Identification of novel carbohydrate modifications on <i>Campylobacter jejuni</i> 11168 flagellin using metabolomics‐based approaches
Bibliographic record
Abstract
It is well known that the flagellin of Campylobacter jejuni is extensively glycosylated by pseudaminic acid and the related acetamindino derivative, in addition to flagellin glycosylation being essential for motility and colonization of host cells. Recently, the use of metabolomics permitted the unequivocal characterization of unique flagellin modifications in Campylobacter, including novel legionaminic acid sugars in Campylobacter coli, which had been impossible to ascertain in earlier studies using proteomics-based approaches. To date, the precise identities of the flagellin glycosylation modifications have only been elucidated for C. jejuni 81-176 and C. coli VC167 and those present in the first genome-sequenced strain C. jejuni 11168 remain elusive due to lability and respective levels of individual glycan modifications. We report the characterization of the carbohydrate modifications on C. jejuni 11168 flagellin using metabolomics-based approaches. Detected as their corresponding CMP-linked precursors, structural information on the flagellin modifications was obtained using a combination of MS and NMR spectroscopy. In addition to the pseudaminic acid and legionaminic acid sugars known to be present on Campylobacter flagellin, two unusual 2,3-di-O-methylglyceric acid modifications of a nonulosonate sugar were identified. By performing a metabolomic analysis of selected isogenic mutants of genes from the flagellin glycosylation locus of this pathogen, these novel CMP-linked precursors were confirmed to be di-O-methylglyceric acid derivatives of pseudaminic acid and the related acetamidino sugar. This is the first comprehensive analysis of the flagellar modifications in C. jejuni 11168 and structural elucidation of di-O-methylglyceric acid derivatives of pseudaminic acid on Campylobacter flagellin.
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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 | 0.000 | 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) | 0.001 | 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".