In house validation of a high resolution mass spectrometry Orbitrap-based method for multiple allergen detection in a processed model food
- 304 Downloads
In recent years, mass spectrometry (MS) has been establishing its role in the development of analytical methods for multiple allergen detection, but most analyses are being carried out on low-resolution mass spectrometers such as triple quadrupole or ion traps. In this investigation, performance provided by a high resolution (HR) hybrid quadrupole-Orbitrap™ MS platform for the multiple allergens detection in processed food matrix is presented. In particular, three different acquisition modes were compared: full-MS, targeted-selected ion monitoring with data-dependent fragmentation (t-SIM/dd2), and parallel reaction monitoring. In order to challenge the HR-MS platform, the sample preparation was kept as simple as possible, limited to a 30-min ultrasound-aided protein extraction followed by clean-up with disposable size exclusion cartridges. Selected peptide markers tracing for five allergenic ingredients namely skim milk, whole egg, soy flour, ground hazelnut, and ground peanut were monitored in home-made cookies chosen as model processed matrix. Timed t-SIM/dd2 was found the best choice as a good compromise between sensitivity and accuracy, accomplishing the detection of 17 peptides originating from the five allergens in the same run. The optimized method was validated in-house through the evaluation of matrix and processing effects, recoveries, and precision. The selected quantitative markers for each allergenic ingredient provided quantification of 60–100 μgingred/g allergenic ingredient/matrix in incurred cookies.
KeywordsHigh resolution mass spectrometry Multi-allergen detection Processed matrix Incurred samples Peptide marker In house validation
Roberto Schena is kindly acknowledged for his technical aid in performing MS measurements. Besana group S.p.A. is also acknowledged for kindly providing hazelnuts and peanuts.
The work was funded by the project Safe & Smart—Nuove tecnologie abilitanti per la food safety e l’integrità delle filiere agro-alimentari in uno scenario globale—National CL.AN-Cluster agroalimentare nazionale programma area 2. The equipment used in this work was supported by the “Biodiversità per la valorizzazione e sicurezza delle produzioni alimentari tipiche pugliesi, BioNet-PTP” project (Cod. 73) funded by Programma Operativo Regionale Puglia FESR 2000-2006 - Risorse liberate - Obiettivo Convergenza.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
- 2.Monaci L, Pilolli R, De Angelis E, Mamone G. Mass spectrometry in food allergen research. In: Picó Y, editor. Comprehensive analytical chemistry. Elsevier Science and Technology; 2015. pp. 359–393.Google Scholar
- 4.Pilolli R, De Angelis E, Godula M, Visconti A, Monaci L. Orbitrap™ monostage MS versus hybrid linear ion trap MS: application to multi-allergen screening in wine. J Mass Spectrom 2014;49:1254–1263.Google Scholar
- 6.Korte R, Monneuse JM, Gemrot E, Metton I, Humpf H-U, Brockmeyer J. New high-performance liquid chromatography coupled mass spectrometry method for the detection of lobster and shrimp allergens in food samples via multiple reaction monitoring and multiple reaction monitoring cubed. J Agric Food Chem. 2016;64:6219–27.CrossRefPubMedGoogle Scholar
- 7.Planque M, Arnould T, Dieu M, Delahaut P, Renard P, Gillard N. Advances in ultra-high performance liquid chromatography coupled to tandem mass spectrometry for sensitive detection of several food allergens in complex and processed foodstuff. J Chromatogr A. 2016;1464:115–23.CrossRefPubMedGoogle Scholar
- 16.European Commission Commission Directive 2007/68/EC. Off J Eur Union. 2007;L310:11–4.Google Scholar
- 19.United States Department of Agriculture Agricultural Research Service. In: USDA Food Composition Databases. USA National Agricultural Library. 2017. https://ndb.nal.usda.gov/ndb/search/list. Accessed 10 July 2017.