Exploration of Compost Soil for the Production of Thermo-Stable Bacillus Protease to Synthesize Bioactive Compounds through Soy Protein Hydrolysis
Bibliographic record
Abstract
Application of bioactive peptides (BAPs) is promising due to their potential antimicrobial, antioxidant, agonistic, and ACE inhibition properties. To achieve a stable and active peptide at relatively high pH and temperatures by microbial fermentation, a wide variety of microorganisms need to be explored from diverse habitats, and compost is the excellent source. In an attempt to isolate potent protease-producing bacteria, gelatin-supplemented DM agar medium was used. Out of 140 pure cultures, initial protease production selects isolate D3L/1 (26 U/mL), and 16S rDNA sequencing confirmed it as Bacillus subtilis. Protease production was increased to 55.55 U/mL, with pH 7.5, 1% glucose, 1% casein, 1% ammonium sulfate, for 96 h of fermentation, at 37 °C under 140 rpm of shaking. Ion-exchange, and size-exclusion chromatography, 30 KDa protease was purified up to 4.1-fold (specific activity 3448.62 U/mL; 67.66% yield). The enzyme was active under broad temperatures (60 °C optimum), organic solvents, and pH variations. A total of 5% H2O2 can only reduce 40% of enzyme activity. However, 1 mM, Fe2+, and Cu2+ increased enzyme activity by five times. Soy hydrolysis (SPI) byD3L/1 protease produces bioactive compound (<3 KDa), which confirmed the peptide bond in the far UV region (205 nm, 215 nm, 225 nm, and 280 nm). The compound was ineffective towards Serratia marcescens but active against Escherechia coli (47%), Staphylococcus aureus (28%), and Pseudomonas aeruginosa (12%).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".