Summary of Study ST003036
This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001879. The data can be accessed directly via it's Project DOI: 10.21228/M8TX45 This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.
| Study ID | ST003036 |
| Study Title | Identifying and mathematically modeling the time-course of extracellular metabolic markers associated with resistance to ceftolozane/tazobactam in Pseudomonas aeruginosa - Part 2 |
| Study Type | Biomedical research |
| Study Summary | 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. |
| Institute | Monash Institute of Pharmaceutical Sciences |
| Department | Drug Delivery, Disposition and Dynamics |
| Laboratory | Cornelia Landersdorfer |
| Last Name | Landersdorfer |
| First Name | Cornelia |
| Address | 399 Royal Pd |
| cornelia.landersdorfer@monash.edu | |
| Phone | +61 3 9903 9061 |
| Submit Date | 2023-12-17 |
| Num Groups | 6 groups with time points |
| Total Subjects | NA |
| Num Males | NA |
| Num Females | NA |
| Publications | Identifying and mathematically modeling the time-course of extracellular metabolic markers associated with resistance to ceftolozane/tazobactam in Pseudomonas aeruginosa |
| Raw Data Available | Yes |
| Raw Data File Type(s) | raw(Thermo) |
| Analysis Type Detail | LC-MS |
| Release Date | 2024-01-11 |
| Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Combined analysis:
| Analysis ID | AN004977 | AN004978 |
|---|---|---|
| Analysis type | MS | MS |
| Chromatography type | HILIC | HILIC |
| Chromatography system | Thermo Dionex Ultimate 3000 | Thermo Dionex Ultimate 3000 |
| Column | Merck SeQuant ZIC-pHILIC (150 x 4.6mm,5um) | Merck SeQuant ZIC-pHILIC (150 x 4.6mm,5um) |
| MS Type | ESI | ESI |
| MS instrument type | Orbitrap | Orbitrap |
| MS instrument name | Thermo Q Exactive Orbitrap | Thermo Q Exactive Orbitrap |
| Ion Mode | POSITIVE | NEGATIVE |
| Units | peak height | peak height |
Chromatography:
| Chromatography ID: | CH003758 |
| Chromatography Summary: | ZIC-pHILIC chromatography at pH 9 using pos neg switching |
| Methods Filename: | Metabolomics_pHILIC_Parkville_v1.pdf |
| Instrument Name: | Thermo Dionex Ultimate 3000 |
| Column Name: | Merck SeQuant ZIC-pHILIC (150 x 4.6mm,5um) |
| Column Temperature: | 25 C |
| Flow Gradient: | 0 min - 80%B, 15 min - 50%B, 18 min - 5%B, 21 min - 5%B, 24 min - 80%B, 32 min - 80%B |
| Flow Rate: | 0.3 ml/min |
| Solvent A: | 20 mM ammonium carbonate |
| Solvent B: | acetonitrile |
| Washing Buffer: | syringe wash 50% IPA |
| Chromatography Type: | HILIC |
| Chromatography ID: | CH003759 |
| Chromatography Summary: | ZIC-pHILIC chromatography at pH 9 using pos neg switching |
| Methods Filename: | Metabolomics_pHILIC_Parkville_v1.pdf |
| Instrument Name: | Thermo Dionex Ultimate 3000 |
| Column Name: | Merck SeQuant ZIC-pHILIC (150 x 4.6mm,5um) |
| Column Temperature: | 25 C |
| Flow Gradient: | 0 min - 80%B, 15 min - 50%B, 18 min - 5%B, 21 min - 5%B, 24 min - 80%B, 32 min - 80%B |
| Flow Rate: | 0.3 ml/min |
| Solvent A: | 20 mM ammonium carbonate |
| Solvent B: | acetonitrile |
| Washing Buffer: | syringe wash 50% IPA |
| Chromatography Type: | HILIC |
