Red death in <i>Caenorhabditis elegans</i> caused by <i>Pseudomonas aeruginosa</i> PAO1
Bibliographic record
Abstract
During host injury, Pseudomonas aeruginosa can be cued to express a lethal phenotype within the intestinal tract reservoir-a hostile, nutrient scarce environment depleted of inorganic phosphate. Here we determined if phosphate depletion activates a lethal phenotype in P. aeruginosa during intestinal colonization. To test this, we allowed Caenorhabditis elegans to feed on lawns of P. aeruginosa PAO1 grown on high and low phosphate media. Phosphate depletion caused PAO1 to kill 60% of nematodes whereas no worms died on high phosphate media. Unexpectedly, intense redness was observed in digestive tubes of worms before death. Using a combination of transcriptome analyses, mutants, and reporter constructs, we identified 3 global virulence systems that were involved in the "red death" response of P. aeruginosa during phosphate depletion; they included phosphate signaling (PhoB), the MvfR-PQS pathway of quorum sensing, and the pyoverdin iron acquisition system. Activation of all 3 systems was required to form a red colored PQS+Fe(3+) complex which conferred a lethal phenotype in this model. When pyoverdin production was inhibited in P. aeruginosa by providing excess iron, red death was attenuated in C. elegans and mortality was decreased in mice intestinally inoculated with P. aeruginosa. Introduction of the red colored PQS+Fe(3+) complex into the digestive tube of C. elegans or mouse intestine caused mortality associated with epithelial disruption and apoptosis. In summary, red death in C. elegans reveals a triangulated response between PhoB, MvfR-PQS, and pyoverdin in response to phosphate depletion that activates a lethal phenotype in P. aeruginosa.
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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".