Expression of a cold-adapted fish trypsin in
Bibliographic record
Abstract
Trypsin is a highly valuable protease that has many industrial and biomedical applications. The growing demand for non-animal sources of the enzyme and for trypsins with special properties has driven the interest to clone and express this protease in microorganisms. Reports about expression of recombinant trypsins show wide differences in the degree of success and are contained mainly in patent applications, which disregard the difficulties associated with the developments. Although the yeast Pichia pastoris appears to be the microbial host with the greatest potential for the production of trypsin, it has shown problems when expressing cold-adapted fish trypsins (CAFTs). CAFTs are considered of immense value for their comparative advantage over other trypsins in a number of food-processing and biotechnological applications. Thus, to investigate potential obstacles related to the production of CAFTs in P. pastoris, the cunner fish trypsin (CFT) was cloned in different Pichia expression vectors. The vectors were constructed targeting both internal and secreted expression and keeping the CFT native signal peptide. Western-blotting analysis confirmed the expression with evident differences for each construct, observing a major effect of the leader peptide sequence on the expression patterns. Immobilized nickel affinity chromatography yielded a partially purified recombinant CFT, which exhibited trypsin-specific activity after activation with bovine enterokinase.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".