NtrBC Selectively Regulates Host-Pathogen Interactions, Virulence, and Ciprofloxacin Susceptibility of Pseudomonas aeruginosa
Bibliographic record
Abstract
Pseudomonas aeruginosa is a metabolically versatile opportunistic pathogen capable of infecting distinct niches of the human body, including skin wounds and the lungs of cystic fibrosis patients. Eradication of P. aeruginosa infection is becoming increasingly difficult due to the numerous resistance mechanisms it employs. Adaptive resistance is characterized by a transient state of decreased susceptibility to antibiotic therapy that is distinct from acquired or intrinsic resistance, can be triggered by various environmental stimuli and reverted by removal of the stimulus. Further, adaptive resistance is intrinsically linked to lifestyles such as swarming motility and biofilm formation, both of which are important in infections and lead to multi-drug adaptive resistance. Here, we demonstrated that NtrBC, the master of nitrogen control, had a selective role in host colonization and a substantial role in determining intrinsic resistance to ciprofloxacin. P. aeruginosa mutant strains (Δ ntrB , Δ ntrC and Δ ntrBC ) colonized the skin but not the respiratory tract of mice as well as WT and, unlike WT, could be reduced or eradicated from the skin by ciprofloxacin. We hypothesized that nutrient availability contributed to these phenomena and found that susceptibility to ciprofloxacin was impacted by nitrogen source in laboratory media. P. aeruginosa Δ ntrB , Δ ntrC and Δ ntrBC also exhibited distinct host interactions, including modestly increased cytotoxicity toward human bronchial epithelial cells, reduced virulence factor production and 10-fold increased uptake by macrophages. These data might explain why NtrBC mutants were less adept at colonizing the upper respiratory tract of mice. Thus, NtrBC represents a link between nitrogen metabolism, adaptation and virulence of the pathogen P. aeruginosa , and could represent a target for eradication of recalcitrant infections in situ .
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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 | 0.001 |
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".