Sufficient coumarin accumulation improves apple resistance to<i>Cytospora mali</i>under high-potassium status
Bibliographic record
Abstract
Cytospora canker, caused by Cytospora mali, is the most destructive disease in production of apples (Malus domestica). Adding potassium (K) to apple trees can effectively control this disease. However, the underlying mechanisms of apple resistance to C. mali under high-K (HK) status remain unknown. Here, we found that HK (9.30 g/kg) apple tissues exhibited high disease resistance. The resistance was impeded when blocking K channels, leading to susceptibility even under HK conditions. We detected a suite of resistance events in HK apple tissues, including upregulation of resistance genes, callose deposition, and formation of ligno-suberized tissues. Further multiomics revealed that the phenylpropanoid pathway was reprogrammed by increasing K content from low-K (LK, 4.30 g/kg) status, leading to increases of 18 antifungal chemicals. Among them, the physiological concentration of coumarin (1,2-benzopyrone) became sufficient to inhibit C. mali growth in HK tissues, and exogenous application could improve the C. mali resistance of LK apple branches. Transgenic apple calli overexpressing beta-glucosidase 40 (MdBGLU40), which encodes the enzyme for coumarin synthesis, contained higher levels of coumarin and exhibited high resistance to C. mali even under LK conditions. Conversely, the suppression of MdBGLU40 through RNAi reduced coumarin content and resistance in HK apple calli, supporting the importance of coumarin accumulation in vivo for apple resistance. Moreover, we found that the upregulation of transcription factor MdMYB1r1 directly activated MdBGLU40 and the binding affinity of MdMYB1r1 to the MdBGLU40 promoter increased in HK apple tissue, leading to high levels of coumarin and resistance in HK apple. Overall, we found that the accumulation of defensive metabolites strengthened resistance in apple when raising K from insufficient to optimal status, and these results highlight the optimization of K content in fertilization practices as a disease management strategy.
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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".