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Comparison of allergen quantification strategies for egg, milk, and peanut in food using targeted LC-MS/MS

Authors :
Chelsea C. Boo
Katherine L. Fiedler
Christine H. Parker
Weili Xiong
Source :
Analytical and Bioanalytical Chemistry. 413:5755-5766
Publication Year :
2021
Publisher :
Springer Science and Business Media LLC, 2021.

Abstract

Methods for the detection and quantification of food allergens in complex matrices are necessary to ensure compliance with labeling regulations and assess the effectiveness of food allergen preventive controls. Liquid chromatography–tandem mass spectrometry (LC-MS/MS) has emerged as an orthogonal technique in complement to immunochemical-based assays. However, the absence of established guidelines for MS-based quantification of allergens in food has limited harmonization among the method development community. In this study, different quantification strategies were evaluated using a previously developed multiplexed LC-MS/MS method for the detection of egg, milk, and peanut. Peptide performance criteria (retention time, signal-to-noise ratio, and ion ratio tolerance) were established and quantification approaches using varying calibrants, internal standards, background matrices, and calibration curve preparation schemes were systematically evaluated to refine the previous method for routine laboratory use. A matrix-matched calibration curve using allergen ingredients as calibrants and stable isotope–labeled peptides as internal standards provided the most accurate quantitative results. The strategy was further verified with commercially available reference materials and allowed for the confident detection and quantification of food allergens. This work highlights the need for transparency in calibration strategy and peptide performance requirements for effective evaluation of mass spectrometric methods for the quantification of food allergens.

Details

ISSN :
16182650 and 16182642
Volume :
413
Database :
OpenAIRE
Journal :
Analytical and Bioanalytical Chemistry
Accession number :
edsair.doi...........435d60d4cfcd75bd3258209d7f9bee81