Modification of the Campylobacter jejuni N-Linked Glycan by EptC Protein-mediated Addition of Phosphoethanolamine
Bibliographic record
Abstract
Campylobacter jejuni is the major worldwide cause of bacterial gastroenteritis. C. jejuni possesses an extensive repertoire of carbohydrate structures that decorate both protein and non-protein surface-exposed structures. An N-linked glycosylation system encoded by the pgl gene cluster mediates the synthesis of a rigidly conserved heptasaccharide that is attached to protein substrates or released as free oligosaccharide in the periplasm. Removal of N-glycosylation results in reduced virulence and impeded host cell attachment. Since the N-glycan is conserved, the N-glycosylation system is also an attractive option for glycoengineering recombinant vaccines in Escherichia coli. To determine whether non-canonical N-glycans are present in C. jejuni, we utilized high throughput glycoproteomics to characterize C. jejuni JHH1 and identified 93 glycosylation sites, including 34 not previously reported. Interrogation of these data allowed the identification of a phosphoethanolamine (pEtN)-modified variant of the N-glycan that was attached to multiple proteins. The pEtN moiety was attached to the terminal GalNAc of the canonical N-glycan. Deletion of the pEtN transferase eptC removed all evidence of the pEtN-glycan but did not globally influence protein reactivity to patient sera, whereas deletion of the pglB oligosaccharyltransferase significantly reduced reactivity. Transfer of eptC and the pgl gene cluster to E. coli confirmed the addition of the pEtN-glycan to a target C. jejuni protein. Significantly reduced, yet above background levels of pEtN-glycan were also observed in E. coli not expressing eptC, suggesting that endogenous E. coli pEtN transferases can mediate the addition of pEtN to N-glycans. The addition of pEtN must be considered in the context of glycoengineering and may alter C. jejuni glycan-mediated structure-function interactions.
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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".