Evidence map›Paper›PMID 24082144›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2013

Molecular crowding limits translation and cell growth.

Stefan Klumpp, Matthew Scott, Steen Pedersen, Terence Hwa

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 169 papers.

0numbers the graph read from it
0cells of the map it votes in
169citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

169 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. mBio · 2026
    Article
  9. Article
  10. The selfish ribosome.PLoS biology · 2026
    Article
  11. Article
  12. Article
  13. Review
  14. Review
  15. Dynamic Constrained Allocation Flux Balance Analysis (dCAFBA).Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

109 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Stefan KlumppMax Planck Institute of Colloids and Interfaces, 14424 Potsdam, Germany.
Matthew Scott
Steen Pedersen
Terence Hwa

Funding

Quantitative Studies of Bacterial Growth PhysiologyR01GM095903 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI HWA, TERENCE · 2011 to 2023
$3.8M
NIGMS NIH HHS R01 GM095903NIGMS NIH HHS R01-GM095903
6 · The paper itself

Abstract

Bacterial growth is crucially dependent on protein synthesis and thus on the cellular abundance of ribosomes and related proteins. Here, we show that the slow diffusion of the bulky tRNA complexes in the crowded cytoplasm imposes a physical limit on the speed of translation, which ultimately limits the rate of cell growth. To study the required allocation of ancillary translational proteins to alleviate the effect of molecular crowding, we develop a model for cell growth based on a coarse-grained partitioning of the proteome. We find that coregulation of ribosome- and tRNA-affiliated proteins is consistent with measured growth-rate dependencies and results in near-optimal allocation over a broad range of growth rates. The analysis further resolves a long-standing controversy in bacterial growth physiology concerning the growth-rate dependence of translation speed and serves as a caution against premature identification of phenomenological parameters with mechanistic processes.

Indexed as

Models, BiologicalEscherichia coliEscherichia coli ProteinsProtein BiosynthesisProteomeRNA, BacterialRNA, TransferEscherichia coli ProteinsProteomeRNA, BacterialRNA, Transfer

Identifiers

PMID24082144
PMCPMC3801028

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.