Role of AprA and pyocyanin from Pseudomonas aeruginosa on Staphylococcus aureus tolerance to silver
Bibliographic record
Abstract
The opportunistic pathogens Staphylococcus aureus and Pseudomonas aeruginosa are often found together causing persistent infections where they exhibit complex interactions that affect their virulence and resistance to treatment. We sought to clarify how interactions between these organisms affect their resistance to the antimicrobial metal silver (AgNO3). As previous work showed that cell-free supernatant from P. aeruginosa enhances the resistance of S. aureus, we aimed to identify the exact factor(s) responsible for this increase. Using molecular weight cutoff filters and proteomics, we identified the protein AprA and pyocyanin as the responsible factors. Transposon-mediated disruption of aprA led to the production of supernatant which could not enhance the silver tolerance of S. aureus. These findings suggest that the protease AprA from P. aeruginosa plays an important role in increasing the tolerance of S. aureus to AgNO3 via in part by mediating the levels of pyocyanin which in turn reduces Ag2+ to detoxify it.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".