Evidence map›Paper›PMID 40729517›Full record

ArticleMolecular biology and evolution2025

Antimutator and Mutational Spectrum Effects Can Combine to Reduce Evolutionary Potential in Escherichia coli ΔnudJ.

Rowan Green, Huw Richards, Deniz Ozbilek, Francesca Tyrrell, Victoria Barton, Ziang Zhang, Simon C Lovell, Danna R Gifford, Mato Lagator, Andrew J McBain and 2 more

Abstract read
In one paragraph

Article in Molecular biology and evolution, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Extended sequence context shapes mutational bias inProceedings of the National Academy of Sciences of the United States of America · 2026
    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

12 authors.

Rowan GreenSchool of Natural Sciences, Faculty of Science and Engineering, University of Manchester, Manchester, UK.ORCID 0000-0002-2147-9087
Huw RichardsSchool of Natural Sciences, Faculty of Science and Engineering, University of Manchester, Manchester, UK.ORCID 0000-0003-4731-3605
Deniz OzbilekSchool of Biological Sciences, Faculty of Biology, Medicine & Health, University of Manchester, Manchester, UK.ORCID 0000-0003-4638-7733
Francesca TyrrellSchool of Biological Sciences, Faculty of Biology, Medicine & Health, University of Manchester, Manchester, UK.ORCID 0009-0009-1857-8146
Victoria BartonSchool of Biological Sciences, Faculty of Biology, Medicine & Health, University of Manchester, Manchester, UK.ORCID 0009-0005-2636-0703
Ziang ZhangSchool of Biological Sciences, Faculty of Biology, Medicine & Health, University of Manchester, Manchester, UK.ORCID 0009-0001-6073-6349
Simon C LovellSchool of Biological Sciences, Faculty of Biology, Medicine & Health, University of Manchester, Manchester, UK.ORCID 0000-0002-4092-8458
Danna R GiffordSchool of Biological Sciences, Faculty of Biology, Medicine & Health, University of Manchester, Manchester, UK.ORCID 0000-0002-4990-8816
Mato LagatorSchool of Biological Sciences, Faculty of Biology, Medicine & Health, University of Manchester, Manchester, UK.ORCID 0000-0001-7847-3594
Andrew J McBainSchool of Health Sciences, Faculty of Biology, Medicine & Health, University of Manchester, Manchester, UK.ORCID 0000-0002-5255-5425
Rok KrašovecSchool of Biological Sciences, Faculty of Biology, Medicine & Health, University of Manchester, Manchester, UK.ORCID 0000-0003-4490-5605
Christopher G KnightSchool of Natural Sciences, Faculty of Science and Engineering, University of Manchester, Manchester, UK.ORCID 0000-0001-9815-4267

Funding

Biotechnology and Biological Sciences Research Council DTP BB/T008725/1Future Leaders Fellowship MR/T021225/1UK Research and Innovation
6 · The paper itself

Abstract

The rate of spontaneous mutation is a key factor in determining the capacity of a population to adapt to a novel environment, for example, a bacterial population exposed to antibiotics. Genetic and environmental factors controlling the mutation rate commonly also cause shifts in the relative rates of different mutational classes, i.e. the mutational spectrum. When the mutational spectrum is altered, the relatively enriched and depleted mutations may differ in their fitness effects. Here, we explore how a reduced mutation rate and altered mutational spectrum can contribute to adaptation in Escherichia coli. We measure mutation rates across a set of Nudix hydrolase deletants, finding multiple strains with an antimutator phenotype. We focus on the antimutator ΔnudJ, which can cause a 6-fold mutation rate reduction relative to the wildtype, with an altered mutational spectrum biased towards A > C transversions. Its reduced mutation rate, most pronounced at low population densities, appears to occur via NudJ's role in nucleotide and/or prenyl metabolism, with a reduced internal ATP pool. Its effects may be reversed by mutations to genes, including waaZ, affecting the outer membrane. Not only does nudJ deletion reduce the probability of antibiotic resistance arising at all but through enhancing an existing hotspot for low fitness A > C rifampicin resistance mutations reduces the expected fitness of strains when resistance does arise. Thus, our findings with ΔnudJ suggest future anti-evolution drug strategies could suppress spontaneous resistance evolution not only through minimizing resistance mutations but also by specifically limiting access to the fittest mutations.

Indexed as

Escherichia coliEscherichia coli ProteinsPyrophosphatasesBiological EvolutionEvolution, MolecularGenetic FitnessMutationMutation RateEscherichia coli ProteinsPyrophosphatasesanti-evolution drugsdensity associated mutation rate plasticitydistribution of fitness effectsmutational signaturemutational spectrummutation ratemutation rate plasticityNudixNudJrifampicinRpoB

Identifiers

PMID40729517
PMCPMC12359138

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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.