A “terminal” case of glycan catabolism: Structural and enzymatic characterization of the sialidases of Clostridium perfringens
Bibliographic record
Abstract
Sialic acids are commonly found on the terminal ends of biologically important carbohydrates, including intestinal mucin O -linked glycans. Pathogens such as Clostridium perfringens , the causative agent of necrotic enteritis in poultry and humans, have the ability to degrade host mucins and colonize the mucus layer, which involves removal of the terminal sialic acid by carbohydrate-active enzymes (CAZymes). Here, we present the structural and biochemical characterization of the GH33 catalytic domains of the three sialidases of C. perfringens and probe their substrate specificity. The catalytically active domains, which we refer to as NanH GH33 , NanJ GH33 , and NanI GH33 , displayed differential activity on various naturally occurring forms of sialic acid. We report the X-ray crystal structures of these domains in complex with relevant sialic acid variants revealing the molecular basis of how each catalytic domain accommodates different sialic acids. NanH GH33 displays a distinct preference for α-2,3-linked sialic acid, but can process α-2,6-linked sialic acid. NanJ GH33 and NanI GH33 both exhibit the ability to process α-2,3- and α-2,6-linked sialic acid without any significant apparent preference. All three enzymes were sensitive to generic and commercially available sialidase inhibitors, which impeded sialidase activity in cultures as well as the growth of C. perfringens on sialylated glycans. The knowledge gained in these studies can be applied to in vivo models for C. perfringens growth and metabolism of mucin O -glycans, with a view toward future mitigation of bacterial colonization and infection of intestinal tissues.
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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 | 0.001 |
| 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".