Influence of enzymatic hydrolysis conditions on antimicrobial activities and peptide profiles of milk protein-derived hydrolysates from white wastewater
Bibliographic record
Abstract
The focus of our investigation lies in the hydrolysis of milk proteins found in the substantial wastewater generated by the dairy industry, particularly in the white and cleaning wastewater resulting from rinsing and cleaning-in-place processes in order to enhance the value of dairy constituents by producing a diverse population of peptides, including potential antimicrobial peptides generated by 4 different enzymes: pepsin, trypsin, pronase E, and thermolysin. The protein/peptide content was influenced by the degree of hydrolysis values ranging from 2 % to 13 %, and UPLC-MS/MS characterization reveals distinct peptide sequences in enzymatic hydrolysates. The impact of hydrolysis time was also examined, revealing significant differences between 30 minutes and 240 minutes, with 555 peptides identified at 30 minutes, increasing to 693 at 240 minutes. After 4 hours, grouping showed variations: 181 peptides (thermolysin), 153 (pepsin), 126 (trypsin), and 83 (pronase E). A comparative analysis of the characterized sequences with antimicrobial peptides databases identified 17 antimicrobial peptides after 240 minutes pronase E and thermolysin hydrolysis, though they were insufficient to inhibit strains like Clostridium tyrobutyricum and Pseudomonas aeruginosa . Antimicrobial assays also revealed that peptides from Pronase T30, Pronase T240, and Thermolysine T240 exhibited antifungal activity against Mucor racemosus (MIC 2.5 mg/mL), but none against Penicillium commune . The effet of enzymatic hydrolysis demonstrated in this study highlights, for the first time, the potential for valorizing dairy white wastewater within the context of a circular economy framework. • Protein hydrolysis for wastewater valorization by generating antimicrobial peptides. • The 4 enzymes tested generated different peptide populations. • 17 antimicrobial peptides generated after 4 h pronase E and thermolysin hydrolysis. • 22 new Potential antifungal peptides identified against M. racemosus
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".