Evidence map›Paper›PMID 40478208›Full record

ArticleMolecular biology and evolution2025

Tripartite Loops Reverse Antibiotic Resistance.

Farhan R Chowdhury, Brandon L Findlay

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 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. Article
  2. Sequential antibiotic exposure restores antibiotic susceptibility.The Journal of antimicrobial chemotherapy · 2025
    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

2 authors.

Farhan R ChowdhuryDepartment of Biology, Concordia University, Montréal, Québec H4B 1R6, Canada.ORCID 0000-0001-7251-4957
Brandon L FindlayDepartment of Biology, Concordia University, Montréal, Québec H4B 1R6, Canada.ORCID 0000-0001-7083-2513

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antibiotic resistance threatens to undo many of the advancements of modern medicine. A slow antibiotic development pipeline makes it impossible to outpace bacterial evolution, making alternative strategies essential to combat resistance. In this study, we introduce cyclic antibiotic regimens composed of 3 drugs or "tripartite loops" to contain resistance within a closed drug cycle. Through 424 discrete adaptive laboratory evolution experiments we show that as bacteria sequentially evolve resistance to the drugs in a loop, they continually trade their past resistance for fitness gains, reverting back to sensitivity. Through fitness and genomic analyses, we find that tripartite loops guide bacterial strains toward evolutionary paths that mitigate fitness costs and reverse resistance to component drugs in the loops and drive levels of resensitization not achievable through previously suggested pairwise regimens. We then apply this strategy to reproducibly resensitize or eradicate 4 drug-resistant clinical isolates over the course of 216 evolutionary experiments. Resensitization occurrs even when bacteria adapted through plasmid-bound mutations instead of chromosomal changes. Combined, these findings outline a sequential antibiotic regimen with high resensitization frequencies, which may improve the clinical longevity of existing antibiotics even in the face of antibiotic resistance.

Indexed as

Anti-Bacterial AgentsDrug Resistance, BacterialBacteriaEvolution, MolecularGenetic FitnessAnti-Bacterial Agentscollateral sensitivitycyclic therapyepistasissequential antibiotic therapysoft agar gradient evolutiontripartite loops

Identifiers

PMID40478208
PMCPMC12164588

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.