<i>Pseudomonas aeruginosa relA</i> Contributes to Virulence in <i>Drosophila melanogaster</i>
Bibliographic record
Abstract
The stringent response is a mechanism by which bacteria adapt to nutritional deficiencies through the production of the guanine nucleotides ppGpp and pppGpp, produced by the RelA enzyme. We investigated the role of the relA gene in the ability of an extracellular pathogen, Pseudomonas aeruginosa, to cause infection. Strains lacking the relA gene were created from the prototypical laboratory strain PAO1 as well as the mucoid cystic fibrosis isolate 6106, which lacks functional quorum-sensing systems. The absence of relA abolished the production of ppGpp and pppGpp under conditions of amino acid starvation. We found that strains lacking relA exhibited reduced virulence in a D. melanogaster feeding assay. In conditions of low magnesium, the relA gene enhanced production of the cell-cell signal N-[3-oxododecanoyl]-l-homoserine lactone, whereas relA reduced the production of the 2-heptyl-3-hydroxy-4-quinolone signal during serine hydroxamate induction of the stringent response. In the relA mutant, alterations in the Pseudomonas quinolone system pathways seemed to increase the production of pyocyanin and decrease the production of elastase. Deletion of relA also resulted in reduced levels of the RpoS sigma factor. These results suggest that adjustment of cellular ppGpp and pppGpp levels could be an important regulatory mechanism in P. aeruginosa adaptation in pathogenic relationships.
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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 | 0.001 |
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".