Constitutive Optimized Production of Streptokinase in<i>Saccharomyces cerevisiae</i>Utilizing Glyceraldehyde 3-Phosphate Dehydrogenase Promoter of<i>Pichia pastoris</i>
Bibliographic record
Abstract
A novel expression vector constructed from genes of Pichia pastoris was applied for heterologous gene expression in Saccharomyces cerevisiae. Recombinant streptokinase (SK) was synthesized by cloning the region encoding mature SK under the control of glyceraldehyde 3-phosphate dehydrogenase (GAP) promoter of Pichia pastoris in Saccharomyces cerevisiae. SK was intracellularly expressed constitutively, as evidenced by lyticase-nitroanilide and caseinolytic assays. The functional activity was confirmed by plasminogen activation assay and in vitro clot lysis assay. Stability and absence of toxicity to the host with the recombinant expression vector as evidenced by southern analysis and growth profile indicate the application of this expression system for large-scale production of SK. Two-stage statistical approach, Plackett-Burman (PB) design and response surface methodology (RSM) was used for SK production medium optimization. In the first stage, carbon and organic nitrogen sources were qualitatively screened by PB design and in the second stage there was quantitative optimization of four process variables, yeast extract, dextrose, pH, and temperature, by RSM. PB design resulted in dextrose and peptone as best carbon and nitrogen sources for SK production. RSM method, proved as an efficient technique for optimizing process conditions which resulted in 110% increase in SK production, 2352 IU/mL, than for unoptimized conditions.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".