The long‐chain fatty acid sensor, PsrA, modulates the expression of <i>rpoS</i> and the type III secretion <i>exsCEBA</i> operon in <i>Pseudomonas aeruginosa</i>
Bibliographic record
Abstract
The Pseudomonas aeruginosa PsrA autorepressor has dual roles as a repressor of the fadBA5beta-oxidation operon and an activator of the stationary-phase sigma factor rpoS and exsCEBA operon of the type III secretion system (TTSS). Previously, we demonstrated that the repression of the fadBA5 operon by PsrA is relieved by long-chain fatty acids (LCFAs). However, the signal affecting the activation of rpoS and exsC via PsrA is unknown. In this study, microarray and gene fusion data suggested that LCFA (e.g. oleate) affected the expression of rpoS and exsC. DNA binding studies confirmed that PsrA binds to the rpoS and exsC promoter regions. This binding was inhibited by LCFA, indicating that LCFA directly affects the activation of these two genes through PsrA. LCFA decreased rpoS and exsC expression, resulting in increased N-(butyryl)-l-homoserine-lactone quorum sensing signal and decreased ExoS/T production respectively. Based on the crystal structure of PsrA, site-directed mutagenesis of amino acid residues, within the hydrophobic channel thought to accommodate LCFA, created two LCFA-non-responsive PsrA mutants. The binding and activation of rpoS and exsC by these PsrA mutants was no longer inhibited by LCFA. These data support a mechanistic model where LCFAs influence PsrA regulation to control LCFA metabolism and some virulence genes in P. aeruginosa.
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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".