Isolation, Characterization, and Genomic Analysis of Bacteriophages Against Pseudomonas aeruginosa Clinical Isolates from Early and Chronic Cystic Fibrosis Patients for Potential Phage Therapy
Bibliographic record
Abstract
Pseudomonas aeruginosa is associated with both community and hospital-acquired infections. It colonizes the lungs of cystic fibrosis (CF) patients, establishing an ecological niche where it adapts and evolves from early to chronic stages, resulting in deteriorating lung function and frequent exacerbations. With antibiotics resistance on the rise, there is a pressing need for alternative personalized treatments (such as bacteriophage therapy) to combat P. aeruginosa infections. In this study, we aimed to isolate and characterize phages targeting both early and chronic P. aeruginosa isolates and evaluate their potential for phage therapy. Four highly virulent phages belonging to myoviral, podviral, and siphoviral morphotypes were isolated from sewage samples. These phages have a broad host range and effectively target 62.5% of the P. aeruginosa isolates with a positive correlation to the early isolates. All the phages have a virulence index of ≥0.90 (0.90–0.98), and one has a large burst size of 331 PFU/cell and a latency period of 30 min. All phages are stable under a wide range of temperature and pH conditions. Genomic analysis suggests the four phages are strictly lytic and devoid of identifiable temperate phage repressors and genes associated with antibiotic resistance and virulence. More significantly, two of the phages significantly delayed the onset of larval death when evaluated in a lethal Galleria mellonella infection model, suggesting their promise as phage therapy candidates for P. aeruginosa infections.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".