Nisin Purification from a Cell-Free Supernatant by Electrodialysis in a Circular Economy Framework
Bibliographic record
Abstract
strains, is a promising natural preservative for the food industry and an alternative to antibiotics for the pharmaceutical industry against Gram-positive bacteria. Nisin purification is commonly performed using salting out and chromatographic techniques, which are characterized by their low yields, the use of solvents and the production of large volumes of effluents. In the present work, the purification of nisin from a cell-free supernatant (CFS), after the production of nisin by fermentation on a whey permeate medium, was studied using ammonium sulfate precipitation and electrodialysis (ED) as a promising eco-friendly process for nisin purification. Results showed an increase in nisin precipitation using a 40% ammonium sulfate saturation (ASS) level with a purification fold of 73.8 compared with 34.5 and no purification fold for a 60% and 20% ASS level, respectively. The results regarding nisin purification using ED showed an increase in nisin purification and concentration fold, respectively, of 21.8 and 156 when comparing the final product to the initial CFS. Nisin-specific activity increased from 75.9 ± 4.4 to 1652.7 ± 236.8 AU/mg of protein. These results demonstrated the effectiveness of ED coupled with salting out for nisin purification compared with common techniques. Furthermore, the process was noteworthy for its relevance in a circular economy scheme, as it does not require any solvents and avoids generating polluting effluents. It can be employed for the purification of nisin and the recovery of salts from salting out, facilitating their reuse in a circular economy.
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 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 | 0.001 |
| 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".