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.
Highlights
The efficacy of antibiotics for the treatment of infections is diminishing rapidly as bacteria evolve new mechanisms to resist antibiotics (Laxminarayan et al, 2013)
We challenged a total of 756 replicate P. aeruginosa populations with sequential treatments across three fully independent evolution experiments, each focused on a different set of three antibiotics (Figure 1, Figure 1—figure supplement 1, Supplementary file 1A, Materials and methods)
The antibiotic concentrations were calibrated to an inhibitory concentration of 75% (IC75), allowing bacteria to adapt to the imposed selection pressure
Summary
The efficacy of antibiotics for the treatment of infections is diminishing rapidly as bacteria evolve new mechanisms to resist antibiotics (Laxminarayan et al, 2013). A failure to account for such rapid bacterial adaptation is likely a common reason for treatment failure (Woods and Read, 2015; Zhou et al, 2020) For this reason, the field of evolutionary medicine accounts for bacterial evolvability and seeks treatment solutions that are hard to overcome by genetic adaptation (Andersson et al, 2020; Merker et al, 2020). While an evolution-proof antibiotic remains to be found, the mechanisms that restrict evolutionary escape are starting to be revealed (Bell and MacLean, 2018). Such evolutionary insight may guide the design of effective and sustainable antibiotic therapy
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