Antibacterial mechanisms of phenyllactic acid against Shewanella putrefaciens by metabolomics and machine learning and its application in sea fish

Résumé fourni par la source

Shewanella is a common spoilage bacterium found in aquatic products, and inhibiting its growth is currently a critical strategy in seafood preservation. In this study, a comprehensive analytical method combining metabolomics and machine learning was used to systematically elucidate the antibacterial mechanisms of phenyllactic acid (PLA) against Shewanella putrefaciens SP22. The minimum inhibitory concentration of PLA was 2.0 mg/mL. PLA disrupts the cell wall integrity, changes cell membrane permeability and integrity, and inhibits key enzyme activities. Non-targeted metabolomic analysis revealed 1,211 significant differential metabolites between PLA treatment and control groups, mainly involving the citric acid cycle, amino acid synthesis, nucleotide metabolism, glycerophospholipid metabolism, and cofactor generation metabolic pathways. Four machine learning models were constructed based on metabolomics data, and key biomarkers (such as citric acid, α -ketoglutaric acid, and 5′-adenylate nucleotide) were screened. Meanwhile, the antibacterial and preservative effects of PLA were verified in large yellow croaker, salmon, and sea bass. This study lays a theoretical foundation for applying PLA as a natural preservative for aquatic product preservation.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.