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In house validation of a high resolution mass spectrometry Orbitrap-based method for multiple allergen detection in a processed model food

Author:
Pilolli, Rosa, De Angelis, Elisabetta, Monaci, Linda
Source:
Analytical and bioanalytical chemistry 2018 v.410 no.22 pp. 5653-5662
ISSN:
1618-2642
Subject:
allergenicity, allergens, cookies, eggs, food matrix, hazelnuts, ingredients, mass spectrometry, models, monitoring, peanuts, peptides, processed foods, skim milk, soy flour, spectrometers
Abstract:
In recent years, mass spectrometry (MS) has been establishing its role in the development of analytical methods for multiple allergen detection, but most analyses are being carried out on low-resolution mass spectrometers such as triple quadrupole or ion traps. In this investigation, performance provided by a high resolution (HR) hybrid quadrupole-Orbitrap™ MS platform for the multiple allergens detection in processed food matrix is presented. In particular, three different acquisition modes were compared: full-MS, targeted-selected ion monitoring with data-dependent fragmentation (t-SIM/dd2), and parallel reaction monitoring. In order to challenge the HR-MS platform, the sample preparation was kept as simple as possible, limited to a 30-min ultrasound-aided protein extraction followed by clean-up with disposable size exclusion cartridges. Selected peptide markers tracing for five allergenic ingredients namely skim milk, whole egg, soy flour, ground hazelnut, and ground peanut were monitored in home-made cookies chosen as model processed matrix. Timed t-SIM/dd2 was found the best choice as a good compromise between sensitivity and accuracy, accomplishing the detection of 17 peptides originating from the five allergens in the same run. The optimized method was validated in-house through the evaluation of matrix and processing effects, recoveries, and precision. The selected quantitative markers for each allergenic ingredient provided quantification of 60–100 μgᵢₙgᵣₑd/g allergenic ingredient/matrix in incurred cookies.
Agid:
6088317