Evidence map›Paper›PMID 31083687›Full record

ArticlePLoS pathogens2019

On the evolutionary ecology of multidrug resistance in bacteria.

Sonja Lehtinen, François Blanquart, Marc Lipsitch, Christophe Fraser, with the Maela Pneumococcal Collaboration

Abstract read
In one paragraph

Article in PLoS pathogens, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing 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

42 citing papers in PubMed.

  1. Trial
  2. Widespread antibiotic-resistantOne health (Amsterdam, Netherlands) · 2026
    Article
  3. Review
  4. Article
  5. Article
  6. Old drugs, new weapons: current trends in repurposing therapies against antimicrobial resistance.Journal of pharmacy & pharmaceutical sciences : a publication of the Canadian Society for Pharmaceutical Sciences, Societe canadienne des sciences pharmaceutiques · 2026
    Review
  7. Genomic profiling of ESBL/AmpC-producingFrontiers in microbiology · 2026
    Article
  8. Article
  9. Article
  10. Article
  11. Disruption ofMicrobiology (Reading, England) · 2025
    Article
  12. Review
  13. Review
  14. Article
  15. Multidrug Resistance ofPathogens (Basel, Switzerland) · 2024
    Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. 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

5 authors.

Sonja LehtinenBig Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.ORCID 0000-0002-4236-828X
François BlanquartBig Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
Marc LipsitchCenter for Communicable Disease Dynamics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America.ORCID 0000-0003-1504-9213
Christophe FraserBig Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.ORCID 0000-0003-2399-9657
with the Maela Pneumococcal Collaboration

Funding

Understanding and controlling antibiotic resistanceU54GM088558 · NIGMS · HARVARD SCHOOL OF PUBLIC HEALTH · PI LIPSITCH, MARC · 2009 to 2018
$26.4M
Models for synthesising molecular, clinical and epidemiological data, and translaU01GM110721 · NIGMS · IMPERIAL COLLEGE OF SCIENCE, TECHNOLOGY AND MEDICINE · PI CAUCHEMEZ, SIMON, FERGUSON, NEIL MORRIS · 2014 to 2018
$1.9M
Medical Research Council MR/R015600/1NIGMS NIH HHS U01 GM110721NIGMS NIH HHS U54 GM088558Wellcome Trust
6 · The paper itself

Abstract

Resistance against different antibiotics appears on the same bacterial strains more often than expected by chance, leading to high frequencies of multidrug resistance. There are multiple explanations for this observation, but these tend to be specific to subsets of antibiotics and/or bacterial species, whereas the trend is pervasive. Here, we consider the question in terms of strain ecology: explaining why resistance to different antibiotics is often seen on the same strain requires an understanding of the competition between strains with different resistance profiles. This work builds on models originally proposed to explain another aspect of strain competition: the stable coexistence of antibiotic sensitivity and resistance observed in a number of bacterial species. We first identify a partial structural similarity in these models: either strain or host population structure stratifies the pathogen population into evolutionarily independent sub-populations and introduces variation in the fitness effect of resistance between these sub-populations, thus creating niches for sensitivity and resistance. We then generalise this unified underlying model to multidrug resistance and show that models with this structure predict high levels of association between resistance to different drugs and high multidrug resistance frequencies. We test predictions from this model in six bacterial datasets and find them to be qualitatively consistent with observed trends. The higher than expected frequencies of multidrug resistance are often interpreted as evidence that these strains are out-competing strains with lower resistance multiplicity. Our work provides an alternative explanation that is compatible with long-term stability in resistance frequencies.

Indexed as

Biological EvolutionDrug Resistance, Multiple, BacterialEcologyModels, StatisticalAnti-Bacterial AgentsBacteriaBacterial InfectionsHumansModels, BiologicalAnti-Bacterial Agents

Identifiers

PMID31083687
PMCPMC6532944

What OpenQuestion holds

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LicenceCC BY
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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.