Parallel Reaction Monitoring Mass Spectrometry Method for Detection of Both Casein and Whey Milk Allergens from a Baked Food Matrix.

Milk allergy is among the most common food allergies present in early childhood, which in some cases may persist into adulthood as well. Proteins belonging to both casein and whey fractions of milk can trigger an allergic response in susceptible individuals. Milk is present as an ingredient in many foods, and it can also be present as casein- or whey-enriched milk-derived ingredients. As whey proteins are more susceptible to thermal processing than caseins, conventional methods often posed a challenge in accurate detection of whey allergens, particularly from a processed complex food matrix. In this study, a targeted mass spectrometry method has been developed to detect the presence of both casein and whey allergens from thermally processed foods. A pool of 19 candidate peptides representing four casein proteins and two whey proteins was identified using a discovery-driven target selection approach from various milk-derived ingredients. These target peptides were evaluated by parallel reaction monitoring of baked cookie samples containing known amounts of nonfat dry milk (NFDM). The presence of milk could be detected from baked cookies incurred with NFDM at levels as low as 1 ppm using seven peptides representing α-, ß-, and κ-casein proteins and three peptides representing a whey protein, ß-lactoglobulin, by this consensus PRM method.

Detection of Six Commercially Processed Soy Ingredients in an Incurred Food Matrix Using Parallel Reaction Monitoring.

Soybeans are one of the major allergenic foods in many countries. Soybeans are commonly processed into different types of soy ingredients to achieve the desired properties. The processing, however, may affect the protein profiles and protein structure, thus affecting the detection of soy proteins. Mass spectrometry (MS) is a potential alternative to the traditional immunoassays for the detection of soy-derived ingredients in foods. This study aims to develop a liquid chromatography-tandem MS method that uniformly detects different types of soy-derived ingredients. Target peptides applicable to the detection of six commercial soy ingredients were identified based on the results of MS label-free quantification and a set of selection criteria. The results indicated that soy ingredient processing can result in different protein profiles. A total of six soy ingredients were then individually incurred into cookie matrices at different levels. Sample preparation methods were optimized, and a distinct improvement in peptide performance was observed after optimization. Cookies and dough incurred with different soy ingredients at 100 ppm total soy protein showed a similar level of peptide recovery (90% mean signal relative to unroasted soy flour), demonstrating the ability of the MS method to detect processed soy ingredients in a uniform manner.

Detection of gelatin adulteration using bio-informatics, proteomics and high-resolution mass spectrometry.

Following the internationalisation of food production and manufacturing, a significant increase of food fraud was discovered, ranging from false label claims to the use of additives and fillers to increase profitability. The accidental or fraudulent mixing of animal products or by-products from different species is an important preoccupation for consumers with health or ethical concerns. Gelatin is widely used during food processing as well as in cosmetics, nutraceutics and medical formulations. It contains mainly type I, II and III collagen polypeptides. Gelatin speciation was performed using a well-defined proteogenomic annotation, carefully chosen surrogate tryptic peptides and analysis using a hybrid quadrupole-Orbitrap MS. Gelatin samples were dissolved in ammonium bicarbonate buffer and proteins were digested with trypsin. The samples were analysed using high-resolution MS. Chromatography was achieved using a 30-min linear gradient on a Thermo BioBasic C8 100 × 1 mm column at a flow rate of 75 µL min-1. The MS was operated in full-scan high resolution and accurate mass and using a data-dependent top-10 method. Collagen proteins were methodically analysed in silico in order to generate tryptic peptide mass lists. Following comprehensive MS and MS/MS analyses, we detected and identified several type I collagen peptides and fully characterised the proteotypic peptides [831-846], [847-879], [949-974] and [975-996] (accession number F1SFA7). Additionally, the method was successfully tested with gelatin used in charcuterie meats obtained from grocery stores, fruit-snacks and gelatin capsules. This targeted method allowed comprehensive gelatin speciation and adulteration detection down to 0.1% (w/w) of undesired pork gelatin.

Detection of meat species adulteration using high-resolution mass spectrometry and a proteogenomics strategy.

Due to the internationalisation of food production and distribution, there has been a significant increase of food fraud in recent years. Food fraud can have serious health implications, and it occurs when food manufacturers implement unethical practices such as making false label claims as well as using additives and fillers within their products to increase profitability. This has been a serious concern. Meat adulteration was examined using a well-defined proteogenomic annotation, carefully selected surrogate tryptic peptides and high-resolution mass spectrometry. Selected mammalian meat samples were homogenised and the proteins extracted and digested with trypsin. Chromatography was achieved using a 30-min linear gradient along with a BioBasic C8 100 × 1 mm column at a flow rate of 75 µl min-1. The mass spectrometer was operated in full-scan high-resolution and accurate mass using resolving powers of 140,000 and 17,500 (FWHM) in full-scan MS and MS/MS respectively. Data independent acquisition (DIA) mode was used including 12 DIA MS/MS scans to cover the mass range 600-1200 m/z. Methodically in silico analyses of myoglobin, myosin-1, myosin-2 and ß-haemoglobin sequences allow for the identification of a species-specific tryptic peptide mass lists and theoretical MS/MS spectra. Following comprehensive MS, MS/MS or DIA analyses, the method was capable of the detection and identification of very specific tryptic peptides for all four targeted proteins for each animal species tested with observed m/z below 3 ppm compared with the theoretical m/z. The analyses were successfully performed with raw and cooked meat. Specifically, the method was capable of detecting 1% (w/w) of pork or horse meat in a mixture before and after cooking (71°C internal temperature).

Assessment of meat authenticity using bioinformatics, targeted peptide biomarkers and high-resolution mass spectrometry.

In recent years a significant increase of food fraud has been observed, ranging from false label claims to the use of additives and fillers to increase profitability. Recently in 2013 horse and pig DNAs were detected in beef products sold from several retailers. Mass spectrometry (MS) has become the workhorse in protein research, and the detection of marker proteins could serve for both animal species and tissue authentication. Meat species authenticity is performed in this paper using a well-defined proteogenomic annotation, carefully chosen surrogate tryptic peptides and analysis using a hybrid quadrupole-Orbitrap MS. Selected mammalian meat samples were homogenised and proteins were extracted and digested with trypsin. The samples were analysed using a high-resolution MS. Chromatography was achieved using a 30-min linear gradient along with a BioBasic C8 100 × 1 mm column at a flow rate of 75 µl min(-1). The MS was operated in full-scan high resolution and accurate mass. MS/MS spectra were collected for selected proteotypic peptides. Muscular proteins were methodically analysed in silico in order to generate tryptic peptide mass lists and theoretical MS/MS spectra. Following a comprehensive bottom-up proteomic analysis, we detected and identified a proteotypic myoglobin tryptic peptide (120-134) for each species with observed m/z below 1.3 ppm compared with theoretical values. Moreover, proteotypic peptides from myosin-1, myosin-2 and ß-haemoglobin were also identified. This targeted method allowed comprehensive meat speciation down to 1% (w/w) of undesired product.