Synergy of the Polymyxin-Chloramphenicol Combination against New Delhi Metallo-β-Lactamase-Producing Klebsiella pneumoniae Is Predominately Driven by Chloramphenicol

Abstract

Carbapenem-resistant Klebsiella pneumoniae has been classified as an Urgent Threat by the Centers for Disease Control and Prevention (CDC). The combination of two “old” antibiotics, polymyxin and chloramphenicol, displays synergistic killing against New Delhi metallo-β-lactamase (NDM)-producing K. pneumoniae. However, the mechanism(s) underpinning their synergistic killing are not well studied. We employed an in vitro pharmacokinetic/pharmacodynamic model to mimic the pharmacokinetics of the antibiotics in patients and examined bacterial killing against NDM-producing K. pneumoniae using a metabolomic approach. Metabolomic analysis was integrated with an isolate-specific genome-scale metabolic network (GSMN). Our results show that metabolic responses to polymyxin B and/or chloramphenicol against NDM-producing K. pneumoniae involved the inhibition of cell envelope biogenesis, metabolism of arginine and nucleotides, glycolysis, and pentose phosphate pathways. Our metabolomic and GSMN modeling results highlight the novel mechanisms of a synergistic antibiotic combination at the network level and may have a significant potential in developing precision antimicrobial chemotherapy in patients.

In silico genome-scale metabolic modeling and in vitro static time-kill studies of exogenous metabolites alone and with polymyxin B against Klebsiella pneumoniae

“…The metabolites were selected based on the previous transcriptomic and metabolomic findings ( Maifiah et al, 2017 ; Han et al, 2018 ; Hussein et al, 2018 ; Abdul Rahim et al, 2021 ), which indicated that the intracellular levels of metabolites R5P, UACGAM, and GLYC3P were significantly perturbed by polymyxin. Furthermore, metabolites PHPYR, OROT, 3PG, and 3PHP have also been identified as significant metabolites perturbed by the combination ( Abdul Rahim et al, 2021 ).…”

“…The metabolites were selected based on the previous transcriptomic and metabolomic findings ( Maifiah et al, 2017 ; Han et al, 2018 ; Hussein et al, 2018 ; Abdul Rahim et al, 2021 ), which indicated that the intracellular levels of metabolites R5P, UACGAM, and GLYC3P were significantly perturbed by polymyxin. Furthermore, metabolites PHPYR, OROT, 3PG, and 3PHP have also been identified as significant metabolites perturbed by the combination ( Abdul Rahim et al, 2021 ). Although many significant metabolites were identified from the studies, the selected metabolites were those that demonstrated perturbations to both gene expression and metabolism of the same pathway [e.g., gnd and R5P in the pentose phosphate pathway (PPP); pgk and 3PG in gluconeogenesis] by the combination ( Abdul Rahim et al, 2020 ; 2021 ).…”

“…Furthermore, metabolites PHPYR, OROT, 3PG, and 3PHP have also been identified as significant metabolites perturbed by the combination ( Abdul Rahim et al, 2021 ). Although many significant metabolites were identified from the studies, the selected metabolites were those that demonstrated perturbations to both gene expression and metabolism of the same pathway [e.g., gnd and R5P in the pentose phosphate pathway (PPP); pgk and 3PG in gluconeogenesis] by the combination ( Abdul Rahim et al, 2020 ; 2021 ). For instance, transcriptomics and metabolomic results revealed that the expression of gene gnd and abundance level of R5P were downregulated and decreased in response to the polymyxin combination treatment, respectively.…”

“…The mechanism of polymyxin action involves free radical-induced death ( Trimble et al, 2016 ). Abdul Rahim et al (2021) postulated that an increase in nucleotide synthesis including R5P and OROT was an initial bacterial stress response to polymyxin combination treatment ( Abdul Rahim et al, 2021 ). Such metabolic perturbation might be exacerbated driven by TCA activity upon metabolite feeding.…”

Optimizing Antimicrobial Therapy by Integrating Multi-Omics With Pharmacokinetic/Pharmacodynamic Models and Precision Dosing

“… Zhu et al (2018) integrated multi-omics data with a genome-scale metabolic model (GSMM) to analyze the responses of P. aeruginosa to polymyxins. Abdul Rahim et al (2021) employed a systems-based model to analyze the synergistic activity of polymyxin B and chloramphenicol. Wozniak et al (2020) adopted a combination of metabolomics and proteomics analysis of S. aureus bacteraemia together with the computational tool as biomarkers to predict mortality risk and recommend personalized therapy.…”