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◆ LWT2026-03-14· Ovotransferrin

Identification of two novel peptides with antibiofilm and antimicrobial effects from ovotransferrin hydrolysates using peptidomic and regression-based machine learning approach

Dan Wang, Mengxue Li, Jiaqi Chen, Jialiang Wang, Xiaoli Liu

原始摘要(英文原文)· Original abstract
Ovotransferrin hydrolysates (OVHs) produced by papain-derived, peptic and tryptic hydrolysis were evaluated for their antibiofilm activities. Exposure to 1250 μg/mL OVHs from peptic hydrolysis caused a 43.71%-50.84% decrease in swimming motility, a 41.95%-54.96% decline in auto-aggregation, a 23.67%-54.46% inhibition of extracellular polysaccharides production, and a 1.33 log CFU/cm 2 -1.89 log CFU/cm 2 reduction in biofilm cell counts. Peptidomic analysis using nanoLC-UHPLC-MS/MS technique was conducted to characterize peptides in OVHs. Meanwhile, partial least-squares discriminant analysis (PLS-DA) discriminated peptide populations based on the enzymes and identified the most discriminated peptides devoting for antibiofilm efficacy. Two novel antibiofilm peptides PEPVL (PVLKDLLFKDSAIMLKRVPSLMDSQL) and PEASY (ASYGNAVCIFEPLGINSHKRNSQLKCQWLKTGQF) were discovered and verified in vitro. PEPVL and PEASY at a concentration of 250 μg/mL inhibited biofilm formation by 84.59%-91.36% and 28.62%-71.97%, respectively. This study investigated the antibiofilm activities of OVH using enzymolysis, and identified two novel peptides with antibiofilm effects. This research will aid in developing innovative techniques to tackle Vibrio parahaemolyticus biofilms in the food industry. • OVHs exhibited biofilm inhibition activity against Vibrio parahaemolyticus. • nanoLC-UHPLC-MS/MS was employed to characterize peptide sequences in OVH. • PLS-DA discriminated peptide populations devoting for antibiofilm efficacy. • Two peptides demonstrating antibiofilm and antimicrobial effects were reported.
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Identification of two novel peptides with antibiofilm and antimicrobial effects from ovotransferrin hydrolysates using peptidomic and regression-based machine learning approach — 科研速览 Science Skim