Evidence map›Paper›PMID 37945946›Full record

ArticleNature ecology & evolution2023

Selection of a de novo gene that can promote survival of Escherichia coli by modulating protein homeostasis pathways.

Idan Frumkin, Michael T Laub

Open access · hybridAbstract read
In one paragraph

Article in Nature ecology & evolution, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
7.8field-weighted citation impact, top 2% 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

21 citing papers in PubMed, 25 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Something from nothing: The birth of new phage defense genes.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  5. Article
  6. De Novo Genes: Current Status and Future Goals.Genome biology and evolution · 2025
    Article
  7. Article
  8. Article
  9. Emergence of antiphage functions from random sequence libraries reveals mechanisms of gene birth.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  10. Review
  11. High-throughput discovery of inhibitory protein fragments with AlphaFold.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  12. Article
  13. De Novo Genes.Annual review of genetics · 2024
    Review
  14. Large Roles of Small Proteins.Annual review of microbiology · 2024
    Review
  15. High-throughput discovery of inhibitory protein fragments with AlphaFold.bioRxiv : the preprint server for biology · 2024
    Article
  16. Article
  17. Article
  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

2 authors at 2 institutions in 1 country.

Idan FrumkinDepartment of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA.
Michael T LaubDepartment of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA. laub@mit.edu.ORCID 0000-0002-8288-7607
Howard Hughes Medical Institute · USMassachusetts Institute of Technology · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cellular novelty can emerge when non-functional loci become functional genes in a process termed de novo gene birth. But how proteins with random amino acid sequences beneficially integrate into existing cellular pathways remains poorly understood. We screened ~10

Indexed as

Escherichia coliEscherichia coli ProteinsDNA-Binding ProteinsEndoribonucleasesProteostasisDNA-Binding ProteinsEndoribonucleasesEscherichia coli ProteinsMazF protein, E coli

Identifiers

PMID37945946
PMCPMC10697842
OpenAlexW4388522901

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.