High potency of sequential therapy with only beta-lactam antibiotics
Abstract
Evolutionary adaptation is a major source of antibiotic resistance in bacterial pathogens. Evolution-informed therapy aims to constrain resistance by accounting for bacterial evolvability. Sequential treatments with antibiotics that target different bacterial processes were previously shown to limit adaptation through genetic resistance trade-offs and negative hysteresis. Treatment with homogeneous sets of antibiotics is generally viewed to be disadvantageous, as it should rapidly lead to cross-resistance. We here challenged this assumption by determining the evolutionary response of Pseudomonas aeruginosa to experimental sequential treatments involving both heterogenous and homogeneous antibiotic sets. To our surprise, we found that fast switching between only β-lactam antibiotics resulted in increased extinction of bacterial populations. We demonstrate that extinction is favored by low rates of spontaneous resistance emergence and low levels of spontaneous cross-resistance among the antibiotics in sequence. The uncovered principles may help to guide the optimized use of available antibiotics in highly potent, evolution-informed treatment designs.
Data availability
Sequencing data have been deposited at NCBI under the BioProject number: PRJNA704789. All other data is provided in the supplementary source data files.
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Cellular hysteresis as a principle to maximize the efficacy of antibiotic therapy - Results on extinction frequencieshttps://doi.org/10.1073/pnas.1810004115.
Article and author information
Author details
Funding
Deutsche Forschungsgemeinschaft (SCHU 1415/12)
- Hinrich Schulenburg
Deutsche Forschungsgemeinschaft (EXC 2167-390884018)
- Stefan Niemann
- Hinrich Schulenburg
Deutsche Forschungsgemeinschaft (GRK 2501)
- Stefan Niemann
- Hinrich Schulenburg
Max-Planck-Gesellschaft (IMPRS Stipend)
- Aditi Batra
Max-Planck-Gesellschaft (Fellowship)
- Hinrich Schulenburg
Leibniz-Gemeinschaft (EvoLUNG)
- Stefan Niemann
- Hinrich Schulenburg
Deutsche Forschungsgemeinschaft (project 407495230)
- Sören Franzenburg
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2021, Batra et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Further reading
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- Evolutionary Biology
- Epidemiology and Global Health
- Microbiology and Infectious Disease
- Genetics and Genomics
eLife is pleased to present a Special Issue to highlight recent advances in the growing and increasingly interdisciplinary field of evolutionary medicine.
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- Evolutionary Biology
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