Evidence map›Paper›PMID 23630452›Full record

ArticlePLoS biology2013

When the most potent combination of antibiotics selects for the greatest bacterial load: the smile-frown transition.

Rafael Pena-Miller, David Laehnemann, Gunther Jansen, Ayari Fuentes-Hernandez, Philip Rosenstiel, Hinrich Schulenburg, Robert Beardmore

Abstract read
In one paragraph

Article in PLoS biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 109 papers.

0numbers the graph read from it
0cells of the map it votes in
109citing 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

109 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Drug combinations targeting antibiotic resistance.npj antimicrobials and resistance · 2024
    Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Evolutionary rescue on genotypic fitness landscapes.Journal of the Royal Society, Interface · 2023
    Article
  17. Review
  18. Article
  19. RSC advances · 2023
    Article
  20. Sequential antibiotic therapy in the laboratory and in the patient.Journal of the Royal Society, Interface · 2023
    Article

49 more citing papers are in PubMed but not listed here.

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

7 authors.

Rafael Pena-MillerBiosciences, Geoffrey Pope Building, University of Exeter, United Kingdom.
David Laehnemann
Gunther Jansen
Ayari Fuentes-Hernandez
Philip Rosenstiel
Hinrich Schulenburg
Robert Beardmore

Funding

Medical Research Council G0802611
6 · The paper itself

Abstract

Conventional wisdom holds that the best way to treat infection with antibiotics is to 'hit early and hit hard'. A favoured strategy is to deploy two antibiotics that produce a stronger effect in combination than if either drug were used alone. But are such synergistic combinations necessarily optimal? We combine mathematical modelling, evolution experiments, whole genome sequencing and genetic manipulation of a resistance mechanism to demonstrate that deploying synergistic antibiotics can, in practice, be the worst strategy if bacterial clearance is not achieved after the first treatment phase. As treatment proceeds, it is only to be expected that the strength of antibiotic synergy will diminish as the frequency of drug-resistant bacteria increases. Indeed, antibiotic efficacy decays exponentially in our five-day evolution experiments. However, as the theory of competitive release predicts, drug-resistant bacteria replicate fastest when their drug-susceptible competitors are eliminated by overly-aggressive treatment. Here, synergy exerts such strong selection for resistance that an antagonism consistently emerges by day 1 and the initially most aggressive treatment produces the greatest bacterial load, a fortiori greater than if just one drug were given. Whole genome sequencing reveals that such rapid evolution is the result of the amplification of a genomic region containing four drug-resistance mechanisms, including the acrAB efflux operon. When this operon is deleted in genetically manipulated mutants and the evolution experiment repeated, antagonism fails to emerge in five days and antibiotic synergy is maintained for longer. We therefore conclude that unless super-inhibitory doses are achieved and maintained until the pathogen is successfully cleared, synergistic antibiotics can have the opposite effect to that intended by helping to increase pathogen load where, and when, the drugs are found at sub-inhibitory concentrations.

Indexed as

Computer SimulationModels, BiologicalAlgorithmsAnti-Bacterial AgentsBacterial InfectionsBacterial LoadDrug Resistance, Multiple, BacterialDrug SynergismDrug Therapy, CombinationEscherichia coli K12Evolution, MolecularHumansMicrobial Sensitivity TestsMicrobial ViabilityOperonPolymorphism, Single NucleotideAnti-Bacterial Agents

Identifiers

PMID23630452
PMCPMC3635860

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.