The apocarotenoid β‐ionone regulates the transcriptome of <i>Arabidopsis thaliana</i> and increases its resistance against <i>Botrytis cinerea</i>
Bibliographic record
Abstract
Carotenoids are isoprenoid pigments indispensable for photosynthesis. Moreover, they are the precursor of apocarotenoids, which include the phytohormones abscisic acid (ABA) and strigolactones (SLs) as well as retrograde signaling molecules and growth regulators, such as β-cyclocitral and zaxinone. Here, we show that the application of the volatile apocarotenoid β-ionone (β-I) to Arabidopsis plants at micromolar concentrations caused a global reprogramming of gene expression, affecting thousands of transcripts involved in stress tolerance, growth, hormone metabolism, pathogen defense, and photosynthesis. This transcriptional reprogramming changes, along with induced changes in the level of the phytohormones ABA, jasmonic acid, and salicylic acid, led to enhanced Arabidopsis resistance to the widespread necrotrophic fungus Botrytis cinerea (B.c.) that causes the gray mold disease in many crop species and spoilage of harvested fruits. Pre-treatment of tobacco and tomato plants with β-I followed by inoculation with B.c. confirmed the effect of β-I in increasing the resistance to this pathogen in crop plants. Moreover, we observed reduced susceptibility to B.c. in fruits of transgenic tomato plants overexpressing LYCOPENE β-CYCLASE, which contains elevated levels of endogenous β-I, providing a further evidence for its effect on B.c. infestation. Our work unraveled β-I as a further carotenoid-derived regulatory metabolite and indicates the possibility of establishing this natural volatile as an environmentally friendly bio-fungicide to control B.c.
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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 | 0.000 |
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".