N-linked glycosylation enzymes in the diatom Thalassiosira oceanica exhibit a diel cycle in transcript abundance and favor for NXT-type sites
Bibliographic record
Abstract
N-linked glycosylation is a posttranslational modification affecting protein folding and function. The N-linked glycosylation pathway in algae is poorly characterized, and further knowledge is needed to understand the cell biology of algae and the evolution of N-linked glycosylation. This study investigated the N-linked glycosylation pathway in Thalassiosira oceanica, an open ocean diatom adapted to survive at growth-limiting iron concentrations. Here we identified and annotated the genes coding for the essential enzymes involved in the N-linked glycosylation pathway of T. oceanica. Transcript levels for genes coding for calreticulin, oligosaccharyltransferase (OST), N-acetylglucosaminyltransferase (GnT1), and UDP-glucose glucosyltransferase (UGGT) under high- and low-iron growth conditions revealed diel transcription patterns with a significant decrease of calreticulin and OST transcripts under iron-limitation. Solid-phase extraction of N-linked glycosylated peptides (SPEG) revealed 118 N-linked glycosylated peptides from cells grown in high- and low-iron growth conditions. The identified peptides had 81% NXT-type motifs, with X being any amino acids except proline. The presence of N-linked glycosylation sites in the iron starvation-induced protein 1a (ISIP1a) confirmed its predicted topology, contributing to the biochemical characterization of ISIP1 proteins. Analysis of extensive oceanic gene databases showed a global distribution of calreticulin, OST, and UGGT, reinforcing the importance of glycosylation in microalgae.
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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) | 0.000 | 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 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".