Functional Characterization of the Flagellar Glycosylation Locus in Campylobacter jejuni 81–176 Using a Focused Metabolomics Approach
Bibliographic record
Abstract
Bacterial genome sequencing has provided a wealth of genetic data. However, the definitive functional characterization of hypothetical open reading frames and novel biosynthetic genes remains challenging. This is particularly true for genes involved in protein glycosylation because the isolation of their glycan moieties is often problematic. We have developed a focused metabolomics approach to define the function of flagellin glycosylation genes in Campylobacter jejuni 81-176. A capillary electrophoresis-electrospray mass spectrometry and precursor ion scanning method was used to examine cell lysates of C. jejuni 81-176 for sugar nucleotides. Novel nucleotide-activated intermediates of the pseudaminic acid (Pse5NAc7NAc) pathway and its acetamidino derivative (PseAm) were found to accumulate within select isogenic mutants, and use of a hydrophilic interaction liquid chromatography-mass spectrometry method permitted large scale purifications of the intermediates. NMR with cryo probe (cold probe) technology was utilized to complete the structural characterization of microgram quantities of CMP-5-acetamido-7-acetamidino-3,5,7,9-tetradeoxy-L-glycero-alpha-L-manno-nonulosonic acid (CMP-Pse5NAc7Am), which is the first report of Pse modified at C7 with an acetamidino group in Campylobacter, and UDP-2,4-diacetamido-2,4,6-trideoxy-alpha-D-glucopyranose, which is a bacillosamine derivative found in the N-linked proteinglycan. Using this focused metabolomics approach, pseB, pseC, pseF, pseI, and for the first time pseA, pseG, and pseH were found to be directly involved in either the biosynthesis of CMP-Pse5NAc7NAc or CMP-Pse5NAc7Am. In contrast, it was shown that pseD, pseE, Cj1314c, Cj1315c, Cjb1301, Cj1334, Cj1341c, and Cj1342c have no role in the CMP-Pse5NAc7NAc or CMP-Pse5NAc7Am pathways. These results demonstrate the usefulness of this approach for targeting compounds within the bacterial metabolome to assign function to genes, identify metabolic intermediates, and elucidate novel biosynthetic pathways.
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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) | 0.001 | 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".