Human Gut Metagenomes Encode Diverse GH156 Sialidases
Bibliographic record
Abstract
Sialic acids occupy terminal positions of human glycans where they act as receptors for microbes, toxins, and immune signaling molecules. Microbial enzymes that remove sialic acids, sialidases, are abundant in the human microbiome where they may contribute to shaping the microbiota community structure or contribute to pathology. Furthermore, sialidases have proven to hold therapeutic potential for cancer therapy. Here, we examined the sequence space of a sialidase family of enzymes, GH156, previously unknown in the human gut environment. Our analyses suggest that human populations with disparate dietary practices harbor distinct varieties and abundances of GH156-encoding genes. Furthermore, we demonstrate the sialidase activity of 5 gut-derived GH156s. These results expand the diversity of sialidases that may contribute to host glycan degradation, and these sequences may have biotechnological or clinical utility.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".