Projects per year
Abstract
Objectives We aimed to conduct a comprehensive genomic analysis of ceftolozane/tazobactam (C/T) resistance mechanisms in Pseudomonas aeruginosa by combining novel institutional data with publicly-available sequencing data. Methods We analysed 1682 P. aeruginosa isolates, comprising 339 isolates from Alfred Hospital (Melbourne, Australia) and 1343 isolates from six public datasets. All isolates underwent whole-genome sequencing and C/T broth microdilution susceptibility testing. We assessed previously reported intrinsic and acquired resistance mechanisms. We then conducted a genome-wide association study and machine learning analysis to identify novel genes associated with resistance. We then evaluated the impact of mutations in these genes on MIC values and ceftolozane binding affinity. Results Among 1682 P. aeruginosa isolates representing 527 distinct sequence types, 343 of 1682 (20.4%) were C/T-resistant. Carbapenemase genes were detected in 206 of 1682 (12.2%) isolates. Mutations in previously reported resistance-associated genes ( ftsI, mpl, ampD, ampC, ampR, and oprD) were more frequent in resistant isolates but were also found in almost all susceptible isolates. Successive mutations conferred additive increases in MIC. A combined genome-wide association study and machine learning analyses a priori identified five key genes significantly associated with resistance: ftsI , ampR , ampC , PA3329, and PA4311. Molecular docking simulation revealed that the R504C mutation in penicillin-binding protein 3, which is encoded by ftsI , reduced binding contacts and hydrogen bonds with ceftolozane, significantly decreasing binding affinity (p 0.016). Conclusions Our analysis of 1682 P. aeruginosa genomes demonstrated complex pathways to C/T resistance and showed that ftsI may play an underappreciated role. We discovered two previously unidentified genes associated with C/T resistance, whose function remains to be determined.
| Original language | English |
|---|---|
| Pages (from-to) | 110-117 |
| Number of pages | 8 |
| Journal | Clinical Microbiology and Infection |
| Volume | 32 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Jan 2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Antimicrobial resistance
- Ceftolozane/tazobactam
- Genome-wide association studies
- Machine learning
- Pseudomonas aeruginosa
Projects
- 3 Finished
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Genomics, Digital Health and Machine Learning: the SuperbugAi Flagship
Peleg, A. (Primary Chief Investigator (PCI)), Holt, K. (Chief Investigator (CI)), Song, J. (Chief Investigator (CI)), Macesic, N. (Chief Investigator (CI)), Ananda-Rajah, M. (Chief Investigator (CI)), Webb, G. (Chief Investigator (CI)), Korman, T. (Chief Investigator (CI)), Stuart, R. (Chief Investigator (CI)), Cheng, A. (Chief Investigator (CI)), Peel, T. (Chief Investigator (CI)), Stewardson, A. (Chief Investigator (CI)), Ayton, D. (Chief Investigator (CI)) & Bain, C. (Chief Investigator (CI))
2/01/21 → 31/12/25
Project: Research
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Integrating genomic and artificial intelligence approaches to combat antimicrobial resistance
Macesic, N. (Primary Chief Investigator (PCI))
NHMRC - National Health and Medical Research Council (Australia)
1/01/20 → 31/12/24
Project: Research
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NOVEL SOLUTIONS FOR ANTIMICROBIAL RESISTANT PATHOGENS
Peleg, A. (Primary Chief Investigator (PCI))
1/01/17 → 31/12/21
Project: Research
Equipment
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High-performance Computing (M3/MASSIVE)
Powell, D. (Manager) & Tan, G. (Manager)
Office of the Vice-Provost (Research and Research Infrastructure)Facility/equipment: Facility
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Monash eResearch
Powell, D. (Manager)
Office of the Vice-Provost (Research and Research Infrastructure)Facility/equipment: Facility
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Research Cloud (Nectar node)
Powell, D. (Manager)
Monash e-Research CentreFacility/equipment: Facility
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