Identification and quantification of wheat allergens in commercial processed foods using an immunomagnetic nanoparticle-enhanced UPLC-MS/MS approach.

Wheat is a major source of dietary protein and calories, and causes allergenic risks and celiac disease in susceptible individuals, yet its quantification in processed foods is hindered by matrix interference and processing modifications that affect peptide detectability and analytical performance. Among 30 commercial processed wheat products, three specific, processing-robust and immunoactive peptides ASIVAGIGGQ, IFWGIPALLK, VFLQQQCSPVAMPQR for γ-gliadin (Tri a 20), HMW-glutenin (Tri a 26) and LMW-glutenin (Tri a 36) were identified based on an MSE-based high-resolution peptidomics. These peptides were further predicted to harbor putative IgE-binding epitope candidates. Importantly, the reported γ-gliadin peptide APFASIVAGIGGQ was outperformed by its truncated form ASIVAGIGGQ due to conformational changes that alter their cleavage sites. Furthermore, a high sensitive IMNP-enhanced UPLC-MS/MS method was established for the quantification of wheat allergens in processed foods. The method showed excellent linearity (R2 > 0.997) over the range of 1-2000 ng/mL, with LODs of 0.060, 0.152, and 0.023 mg/kg and LOQs of 0.121, 0.456, and 0.069 mg/kg for Tri a 20, Tri a 26, and Tri a 36, respectively. Recoveries ranged from 83.83 to 113.84% with RSDs less than 6.25%, indicating good accuracy and precision. This study indicates that combining processing stability with BepiPred B-cell epitope prediction may facilitate the identification of characteristic peptides in processed foods. This IMNPs-enhanced UPLC-MS/MS method provides a robust analytical foundation for improving wheat allergen surveillance, exposure assessment, and risk management in complex processed food systems.