Competition between Pseudomonas aeruginosa and Staphylococcus aureus is dependent on intercellular signaling and regulated by the NtrBC two-component system
Bibliographic record
Abstract
Pseudomonas aeruginosa and Staphylococcus aureus are often comorbid human pathogens, isolated from expectorated sputum of cystic fibrosis patients and chronically infected wounds. Prior studies revealed a competitive advantage of P. aeruginosa over S. aureus in vitro that was slightly muted in vivo. Here, we demonstrated that the two-component regulatory system NtrBC influences the competitive advantage of P. aeruginosa over S. aureus in skin organoid and mouse models of co-infection. Expression of ntrBC was induced during co-culture of the two species and could be recapitulated in monoculture by the addition of the metabolite N-acetylglucosamine that is released from S. aureus following lysis. P. aeruginosa LESB58 WT, but not mutant (ΔntrC and ΔntrBC) strains, induced lysis of S. aureus USA300 LAC during planktonic growth and outcompeted S. aureus USA300 LAC during biofilm formation in vitro. We confirmed these findings in a murine abscess model of high-density infection. Accordingly, the secretory profile of P. aeruginosa LESB58 mutants revealed reduced production of anti-staphylococcal virulence factors including pyoverdine, pyocyanin and elastase. These phenotypes of LESB58 ΔntrBC could be at least partly complemented by overexpression of quorum sensing molecules including homoserine lactones or alkylquinolone signaling molecules. These data implicate the NtrBC two-component system in the complex regulatory cascade triggered by interspecies signaling that gives P. aeruginosa LESB58 a competitive edge over S. aureus USA300 LAC.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".