Exometabolomic Analysis of Susceptible and Multi-Drug Resistant Pseudomonas aeruginosa

Identifying and mathematically modeling the time-course of extracellular metabolic markers associated with resistance to ceftolozane/tazobactam in Pseudomonas aeruginosa

Extracellular bacterial metabolites have potential as markers of bacterial growth and resistance emergence but have not been evaluated in dynamic in vitro studies. We investigated the dynamic metabolomic footprint of a multidrug-resistant hypermutable Pseudomonas aeruginosa isolate exposed to ceftolozane/tazobactam as continuous infusion (4.5 g/day, 9 g/day) in a hollow-fiber infection model over 7-9 days in biological replicates (n = 5). Bacterial samples were collected at 0, 7, 23, 47, 71, 95, 143, 167, 191, and 215 h, the supernatant quenched, and extracellular metabolites extracted. Metabolites were analyzed via untargeted metabolomics, including hierarchical clustering and correlation with quantified total and resistant bacterial populations. The time-courses of five (of 1,921 detected) metabolites from enriched pathways were mathematically modeled. Absorbed L-arginine and secreted L-ornithine were highly correlated with the total bacterial population (r -0.79 and 0.82, respectively, P<0.0001). Ribose-5-phosphate, sedoheptulose-7-phosphate, and trehalose-6-phosphate correlated with the resistant subpopulation (0.64, 0.64, and 0.67, respectively, P<0.0001) and were likely secreted due to resistant growth overcoming oxidative and osmotic stress induced by ceftolozane/tazobactam. Using pharmacokinetic/pharmacodynamic-based transduction models, these metabolites were successfully modeled based on the total or resistant bacterial populations. The models well described the abundance of each metabolite across the differing time-course profiles of biological replicates, based on bacterial killing and, importantly, resistant regrowth. These proof-of-concept studies suggest that further exploration is warranted to determine the generalizability of these findings. The metabolites modeled here are not exclusive to bacteria. Future studies may use this approach to identify bacteria-specific metabolites correlating with resistance, which would ultimately be extremely useful for clinical translation.

Impact of CRAMP-34 on Pseudomonas aeruginosa biofilms and extracellular metabolites

Biofilm is a structured community of bacteria encased within a self-produced extracellular matrix. When bacteria form biofilms, they undergo a phenotypic shift that enhances their resistance to antimicrobial agents. Consequently, inducing the transition of biofilm bacteria to the planktonic state may offer a viable approach for addressing infections associated with biofilms. Our previous study has shown that the mouse antimicrobial peptide CRAMP-34 can disperse Pseudomonas aeruginosa (P. aeruginosa) biofilm, and the potential mechanism of CRAMP-34 eradicate P. aeruginosa biofilms was also investigated by combined omics. However, changes in bacterial extracellular metabolism have not been identified. To further explore the mechanism by which CRAMP-34 disperses biofilm, this study analyzed its effects on the extracellular metabolites of biofilm cells via metabolomics. The results demonstrated that a total of 258 significantly different metabolites were detected in the untargeted metabolomics, of which 73 were downregulated and 185 were upregulated. Pathway enrichment analysis of differential metabolites revealed that metabolic pathways are mainly related to the biosynthesis and metabolism of amino acids, and it also suggested that CRAMP-34 may alter the sensitivity of biofilm bacteria to antibiotics. Subsequently, it was confirmed that the combination of CRAMP-34 with vancomycin and colistin had a synergistic effect on dispersed cells. These results, along with our previous findings, suggest that CRAMP-34 may promote the transition of PAO1 bacteria from the biofilm state to the planktonic state by upregulating the extracellular glutamate and succinate metabolism and eventually leading to the dispersal of biofilm. In addition, increased extracellular metabolites of myoinositol, palmitic acid and oleic acid may enhance the susceptibility of the dispersed bacteria to the antibiotics colistin and vancomycin. CRAMP-34 also delayed the development of bacterial resistance to colistin and ciprofloxacin. These results suggest the promising development of CRAMP-34 in combination with antibiotics as a potential candidate to provide a novel therapeutic approach for the prevention and treatment of biofilm-associated infections.