ArticlePLoS biology2013
When the most potent combination of antibiotics selects for the greatest bacterial load: the smile-frown transition.
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.
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Who cites it
109 citing papers in PubMed.
- Simple birth-death-mutation models predict some-but not all-aspects of the experimental evolution of antibiotic resistance.PLoS computational biology · 2026Article
- Antimicrobial Resistance: A Bibliometric Review of Patient Health, Mechanisms, and Therapeutic Strategies.Pathogens (Basel, Switzerland) · 2026Review
- Evolutionary drivers of divergent collateral sensitivity responses during antibiotic therapy.Nature ecology & evolution · 2026Review
- Combined Forces Against Bacteria: Phages and Antibiotics.Health science reports · 2025Article
- Interactions within higher-order antibiotic combinations do not influence the rate of adaptation in bacteria.Evolution; international journal of organic evolution · 2025Article
- Meeting Report on the Symposium "Evolutionary Applications" at the 3rd Joint Congress on Evolutionary Biology.Evolutionary applications · 2025Article
- Drug combinations targeting antibiotic resistance.npj antimicrobials and resistance · 2024Review
- The many dimensions of combination therapy: How to combine antibiotics to limit resistance evolution.Evolutionary applications · 2024Article
- Variation in the response to antibiotics and life-history across the majorMicrobiology spectrum · 2024Article
- The evolution of antimicrobial peptide resistance in Pseudomonas aeruginosa is severely constrained by random peptide mixtures.PLoS biology · 2024Article
- Preserving the efficacy of antibiotics to tackle antibiotic resistance.Microbial biotechnology · 2024Review
- Modeling spatial evolution of multi-drug resistance under drug environmental gradients.PLoS computational biology · 2024Article
- Plasmid-mediated phenotypic noise leads to transient antibiotic resistance in bacteria.Nature communications · 2024Article
- Article
- Modeling spatial evolution of multi-drug resistance under drug environmental gradients.bioRxiv : the preprint server for biology · 2023Article
- Evolutionary rescue on genotypic fitness landscapes.Journal of the Royal Society, Interface · 2023Article
- The uncertain role of substandard and falsified medicines in the emergence and spread of antimicrobial resistance.Nature communications · 2023Review
- Mutators can drive the evolution of multi-resistance to antibiotics.PLoS genetics · 2023Article
- Article
- Sequential antibiotic therapy in the laboratory and in the patient.Journal of the Royal Society, Interface · 2023Article
49 more citing papers are in PubMed but not listed here.
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Authors and funding
7 authors.
Funding
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.
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