Targeted Metabolomics Analysis of Campylobacter coli VC167 Reveals Legionaminic Acid Derivatives as Novel Flagellar Glycans
Bibliographic record
Abstract
Glycosylation of Campylobacter flagellin is required for the biogenesis of a functional flagella filament. Recently, we used a targeted metabolomics approach using mass spectrometry and NMR to identify changes in the metabolic profile of wild type and mutants in the flagellar glycosylation locus, characterize novel metabolites, and assign function to genes to define the pseudaminic acid biosynthetic pathway in Campylobacter jejuni 81-176 (McNally, D. J., Hui, J. P., Aubry, A. J., Mui, K. K., Guerry, P., Brisson, J. R., Logan, S. M., and Soo, E. C. (2006) J. Biol. Chem. 281, 18489-18498). In this study, we use a similar approach to further define the glycome and metabolomic complement of nucleotide-activated sugars in Campylobacter coli VC167. Herein we demonstrate that, in addition to CMP-pseudaminic acid, C. coli VC167 also produces two structurally distinct nucleotide-activated nonulosonate sugars that were observed as negative ions at m/z 637 and m/z 651 (CMP-315 and CMP-329). Hydrophilic interaction liquid chromatography-mass spectrometry yielded suitable amounts of the pure sugar nucleotides for NMR spectroscopy using a cold probe. Structural analysis in conjunction with molecular modeling identified the sugar moieties as acetamidino and N-methylacetimidoyl derivatives of legionaminic acid (Leg5Am7Ac and Leg5AmNMe7Ac). Targeted metabolomic analyses of isogenic mutants established a role for the ptmA-F genes and defined two new ptm genes in this locus as legionaminic acid biosynthetic enzymes. This is the first report of legionaminic acid in Campylobacter sp. and the first report of legionaminic acid derivatives as modifications on a protein.
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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".