Selecting Processing Robust Markers Using High-Resolution Mass Spectrometry for the Detection of Milk in Food Products.


Journal

Journal of AOAC International
ISSN: 1944-7922
Titre abrégé: J AOAC Int
Pays: England
ID NLM: 9215446

Informations de publication

Date de publication:
15 Mar 2022
Historique:
received: 10 08 2021
revised: 14 10 2021
accepted: 06 11 2021
pubmed: 19 11 2021
medline: 18 3 2022
entrez: 18 11 2021
Statut: ppublish

Résumé

Cow's milk allergy is one of the most reported food allergies in Europe. To help patients suffering from food allergies it is important to be able to detect milk in different foods. An analytical method that is gaining interest in the field of allergen detection is ultrahigh performance liquid chromatography-tandem mass spectrometry, where the analyte is a target peptide. When these peptide biomarkers are selected, the effect of food processing should be taken into account to allow a robust detection method. This work aims at identifying such processing stable peptide markers for milk for the ultrahigh performance liquid chromatography-tandem mass spectrometry based detection of food allergens in different food products. Milk-incurred food materials that underwent several processing techniques were produced. This was followed by establishing tryptic peptide profiles from each matrix using ultrahigh performance liquid chromatography-high resolution mass spectrometry. A careful comparison of peptide profiles/intensities and the use of specific exclusion criteria resulted in the selection of eight peptide biomarkers suitable for application in ultrahigh performance liquid chromatography-tandem mass spectrometry based milk detection methods. One of these markers is an α-lactalbumin specific peptide, which has been determined to be stable in different incurred materials for the first time. To our knowledge, this is the first systematic and experimentally based approach for the selection of suitable milk peptide biomarkers robust toward multiple, often applied food processing techniques for milk. Ensuring the exact knowledge of the food processing circumstances by starting from well-defined raw material and using fully controlled settings to produce incurred test material allowed the construction of a peptide database with robust markers. These robust markers can be used for the development of a robust detection method for milk in different food matrixes. To facilitate food allergen detection in processed food, processing stable peptide markers for the detection of milk in food products were determined using Ultra-High Performance Liquid Chromatography-High Resolution Mass Spectrometry on well-defined raw materials which were processed in accordance with often used processing techniques.

Sections du résumé

BACKGROUND BACKGROUND
Cow's milk allergy is one of the most reported food allergies in Europe. To help patients suffering from food allergies it is important to be able to detect milk in different foods. An analytical method that is gaining interest in the field of allergen detection is ultrahigh performance liquid chromatography-tandem mass spectrometry, where the analyte is a target peptide. When these peptide biomarkers are selected, the effect of food processing should be taken into account to allow a robust detection method.
OBJECTIVE OBJECTIVE
This work aims at identifying such processing stable peptide markers for milk for the ultrahigh performance liquid chromatography-tandem mass spectrometry based detection of food allergens in different food products.
METHOD METHODS
Milk-incurred food materials that underwent several processing techniques were produced. This was followed by establishing tryptic peptide profiles from each matrix using ultrahigh performance liquid chromatography-high resolution mass spectrometry.
RESULTS RESULTS
A careful comparison of peptide profiles/intensities and the use of specific exclusion criteria resulted in the selection of eight peptide biomarkers suitable for application in ultrahigh performance liquid chromatography-tandem mass spectrometry based milk detection methods. One of these markers is an α-lactalbumin specific peptide, which has been determined to be stable in different incurred materials for the first time.
CONCLUSIONS CONCLUSIONS
To our knowledge, this is the first systematic and experimentally based approach for the selection of suitable milk peptide biomarkers robust toward multiple, often applied food processing techniques for milk. Ensuring the exact knowledge of the food processing circumstances by starting from well-defined raw material and using fully controlled settings to produce incurred test material allowed the construction of a peptide database with robust markers. These robust markers can be used for the development of a robust detection method for milk in different food matrixes.
HIGHLIGHTS CONCLUSIONS
To facilitate food allergen detection in processed food, processing stable peptide markers for the detection of milk in food products were determined using Ultra-High Performance Liquid Chromatography-High Resolution Mass Spectrometry on well-defined raw materials which were processed in accordance with often used processing techniques.

Identifiants

pubmed: 34791331
pii: 6428662
doi: 10.1093/jaoacint/qsab147
doi:

Substances chimiques

Allergens 0
Biomarkers 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

463-475

Subventions

Organisme : Belgian Federal Public Service of Health, Food Chain Safety, and Environment
ID : RT 15/10 ALLERSENS

Informations de copyright

© The Author(s) 2021. Published by Oxford University Press on behalf of AOAC INTERNATIONAL. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Auteurs

Kaatje Van Vlierberghe (K)

ILVO Flanders Research Institute for Agriculture, Fisheries, and Food, Technology and Food Science Unit, Brusselsesteenweg 370, BE-9090 Melle, Belgium.

Maxime Gavage (M)

CER Groupe, Rue du Point du Jour 8, 6900 Marloie, Belgium.
University of Namur, Laboratory of Biochemistry and Cell Biology (URBC)-Namur Research Institute for Life Sciences (NARILIS), 61, rue de Bruxelles, 5000 Namur, Belgium.

Marc Dieu (M)

University of Namur, Laboratory of Biochemistry and Cell Biology (URBC)-Namur Research Institute for Life Sciences (NARILIS), 61, rue de Bruxelles, 5000 Namur, Belgium.

Patsy Renard (P)

University of Namur, Laboratory of Biochemistry and Cell Biology (URBC)-Namur Research Institute for Life Sciences (NARILIS), 61, rue de Bruxelles, 5000 Namur, Belgium.

Thierry Arnould (T)

University of Namur, Laboratory of Biochemistry and Cell Biology (URBC)-Namur Research Institute for Life Sciences (NARILIS), 61, rue de Bruxelles, 5000 Namur, Belgium.

Nathalie Gillard (N)

CER Groupe, Rue du Point du Jour 8, 6900 Marloie, Belgium.

Katleen Coudijzer (K)

ILVO Flanders Research Institute for Agriculture, Fisheries, and Food, Technology and Food Science Unit, Brusselsesteenweg 370, BE-9090 Melle, Belgium.

Marc de Loose (M)

ILVO Flanders Research Institute for Agriculture, Fisheries, and Food, Technology and Food Science Unit, Brusselsesteenweg 370, BE-9090 Melle, Belgium.

Kris Gevaert (K)

VIB-UGent Center for Medical Biotechnology, Technologiepark-Zwijnaarde 75, BE-9052 Ghent, Belgium.
Ghent University, Department of Biomolecular Medicine, Technologiepark-Zwijnaarde 75, BE-9052 Ghent, Belgium.

Christof Van Poucke (C)

ILVO Flanders Research Institute for Agriculture, Fisheries, and Food, Technology and Food Science Unit, Brusselsesteenweg 370, BE-9090 Melle, Belgium.

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Classifications MeSH