The regulation of 4-hydroxy-2-alkylquinoline biosynthesis by (p)ppGpp signalling and membrane stress in «Pseudomonas aeruginosa»
Bibliographic record
Abstract
Pseudomonas aeruginosa is a ubiquitous environmental bacterium and a major opportunistic human pathogen.This bacterium produces a family of small molecules called 4hydroxy-2-alkylquinolines (HAQ) that have many biological functions including in quorum sensing signaling (cell-cell communication), iron entrapment, antibiotic tolerance and antimicrobial activities.The stringent response is a global stress response mediated by the alarmone (p)ppGpp that allows bacteria to respond and adapt to nutrient and environmental stresses, and HAQs are overproduced when (p)ppGpp signaling is inactivated.The overall objective of this thesis was to understand the regulation of HAQ biosynthesis.The first objective of this thesis was to characterize how the stringent response and (p)ppGpp signaling regulates HAQ biosynthesis.We demonstrated that HHQ and PQS are overproduced in the SR mutant ((p)ppGpp-null) due to upregulation of the biosynthetic genes pqsABCD and pqsH.To determine the regulatory network that controls HAQ biosynthesis and how it is modulated by the stringent response, we reported that upregulation of pqsA in the SR mutant is the result of both increased PqsR mediated positive control, as well as reduced RhlR mediated inhibitory control.Furthermore, we uncovered that (p)ppGpp signaling is required for full expression of both las and rhl quorum sensing systems, and that the hierarchy of these interconnected signaling systems is modulated by the stringent response.Although PqsR is the primary known positive transcriptional regulators of HAQ biosynthesis, we observed that pqsA expression remains upregulated in the SRpqsR mutant suggesting other yet unknown regulators of HAQ biosynthesis.Our second objective was thus to identify novel positive regulators of HAQ biosynthesis by performing a random transposon mutagenesis screen for reduced pqsA-lacZ reporter activity in the SRpqsR mutant.From over 50,000 mutant clones screened, we identified 26 candidate genes as potential positive regulators of pqsA expression.Following
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".