The effect of nitrogen source on yield and glycosylation of a human cystatin C mutant expressed in Pichia pastoris
Bibliographic record
Abstract
Human cystatin C is a cysteine proteinase inhibitor with potential applications as an anti-viral agent, cancer tumor growth inhibitor, and in prevention of proteolysis during food processing. A glycosylated cystatin C mutant with increased temperature stability was developed for the latter application [Nakamura et al. (1998) FEBS Lett 427:252-254]. A recombinant variant of cystatin C [Nakamura et al. (2000) International patent no. PLTCA99/00717] with two potential sites for N-linked glycosylation was expressed in Pichia pastoris Mut(s). Little of the cystatin C produced was in the glycosylated form under fermentation conditions of pH 6, temperature 28 degrees C, methanol only feed, and ammonium hydroxide as a nitrogen source. Thus, the effect of addition of complex nitrogen sources, peptone and amino acid supplements, on the yield and glycosylation of this mutant cystatin C were investigated. A full factorial design experiment using 2-l fermenters was performed with three factors: ammonium hydroxide, peptone, and an amino acid mix, at two levels, absent or present. Peptone addition was found to have a positive, and the most significant, effect on cell specific cystatin C yield. A maximum mutant cystatin C yield of 0.82 mumol (g-dry cell weight)(-1) min(-1) was obtained when all three nitrogen sources were used together. However, under these conditions only 16% of protein was in the glycosylated form since ammonia was found to have a significant negative effect on glycosylation extent. The maximum extent of glycosylation was 30% when peptone and amino acid mix were the only nitrogen sources added.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".