Undeclared food allergens account for 30–40% of food recalls in the United States. Reliable methods for allergen detection and quantitation are required for implementing effective allergen control plans and complying with ingredient labeling regulations. These methods must be effective despite food-processing-induced changes to the biophysical and immunological properties of allergen proteins within a food matrix sample. In this work, a liquid chromatography (LC)-mass spectrometry (MS) multi-allergen method was developed for allergen detection in complex food samples. Combining enhanced protein solubilization with differential MS methodologies enables a peptide-specific view of changes in allergen proteins induced by food processing. Using an MS1-based global mapping of the A. hypogaea proteome, a characterization of structural isoforms, cultivar variations, and protein modifications enable the identification of peanut in a variety of foods. The application of this approach is exemplified in the detection of undeclared food allergens in cumin, one of the largest food safety recalls since the Food Allergen Labeling and Consumer Protection Act (FALCPA) of 2004. To meet the need for multi-analyte detection of homologous protein allergen families, a multiplexed mass spectrometry screening method was designed to identify and differentiate cross-reactive legume and tree nut allergens. Understanding the advantages and limitations of available methods for food allergen detection, with respect to sample extraction, thermal processing, and biomarker selection, aids to enforce regulatory compliance, support allergen management in the food industry, and most importantly, mitigate the risk to consumers with food allergies.

Presence of undeclared allergens in food: A multi-allergen approach by mass spectrometry

254th National Meeting (2017)

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.