Characterization of Alanine Catabolism in<i>Pseudomonas aeruginosa</i>and Its Importance for Proliferation In Vivo
Bibliographic record
Abstract
The opportunistic pathogen Pseudomonas aeruginosa causes a variety of infections in immunocompromised individuals, including individuals with the heritable disease cystic fibrosis. Like the carbon sources metabolized by many disease-causing bacteria, the carbon sources metabolized by P. aeruginosa at the host infection site are unknown. We recently reported that l-alanine is a preferred carbon source for P. aeruginosa and that two genes potentially involved in alanine catabolism (dadA and dadX) are induced during in vivo growth in the rat peritoneum and during in vitro growth in sputum (mucus) collected from the lungs of individuals with cystic fibrosis. The goals of this study were to characterize factors required for alanine catabolism in P. aeruginosa and to assess the importance of these factors for in vivo growth. Our results reveal that dadA and dadX are arranged in an operon and are required for catabolism of l-alanine. The dad operon is inducible by l-alanine, d-alanine, and l-valine, and induction is dependent on the transcriptional regulator Lrp. Finally, we show that a mutant unable to catabolize dl-alanine displays decreased competitiveness in a rat lung model of infection.
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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) | 0.001 | 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".