Proteome-wide analysis of hydrogen peroxide-induced protein carbonylation in Arabidopsis thaliana
Bibliographic record
Abstract
Introduction: Protein carbonylation is a non-enzymatic and irreversible post-translational modification that occurs naturally in living organisms under the direct or indirect effect of reactive oxygen species (ROS). In animals, signaling pathways involving numerous carbonylated proteins have been identified, highlighting the dual role of these molecules in ROS signal transduction. In plants, studies on phytohormone signaling (auxin, methyl jasmonate, abscisic acid) have shown that reactive carbonyl species (RCS: acrolein, malondialdehyde, 4-hydroxynonenal, etc.), derived from the action of ROS on lipids, play important roles in secondary root formation and stomatal closure. However, the carbonylated proteins involved in these signaling pathways remain to be identified. Methods: In this study, we analyzed proteins responsive to carbonylation by exogenous hydrogen peroxide (H2O2) by profiling the carbonyl proteome extracted from Arabidopsis thaliana leaves after H2O2 treatment. Carbonylated proteins were enriched at the peptide level and analyzed by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). Results and discussion: We identified 35 and 39 uniquely carbonylated proteins in the untreated and the H2O2-treated plant samples, respectively. In comparison to the control treatment, gene ontology enrichment analysis revealed that most of the carbonylated proteins identified in the H2O2-treated plant samples are related to sulfate adenylyl transferases and amidophosphoribosyl transferases involved in the immune system response, defense response, and external stimulus-response. These results indicated that exogenous H2O2 caused a change in the pattern of protein carbonylation in A. thaliana leaves. Protein carbonylation may thus influence the plant transcriptome and metabolism in response to H2O2 and ROS-triggering external stimuli.
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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 | 0.001 | 0.001 |
| 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".