Evidence map›Paper›PMID 42303634›Full record

ArticleNPJ systems biology and applications2026

Growth rate-dependent mutations and phenotypic switching facilitate rapid adaptation.

Anton Grishechkin, Omer Karin

Abstract read
In one paragraph

Article in NPJ systems biology and applications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Anton GrishechkinDepartment of Mathematics, Imperial College London, London, UK.
Omer KarinDepartment of Mathematics, Imperial College London, London, UK. o.karin@imperial.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The mutation rates of many species are regulated in response to internal and external conditions. Studies in several model organisms have shown that mutation rates can be modulated by the organism's growth rate, particularly through stress-induced mutagenesis. Here, we investigate the functional consequences of this coupling. Using a model of asexual evolution on a high-dimensional, single-peaked fitness landscape, we show that regulating mutation rate through growth rate provides an efficient strategy for rapid adaptation. This mechanism maximizes growth by balancing mutation and selection pressures. We approximate the optimal coupling as a biphasic response function that prescribes a low, constant mutation rate at high growth rates, which gradually increases once growth falls below a critical threshold. This adaptive strategy depends on two key parameters: mutational gain and critical growth rate, both determined by environmental conditions. This raises the question of how organisms establish these parameters in fluctuating environments. We demonstrate that weak selection in well-adapted populations, combined with long-term phenotypic fluctuations, can generate variability in these parameters. Such standing variation prepares populations for rapid evolution following environmental change. Our findings connect this adaptive strategy to specific molecular regulatory circuits and provide predictions for sequential antibiotic treatment regimens.

Indexed as

Adaptation, PhysiologicalMutationMutation RateBiological EvolutionModels, GeneticPhenotypeSelection, Genetic

Identifiers

PMID42303634
PMCPMC13635105

What OpenQuestion holds

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Registered trials

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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.