Pqs<scp>R</scp>‐dependent and Pqs<scp>R</scp>‐independent regulation of motility and biofilm formation by <scp>PQS</scp> in <i>Pseudomonas aeruginosa</i> PAO1
Bibliographic record
Abstract
Pseudomonas aeruginosa is an opportunistic pathogen capable of group behaviors including swarming motility and biofilm formation. Swarming motility plays an important role in the bacterium's spread to new environments, attachment to surfaces, and biofilm formation. Bacterial biofilm is associated with many persistent infections and increased resistance to antibiotics. In this study, we tested the effect of a 2-alkyl-4(1H)-quinolone (AHQ) signal, the Pseudomonas quinolone signal (PQS) on P. aeruginosa swarming and biofilm formation. Our results show that PQS repressed the swarming motility of P. aeruginosa PAO1. Such repression was independent of its cognate receptor PqsR and was not related to changes in the flagellae, type IV pili or the production of the surface-wetting agent rhamnolipid surfactant. While PQS did not affect twitching motility in PAO1, a pqsR deletion abolished twitching motility, indicating that pqsR is required for twitching motility. Our results also indicate that the enhancement of biofilm formation by PQS is at least partially dependent on the GacAS-Rsm regulatory pathway but does not involve the las or rhl QS systems.
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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 | 0.000 |
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".