» Articles » PMID: 36832800

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

Overview
Journal Foods
Specialty Biotechnology
Date 2023 Feb 25
PMID 36832800
Authors
Affiliations
Soon will be listed here.
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 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.

Citing Articles

Mass Spectrometry-Based Method for Multiple Allergens Control: Application to Bakery Goods.

Luparelli A, De Angelis E, Pilolli R, Lambertini F, Suman M, Monaci L Foods. 2025; 14(5).

PMID: 40077429 PMC: 11899636. DOI: 10.3390/foods14050726.


Improved multi-food allergen analysis of processed foods using HRAM-LC-MS/MS with an ELISA-validated extraction solution and MS sample prep kit.

Oyama Y, Hamasaka T, Okada H, Nagashima Y, Morita M Anal Bioanal Chem. 2024; 416(23):5165-5175.

PMID: 39078454 DOI: 10.1007/s00216-024-05454-y.


In-house validation of an LC-MS method for the multiplexed quantitative determination of total allergenic food in chocolate.

Pilolli R, Lamonaca A, Nitride C, De Angelis E, Van Poucke C, Gillard N Anal Bioanal Chem. 2023; 416(3):809-825.

PMID: 37615691 PMC: 10766722. DOI: 10.1007/s00216-023-04894-2.

References
1.
Barazorda-Ccahuana H, Theiss-De-Rosso V, Valencia D, Gomez B . Heat-Stable Hazelnut Profilin: Molecular Dynamics Simulations and Immunoinformatics Analysis. Polymers (Basel). 2020; 12(8). PMC: 7464029. DOI: 10.3390/polym12081742. View

2.
Maleki S . Food processing: effects on allergenicity. Curr Opin Allergy Clin Immunol. 2004; 4(3):241-5. DOI: 10.1097/00130832-200406000-00018. View

3.
Monaci L, De Angelis E, Guagnano R, Ganci A, Garaguso I, Fiocchi A . Validation of a MS Based Proteomics Method for Milk and Egg Quantification in Cookies at the Lowest VITAL Levels: An Alternative to the Use of Precautionary Labeling. Foods. 2020; 9(10). PMC: 7603226. DOI: 10.3390/foods9101489. View

4.
Sicherer S, Sampson H . Food allergy: A review and update on epidemiology, pathogenesis, diagnosis, prevention, and management. J Allergy Clin Immunol. 2017; 141(1):41-58. DOI: 10.1016/j.jaci.2017.11.003. View

5.
DunnGalvin A, Chan C, Crevel R, Grimshaw K, Poms R, Schnadt S . Precautionary allergen labelling: perspectives from key stakeholder groups. Allergy. 2015; 70(9):1039-51. DOI: 10.1111/all.12614. View