An enlarged cell wall proteome of <i>Arabidopsis thaliana</i> rosettes
Bibliographic record
Abstract
Plant cells are surrounded by cell walls playing many roles during development and in response to environmental constraints. Cell walls are mainly composed of polysaccharides (cellulose, hemicelluloses and pectins), but they also contain proteins which are critical players in cell wall remodeling processes. Today, the cell wall proteome of Arabidopsis thaliana, a major dicot model plant, comprises more than 700 proteins predicted to be secreted (cell wall proteins-CWPs) identified in different organs or in cell suspension cultures. However, the cell wall proteome of rosettes is poorly represented with only 148 CWPs identified after extraction by vacuum infiltration. This new study allows enlarging its coverage. A destructive method starting with the purification of cell walls has been performed and two experiments have been compared. They differ by the presence/absence of protein separation by a short 1D-electrophoresis run prior to tryptic digestion and different gradient programs for peptide separation before mass spectrometry analysis. Altogether, the rosette cell wall proteome has been significantly enlarged to 361 CWPs, among which 213 newly identified in rosettes and 57 newly described. The identified CWPs fall in four major functional classes: 26.1% proteins acting on polysaccharides, 11.1% oxido-reductases, 14.7% proteases and 11.7% proteins possibly related to lipid metabolism.
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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".