Open AccessAdvances in LC–MS/MS Methods for Allergen Testing, Meat Speciation, and Gelatin Speciation
Author(s) -
Jianru Stahl-Zeng,
Ashley Sage,
Philip R. Taylor,
Jeremy Dietrich Netto,
Tuo Zhang
Publication year - 2019
Publication title -
journal of aoac international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.432
H-Index - 87
eISSN - 1944-7922
pISSN - 1060-3271
DOI - 10.1093/jaoac/102.5.1309
Subject(s) - analyte , tandem mass spectrometry , chemistry , mass spectrometry , chromatography , detection limit , complex matrix , proteome , food allergens , food products , genetic algorithm , liquid chromatography–mass spectrometry , allergen , matrix (chemical analysis) , food science , computational biology , biology , biochemistry , allergy , evolutionary biology , immunology
Background: Food authenticity is demanded by the consumer at all times. The consumer places trust in the manufacturer that the food product is genuine in terms of what is recorded on the packaging label. Objective: Recent advancements in LC–tandem MS methodology in the detection of allergens, meat, and gelatin speciation in raw food products and processed foods are detailed in this paper. Method: For each of the three methods, initial proteome analysis and the screening leading to the determination of unique tryptic peptides were conducted using a high-resolution, accurate tandem mass spectrometer. Having identified the unique markers, the method was transferred to a tandem quadrupole mass spectrometer for a higher-sensitivity quantitative study, multiple reaction monitoring transition analysis. Results: For the allergens method a detection limit of at least 10 ppm was attained across the 12 allergen peptides in this workflow. In the gluten workflow the resulting chromatograms show good detection down to 5 ppm, with no interference from the food matrices. The meat speciation method details that signature peptides could be readily identified at 1% w/w with no matrix interference. Conclusions: These single-injection workflows with cycle-time optimization enable wide coverage of analytes to identify multiple species within challenging matrix samples.