Identification and Biochemical Characterization of the Novel α2,3-Sialyltransferase WbwA from Pathogenic Escherichia coli Serotype O104
Bibliographic record
Abstract
UNLABELLED: The sialyl-T antigen sialylα2-3Galβ1-3GalNAc is a common O-glycan structure in human glycoproteins and is synthesized by sialyltransferase ST3Gal1. The enterohemorrhagic Escherichia coli serotype O104 has the rare ability to synthesize a sialyl-T antigen mimic. We showed here that the wbwA gene of the E. coli O104 antigen synthesis gene cluster encodes an α2,3-sialyltransferase WbwA that transfers sialic acid from CMP-sialic acid to Galβ1-3GalNAcα-diphosphate-lipid acceptor. Nuclear magnetic resonance (NMR) analysis of purified WbwA enzyme reaction product indicated that the sialyl-T antigen sialylα2-3Galβ1-3GalNAcα-diphosphate-lipid was synthesized. We showed that the conserved His-Pro (HP) motif and Glu/Asp residues of two EDG motifs in WbwA are important for the activity. The characterization studies showed that WbwA from E. coli O104 is a monofunctional α2,3-sialyltransferase and is distinct from human ST3Gal1 as well as all other known sialyltransferases due to its unique acceptor specificity. This work contributes to knowledge of the biosynthesis of bacterial virulence factors. IMPORTANCE: This is the first characterization of a sialyltransferase involved in the synthesis of an O antigen in E. coli. The enzyme contributes to the mimicry of human sialyl-T antigen and has unique substrate specificity but very little sequence identity to other sialyltransferases. Thus, the bacterial sialyltransferase is related to the human counterpart only by the similarity of biochemical activity.
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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".