Brassinosteroid functions to protect the translational machinery and heat‐shock protein synthesis following thermal stress
Bibliographic record
Abstract
In addition to their essential role in plant development, brassinosteroids have the ability to protect plants from various environmental stresses. Currently it is not understood how brassinosteroids control plant stress responses at the molecular level. We have begun an investigation into the molecular mechanisms underlying 24-epibrassinolide (EBR)-mediated stress resistance. Earlier we found that treatment of Brassica napus seedlings with EBR leads to a significant increase in their basic thermotolerance, and results in higher accumulation of four major classes of heat-shock proteins (hsps) as compared to untreated seedlings. Surprisingly, previous studies have shown that while hsp levels were significantly higher in treated seedlings during the recovery period, transcripts corresponding to these hsps were present at higher levels in untreated seedlings. To understand mechanisms controlling hsp synthesis in EBR-treated and untreated seedlings, we studied protein synthesis in vivo as well as in vitro, and assessed the levels of components of the translational machinery in these seedlings. We report here that increased accumulation of hsps in EBR-treated seedlings results from higher hsp synthesis, even when the mRNA levels are lower than in untreated seedlings, and that several translation initiation and elongation factors are present at significantly higher levels in EBR-treated seedlings as compared to untreated seedlings. These results suggest that EBR treatment limits the loss of some of the components of the translational apparatus during prolonged heat stress, and increases the level of expression of some of the components of the translational machinery during recovery, which correlates with a more rapid resumption of cellular protein synthesis following heat stress and a higher survival rate.
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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) | 0.001 | 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".