A general protein O-glycosylation machinery conserved in Burkholderia species improves bacterial fitness and elicits glycan immunogenicity in humans
Bibliographic record
Abstract
The Burkholderia genus encompasses many Gram-negative bacteria living in the rhizosphere. Some Burkholderia species can cause life-threatening human infections, highlighting the need for clinical interventions targeting specific lipopolysaccharide proteins. Burkholderia cenocepacia O -linked protein glycosylation has been reported, but the chemical structure of the O -glycan and the machinery required for its biosynthesis are unknown and could reveal potential therapeutic targets. Here, using bioinformatics approaches, gene-knockout mutants, purified recombinant proteins, LC-MS–based analyses of O -glycans, and NMR-based structural analyses, we identified a B. cenocepacia O -glycosylation ( ogc ) gene cluster necessary for synthesis, assembly, and membrane translocation of a lipid-linked O -glycan, as well as its structure, which consists of a β-Gal-(1,3)–α-GalNAc-(1,3)–β-GalNAc trisaccharide. We demonstrate that the ogc cluster is conserved in the Burkholderia genus, and we confirm the production of glycoproteins with similar glycans in the Burkholderia species: B. thailandensis , B. gladioli , and B. pseudomallei . Furthermore, we show that absence of protein O- glycosylation severely affects bacterial fitness and accelerates bacterial clearance in a Galleria mellonella larva infection model. Finally, our experiments revealed that patients infected with B. cenocepacia , Burkholderia multivorans , B. pseudomallei , or Burkholderia mallei develop O- glycan–specific antibodies. Together, these results highlight the importance of general protein O- glycosylation in the biology of the Burkholderia genus and its potential as a target for inhibition or immunotherapy approaches to control Burkholderia infections.
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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".