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 multitarget 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 TM 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 0.1 g/g for milk to 0.3 g/g for egg and 2 g/g for soy.

Multi-allergen detection in food by micro high-performance liquid chromatography coupled to a dual cell linear ion trap mass spectrometry

L Monaci;R Pilolli;E De Angelis;
2014

Abstract

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 multitarget 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 TM 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 0.1 g/g for milk to 0.3 g/g for egg and 2 g/g for soy.
2014
Istituto di Scienze delle Produzioni Alimentari - ISPA
File in questo prodotto:
File Dimensione Formato  
prod_287861-doc_87621.pdf

solo utenti autorizzati

Descrizione: Multi-allergen detection in food by micro high-performance liquid chromatography coupled to a dual cell linear ion trap mass spectrometry
Dimensione 965.18 kB
Formato Adobe PDF
965.18 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/227826
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 80
  • ???jsp.display-item.citation.isi??? ND
social impact