Optimization of a sample preparation workflow based on UHPLC-MS/MS method for multi-allergen detection in chocolate: An outcome of the ThRAll project

Developing reliable methodologies for detecting and quantifying allergens in processed food commodities is crucial to support food business operators in allergen risk assessment and properly implementing precautionary allergen labels whenever required to safeguard the health of allergic consumers. Multiple Mass Spectrometry (MS) methods have been developed so far and applied for single and multi-allergen detection in foods, generating a heterogeneous literature on this topic, with little attention paid to the extraction and the digestion steps, crucial in delivering accurate allergen measurements. This investigation carried out within an international consortium specifically built up to convey a prototype MS based reference method, reports on the first part of the method development, namely the optimization of the sample preparation protocol for six allergens detection (cow's milk, hen's egg, soy, peanut, hazelnut, and almond) in chocolate. The latter was chosen as model complex food matrix, having a high lipid and polyphenol content. Different steps of the sample preparation protocol have been taken into consideration: (i) sampling, (ii) composition of the extraction buffer, (iii) protein purification, (iv) protein enzymatic digestion, (v) peptide purification and pre-concentration, and some experiments were carried out by two independent laboratories and two different MS platforms to provide a first assessment of the robustness of the method under development. Fifty target peptides were monitored in multiple reaction monitoring mode and validated in different laboratories to trace the six allergenic ingredients in the incurred chocolate and the best performing protocol for sample preparation was identified. This work paves the way of the forthcoming full analytical validation of a prototype reference method for MS-based allergen quantification.