Ethylene‐dependent/ethylene‐independent ABA regulation of tomato plants colonized by arbuscular mycorrhiza fungi
Bibliographic record
Abstract
We investigated the relationship between ABA and ethylene regulating the formation of the arbuscular mycorrhiza (AM) symbiosis in tomato (Solanum lycopersicum) plants and tried to define the specific roles played by each of these phytohormones in the mycorrhization process. We analysed the impact of ABA biosynthesis inhibition on mycorrhization by Glomus intraradices in transgenic tomato plants with an altered ethylene pathway. We also studied the effects on mycorrhization in sitiens plants treated with the aminoethoxyvinyl glycine hydrochloride (AVG) ethylene biosynthesis inhibitor and supplemented with ABA. In addition, the expression of plant and fungal genes involved in the mycorrhization process was studied. ABA biosynthesis inhibition qualitatively altered the parameters of mycorrhization in accordance with the plant's ethylene perception and ethylene biosynthesis abilities. Inhibition of ABA biosynthesis in wild-type plants negatively affected all the mycorrhization parameters studied, while tomato mutants impaired in ethylene synthesis only showed a reduced arbuscular abundance in mycorrhizal roots. Inhibition of ethylene synthesis in ABA-deficient sitiens plants increased the intensity of mycorrhiza development, while ABA application rescued arbuscule abundance in the root's mycorrhizal zones. The results of our study show an antagonistic interaction between ABA and ethylene, and different roles of each of the two hormones during AM formation. This suggests that a dual ethylene-dependent/ethylene-independent mechanism is involved in ABA regulation of AM formation.
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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".