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

Fuhs, D. T.; Cortes-Lara, S.; Tait, J. R.; Rogers, K. E.; Lopez-Causape, C.; Lee, W. L.; Shackleford, D. M.; Nation, R. L.; Oliver, A.; Landersdorfer, C. B.

doi:10.1101/2024.02.17.579784

bioRxiv · 10.1101/2024.02.17.579784

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

Fuhs, D. T.·Cortes-Lara, S.·Tait, J. R.·Rogers, K. E.·Lopez-Causape, C.·Lee, W. L.·Shackleford, D. M.·Nation, R. L.·Oliver, A.·Landersdorfer, C. B.

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Abstract

Meropenem is commonly used against Pseudomonas aeruginosa. Traditionally, the time unbound antibiotic concentration exceeds the MIC (fT>MIC) is used to select carbapenem regimens. We aimed to: characterize the effects of different baseline resistance mechanisms on bacterial killing and resistance emergence; evaluate whether fT>MIC can predict these effects; and, develop a novel quantitative and systems pharmacology (QSP) model to describe effects of baseline resistance mechanisms on the time-course of bacterial response. Seven isogenic P. aeruginosa strains with a range of resistance mechanisms and MICs were used in 10-day hollow-fiber infection model studies. 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 simultaneously subjected to QSP modeling. Whole genome sequencing was completed for total population samples and emergent resistant colonies at 239h. Regimens achieving [≥]98%fT>1xMIC suppressed resistance emergence of the mexR knockout strain. Even 100%fT>5xMIC failed to achieve this against the strain with OprD loss and the ampD and mexR double-knockout strain. Baseline resistance mechanisms affected bacterial outcomes, even for strains with the same MIC. Genomic analysis revealed that pre-existing resistant subpopulations drove resistance emergence. 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 QSP model well characterized all bacterial outcomes of the seven strains simultaneously, which fT>MIC could not.

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Fuhs, D. T., Cortes-Lara, S., Tait, J. R., Rogers, K. E., Lopez-Causape, C., Lee, W. L., Shackleford, D. M., Nation, R. L., Oliver, A., Landersdorfer, C. B.. 2024-02-17. Elucidating effects of single and multiple resistance mechanisms on bacterial response to meropenem by quantitative and systems pharmacology modeling and population genomics. https://doi.org/10.1101/2024.02.17.579784

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