Sweet to the extreme: protein glycosylation in Archaea
Bibliographic record
Abstract
Post-translational modifications account for much of the biological diversity generated at the proteome level. Of these, glycosylation is the most prevalent. Long thought to be unique to Eukarya, it is now clear that both Bacteria and Archaea are also capable of N-glycosylation, namely the covalent linkage of oligosaccharides to select target asparagine residues. However, while the eukaryal and bacterial N-glycosylation pathways are relatively well defined, little is known of the parallel process in Archaea. Of late, however, major advances have been made in describing the process of archaeal N-glycosylation. Such efforts have shown, as is often the case in archaeal biology, that protein N-glycosylation in Archaea combines particular aspects of the eukaryal and bacterial pathways along with traits unique to this life form. For instance, while the oligosaccharides of archaeal glycoproteins include nucleotide-activated sugars formed by bacterial pathways, the lipid carrier on which such oligosaccharides are assembled is the same as used in eukaryal N-glycosylation. By contrast, transfer of assembled oligosaccharides to their protein targets shows Archaea-specific properties. Finally, addressing N-glycosylation from an archaeal perspective is providing new general insight into this event, as exemplified by the solution of the first crystal structure of an oligosaccharide transferase from an archaeal source.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".