Development of innovative methods for the multiple analysis of allergens in processed foods

Allergy to nuts and peanuts represents a global relevant problem, especially due to the risk of their ingestion as hidden allergens, often resulting from cross‐contamination between production lines at industrial level during food manufacturing. Mass spectrometry have high potential as screening tools in food safety and different studies in literature have proven its suitability for the identification and quantification of allergenic ingredients at part-per-million (ppm) levels. The most widespread and sensitive approach for protein quantitative analysis in complex food matrix is the so-called “bottom-up” approach where the analysis target is a specific peptide resulting from the enzymatic digestion of the protein under investigation. Moreover, MS methods allow multiplex allergen detection with high molecular-level specificity in a single run, enabling the unequivocal identification of allergens in a variety of food commodities[1, 2]. The main objective of the current industrial PhD project is to develop a sensitive and robust multi-target method, based on ultra-high-performance liquid chromatography coupled with high resolution Orbitrap™-based mass spectrometry (UHPLC-HRMS/MS), for the simultaneous detection of allergens from different species of nuts (almond, hazelnut, cashew, walnut and pistachio) and peanuts in complex and highly processed food matrices in order to provide a useful tool to be employed at industrial level for the final protection of allergic consumers’ health. Experiments were accomplished on incurred cookies model food produced in-house by adding roasted and powdered nuts/peanut upon dough preparation and before baking. The following pipeline was used for the LC-MS/MS method development: 1) LC-HRMS/MS untargeted analysis of both raw and roasted ingredients for the selection of the most appropriate candidate marker peptides for detecting nuts and peanut allergens 2) constraining of the resulting peptide list by following the specific criteria as previously reported in literature [review di Rosa], 3) evaluation of the impact of processing on candidate peptides detectability by monitoring selected peptides in cookie extract, 4) selection of the most appropriate marker peptides for tracing nuts/peanut in cookie food, 5) evaluation of method performance by building up specific curve calibration for each investigated peptide and assessment of the most relevant method parameters (linearity, limit of detection (LOD), limit of quantification (LOQ), repeatability inter-day and inter-day), 6) comparison of method performance with VITAL 3.0 thresholds. Suitable and thermostable peptide markers for each allergenic ingredient were selected on the base of stringent criteria ad hoc defined for marker peptides selection. The LOD and LOQ values obtained for each allergen calculated in incurred cookies (referred to the protein content) allowed to detect levels of contamination complying with the reference thresholds set for each allergen and recommended (action level 1) by the VITAL program v 3.0. Additionally, method precision provided good results for all the allergenic ingredients analyzed in this matrix. This method could represent an important tool to support the risk assessment for allergen management also preventing the overuse of PAL (Precautionary Allergen Labelling). References: [1] Pilolli, R. et al. Food Chem 343 2021 [2] Monaci, L. et al. Food Add. Contam. Part A 32.10 2015