Evidence map›Paper›PMID 42726510›Full record

ReviewMicrobiology (Reading, England)2026

Simulating the host niche: balancing complexity and control in the experimental evolution of antibiotic resistance and pathoadaptation.

Juan Hernandez-Bird, Lucas A Meirelles

Abstract readReview
In one paragraph

Review in Microbiology (Reading, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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.

Juan Hernandez-BirdCenter for Computational and Integrative Biology, Massachusetts General Hospital, Boston, MA, USA.
Lucas A MeirellesCenter for Computational and Integrative Biology, Massachusetts General Hospital, Boston, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The 'ESKAPE' pathogens cause the majority of antibiotic-resistant infections in humans, with associated mortality expected to surpass that of cancer by 2050. Outbreak strains of these pathogens often demonstrate a remarkable ability to establish infection and easily acquire novel antimicrobial resistance mechanisms. Because the expression of virulence factors and antimicrobial resistance genes often imposes a fitness cost, successful host-adapted strains must evolve without compromising their ability to colonize the niches found in the human body. The ongoing spread of these multidrug-resistant strains suggests that these bacterial pathogens are actively adapting to antibiotic-treated hosts. With whole-genome sequencing, we can now identify the multiple genetic changes associated with host adaptation and increased antibiotic resistance. Yet, pinpointing the specific mutations responsible for phenotypic shifts through sequencing of clinical isolates remains challenging due to the high mutational load accumulated during infection. For this reason, our understanding of how pathogens evolve within specific host niches, both in the presence and absence of antibiotics, remains limited. Experimental evolution within host tissues now allows us to more accurately simulate the conditions under which antibiotic resistance and pathoadaptations emerge. In this Perspective article, we evaluate some of the systems currently employed, discuss their respective advantages and limitations and introduce engineered human microtissue models as a promising platform for bacterial experimental evolution.

Indexed as

BacteriaDrug Resistance, BacterialHost AdaptationHost-Pathogen InteractionsAdaptation, PhysiologicalAnimalsAnti-Bacterial AgentsBacterial InfectionsEvolution, MolecularHumansMutationVirulence FactorsAnti-Bacterial AgentsVirulence Factorsantibiotic resistancebacterial pathogenesisexperimental evolutionhuman microtissue modelspathoadaptation

Identifiers

PMID42726510
PMCPMC13567839

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.