Endoplasmic reticulum‐associated N‐glycan degradation of cold‐upregulated glycoproteins in response to chilling stress in <i>Arabidopsis</i>
Bibliographic record
Abstract
N-glycosylation has a great impact on glycoprotein structure, conformation, stability, solubility, immunogenicity and enzyme activity. Structural characterization of N-glycoproteome has been challenging but can provide insights into the extent of protein folding and surface topology. We describe a highly sensitive proteomics method for large-scale identification and quantification of glycoproteins in Arabidopsis through (15) N-metabolic labeling, selective enrichment of glycopeptides, data-dependent MS/MS analysis and automated database searching. In-house databases of Arabidopsis glycoproteins and glycopeptides containing Asn-X-Ser/Thr/Cys motifs were constructed by reducing 20% and 90% of the public database size, respectively, to enable a rapid analysis of large datasets for comprehensive identification and quantification of glycoproteins and heterogeneous N-glycans in a complex mixture. Proteome-wide analysis identified c. 100 stress-related N-glycoproteins, of which the endoplasmic reticulum (ER) resident proteins were examined to be up-regulated. Quantitative measurements provided a molecular signature specific to glycoproteins for determining the degree of plant stress at low temperature. Structural N-glycoproteomics following time-course cold treatments revealed the stress-responsive degradation of high-mannose type N-glycans in ER in response to chilling stress, which may aid in elucidating the cellular mechanisms of protein relocation, transport, trafficking, misfolding and degradation under stress conditions.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 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".