Formulation of enzyme blends to maximize the hydrolysis of alkaline peroxide pretreated alfalfa hay and barley straw by rumen enzymes and commercial cellulases
Bibliographic record
Abstract
BACKGROUND: Efficient conversion of lignocellulosic biomass to fermentable sugars requires the synergistic action of multiple enzymes; consequently enzyme mixtures must be properly formulated for effective hydrolysis. The nature of an optimal enzyme blends depends on the type of pretreatment employed as well the characteristics of the substrate. In this study, statistical experimental design was used to develop mixtures of recombinant glycosyl hydrolases from thermophilic and anaerobic fungi that enhanced the digestion of alkaline peroxide treated alfalfa hay and barley straw by mixed rumen enzymes as well as commercial cellulases (Accelerase 1500, A1500; Accelerase XC, AXC). RESULTS: Combinations of feruloyl and acetyl xylan esterases (FAE1a; AXE16A_ASPNG), endoglucanase GH7 (EGL7A_THITE) and polygalacturonase (PGA28A_ASPNG) with rumen enzymes improved straw digestion. Inclusion of pectinase (PGA28A_ASPNG), endoxylanase (XYN11A_THITE), feruloyl esterase (FAE1a) and β-glucosidase (E-BGLUC) with A1500 or endoglucanase GH7 (EGL7A_THITE) and β-xylosidase (E-BXSRB) with AXC increased glucose release from alfalfa hay. Glucose yield from straw was improved when FAE1a and endoglucanase GH7 (EGL7A_THITE) were added to A1500, while FAE1a and AXE16A_ASPNG enhanced the activity of AXC on straw. Xylose release from alfalfa hay was augmented by supplementing A1500 with E-BGLUC, or AXC with EGL7A_THITE and XYN11A_THITE. Adding arabinofuranosidase (ABF54B_ASPNG) and esterases (AXE16A_ASPNG; AXE16B_ASPNG) to A1500, or FAE1a and AXE16A_ASPNG to AXC enhanced xylose release from barley straw, a response confirmed in a scaled up assay. CONCLUSION: The efficacy of commercial enzyme mixtures as well as mixed enzymes from the rumen was improved through formulation with synergetic recombinant enzymes. This approach reliably identified supplemental enzymes that enhanced sugar release from alkaline pretreated alfalfa hay and barley straw.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".