Flagellar Glycosylation in Burkholderia pseudomallei and Burkholderia thailandensis
Bibliographic record
Abstract
Glycosylation of proteins is known to impart novel physical properties and biological roles to proteins from both eukaryotes and prokaryotes. In this study, gel-based glycoproteomics were used to identify glycoproteins of the potential biothreat agent Burkholderia pseudomallei and the closely related but nonpathogenic B. thailandensis. Top-down and bottom-up mass spectrometry (MS) analyses identified that the flagellin proteins of both species were posttranslationally modified by novel glycans. Analysis of proteins from two strains of each species demonstrated that B. pseudomallei flagellin proteins were modified with a glycan with a mass of 291 Da, while B. thailandensis flagellin protein was modified with related glycans with a mass of 300 or 342 Da. Structural characterization of the B. thailandensis carbohydrate moiety suggests that it is an acetylated hexuronic acid. In addition, we have identified through mutagenesis a gene from the lipopolysaccharide (LPS) O-antigen biosynthetic cluster which is involved in flagellar glycosylation, and inactivation of this gene eliminates flagellar glycosylation and motility in B. pseudomallei. This is the first report to conclusively demonstrate the presence of a carbohydrate covalently linked to a protein in B. pseudomallei and B. thailandensis, and it suggests new avenues to explore in order to examine the marked differences in virulence between these two species.
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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".