Chymostatin can combine with pepstatin to eliminate extracellular protease activity in cultures of Aspergillus niger NRRL-3
Bibliographic record
Abstract
Aspergillus strains are being considered as potential hosts for recombinant heterologous protein production because of their excellent extracellular enzyme production characteristics. However, Aspergillus proteases are problematic in that they modify and degrade the heterologous proteins in the extracellular medium. In previous studies we observed that media adjustments and maintenance of a filamentous morphology greatly reduced protease activity and that a low concentration of the aspartic protease inhibitor pepstatin inhibited the latter protease activity to the extent of approximately 90%. In this paper we report that when the serine protease inhibitor chymostatin is used in combination with pepstatin 99-100% of total protease activity in Aspergillus cultures is inhibited. In protease assays a concentration of 30 microM chymostatin combined with 0.075 microM pepstatin was required for maximum inhibition. Inhibitor concentrations of chymostatin and pepstatin of 120 and 0.3 microM, respectively, when added to Aspergillus cultures, has no significant effect on biomass production, glucose utilization or culture pH pattern. The potential of using these protease inhibitors in cultures of recombinant Aspergillus strains producing heterologous proteins will now be investigated to determine if the previously observed recombinant protein denaturing effects of Aspergillus proteases can be negated.
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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 | 0.000 |
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".