High-Throughput Identification of Allergens in a Food System via Hybridization Probe Cluster-Targeted Next-Generation Sequencing.

Abstract

Food allergies (FAs) are a crucial public health problem and a severe food safety issue, resulting in an urgent need for an accurate method to detect all of the hidden allergens that exist in food systems. Current methods for detecting allergens typically utilize ELISA, PCR, or LC-MS, which are suitable for the confirmatory analysis of allergens from ingredients rather than unintended contaminants. In this study, we demonstrate a hybridization probe cluster-targeted next-generation sequencing (HPC-NGS) platform for high-throughput screening of potential allergens in food systems. The HPC-NGS successfully captured target DNA fragments and identified 19 allergenic ingredients in a complex food system. Additionally, the HPC-NGS provided expected allergenic species matching rates of 94.24-100% in single food materials and 99.87-99.98% in processed food products. Thus, HPC-NGS enables the accurate characterization of allergenic ingredients and unintended allergenic contaminants in foods. Our results provide new perspectives on the use of HPC-NGS in the accuracy of high-throughput detection technologies for allergens imposed by the complex matrix effect.