The end of the reign of a “master regulator’’? A defect in function of the LasR quorum sensing regulator is a common feature of <i>Pseudomonas aeruginosa</i> isolates
Bibliographic record
Abstract
ABSTRACT Pseudomonas aeruginosa , a bacterium causing infections in immunocompromised individuals, regulates several of its virulence functions using three interlinked quorum sensing (QS) systems ( las , rhl , and pqs ). Despite its presumed importance in regulating virulence, dysfunction of the las system regulator LasR occurs frequently in strains isolated from various environments, including clinical infections. This newfound abundance of LasR-defective strains calls into question existing hypotheses regarding their selection. Indeed, current assumptions concerning factors driving the emergence of LasR-deficient isolates and the role of LasR in the QS hierarchy must be reconsidered. Here, we propose that LasR is not the primary master regulator of QS in all P. aeruginosa genetic backgrounds, even though it remains ecologically significant. We also revisit and complement current knowledge on the ecology of LasR-dependent QS in P. aeruginosa , discuss the hypotheses explaining the putative adaptive benefits of selecting against LasR function, and consider the implications of this renewed understanding.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".