Multi-allergen detection in food by micro high-performance liquid chromatography coupled to a dual cell linear ion trap mass spectrometry
Language English Country Netherlands Media print-electronic
Document type Journal Article, Research Support, Non-U.S. Gov't
PubMed
25042441
DOI
10.1016/j.chroma.2014.06.092
PII: S0021-9673(14)01037-1
Knihovny.cz E-resources
- Keywords
- Cookies, Food allergens, Linear ion trap, Mass spectrometry, Multi-allergen analysis,
- MeSH
- Allergens isolation & purification MeSH
- Food Analysis methods MeSH
- Humans MeSH
- Limit of Detection MeSH
- Milk Proteins isolation & purification MeSH
- Milk chemistry MeSH
- Flour analysis MeSH
- Peptides analysis MeSH
- Soybean Proteins isolation & purification MeSH
- Soy Foods analysis MeSH
- Tandem Mass Spectrometry methods MeSH
- Egg Proteins isolation & purification MeSH
- Eggs analysis MeSH
- Sonication MeSH
- Chromatography, High Pressure Liquid methods MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Names of Substances
- Allergens MeSH
- Milk Proteins MeSH
- Peptides MeSH
- Soybean Proteins MeSH
- Egg Proteins MeSH
There is a raising demand for sensitive and high throughput MS based methods for screening purposes especially tailored to the detection of allergen contaminants in different food commodities. A challenging issue is represented by complex food matrices where the antibody-based kits commercially available might encounter objective limitations consequently to epitope masking phenomena due to a multitude of interfering compounds arising from the matrix. The performance of a method duly optimized for the extraction and simultaneous detection of soy, egg and milk allergens in a cookie food matrix by microHPLC-ESI-MS/MS, is herein reported. Thanks to the innovative configuration and the versatility shown by the dual cell linear ion trap MS used, the most intense and reliable peptide markers were first identified by untargeted survey experiment, and subsequently employed to design an ad hoc multi-target SRM method, based on the most intense transitions recorded for each selected precursor peptide. A sample extraction and purification protocol was optimized also including an additional step based on sonication, which resulted in a considerable improvement in the detection of milk allergen peptides. Data Dependent™ Acquisition scheme allowed to fill out a tentative list of potential peptide markers, which were further filtered upon fulfilling specific requirements. A total of eleven peptides were monitored simultaneously for confirmation purposes of each allergenic contaminant and the two most sensitive peptide markers/protein were selected in order to retrieve quantitative information. Relevant LODs were found to range from 0.1μg/g for milk to 0.3μg/g for egg and 2μg/g for soy.
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