Four cellulose-active lytic polysaccharide monooxygenases from Cellulomonas species
Bibliographic record
Abstract
BACKGROUND: The discovery of lytic polysaccharide monooxygenases (LPMOs) has fundamentally changed our understanding of microbial lignocellulose degradation. Cellulomonas bacteria have a rich history of study due to their ability to degrade recalcitrant cellulose, yet little is known about the predicted LPMOs that they encode from Auxiliary Activity Family 10 (AA10). RESULTS: Here, we present the comprehensive biochemical characterization of three AA10 LPMOs from Cellulomonas flavigena (CflaLPMO10A, CflaLPMO10B, and CflaLPMO10C) and one LPMO from Cellulomonas fimi (CfiLPMO10). We demonstrate that these four enzymes oxidize insoluble cellulose with C1 regioselectivity and show a preference for substrates with high surface area. In addition, CflaLPMO10B, CflaLPMO10C, and CfiLPMO10 exhibit limited capacity to perform mixed C1/C4 regioselective oxidative cleavage. Thermostability analysis indicates that these LPMOs can refold spontaneously following denaturation dependent on the presence of copper coordination. Scanning and transmission electron microscopy revealed substrate-specific surface and structural morphological changes following LPMO action on Avicel and phosphoric acid-swollen cellulose (PASC). Further, we demonstrate that the LPMOs encoded by Cellulomonas flavigena exhibit synergy in cellulose degradation, which is due in part to decreased autoinactivation. CONCLUSIONS: Together, these results advance understanding of the cellulose utilization machinery of historically important Cellulomonas species beyond hydrolytic enzymes to include lytic cleavage. This work also contributes to the broader mapping of enzyme activity in Auxiliary Activity Family 10 and provides new biocatalysts for potential applications in biomass modification.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".