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.