Production of a recombinant vaccine candidate against Burkholderia pseudomallei exploiting the bacterial N-glycosylation machinery
Bibliographic record
Abstract
Vaccines developing immune responses toward surface carbohydrates conjugated to proteins are effective in preventing infection and death by bacterial pathogens. Traditional production of these vaccines utilizes complex synthetic chemistry to acquire and conjugate the glycan to a protein. However, glycoproteins produced by bacterial protein glycosylation systems are significantly easier to produce, and could possible be used as vaccine candidates. In this work, we functionally expressed the Burkholderia pseudomallei O polysaccharide (OPS II), the Campylobacter jejuni oligosaccharyltransferase (OTase), and a suitable glycoprotein (AcrA) in a designer E. coli strain with a higher efficiency for production of glycoconjugates. We were able to produce and purify the OPS II-AcrA glycoconjugate, and MS analysis confirmed correct glycan was produced and attached. We observed the attachment of the O-acetylated deoxyhexose directly to the acceptor protein, which expands the range of substrates utilized by the OTase PglB. Injection of the glycoprotein into mice generated an IgG immune response against B. pseudomallei, and this response was partially protective against an intranasal challenge. Our experiments show that bacterial engineered glycoconjugates can be utilized as vaccine candidates against B. pseudomallei. Additionally, our new E. coli strain SDB1 is more efficient in glycoprotein production, and could have additional applications in the future.
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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".