N-Linked Glycosylation in Archaea: a Structural, Functional, and Genetic Analysis
Bibliographic record
Abstract
N-glycosylation of proteins is one of the most prevalent posttranslational modifications in nature. Accordingly, a pathway with shared commonalities is found in all three domains of life. While excellent model systems have been developed for studying N-glycosylation in both Eukarya and Bacteria, an understanding of this process in Archaea was hampered until recently by a lack of effective molecular tools. However, within the last decade, impressive advances in the study of the archaeal version of this important pathway have been made for halophiles, methanogens, and thermoacidophiles, combining glycan structural information obtained by mass spectrometry with bioinformatic, genetic, biochemical, and enzymatic data. These studies reveal both features shared with the eukaryal and bacterial domains and novel archaeon-specific aspects. Unique features of N-glycosylation in Archaea include the presence of unusual dolichol lipid carriers, the use of a variety of linking sugars that connect the glycan to proteins, the presence of novel sugars as glycan constituents, the presence of two very different N-linked glycans attached to the same protein, and the ability to vary the N-glycan composition under different growth conditions. These advances are the focus of this review, with an emphasis on N-glycosylation pathways in Haloferax, Methanococcus, and Sulfolobus.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".