ArticlePLoS computational biology2015
Steering Evolution with Sequential Therapy to Prevent the Emergence of Bacterial Antibiotic Resistance.
Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 89 papers.
What it found
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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.
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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.
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Who cites it
89 citing papers in PubMed, 187 citations in OpenAlex.
- Simple birth-death-mutation models predict some-but not all-aspects of the experimental evolution of antibiotic resistance.PLoS computational biology · 2026Article
- Evolutionary adaptation proceeds through a small number of phenotypic modules.Molecular biology and evolution · 2026Article
- Stochastic Evolutionary Control in Heterogeneous Populations.bioRxiv : the preprint server for biology · 2026Article
- Evolutionary drivers of divergent collateral sensitivity responses during antibiotic therapy.Nature ecology & evolution · 2026Review
- Computational framework for streamlining the success of sequential antibiotic therapy.npj antimicrobials and resistance · 2025Article
- Evolution under vancomycin selection drives divergent collateral sensitivity patterns inProceedings of the National Academy of Sciences of the United States of America · 2025Article
- The balance between intrinsic and ecological fitness reveals hidden regimes in eco-evolutionary population dynamics.Research square · 2025Article
- The balance between intrinsic and ecological fitness reveals hidden regimes in eco-evolutionary population dynamics.bioRxiv : the preprint server for biology · 2025Article
- Fitness seascapes are necessary for realistic modeling of the evolutionary response to drug therapy.Science advances · 2025Article
- Review
- Bioengineering hybrid artificial life.Frontiers in bioinformatics · 2025Review
- Dynamic collateral sensitivity profiles highlight opportunities and challenges for optimizing antibiotic treatments.PLoS biology · 2025Article
- Linking spatial drug heterogeneity to microbial growth dynamics in theory and experiment.bioRxiv : the preprint server for biology · 2024Article
- Cell-cell fusion in cancer: The next cancer hallmark?The international journal of biochemistry & cell biology · 2024Review
- Threshold-awareness in adaptive cancer therapy.PLoS computational biology · 2024Article
- Antibacterial properties of natural products from marine fungi reported between 2012 and 2023: a review.Archives of pharmacal research · 2024Review
- Modeling spatial evolution of multi-drug resistance under drug environmental gradients.PLoS computational biology · 2024Article
- Reinforcement learning informs optimal treatment strategies to limit antibiotic resistance.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Unraveling resistance mechanisms in combination therapy: A comprehensive review of recent advances and future directions.Heliyon · 2024Review
- In Vitro Microevolution and Co-Selection Assessment of Amoxicillin and Cefotaxime Impact onAntibiotics (Basel, Switzerland) · 2024Article
29 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 4 institutions in 2 countries.
Funding
Abstract
The increasing rate of antibiotic resistance and slowing discovery of novel antibiotic treatments presents a growing threat to public health. Here, we consider a simple model of evolution in asexually reproducing populations which considers adaptation as a biased random walk on a fitness landscape. This model associates the global properties of the fitness landscape with the algebraic properties of a Markov chain transition matrix and allows us to derive general results on the non-commutativity and irreversibility of natural selection as well as antibiotic cycling strategies. Using this formalism, we analyze 15 empirical fitness landscapes of E. coli under selection by different β-lactam antibiotics and demonstrate that the emergence of resistance to a given antibiotic can be either hindered or promoted by different sequences of drug application. Specifically, we demonstrate that the majority, approximately 70%, of sequential drug treatments with 2-4 drugs promote resistance to the final antibiotic. Further, we derive optimal drug application sequences with which we can probabilistically 'steer' the population through genotype space to avoid the emergence of resistance. This suggests a new strategy in the war against antibiotic-resistant organisms: drug sequencing to shepherd evolution through genotype space to states from which resistance cannot emerge and by which to maximize the chance of successful therapy.
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Registered trials
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.