Role of camalexin, indole glucosinolates, and side chain modification of glucosinolate‐derived isothiocyanates in defense of Arabidopsis against <i>Sclerotinia sclerotiorum</i>
Bibliographic record
Abstract
Plant secondary metabolites are known to facilitate interactions with a variety of beneficial and detrimental organisms, yet the contribution of specific metabolites to interactions with fungal pathogens is poorly understood. Here we show that, with respect to aliphatic glucosinolate-derived isothiocyanates, toxicity against the pathogenic ascomycete Sclerotinia sclerotiorum depends on side chain structure. Genes associated with the formation of the secondary metabolites camalexin and glucosinolate were induced in Arabidopsis thaliana leaves challenged with the necrotrophic pathogen S. sclerotiorum. Unlike S. sclerotiorum, the closely related ascomycete Botrytis cinerea was not identified to induce genes associated with aliphatic glucosinolate biosynthesis in pathogen-challenged leaves. Mutant plant lines deficient in camalexin, indole, or aliphatic glucosinolate biosynthesis were hypersusceptible to S. sclerotiorum, among them the myb28 mutant, which has a regulatory defect resulting in decreased production of long-chained aliphatic glucosinolates. The antimicrobial activity of aliphatic glucosinolate-derived isothiocyanates was dependent on side chain elongation and modification, with 8-methylsulfinyloctyl isothiocyanate being most toxic to S. sclerotiorum. This information is important for microbial associations with cruciferous host plants and for metabolic engineering of pathogen defenses in cruciferous plants that produce short-chained aliphatic glucosinolates.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
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".