Evasion of neutrophil-mediated bacterial clearance in <i>Pseudomonas aeruginosa</i> isolates from new-onset infections in cystic fibrosis children
Bibliographic record
Abstract
Abstract Chronic Pseudomonas aeruginosa (PA) infections in cystic fibrosis (CF) patients can persist for decades and are associated with poor clinical outcomes. New-onset PA infections are routinely treated with antibiotics, but unfortunately up to 40% of patients fail eradication therapy due to reasons that are poorly understood. Recently, we found that Persistent PA isolates from CF patients who failed tobramycin eradication therapy were more resistant to in vitro neutrophil-mediated opsonophagocytosis and intracellular bacterial killing (OPK) and were significantly associated with a non-twitching phenotype compared to Eradicated isolates. In this study, we sought to investigate how Persistent isolates evade in neutrophil-mediated bacterial clearance in vitro and whether these PA isolates also persist in vivo . Furthermore, we investigated whether restoring pilus-mediated twitching motility is sufficient to restore susceptibility to in vitro OPK and in vivo bacterial clearance. Using primary murine serum and bone marrow-derived neutrophils, we demonstrated that Persistent isolates are resistant to several neutrophil antibacterial functions compared to Eradicated isolates. Additionally, mice failed to clear pulmonary infections caused by Persistent isolates but not Eradicated isolates despite comparable responses in leukocyte recruitment and cytokine responses. We demonstrate that loss of Type IV pilus-mediated twitching motility confers a fitness advantage for a Persistent isolate during a murine pulmonary infection, and restoration of pilus-mediated twitching motility improves in vivo bacterial clearance. Our findings show that resistance to neutrophil-mediated bacterial clearance in Persistent isolates are partly mediated by loss of Type IV pilus-dependent motility and contributes to the persistence of new onset PA 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 | 0.000 |
| 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 | 0.001 |
| 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".