<i>In planta</i> sequential hydroxylation and glycosylation of a fungal phytotoxin: Avoiding cell death and overcoming the fungal invader
Bibliographic record
Abstract
To facilitate plant colonization, some pathogenic fungi produce phytotoxic metabolites that damage tissues; plants may be resistant to a particular pathogen if they produce an enzyme(s) that catalyzes detoxification of this metabolite(s). Alternaria blackspot is one of the most damaging and significant fungal diseases of brassica crops, with no source of resistance known within the Brassica species. Destruxin B is the major phytotoxin produced by the blackspot-causing fungus, Alternaria brassicae (Berkley) Saccardo. We have established that a blackspot-resistant species (Sinapis alba) metabolized (14)C-labeled destruxin B to a less toxic product substantially faster than any of the susceptible species. The first metabolite, hydroxydestruxin B ((14)C-labeled), was further biotransformed to the beta-d-glucosyl derivative at a slower rate. The structures of hydroxydestruxin B and beta-d-glucosyl hydroxydestruxin B were deduced from their spectroscopic data [NMR, high resolution (HR)-MS, Fourier transform infrared (FTIR)] and confirmed by total chemical synthesis. Although these hydroxylation and glucosylation reactions occurred in both resistant (S. alba) and susceptible (Brassica napus, Brassica juncea, and Brassica rapa) species, hydroxylation was the rate limiting step in the susceptible species, whereas glucosylation was the rate limiting step in the resistant species. Remarkably, it was observed that the hydroxydestruxin B induced the biosynthesis of phytoalexins in blackspot-resistant species but not in susceptible species. This appears to be a unique example of phytotoxin detoxification and simultaneous phytoalexin elicitation by the detoxification product. Our studies suggest that S. alba can overcome the fungal invader through detoxification of destruxin B coupled with production of phytoalexins.
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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".