Evidence map›Paper›PMID 32437534›Full record

ArticleMolecular biology and evolution2020

Collateral Toxicity Limits the Evolution of Bacterial Release Factor 2 toward Total Omnipotence.

Hind Abdalaal, Shreya Pundir, Xueliang Ge, Suparna Sanyal, Joakim Näsvall

Abstract read
In one paragraph

Article in Molecular biology and evolution, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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

5 citing papers in PubMed.

  1. Article
  2. Article
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  4. Article
  5. Comparative Analysis of anti-Shine- Dalgarno Function inFrontiers in molecular biosciences · 2021
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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

5 authors.

Hind AbdalaalDepartment of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.
Shreya PundirDepartment of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden.
Xueliang GeDepartment of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden.
Suparna SanyalDepartment of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden.
Joakim NäsvallDepartment of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

When new genes evolve through modification of existing genes, there are often tradeoffs between the new and original functions, making gene duplication and amplification necessary to buffer deleterious effects on the original function. We have used experimental evolution of a bacterial strain lacking peptide release factor 1 (RF1) in order to study how peptide release factor 2 (RF2) evolves to compensate the loss of RF1. As expected, amplification of the RF2-encoding gene prfB to high copy number was a rapid initial response, followed by the appearance of mutations in RF2 and other components of the translation machinery. Characterization of the evolved RF2 variants by their effects on bacterial growth rate, reporter gene expression, and in vitro translation termination reveals a complex picture of reduced discrimination between the cognate and near-cognate stop codons and highlights a functional tradeoff that we term "collateral toxicity." We suggest that this type of tradeoff may be a more serious obstacle in new gene evolution than the more commonly discussed evolutionary tradeoffs between "old" and "new" functions of a gene, as it cannot be overcome by gene copy number changes. Further, we suggest a model for how RF2 autoregulation responds to alterations in the demand not only for RF2 activity but also for RF1 activity.

Indexed as

Codon, TerminatorEvolution, MolecularPeptide Termination FactorsSalmonella entericaCodon, Terminatorpeptide chain termination release factor 2Peptide Termination Factorsexperimental evolutionnew gene evolutionpeptide release factortradeoff

Identifiers

PMID32437534
PMCPMC7530605

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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.