Evidence map›Paper›PMID 25086000›Full record

ArticleMolecular biology and evolution2014

Amino Acid metabolism conflicts with protein diversity.

Teresa Krick, Nina Verstraete, Leonardo G Alonso, David A Shub, Diego U Ferreiro, Michael Shub, Ignacio E Sánchez

Open access · hybridAbstract read
In one paragraph

Article in Molecular biology and evolution, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
1.4field-weighted citation impact, top 19% of its field
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

25 citing papers in PubMed, 59 citations in OpenAlex.

  1. Dynamic [Research square · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Yeast has evolved to minimize protein resource cost for synthesizing amino acids.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article
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

7 authors at 5 institutions in 2 countries.

Teresa KrickDepartamento de Matemática, Facultad de Ciencias Exactas y Naturales and IMAS-CONICET, Universidad de Buenos Aires, Buenos Aires, Argentina.
Nina VerstraeteProtein Physiology Laboratory, Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales and IQUIBICEN-CONICET, Universidad de Buenos Aires, Buenos Aires, Argentina.
Leonardo G AlonsoFundación Instituto Leloir-IIBBA CONICET, Buenos Aires, Argentina.
David A ShubDepartment of Biological Sciences, University at Albany, State University of New York.
Diego U FerreiroProtein Physiology Laboratory, Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales and IQUIBICEN-CONICET, Universidad de Buenos Aires, Buenos Aires, Argentina.
Michael ShubIMAS-CONICET, Universidad de Buenos Aires, Buenos Aires, Argentina.
Ignacio E SánchezProtein Physiology Laboratory, Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales and IQUIBICEN-CONICET, Universidad de Buenos Aires, Buenos Aires, Argentina isanchez@qb.fcen.uba.ar.
Consejo Nacional de Investigaciones Científicas y Técnicas · ARUniversity of Buenos Aires · ARAlbany State University · USFundación Ciencias Exactas y Naturales · ARFundación Instituto Leloir · AR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The 20 protein-coding amino acids are found in proteomes with different relative abundances. The most abundant amino acid, leucine, is nearly an order of magnitude more prevalent than the least abundant amino acid, cysteine. Amino acid metabolic costs differ similarly, constraining their incorporation into proteins. On the other hand, a diverse set of protein sequences is necessary to build functional proteomes. Here, we present a simple model for a cost-diversity trade-off postulating that natural proteomes minimize amino acid metabolic flux while maximizing sequence entropy. The model explains the relative abundances of amino acids across a diverse set of proteomes. We found that the data are remarkably well explained when the cost function accounts for amino acid chemical decay. More than 100 organisms reach comparable solutions to the trade-off by different combinations of proteome cost and sequence diversity. Quantifying the interplay between proteome size and entropy shows that proteomes can get optimally large and diverse.

Indexed as

GenomeModels, BiologicalAdenosine TriphosphateAmino AcidsAmino Acid SequenceEntropyGenomic Structural VariationLeast-Squares AnalysisMolecular Sequence DataProtein BiosynthesisProteomeAdenosine TriphosphateAmino AcidsProteomeamino acid decayamino acid metabolisminformation theorymaximum entropyproteomics

Identifiers

PMID25086000
PMCPMC4209132
OpenAlexW2108967474

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.