Selecting processing robust markers using high resolution mass spectrometry for the detection of milk in food products.

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 Ultra-High 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 This works aims at identifying such processing stable peptide markers for milk for the Ultra-High Performance Liquid Chromatography-tandem Mass Spectrometry based detection of food allergens in different food products. METHODS Milk-incurred food materials that underwent several processing techniques were produced. This was followed by establishing tryptic peptide profiles from each matrix using Ultra-High Performance Liquid Chromatography-High Resolution Mass Spectrometry . RESULT A careful comparison of peptide profiles/intensities and the use of specific exclusion criteria resulted in the selection of 8 peptide biomarkers suitable for application in Ultra-High Performance Liquid Chromatography-tandem Mass Spectrometry based milk detection methods. One of these markers is a α-lactalbumin specific peptide, which has been determined to be stable in different incurred materials for the first time. CONCLUSION To our knowledge, this is the first systematic and experimentally based approach for the selection of suitable milk peptide biomarkers robust towards 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 matrices.