Combining pieces: a thorough analysis of light activation boosting power and co-substrate preferences for the catalytic efficiency of lytic polysaccharide monooxygenase MtLPMO9A
Bibliographic record
Abstract
Cost-efficient plant biomass conversion using biochemical and/or chemical routes is essential for transitioning to sustainable chemical technologies and renewable biofuels. Lytic polysaccharide monooxygenases (LPMOs) are copper-dependent enzymes that make part of modern hydrolytic cocktails destined for plant biomass degradation. Here, we characterized MtLPMO9A from Thermothelomyces thermophilus M77 (formerly Myceliophthora thermophila) and demonstrated that it could be efficiently driven by chlorophyllin excited by light in the presence of a reductant agent. However, in the absence of chemical reductant, chlorophyllin and light alone do not lead to a significant release of the reaction products by the LPMO, indicating a low capacity of MtLPMO9A reduction (either via direct electron transfer or via superoxide ion, O2•-). We showed that photocatalysis could significantly increase the LPMO activity against highly crystalline and recalcitrant cellulosic substrates, which are poorly degraded in the absence of chlorophyllin and light. We also evaluated the use of co-substrates by MtLPMO9A, revealing that the enzyme can use both hydrogen peroxide (H2O2) and molecular oxygen (O2) as co-substrates for cellulose catalytic oxidation.
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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 | 0.002 | 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 | 0.000 |
| 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".