Growing cells coordinate protein translation with metabolic rates. Central to this coordination is ribosome production. Ribosomes drive cell growth, but translation of ribosomal proteins competes with production of non-ribosomal proteins. Theory shows that cell growth is maximized when all expressed ribosomes are constantly translating. To examine whether budding yeast function at this limit of full ribosomal usage, we profiled the proteomes of cells growing in different environments. We find that cells produce excess ribosomal proteins, amounting to a constant ≈8% of the proteome. Accordingly, ≈25% of ribosomal proteins expressed in rapidly growing cells does not contribute to translation. Further, this fraction increases as growth rate decreases and these excess ribosomal proteins are employed when translation demands unexpectedly increase. We suggest that steadily growing cells prepare for conditions that demand increased translation by producing excess ribosomes, at the expense of lower steady-state growth rate.
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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.