An uncharacterized gene from the Actinobacillus genus encodes a glucosyltransferase with successive transfer activity and unique substrate specificity
Bibliographic record
Abstract
Elucidating the functions of glycosyltransferases is a necessary step toward understanding their biological roles and producing drug leads, cosmetics, and foods that utilize glycans as functional molecules. We found a previously uncharacterized protein classified as a glycosyltransferase encoded in the Actinobacillus minor NM305 genome and named the gene product A. minor glucoside-glucosyltransferase (AmGGT). To clarify the biochemical properties of the AmGGT protein, we determined its substrate specificity and crystal structure. AmGGT exhibited processive glycosyltransferase activity when UDP-Glc was used as the donor substrate and, unexpectedly, showed different acceptor substrate specificity from that of the homologous Agt proteins of other Actinobacillus species. While the homologous proteins transfer glucose residues to the nonreducing end of oligosaccharide chains linked to peptides, AmGGT cannot use glycopeptides as acceptors and requires the nonreducing end of oligosaccharides. The crystal structure provided clues to identify a sequence motif consisting of two pairs of two amino acid residues that defines the acceptor specificity, oligosaccharide, or glycopeptide. Based on this discovery, the acceptor substrate of AmGGT was changed from an oligosaccharide to a glycopeptide by transplanting the sequence motif from the homologous proteins. Furthermore, the AmGGT protein could utilize eukaryotic high-mannose type N-glycans as acceptors, as a model for branched oligosaccharides. The sequential glycosyltransfer activity and controllable substrate specificity of AmGGT will make it a useful tool in glycosyltransferase engineering to synthesize functional glycans and 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 | 0.000 | 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".