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

Xiong, Weili; Parker, Christine H.; Boo, Chelsea C.; Fiedler, Katherine L. ✉

Angol nyelvű Szakcikk (Folyóiratcikk) Tudományos
Megjelent: ANALYTICAL AND BIOANALYTICAL CHEMISTRY 1618-2642 1618-2650 413 (23) pp. 5755-5766 2021
  • SJR Scopus - Analytical Chemistry: Q1
Azonosítók
Szakterületek:
  • Biológiai tudományok
  • Kémiai tudományok
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.
Hivatkozás stílusok: IEEEACMAPAChicagoHarvardCSLMásolásNyomtatás
2022-12-04 03:58