Evidence map›Paper›PMID 32385156›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2020

Collateral fitness effects of mutations.

Jacob D Mehlhoff, Frank W Stearns, Dahlia Rohm, Buheng Wang, Erh-Yeh Tsou, Nisita Dutta, Meng-Hsuan Hsiao, Courtney E Gonzalez, Alan F Rubin, Marc Ostermeier

Erratum issuedOpen access · bronzeAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
6.5field-weighted citation impact, top 3% 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

24 citing papers in PubMed, 49 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. A null model for the distribution of fitness effects of mutations.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  11. Article
  12. Article
  13. Mutational fitness landscape and drug resistance.Current opinion in structural biology · 2023
    Review
  14. Review
  15. Article
  16. Article
  17. Article
  18. Non-Darwinian Molecular Biology.Frontiers in genetics · 2022
    Review
  19. Article
  20. High throughput and quantitative enzymology in the genomic era.Current opinion in structural biology · 2021
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 2 countries.

Jacob D MehlhoffDepartment of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218.ORCID 0000-0003-1632-5291
Frank W StearnsDepartment of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218.ORCID 0000-0002-2779-9057
Dahlia RohmDepartment of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218.
Buheng WangDepartment of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218.ORCID 0000-0002-0661-376X
Erh-Yeh TsouDepartment of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218.ORCID 0000-0002-5836-163X
Nisita DuttaDepartment of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218.
Meng-Hsuan HsiaoDepartment of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218.ORCID 0000-0002-3190-7081
Courtney E GonzalezDepartment of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218.
Alan F RubinBioinformatics Division, Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia.ORCID 0000-0003-1474-605X
Marc OstermeierDepartment of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218; oster@jhu.edu.
Johns Hopkins University · USThe University of Melbourne · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The distribution of fitness effects of mutation plays a central role in constraining protein evolution. The underlying mechanisms by which mutations lead to fitness effects are typically attributed to changes in protein specific activity or abundance. Here, we reveal the importance of a mutation's collateral fitness effects, which we define as effects that do not derive from changes in the protein's ability to perform its physiological function. We comprehensively measured the collateral fitness effects of missense mutations in the

Indexed as

Evolution, Molecularbeta-LactamasesEscherichia coliEscherichia coli ProteinsGenetic FitnessMutation, Missensebeta-Lactamasesbeta-lactamase TEM-1Escherichia coli Proteinsbeta-lactamasefitness landscapeprotein aggregationprotein evolutionstress response

Identifiers

PMID32385156
PMCPMC7261132
OpenAlexW3023074808

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.