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Multi-Target Detection of Nuts and Peanuts as Hidden Allergens in Bakery Products through Bottom-Up Proteomics and High-Resolution Mass Spectrometry

Authors :
Anna Luparelli
Ilario Losito
Elisabetta De Angelis
Rosa Pilolli
Linda Monaci
Source :
Foods, Vol 12, Iss 4, p 726 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Due to the growing global incidence of allergy to nuts and peanuts, the need for better protection of consumers sensitive to those products is constantly increasing. The best strategy to defend them against adverse immunological reactions still remains the total removal of those products from their diet. However, nuts and peanuts traces can also be hidden in other food products, especially processed ones, such as bakery products, because of cross-contamination occurring during production. Precautionary labelling is often adopted by producers to warn allergic consumers, usually without any evaluation of the actual risk, which would require a careful quantification of nuts/peanuts traces. In this paper, the development of a multi-target method based on liquid chromatography-tandem high resolution mass spectrometry (LC-MS, MS/MS), able to detect traces of five nuts species (almonds, hazelnuts, walnuts, cashews and pistachios) and of peanuts in an in-house incurred bakery product (cookie) through a single analysis is described. Specifically, allergenic proteins of the six ingredients were used as the analytical targets, and the LC-MS responses of selected peptides resulting from their tryptic digestion, after extraction from the bakery product matrix, were exploited for quantification, following a bottom-up approach typical of proteomics. As a result, nuts/peanuts could be detected/quantified down to mg·kg−1 levels in the model cookie, thus opening interesting perspectives for the quantification of hidden nuts/peanuts in bakery products and, consequently, for a more rational use of precautionary labelling.

Details

Language :
English
ISSN :
23048158
Volume :
12
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Foods
Publication Type :
Academic Journal
Accession number :
edsdoj.509075f8f3c4ee29ffda077b3a525a7
Document Type :
article
Full Text :
https://doi.org/10.3390/foods12040726