| Title | Circular Economy in the Food Chain: Retrieval and Characterization of Antimicrobial Peptides from Fish Waste Hydrolysates |
|---|---|
| ID_Doc | 27827 |
| Authors | Salerno, TMG; Coppolino, C; Arena, P; Aichouni, A; Cerrato, A; Capriotti, AL; Rigano, F; Donnarumma, D; Donato, P; Mondello, A; Mondello, L |
| Title | Circular Economy in the Food Chain: Retrieval and Characterization of Antimicrobial Peptides from Fish Waste Hydrolysates |
| Year | 2024 |
| Published | Food Analytical Methods, 17.0, 2 |
| Abstract | The last decade has witnessed a steady transition from the linear economic model to a restorative system that drives substantial and lasting improvements of the global resource productivity. In this scenario, the blue economy encompasses all industries and sectors related to oceans, seas and coasts. The blue economy model promotes a series of actions towards sustainability, which include minimization of food waste production through the re-utilization of the marine by-products. Within the food chain, the large amount of waste generated by the tuna fishery industry represents a rich pool of bioactive molecules, including polyunsaturated fatty acids, vitamins, amino acids (AAs) and peptides. Specifically, small- and medium-size peptides are emerging as a more convenient alternative to conventional antibiotic agents, against a variety of bacteria, fungi and viruses. This study focused on the retrieval of the protein fractions contained in the discards from the yellowfin tuna (Thunnus albacares) cannery industry. Protein hydrolysates obtained by enzymatic digestion were characterized by a peptidomic strategy based on reversed-phase ultra-high-pressure liquid chromatography followed by quadrupole-time-of-flight tandem mass spectrometry detection (data dependent analysis). A total of 196 AAs sequences were identified by matching MASCOT database, and their activity was predicted by support vector machine-based computational tools. As a result, significant antimicrobial scores were obtained for 22% of the identified peptides. Specifically, antibacterial, antifungal and antiviral properties were predicted based on compositional features (pseudo AA compositions and normalized AA compositions) and physicochemical properties (isoelectric point, hydrophobicity and net-charge). |
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