Enzymatic production of 4-O-methyl d-glucaric acid from hardwood xylan
Bibliographic record
Abstract
Abstract Background Dicarboxylic acids offer several applications in detergent builder and biopolymer fields. One of these acids, 4-O-methyl d-glucaric acid, could potentially be produced from glucuronoxylans, which are a comparatively underused fraction of wood and agricultural biorefineries. Results Accordingly, an enzymatic pathway was developed that combines AxyAgu115A, a GH115 α-glucuronidase from Amphibacillus xylanus, and GOOX, an AA7 gluco-oligosaccharide oxidase from Sarocladium strictum, to produce this bio-based chemical from glucuronoxylan. AxyAgu115A was able to release almost all 4-O-methyl d-glucuronic acid from glucuronoxylan while a GOOX variant, GOOX-Y300A, could convert 4-O-methyl d-glucuronic acid to the corresponding glucaric acid at a yield of 62%. Both enzymes worked effectively at alkaline conditions that increase xylan solubility. Given the sensitivity of AxyAgu115A to hydrogen peroxide and optimal performance of GOOX-Y300A at substrate concentrations above 20 mM, the two-step enzyme pathway was demonstrated as a sequential, one-pot reaction. Additionally, the resulting xylan was easily recovered from the one-pot reaction, and it was enzymatically hydrolysable. Conclusions The pathway in this study requires only two enzymes while avoiding a supplementation of costly cofactors. This cell-free approach provides a new strategy to make use of the underutilized hemicellulose stream from wood and agricultural biorefineries.
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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 | 0.000 |
| 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 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".