Characterization of the -2,8-polysialyltransferase from Neisseria meningitidis with synthetic acceptors, and the development of a self-priming polysialyltransferase fusion enzyme
Bibliographic record
Abstract
Glycoconjugates containing polysialic acid have many biological activities and represent target molecules for therapeutic interventions. Enzymatic synthesis of these glycoconjugates should give access to these important molecules to evaluate their potential. The polysialyltransferases from both Neisseria meningitidis and Escherichia coli were cloned and expressed as recombinant proteins in E. coli. We have used synthetic acceptors to probe the acceptor requirement of these enzymes and to examine the basic enzymology. The minimum number of sialic acid residues (Neu5Ac) on the acceptor for activity in vitro was shown to be 2 for both enzymes, but a large increase in activity was seen if the acceptor had three Neu5Ac residues. The polysialyltransferase from N. meningitidis generated longer reaction products than the enzyme from E. coli on FCHASE acceptors. Examination of the products showed them to be a heterogeneous mixture, but products with >50 Neu5Ac residues could be seen using capillary zone electrophoresis analyses. In addition we made fusion proteins of these polysialyltransferase enzymes with the bifunctional alpha-2,3/alpha-2,8-sialyltransferase from Campylobacter jejuni to create self priming polysialyltransferases. These bifunctional sialyltransferases utilized various synthetic disaccharide acceptors with a terminal galactose, and we demonstrate here that the PST enzyme from N. meningitidis and its fusion protein with the C. jejuni sialyltransferase can be used to create polysialic acid on O-linked glycopeptides.
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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".