Evidence map›Paper›PMID 41744059›Full record

ArticleThe ISME journal2026

Resistance variation and bacterial interactions shape adaptation of a genetically diverse pathogen population to antibiotic therapy.

Aditi Batra, Leif Tueffers, Kira Haas, Tabea Loeblein, João Botelho, Michael Habig, Daniel Schuetz, Gabija Sakalyte, Florian Buchholz, Ernesto Berríos-Caro and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The ISME journal, 2026. 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. Pyocyanin produced byAntimicrobial agents and chemotherapy · 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

13 authors.

Aditi BatraDepartment of Evolutionary Ecology and Genetics, Kiel University, 24098 Kiel, Germany.ORCID 0000-0001-6910-3532
Leif TueffersDepartment of Evolutionary Ecology and Genetics, Kiel University, 24098 Kiel, Germany.ORCID 0000-0001-5496-9456
Kira HaasDepartment of Evolutionary Ecology and Genetics, Kiel University, 24098 Kiel, Germany.
Tabea LoebleinDepartment of Evolutionary Ecology and Genetics, Kiel University, 24098 Kiel, Germany.
João BotelhoDepartment of Evolutionary Ecology and Genetics, Kiel University, 24098 Kiel, Germany.
Michael HabigFungal Evolutionary Genetics, Kiel University, 24098 Kiel, Germany.
Daniel SchuetzDepartment of Evolutionary Ecology and Genetics, Kiel University, 24098 Kiel, Germany.
Gabija SakalyteInstitute for Experimental Medicine, Kiel University, 24098 Kiel, Germany.
Florian BuchholzDepartment of Evolutionary Ecology and Genetics, Kiel University, 24098 Kiel, Germany.ORCID 0000-0003-3882-9132
Ernesto Berríos-CaroDepartment of Evolutionary Ecology and Genetics, Kiel University, 24098 Kiel, Germany.
Hildegard UeckerResearch Group Stochastic Evolutionary Dynamics, Department of Theoretical Biology, Max-Planck-Institute for Evolutionary Biology, 24306 Plön, Germany.ORCID 0000-0001-9435-2813
Daniel UnterwegerInstitute for Experimental Medicine, Kiel University, 24098 Kiel, Germany.
Hinrich SchulenburgDepartment of Evolutionary Ecology and Genetics, Kiel University, 24098 Kiel, Germany.ORCID 0000-0002-1413-913X

Funding

Deutsche ForschungsgemeinschaftExcellence Cluster Precision Medicine in Chronic Inflammation 2167-390884018Walter Benjamin 512851323Walter Benjamin BE 8013/1-1
6 · The paper itself

Abstract

Antimicrobial resistance (AMR) poses a major threat to global human health. The emergence and spread of AMR is usually studied for single pathogen lineages. Therefore, we currently have only limited knowledge on the causes and dynamics of resistance evolution in polymicrobial or multistrain infections that involve different pathogen species or strains, respectively, even though these kinds of infections are widespread. To address these current knowledge gaps, we here used the opportunistic human pathogen Pseudomonas aeruginosa as a model to investigate how AMR evolves in populations with different genetically distinct strains (multistrain communities). By using controlled evolution experiments, extensive phenotyping and genome sequence analysis, we demonstrate that the response to antibiotic selection is shaped by a combination of strain-specific resistance profiles, ecological interactions between strains, and metapopulation structure. Moreover, the likelihood of de novo resistance evolution varied in dependence on mutation rates for resistance. A second independent evolution experiment emphasized the central role of strain variation and strain-strain interactions during adaptation. We conclude that AMR evolution in genetically diverse pathogen populations is driven by the interplay of ecological and evolutionary dynamics, thus deserving particular attention during treatment of polymicrobial infections.

Indexed as

Anti-Bacterial AgentsDrug Resistance, BacterialPseudomonas aeruginosaAdaptation, PhysiologicalEvolution, MolecularGenetic VariationHumansPseudomonas InfectionsAnti-Bacterial Agentsantimicrobial resistance evolutioneco-evolutionary feedbackevolution experimentpolymicrobial infectionPseudomonas aeruginosa

Identifiers

PMID41744059
PMCPMC13007599

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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.