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High potency of sequential therapy with only β-lactam antibiotics

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Batra,  Aditi
IMPRS for Evolutionary Biology, Max Planck Institute for Evolutionary Biology, Max Planck Society;
Max Planck Fellow Group Antibiotic Resistance Evolution, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Römhild,  Roderich
IMPRS for Evolutionary Biology, Max Planck Institute for Evolutionary Biology, Max Planck Society;
Max Planck Fellow Group Antibiotic Resistance Evolution, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Schulenburg,  Hinrich
Max Planck Fellow Group Antibiotic Resistance Evolution, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Citation

Batra, A., Römhild, R., Rousseau, E., Franzenburg, S., Niemann, S., & Schulenburg, H. (2021). High potency of sequential therapy with only β-lactam antibiotics. eLife, 10: e68876. doi:10.7554/eLife.68876.


Cite as: https://hdl.handle.net/21.11116/0000-000A-A227-3
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.