Report of epidemic Pseudomonas aeruginosa AUST-03 (ST 242) strains and resistomes in South African cystic fibrosis patients
Bibliographic record
Abstract
Introduction: Pseudomonas aeruginosa AUST-03 (ST242) has been reported to cause epidemics in cystic fibrosis (CF) patients from Tasmania and Australia and has been associated with multidrug resistance and increased morbidity and mortality. Here, we report epidemic P. aeruginosa (AUST-03) strains in South African CF patients at a public academic hospital detected during a previous study and characterise the resistomes. Methods: The P. aeruginosa AUST-03 (ST242) strains were analysed with whole genome sequencing using the Illumina NextSeq2000 platform. Raw sequencing reads were processed using the Jekesa pipeline and multi-locus sequence typing and resistome characterisation was performed using public databases. Core single nucleotide polymorphism phylogenies were performed on P. aeruginosa ST242 strains from the study and from public databases. Antibiotic susceptibility testing was performed using the disk diffusion and broth microdilution techniques. Results: A total of 11 P. aeruginosa AUST-03 strains were isolated from two children with CF who had pulmonary exacerbations. The majority of the P. aeruginosa AUST-03 strains (8/11) were multidrug resistant (MDR) or extensively drug resistant; and the multidrug efflux pumps MexAB-OprM, MexCD-OprJ, MexEF-OprN, MexXY-OprM were the most clinically relevant antibiotic resistance determinants and were detected in all of the strains. The P. aeruginosa AUST-03 (ST242) study strains were most closely related to strains from Canada, China, Denmark and Slovenia. Conclusion: Epidemic MDR P. aeruginosa strains are present at South African public CF clinics and need to be considered when implementing patient segregation and infection control strategies to prevent further spread and outbreaks.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".