Direct in Situ Observation of Synergism between Cellulolytic Enzymes during the Biodegradation of Crystalline Cellulose Fibers
Bibliographic record
Abstract
High-resolution atomic force microscopy (AFM) was used to image the real-time in situ degradation of crystalline by three types of T. reesei cellulolytic enzymes-TrCel6A, TrCel7A, and TrCel7B-and their mixtures. TrCel6A and TrCel7A are exo-acting cellobiohydrolases processing cellulose fibers from the nonreducing and reducing ends, respectively. TrCel7B is an endoglucanase that hydrolyzes amorphous cellulose within fibers. When acting alone on native cellulose fibers, each of the three enzymes is incapable of significant degradation. However, mixtures of two enzymes exhibited synergistic effects. The degradation effects of this synergism depended on the order in which the enzymes were added. Faster hydrolysis rates were observed when TrCel7A (exo) was added to fibers pretreated first with TrCel7B (endo) than when adding the enzymes in the opposite order. Endo-acting TrCel7B removed amorphous cellulose, softened and swelled the fibers, and exposed single microfibrils, facilitating the attack by the exo-acting enzymes. AFM images revealed that exo-acting enzymes processed the TrCel7B-pretreated fibers preferentially from one specific end (reducing or nonreducing). The most efficient (almost 100%) hydrolysis was observed with the mixture of the three enzymes. In this mixture, TrCel7B softened the fiber and TrCel6A and TrCel7A were directly observed to process it from the two opposing ends. This study provides high-resolution direct visualization of the nature of the synergistic relation between T. reesei exo- and endo-acting enzymes digesting native crystalline cellulose.
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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) | 0.001 | 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 | 0.001 |
| 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".