Activity-based protein profiling reveals dynamic substrate-specific cellulase secretion by saprotrophic basidiomycetes
Bibliographic record
Abstract
BACKGROUND: Fungal saccharification of lignocellulosic biomass occurs concurrently with the secretion of a diverse collection of proteins, together functioning as a catalytic system to liberate soluble sugars from insoluble composite biomaterials. How different fungi respond to different substrates is of fundamental interest to the developing biomass saccharification industry. Among the cornerstones of fungal enzyme systems are the highly expressed cellulases (endo-β-glucanases and cellobiohydrolases). Recently, a cyclophellitol-derived activity-based probe (ABP-Cel) was shown to be a highly sensitive tool for the detection and identification of cellulases. RESULTS: Here we show that ABP-Cel enables endo-β-glucanase profiling in diverse fungal secretomes. In combination with established ABPs for β-xylanases and β-D-glucosidases, we collected multiplexed in-gel fluorescence activity-based protein profiles of 240 secretomes collected over ten days from biological replicates of ten different basidiomycete fungi grown on maltose, wheat straw, or aspen pulp. Our results reveal the remarkable dynamics and unique enzyme fingerprints associated with each species substrate combination. Chemical proteomic analysis identifies significant arsenals of cellulases secreted by each fungal species during growth on lignocellulosic biomass. Recombinant production and characterization of a collection of probe-reactive enzymes from GH5, GH10, and GH12 confirm that ABP-Cel shows broad selectivity towards enzymes with endo-β-glucanase activity. CONCLUSION: Using small-volume samples with minimal sample preparation, the results presented here demonstrate the ready accessibility of sensitive direct evidence for fungal enzyme secretion during early stages of growth on complex lignocellulosic substrates.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".