Mechanisms of the sialidase and trans-sialidase activities of bacterial sialyltransferases from glycosyltransferase family 80
Bibliographic record
Abstract
Many important biological functions are mediated by complex glycan structures containing the nine-carbon sugar sialic acid (Sia) at terminal, non-reducing positions. Sia are introduced onto glycan structures by enzymes known as sialyltransferases (STs). Bacterial STs from the glycosyltransferase family GT80 are a group of well-studied enzymes used for the synthesis of sialylated glycan structures. While highly efficient at sialyl transfer, these enzymes also demonstrate sialidase and trans-sialidase activities for which there is some debate surrounding the corresponding enzymatic mechanisms. Here we propose a mechanism for STs from the glycosyltransferase family GT80 in which sialidase and trans-sialidase activities occur through reverse sialylation of CMP. The resulting CMP-Sia is then enzymatically hydrolyzed or used as a donor in subsequent ST reactions resulting in sialidase and trans-sialidase activities, respectively. We provide evidence for this mechanism by demonstrating that CMP is required for sialidase and trans-sialidase activities and that its removal with phosphatase ablates activity. We also confirm the formation of CMP-Sia using a coupled enzyme assay. A clear understanding of the sialidase and trans-sialidase mechanisms for this class of enzymes allows for more effective use of these enzymes in the synthesis of glycoconjugates.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".