PR001879 (Project)

Description: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 (4.5g/day, 9g/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 215h, 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 metabolites were mathematically modeled. These five (of 1921 detected) metabolites were from enriched pathways (arginine and central carbon metabolism). 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 PK/PD-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 further exploration is warranted to determine the generalizability of these findings. The metabolites modeled in this work are not exclusive to bacterial cells. Future studies may use this approach to identify bacteria-specific metabolites correlating with resistance, which would ultimately be extremely useful for clinical translation.