Production of quorum sensing-related metabolites and phytoalexins during Pseudomonas aeruginosa–Brassica napus interaction
Bibliographic record
Abstract
Pseudomonas aeruginosa is an opportunistic bacterial pathogen that has been shown to interact with many organisms throughout the domains of life, including plants. How this broad-host-range bacterium interacts with each of its diverse hosts, especially the metabolites that mediate these interactions, is not completely known. In this work, we used a liquid culture root infection system to collect plant and bacterial metabolites on days 1, 3 and 5 post- P . aeruginosa (strain PA14) infection of the oilseed plant, canola ( Brassica napus ). Using MS-based metabolomics approaches, we identified the overproduction of quorum sensing (QS)-related (both signalling molecules and regulated products) metabolites by P. aeruginosa while interacting with canola plants. However, the P. aeruginosa infection induced the production of several phytoalexins, which is a part of the hallmark plant defence response to microbes. The QS system of PA14 appears to only mediate part of the canola –P. aeruginosa metabolomic interactions, as the use of isogenic mutant strains of each of the three QS signalling branches did not significantly affect the induction of the phytoalexin brassilexin, while induction of spirobrassinin was significantly decreased. Interestingly, a treatment of purified QS molecules in the absence of bacteria was not able to induce any phytoalexin production, suggesting that active bacterial colonization is required for eliciting phytoalexin production. Furthermore, we identified that brassilexin, the only commercially available phytoalexin that was detected in this study, demonstrated a MIC of 400 µg ml −1 against P. aeruginosa PA14. The production of phytoalexins can be an effective component of canola innate immunity to keep potential infections by the opportunistic pathogen P. aeruginosa at bay.
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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 | 0.000 | 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) | 0.000 | 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".