Characterization of Five β-Glycoside Hydrolases from Cellulomonas fimi ATCC 484
Bibliographic record
Abstract
The Gram-positive bacterium Cellulomonas fimi produces a large array of carbohydrate-active enzymes. Analysis of the collection of carbohydrate-active enzymes from the recent genome sequence of C. fimi ATCC 484 shows a large number of uncharacterized genes for glycoside hydrolase (GH) enzymes potentially involved in biomass utilization. To investigate the enzymatic activity of potential β-glucosidases in C. fimi, genes encoding several GH3 enzymes and one GH1 enzyme were cloned and recombinant proteins were expressed in Escherichia coli. Biochemical analysis of these proteins revealed that the enzymes exhibited different substrate specificities for para-nitrophenol-linked substrates (pNP), disaccharides, and oligosaccharides. Celf_2726 encoded a bifunctional enzyme with β-d-xylopyranosidase and α-l-arabinofuranosidase activities, based on pNP-linked substrates (CfXyl3A). Celf_0140 encoded a β-d-glucosidase with activity on β-1,3- and β-1,6-linked glucosyl disaccharides as well as pNP-β-Glc (CfBgl3A). Celf_0468 encoded a β-d-glucosidase with hydrolysis of pNP-β-Glc and hydrolysis/transglycosylation activities only on β-1,6-linked glucosyl disaccharide (CfBgl3B). Celf_3372 encoded a GH3 family member with broad aryl-β-d-glycosidase substrate specificity. Celf_2783 encoded the GH1 family member (CfBgl1), which was found to hydrolyze pNP-β-Glc/Fuc/Gal, as well as cellotetraose and cellopentaose. CfBgl1 also had good activity on β-1,2- and β-1,3-linked disaccharides but had only very weak activity on β-1,4/6-linked glucose.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".