Mechanistic Systems Biology of High-Salinity Fermented Seafood: Multi-Omics Integration for Microbial Safety and Quality Prediction

Foodborne diseases present a serious public health challenge, causing roughly 600 million illnesses and 420,000 deaths annually. A significant portion of this impact is felt in Asia, where traditional fermented and dry-salted seafood, such as <i>katsuobushi</i>, <i>budu</i>, and <i>peda</i>, are dietary staples. These products rely on diverse microbial communities that determine their final safety, flavor, texture, and shelf life. Historically, research has centered on lactic acid bacteria (LAB), yet the functional contributions of non-LAB halotolerant species, including genera like <i>Tetragenococcus</i>, <i>Staphylococcus</i>, and <i>Bacillus</i>, are functionally important in these high-salinity niches. This review evaluates the transition from basic taxonomic surveys to mechanistic multi-omics approaches, integrating genomics, transcriptomics, proteomics, and metabolomics to decode microbial functionality under selective environmental pressures. We discuss how genomic mining using platforms such as BAGEL4 and antiSMASH can uncover biosynthetic gene clusters and antimicrobial peptides, while CARD supports antimicrobial resistance monitoring. Transcriptomic analysis reveals microbial responses to osmotic stress, low water activity, and pH fluctuations, whereas proteomic profiling links gene expression to active enzymes, stress proteins, and functional biomarkers. Metabolomics captures the chemical outcomes of fermentation, including amino acids, volatile organic compounds, spoilage markers, and biogenic amines. By merging these high-dimensional datasets with artificial intelligence, researchers can move toward predictive modeling that distinguishes biological causation from simple correlation. This shift offers a strategy to improve the safety, consistency, and resilience of traditional high-salinity fermented seafood systems.