Specificity Fingerprinting of Retaining β‐1,4‐Glycanases in the <i>Cellulomonas fimi</i> Secretome Using Two Fluorescent Mechanism‐Based Probes
Bibliographic record
Abstract
Functional proteomics methods are crucial for activity- and mechanism-based investigation of enzymes in biological systems at a post-translational stage. Glycosidases have central roles in cellular metabolism and its regulation, and their dysfunction can have detrimental effects. These enzymes also play key roles in biomass conversion. A functional profiling methodology was developed for direct, fluorescence-based, in-gel analysis of retaining beta-glycosidases. Two spectrally nonoverlapping fluorescent, mechanism-based probes containing different recognition elements for retaining cellulases and xylanases were prepared. The specificity-based covalent labelling of retaining glycanases by the two probes was demonstrated in model enzyme mixtures. Using the two probes and mass spectrometry, the secretomes of the biomass-converting bacterium Cellulomonas fimi, under induction by different polyglycan growth substrates, were analysed to obtain a specificity profile of the C. fimi retaining beta-glycanases. This is a facile strategy for the analysis of glycosidases produced by biomass-degrading organisms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".