Elucidating effects of single and multiple resistance mechanisms on bacterial response to meropenem by quantitative and systems pharmacology modeling and population genomics

Abstract

Meropenem is commonly used againstPseudomonas aeruginosa; however, resistance is emerging. Traditionally, the time unbound antibiotic concentration exceeds the MIC (fT>MIC) is used to select carbapenem regimens. We aimed to 1) characterize the effects of different resistance mechanisms on bacterial killing and resistance emergence, 2) evaluate whetherfT>MICcan predict these effects, and 3) develop a novel quantitative and systems pharmacology model to elucidate effects of baseline resistance mechanisms on the time-course of bacterial response. Seven isogenicP. aeruginosastrains with a range of resistance mechanisms and MICs were used in 10-day hollow-fibre infection model studies (HFIM). Meropenem pharmacokinetic profiles were simulated for various regimens (t1/2,meropenem=1.5h). All viable counts on drug-free, 3xMIC and 5xMIC meropenem-containing agar across all strains, five regimens and control (n=90 profiles) were modelled simultaneously. Whole genome sequencing was completed for resistant colonies and total population samples at 239h. Regimens achieving ≥98%fT>1xMICsuppressed resistance emergence of the mexR knockout strain. Even 100%fT>5xMICfailed to achieve this against the strain with OprD loss and the ampD and mexR double-knockout strain. The model well characterized total and less-susceptible bacteria for all strains. Supported by genomic analysis, pre-existing resistant subpopulations drove resistance emergence in the model. During meropenem exposure, mutations in mexR were selected in strains with baseline oprD mutations, and vice versa, confirming these as major mechanisms of resistance emergence. Secondary mutations occurred in lysS or argS, coding for lysyl and arginyl tRNA synthetases, respectively. The model well characterized all bacterial outcomes of seven strains simultaneously, whichfT>MICcould not.