Characterization of in vitro stability for two processive endoglucanases as exogenous fibre biocatalysts in pig nutrition
Bibliographic record
Abstract
Abstract Development of highly efficacious exogenous fibre degradation enzymes can enhance efficiency of dietary fibre utilization and sustainability of global pork production. The objectives of this study were to investigate in vitro stability for two processive endoglucanases, referred to as GH5-tCel5A1 and GH5-p4818Cel5_2A that were overexpressed in CLEARCOLIBL21(DE3). Three-dimensional models predicted presence of Cys residues on the catalytic site surfaces of GH5-tCel5A1 and GH5-p4818Cel5_2A; and time course experimental results shown that both cellulases were susceptible to auto-oxidation by airborne O2and were unstable. Furthermore, we examined these endoglucanases’ stability under the mimicked in vitro porcine gastric and the small intestinal pH and proteases’ conditions. Eadie-Hofstee inhibition kinetic analyses showed that GH5-tCel5A1 and GH5-p4818Cel5_2A respectively lost 18 and 68% of their initial activities after 2-h incubations under the gastric conditions and then lost more than 90% of their initial activities after 2–3 h of incubations under the small intestinal conditions. Therefore, further enzyme protein engineering to improve resistance and alternatively post-fermentation enzyme processing such as coating to bypass the gastric-small intestinal environment will be required to enable these two processive endoglucanases as efficacious exogenous fibre enzymes in pig nutrition application.
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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) | 0.000 | 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".