Proteome modifications on tomato under extreme high light induced-stress
Bibliographic record
Abstract
Abiotic stress reduces photosynthetic yield and plant growth, negatively impacting global crop production and is a major constraint faced by agriculture. However, the knowledge on the impact on plants under extremely high irradiance is limited. We present the first in-depth proteomics analysis of plants treated with a method developed by our research group to generate a light gradient using an extremely intense light. The method consists of utilizing light emitting diodes (LED) to create a single spot at 24,000 μmol m − 2 s − 1 irradiance, generating three light stress levels. A light map and temperature profile were obtained during the light experiment. The proteins expressed in the treated tomato ( Solanum lycopersicum , Heinz H1706) leaves were harvested 10 days after the treatment, allowing for the detection of proteins involved in a long-term recovery. A multiplex labeled proteomics method (iTRAQ) was analyzed by LC-MS/MS. A total of 3994 proteins were identified at 1% false discovery rate and matched additional quality filters. Hierarchical clustering analysis resulted in four types of patterns related to the protein expression, with one being directly linked to the increased LED irradiation. A total of 37 proteins were found unique to the least damaged leaf zone, while the medium damaged zone had 372 proteins, and the severely damaged presented unique 1003 proteins. Oxygen evolving complex and PSII complex proteins (PsbH, PsbS, PsbR and Psb28) were found to be abundant in the most damaged leaf zone. This leaf zone presented a protein involved in the salicylic acid response, while it was not abundant in the other leaf zones. The mRNA level of PsbR was significantly lower (1-fold) compared the control in the most damaged zone of the leaf, while Psb28 and PsbH were lower (1-fold) in the less damaged leaf zones. PsbS mRNA abundance in all leaf zones tested presented no statistically significant change from the control. We present the first characterization of the proteome changes caused by an extreme level of high-light intensity (24,000 μmol m − 2 s − 1 ). The proteomics results show the presence of specific defense responses to each level of light intensity, with a possible involvement of proteins PsbH, Psb28, PsbR, and PsbS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".