Plug-in Assembly of a Surface-Displayed Cellulolytic Arsenal and Evaluation of Its Effects on the Saccharification of Lignocellulosic Material
Bibliographic record
Abstract
Due to their highly efficient bioconversion of lignocellulosic biomass, the design and development of artificial cellulosomes are of tremendous interest. In this study, we displayed a designed scaffoldin, comprising three tandem peptides split from SpyRing, SnoopRing, and DogRing, on the Escherichia coli BL21 (DE3) cell surface by fusing to curli fiber protein CsgA. Subsequently, an artificial cellulosome was constructed by recruiting carbohydrate-active enzymes (CAZymes) with diverse acting modes, including xylanase TfXYN11, glucanase IDSGLUC5, lytic polysaccharide monooxygenase BsLPMO10A, and ferulic acid esterase AmFAE1A, via isopeptide-mediated ligation. Importantly, plug-and-socket assembly of the cellulosome was achieved within 5 min over broad pH (2.2–9.0) and temperature (0–37 °C) ranges. The engineered BL21:Δ CsgA /ASC anchored to the designed cellulosome was catalytically proficient against plant-derived polysaccharides glucan and xylan in terms of both activity and reusability. In addition, BL21:Δ CsgA /ASC catalyzed the saccharification of wheat straw, providing novel strategies for consolidated bioprocessing and the development of feed additives.
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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) | 0.000 | 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) | 0.001 | 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".