Diurnal changes in concerted plant protein phosphorylation and acetylation in Arabidopsis organs and seedlings
Bibliographic record
Abstract
Protein phosphorylation and acetylation are the two most abundant post-translational modifications (PTMs) that regulate protein functions in eukaryotes. In plants, these PTMs have been investigated individually; however, their co-occurrence and dynamics on proteins is currently unknown. Using Arabidopsis thaliana, we quantified changes in protein phosphorylation, acetylation and protein abundance in leaf rosettes, roots, flowers, siliques and seedlings at the end of day (ED) and at the end of night (EN). This identified 2549 phosphorylated and 909 acetylated proteins, of which 1724 phosphorylated and 536 acetylated proteins were also quantified for changes in PTM abundance between ED and EN. Using a sequential dual-PTM workflow, we identified significant PTM changes and intersections in these organs and plant developmental stages. In particular, cellular process-, pathway- and protein-level analyses reveal that the phosphoproteome and acetylome predominantly intersect at the pathway- and cellular process-level at ED versus EN. We found 134 proteins involved in core plant cell processes, such as light harvesting and photosynthesis, translation, metabolism and cellular transport, that were both phosphorylated and acetylated. Our results establish connections between PTM motifs, PTM catalyzing enzymes and putative substrate networks. We also identified PTM motifs for further characterization of the regulatory mechanisms that control cellular processes during the diurnal cycle in different Arabidopsis organs and seedlings. The sequential dual-PTM analysis expands our understanding of diurnal plant cell regulation by PTMs and provides a useful resource for future analyses, while emphasizing the importance of analyzing multiple PTMs simultaneously to elucidate when, where and how they are involved in plant cell regulation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".