β-ionone regulates <i>Arabidopsis thaliana</i> transcriptome and increases its resistance against <i>Botrytis cinerea</i>
Bibliographic record
Abstract
Abstract Carotenoids are isoprenoid pigments vital for photosynthesis. Moreover, they are the precursor of apocarotenoids that include the phytohormones abscisic acid (ABA) and strigolactones (SLs), and retrograde signaling molecules and growth regulators, such as β-cyclocitral and zaxinone. The apocarotenoid β-ionone (β-I) was previously reported to exert antimicrobial effects. Here, we showed that the application of this scent 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. These changes, along with modulating the levels of the phytohormones ABA, jasmonic acid and salicylic acid, led to enhanced Arabidopsis resistance to Botrytis cinerea ( B.c. ), one of the most aggressive and widespread pathogenic fungi affecting numerous plant hosts and causing severe losses of postharvest fruits. Pre-treatment of tobacco and tomato plants with β-I followed by inoculation with B.c. confirms the conserved effect of β-I and induced immune responses in leaves and fruits. Moreover, there was reduced susceptibility to B.c. in LYCOPENE β-CYCLASE- expressing tomato fruits possessing elevated levels of the endogenous β-I, indicating beneficial biological activities of this compound in planta . Our work unraveled β-I as a further carotenoid-derived regulatory metabolite and opens up new possibilities to control B.c. infection by establishing this natural volatile as an environmentally friendly bio-fungicide.
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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".