Recombinant <i>E. coli</i> Cellulases, β-Glucosidase, and Polygalacturonase Convert a Citrus Processing Waste into Biofuel Precursors
Bibliographic record
Abstract
Molecular and biochemical characterization of lignocellulohydrolases cel12B, cel8C, β-glucosidase, and peh28 from Pectobacterium carotovorum subsp. carotovorum ( Pcc ) expressed in Escherichia coli ( E. coli ) was reported in a previous work. The current preliminary study investigates the enzymes’ catalytic performance on Rio-Red grapefruit processing waste (GPW) conversion which can lead to the development of low-cost and effective strategies with strain engineering and/or modified catalysts for production of biofuel precursors. The GPW utilized for the study is known for its low ash and lignin contents compared with corn stover, wheat straw, and sugar cane bagasse, while yielding soluble sugars and polysaccharide constituents proportionally comparable to wastes from other citrus sources. Pretreatment of GPW at 120 °C with 1% w/w NaOH for 15 min resulted in significant total solid losses due primarily to conversion of glucans and lignin. Subsequent enzymatic bioconversion using the recombinant E. coli lignocellulolytic system resulted in production of 24, 11, and 14 g/kg solid biomass for the respective glucose, cellobiose, and galacturonic acid products from GPW over 24 h at 45 °C and pH 5.4. Other sugar products (e.g., xylose, arabinose, galactose, mannose, and rhamnose) were also detectable throughout the catalysis but at lower concentrations compared with the main products.
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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".