Polymyxin dose tunes the evolutionary dynamics of resistance in multidrug-resistant Acinetobacter baumannii
Evolutionary principles have informed the design of strategies that slow or prevent antibiotic resistance. However, how antibiotic treatment regimens shape the evolutionary dynamics of resistance mutations remains an open question. Here, we investigate varying concentrations of the last-resort polymyxins on the evolution of resistance in Acinetobacter baumannii. Polymyxin resistance was measured in 18 multidrug-resistant A. baumannii AB5075 populations treated over 14 days with concentrations of polymyxin B informed by human pharmacokinetics. Time-resolved whole-population sequencing was conducted to track the genetics and population dynamics of susceptible and resistant subpopulations. A critical threshold concentration of polymyxin B (1 mg/L; i.e. 4 × MIC) was identified. Below this threshold concentration, low levels of resistance repeatedly evolved, but no mutations were fixed, and this resistance was reversed upon removal of the antibiotic. This contrasted with evolution at super-MIC levels (≥4 × MIC) of polymyxin B, which drove the evolution of irreversible resistance, with higher levels of antibiotic correlating with greater rates of molecular evolution. Polymyxin-resistant subpopulations carried mutations in a variety of genes, most commonly pmrB, ompA, glmU/glmS, and wecB/wecC, which contributed to membrane remodelling and virulence in A. baumannii. Our results show that the strength of the selective pressure applied by polymyxin tunes the dynamics of genetic variants within the population, leading to different evolutionary outcomes for the degree, cost and reversibility of resistance. Our study highlights the critical role of integrating evolutionary findings into pharmacokinetics/pharmacodynamics to optimise antibiotic use in patients.
Citation
@article{zhao2022,
author = {Zhao, Jinxin and Zhu, Yan and Lin, Yu-Wei and Yu, Heidi and
Wickremasinghe, Hasini and Han, Jiru and Velkov, Tony and Li, Jian},
title = {Polymyxin Dose Tunes the Evolutionary Dynamics of Resistance
in Multidrug-Resistant {Acinetobacter} Baumannii},
journal = {Clinical Microbiology and Infection},
volume = {28},
number = {7},
date = {2022-03-10},
url = {https://doi.org/10.1016/j.cmi.2022.02.043},
doi = {10.1016/j.cmi.2022.02.043},
langid = {en},
abstract = {Evolutionary principles have informed the design of
strategies that slow or prevent antibiotic resistance. However, how
antibiotic treatment regimens shape the evolutionary dynamics of
resistance mutations remains an open question. Here, we investigate
varying concentrations of the last-resort polymyxins on the
evolution of resistance in Acinetobacter baumannii. Polymyxin
resistance was measured in 18 multidrug-resistant A. baumannii
AB5075 populations treated over 14 days with concentrations of
polymyxin B informed by human pharmacokinetics. Time-resolved
whole-population sequencing was conducted to track the genetics and
population dynamics of susceptible and resistant subpopulations. A
critical threshold concentration of polymyxin B (1 mg/L; i.e. 4 ×
MIC) was identified. Below this threshold concentration, low levels
of resistance repeatedly evolved, but no mutations were fixed, and
this resistance was reversed upon removal of the antibiotic. This
contrasted with evolution at super-MIC levels (≥4 × MIC) of
polymyxin B, which drove the evolution of irreversible resistance,
with higher levels of antibiotic correlating with greater rates of
molecular evolution. Polymyxin-resistant subpopulations carried
mutations in a variety of genes, most commonly pmrB, ompA,
glmU/glmS, and wecB/wecC, which contributed to membrane remodelling
and virulence in A. baumannii. Our results show that the strength of
the selective pressure applied by polymyxin tunes the dynamics of
genetic variants within the population, leading to different
evolutionary outcomes for the degree, cost and reversibility of
resistance. Our study highlights the critical role of integrating
evolutionary findings into pharmacokinetics/pharmacodynamics to
optimise antibiotic use in patients.}
}