The Stringent Response Modulates 4-Hydroxy-2-Alkylquinoline Biosynthesis and Quorum-Sensing Hierarchy in Pseudomonas aeruginosa
Bibliographic record
Abstract
As a ubiquitous environmental organism and an important human pathogen, Pseudomonas aeruginosa readily adapts and responds to a wide range of conditions and habitats. The intricate regulatory networks that link quorum sensing and other global regulators allow P. aeruginosa to coordinate its gene expression and cell signaling in response to different growth conditions and stressors. Upon nutrient transitions and starvation, as well as other environmental stresses, the stringent response is activated, mediated by the signal (p)ppGpp. P. aeruginosa produces a family of molecules called HAQ (4-hydroxy-2-alkylquinolines), some of which exhibit antibacterial and quorum-sensing signaling functions and regulate virulence genes. In this study, we report that (p)ppGpp negatively regulates HAQ biosynthesis: in a (p)ppGpp-null (ΔSR) mutant, HHQ (4-hydroxyl-2-heptylquinoline) and PQS (3,4-dihydroxy-2-heptylquinoline) levels are increased due to upregulated pqsA and pqsR expression and reduced repression by the rhl system. We also found that (p)ppGpp is required for full expression of both rhl and las AHL (acyl-homoserine lactone) quorum-sensing systems, since the ΔSR mutant has reduced rhlI, rhlR, lasI, and lasR expression, butanoyl-homoserine lactone (C4-HSL) and 3-oxo-dodecanoyl-homoserine lactone (3-oxo-C12-HSL) levels, and rhamnolipid and elastase production. Furthermore, (p)ppGpp significantly modulates the AHL and PQS quorum-sensing hierarchy, as the las system no longer has a dominant effect on HAQ biosynthesis when the stringent response is inactivated.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".