High potency of sequential therapy with only β-lactam antibiotics

eLife

Emilie Rousseau¹  Stefan Niemann¹  Sören Franzenburg²  Hinrich Schulenburg³  Aditi Batra³  Roderich Roemhild⁴ 

[1] Borstel Research Centre, National Reference Center for Mycobacteria, Borstel, Germany;Competence Centre for Genomic Analysis Kiel, University of Kiel, Kiel, Germany;Department of Evolutionary Ecology and Genetics, University of Kiel, Kiel, Germany;Max Planck Institute for Evolutionary Biology, Ploen, Germany;Department of Evolutionary Ecology and Genetics, University of Kiel, Kiel, Germany;Max Planck Institute for Evolutionary Biology, Ploen, Germany;Institute of Science and Technology, Klosterneuburg, Austria;

关键词: pseudomonas aeruginosa;    antibiotic resistance;    sequential therapy;    evolutionary medicine;    collateral sensitivity;    cellular hysteresis;    Other;   

DOI  :  10.7554/eLife.68876

来源: eLife Sciences Publications, Ltd

【 摘 要 】

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.

【 授权许可】

CC BY