Staphylococcus aureus interaction with Pseudomonas aeruginosa biofilm enhances tobramycin resistance
Bibliographic record
Abstract
Abstract Antimicrobial resistance is a significant threat to the treatment of infectious disease. Multiple mechanisms of resistance to different classes of antibiotics have been identified and well-studied. However, these mechanisms are studied with bacteria in isolation, whereas often, infections have a polymicrobial basis. Using a biofilm slide chamber model, we visualized the formation and development of clinical Pseudomonas aeruginosa biofilms in the presence of secreted Staphylococcus aureus exoproducts, two bacteria that commonly co-infect pediatric patients with cystic fibrosis. We showed that, over time, certain isolates of P. aeruginosa can form different biofilm architecture in the presence of S. aureus exoproducts. We further determined that this interaction was dependent on Psl produced by P. aeruginosa and staphylococcal protein A from S. aureus . Importantly, we identified a mechanism of antibiotic resistance to tobramycin that is dependent on the polymicrobial interactions between these two bacteria. This interaction occurred in isolates of P. aeruginosa recovered from children with cystic fibrosis who failed to clear P. aeruginosa following inhaled tobramycin treatment.
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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".