Affinity-Capture Tandem Mass Spectrometric Characterization of Polyprenyl-Linked Oligosaccharides: Tool to Study Protein N-Glycosylation Pathways
Bibliographic record
Abstract
N-glycosylation of proteins is recognized as one of the most common post-translational modifications. Until recently it was believed that N-glycosylation occurred exclusively in eukaryotes before the discovery of the general protein glycosylation pathway (Pgl) in Campylobacter jejuni. To date, most techniques to analyze lipid-linked oligosaccharides (LLOs) of these pathways involve the use of radiolabels and chromatographic separation. Technologies capable of characterizing eukaryotic and the newly described bacterial N-glycosylation systems from biologically relevant samples in a quick, accurate, and cost-effective manner are needed. In this paper a new glycomics strategy based on lectin-affinity capture was devised and validated on the C. jejuni N-glycan pathway and the engineered Escherichia coli strains expressing the functional C. jejuni pathway. The lipid-linked oligosaccharide intermediates of the Pgl pathway were then enriched using SBA-agarose affinity-capture and examined by capillary electrophoresis-mass spectrometry (CE-MS). We demonstrate that this method is capable of detecting low levels of LLOs, the sugars are indeed assembled on undecaprenylpyrophosphate, and structural information for expected and unexpected LLOs can be obtained without further sample manipulation. Furthermore, CE-MS analyses of C. jejuni and the E. coli "glyco-factories" showed striking differences in the assembly and control of N-glycan biosynthesis.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".