Evidence map›Paper›PMID 40349169›Full record

ArticleThe ISME journal2025

Drug delivery dynamics dictate evolution of bacterial antibiotic responses.

John C Crow, Hao Geng, Christopher J Geiger, Timothy J Sullivan, Shannon M Soucy, Daniel Schultz

Abstract read
In one paragraph

Article in The ISME journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

6 authors.

John C CrowDepartment of Microbiology & Immunology, Dartmouth - Geisel School of Medicine, Hanover, NH 03755, United States.ORCID 0009-0005-3734-7782
Hao GengDepartment of Microbiology & Immunology, Dartmouth - Geisel School of Medicine, Hanover, NH 03755, United States.
Christopher J GeigerDepartment of Microbiology & Immunology, Dartmouth - Geisel School of Medicine, Hanover, NH 03755, United States.ORCID 0000-0001-6690-2005
Timothy J SullivanDepartment of Biomedical Data Science, Dartmouth - Geisel School of Medicine, Hanover, NH 03755, United States.
Shannon M SoucyDepartment of Biomedical Data Science, Dartmouth - Geisel School of Medicine, Hanover, NH 03755, United States.ORCID 0000-0001-8672-316X
Daniel SchultzDepartment of Microbiology & Immunology, Dartmouth - Geisel School of Medicine, Hanover, NH 03755, United States.ORCID 0000-0002-3080-3416

Funding

Translational Engineering in Cancer (TEC)P30CA023108 · NCI · DARTMOUTH COLLEGE · PI Fred W Kolling IV · 1985 to 2026
$91.3M
Zhao - Proj 2P20GM130454 · NIGMS · DARTMOUTH COLLEGE · PI Li Song · 2019 to 2026
$27.2M
Acquisition of the NextSeq2000 Sequencing platform to Increase Next Generation Sequencing Throughput While Reducing Costs at DartmouthS10OD030242 · OD · DARTMOUTH COLLEGE · PI KOLLING IV, FRED W · 2021 to 2021
$321k
10X Genomics Chromium Single-cell Sequencing to Expand Research At DartmouthS10OD025235 · OD · DARTMOUTH COLLEGE · PI TOMLINSON, CRAIG R · 2018 to 2018
$125k
Dartmouth Center for Quantitative BiologyGenomic Data Science CoreGenomics and Molecular Biology Shared ResourceNCI Cancer Center Support 5P30CA023108NCI NIH HHS P30 CA023108NIGMS NIH HHS P20 GM130454NIGMS NIH HHS P20GM130454NIH HHS 1S10OD030242NIH HHS S10 OD025235NIH HHS S10OD025235NIH HHS S10 OD030242NSF/PHY 2412766
6 · The paper itself

Abstract

Microbes inhabit natural environments that are remarkably dynamic. Therefore, microbes harbor regulated genetic mechanisms to sense shifts in conditions and induce the appropriate responses. Recent studies suggest that the initial evolution of microbes occupying new niches favors mutations in regulatory pathways. However, it is not clear how this evolution is affected by how quickly conditions change (i.e. dynamics), or which mechanisms are commonly used to implement new regulation. Here, we perform experimental evolution on continuous cultures of Escherichia coli carrying the tetracycline resistance tet operon to identify specific mutations that adapt drug responses to different dynamic regimens of drug administration. We find that cultures evolved under gradually increasing tetracycline concentrations show no mutations in the tet operon, but instead a predominance of fine-tuning mutations increasing the affinity of an alternative efflux pump AcrB to tetracycline. When cultures are instead periodically exposed to large drug doses, all populations evolved transposon insertions in repressor TetR, resulting in loss of regulation and constitutive expression of efflux pump TetA. We use a mathematical model of the dynamics of antibiotic responses to show that sudden exposure to large drug concentrations overwhelm regulated responses, which cannot induce resistance fast enough, resulting in selection for constitutive expression of resistance. These results help explain the frequent loss of regulation of antibiotic resistance by pathogens evolved in clinical environments. Our experiment supports the notion that initial evolution in new ecological niches proceeds largely through regulatory mutations and suggests that transposon insertions are the main mechanism driving this process.

Indexed as

Anti-Bacterial AgentsEscherichia coliTetracyclineAntiportersATP-Binding Cassette, Sub-Family C ProteinsBacterial ProteinsEscherichia coli ProteinsEvolution, MolecularGene Expression Regulation, BacterialMutationOperonTetracycline ResistanceAcrB protein, E coliAnti-Bacterial AgentsAntiportersATP-Binding Cassette, Sub-Family C ProteinsBacterial ProteinsEscherichia coli ProteinstetA protein, BacteriaTetracyclineantibiotic resistancegene regulationmicrobial evolution

Identifiers

PMID40349169
PMCPMC12086408

What OpenQuestion holds

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LicenceCC BY
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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.