Evidence map›Paper›PMID 41489361›Full record

ReviewApplied and environmental microbiology2026

The plasmid-host fitness landscape: a new paradigm for predicting the fate of mobile resistance.

Hevar N Abdulqadir

Abstract readReview
In one paragraph

Review in Applied and environmental microbiology, 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. Global spread of carbapenem-resistantOne health (Amsterdam, Netherlands) · 2026
    Article
  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

1 author.

Hevar N AbdulqadirMLS Department, Komar University of Science and Technology, Sulaymaniyah, Iraq.ORCID 0009-0001-3783-5998

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The widespread persistence of antimicrobial resistance (AMR) plasmids presents a fundamental challenge to microbial evolution, known as the "plasmid paradox": if these plasmids cause fitness cost, why are they not eliminated by selection? The classical view, which imposed a fixed generic fitness cost, is insufficient to explain their epidemiological success. Here, we propose a new paradigm-the plasmid-host fitness landscape-a multi-dimensional model that takes into account the complex interplay between ecology and genetics. This landscape unfolds into three main axes. First, the host axis reveals that fitness costs often arise from host-dependent genetic conflicts, not a generic burden. Second, the time axis demonstrates that the fitness cost of any plasmid can be negated over time through plasmid or chromosome compensations, which leads to ameliorating initial costs and locking in resistance. Third, the environmental axis shows that the fitness cost of any plasmid can be affected by external factors like temperature and sub-inhibitory concentrations of antibiotics. These factors dynamically modulate the benefits and costs of plasmid carriage. By integrating the complex interplay between these dimensions, we argue that the plasmid fitness costs are not a fixed generic measurement, but rather a contingent trajectory across this landscape. This paradigm shifts the focus from static measurements to a dynamic, predictive science, providing a new foundation for assessing and managing the threat of mobile resistance.

Indexed as

BacteriaDrug Resistance, BacterialGenetic FitnessPlasmidsAnti-Bacterial AgentsAnti-Bacterial Agentsantimicrobial resistance (AMR)co-evolutioncompensatory evolutionhorizontal gene transfer (HGT)plasmid fitness costplasmid-host fitness landscape

Identifiers

PMID41489361
PMCPMC12838339

What OpenQuestion holds

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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.