Discovery and characterization of family 39 glycoside hydrolases from rumen anaerobic fungi with polyspecific activity on rare arabinosyl substrates
Bibliographic record
Abstract
Enzyme activities that improve digestion of recalcitrant plant cell wall polysaccharides may offer solutions for sustainable industries. To this end, anaerobic fungi in the rumen have been identified as a promising source of novel carbohydrate active enzymes (CAZymes) that modify plant cell wall polysaccharides and other complex glycans. Many CAZymes share insufficient sequence identity to characterized proteins from other microbial ecosystems to infer their function; thus presenting challenges to their identification. In this study, four rumen fungal genes ( nf2152 , nf2215 , nf2523 , and pr2455 ) were identified that encode family 39 glycoside hydrolases (GH39s), and have conserved structural features with GH51s. Two recombinant proteins, NF2152 and NF2523, were characterized using a variety of biochemical and structural techniques, and were determined to have distinct catalytic activities. NF2152 releases a single product, β1,2-arabinobiose (Ara 2 ) from sugar beet arabinan (SBA), and β1,2-Ara 2 and α-1,2-galactoarabinose (Gal-Ara) from rye arabinoxylan (RAX). NF2523 exclusively releases α-1,2-Gal-Ara from RAX, which represents the first description of a galacto-(α-1,2)-arabinosidase. Both β-1,2-Ara 2 and α-1,2-Gal-Ara are disaccharides not previously described within SBA and RAX. In this regard, the enzymes studied here may represent valuable new biocatalytic tools for investigating the structures of rare arabinosyl-containing glycans, and potentially for facilitating their modification in industrial applications.
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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".