Precision food safety: Advances in omics-based surveillance for proactive detection and management of foodborne pathogens

The field of food safety is undergoing a paradigm shift from reactive detection to precision-based prediction and prevention, driven by advances in omics technologies and high-resolution surveillance methods. Among the most novel developments are microbiome-based monitoring strategies, which have the potential to serve as early indicators of increased contamination risk or pathogen persistence by identifying shifts in microbial community composition in food and food processing environments. Additionally, wastewater-based surveillance is emerging as a powerful, population-level early warning system with the potential to enhance traditional case-based surveillance by detecting elevated levels of foodborne pathogens in the community before clinical cases are reported. These innovations, alongside advances in whole-genome sequencing, metagenomics, and quasimetagenomics, form the foundation of precision food safety by enabling granular insights into pathogens across the supply chain. While artificial intelligence is not yet widely implemented in food safety, it is increasingly being explored as a tool to integrate and interpret complex omics and other data. In the future, AI has the potential to optimize resource allocation, improve the accuracy of risk assessments, and support earlier, more targeted interventions. This review summarizes recent innovations in sequencing-based detection and characterization of microbial hazards and discusses how omics data can be leveraged to enhance food safety surveillance and decision-making.