The Comparative Abilities of a Small Laccase and a Dye-Decoloring Peroxidase From the Same Bacterium to Transform Natural and Technical Lignins
Bibliographic record
Abstract
The relative ability of the small laccase (sLac) and dye-decoloring peroxidase (DyP2) from Amycolatopsis sp. 75iv2 to transform a variety of lignins was investigated using time-of-flight secondary ion mass spectrometry (ToF-SIMS). The enzymes modified organosolv hardwood lignin to different extents even in the absence of an added mediator. More particularly, sLac decreased the lignin modification metric S (S-lignin)/Ar (total aromatics) by 58% over 16h, while DyP2 lowered this ratio by 31% in the absence of exogenous H 2 O 2 . When used on their own, both sLac and DyP2 also modified native lignin present in aspen wood powder, albeit to lesser extents than in the organosolv lignin. The addition of ABTS for sLac and Mn 2+ as well as H 2 O 2 for DyP2 led to increased lignin modification in aspen wood powder as reflected by a decrease in the G/Ar metric by up to a further 13%. This highlights the importance of exogenous mediators for transforming lignin within its native matrix. Furthermore, the addition of ABTS reduced the selectivity of sLac for S-lignin over G-lignin, indicating that the mediator also altered the product profiles. Finally, when sLac was included in reactions containing DyP2, in part to generate H 2 O 2 in situ , the relative abundance of lignin products differed from individual enzymatic treatments. Overall, these results identify possible routes to tuning lignin modification or delignification through choice of enzyme and mediator. Moreover, the current study expands the application of ToF-SIMS to evaluating enzyme action on technical lignins, which can accelerate the discovery and engineering of industrially relevant enzymes for lignin valorization.
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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 | 0.000 |
| 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".