Combined use of peptide ion and normalized delta scores to evaluate milk authenticity by ion-trap based proteomics coupled with error tolerant searching

An automated food protein isolation approach on preparative scale by two‐dimensional liquid chromatography with active modulation interface

“…Before the 2D‐LC separation, a shot‐gun analysis by LC–MS/MS was performed for the identification of proteins present in the sample. Good results were obtained in terms of protein characterization, with a Mascot score ranging from 120 to 860 (well above the identity threshold) and a percentage coverage of 15–45% (Supporting Information Table 2), evaluated after the postprocessing validation of the Peptide Spectrum Matches . Five egg proteins were identified: ovalbumin, vitellogenin, ovotransferrin, apovitellenin, and ovomucoid; an estimation of their MWs was performed on the basis of the total amino acid sequence range associated to the identified peptides by using the p I /MW computation tool by ExPASy (Bioinformatics Resource Portal; https://web.expasy.org/compute_pi/, accessed on 31 May 2018).…”

“…The procedure for the insolution enzymatic digestion of the egg powder sample was described by Azarnia et al. with minor modifications . Other details concerning the proteolytic protocol, as well as LC and MS analysis, including database search and postprocessing validation, are reported in the Supporting Information.…”

The Application of FTIR Spectroscopy and Chemometrics for the Authentication Analysis of Horse Milk

“…Milk authenticity is an important issue nowadays, not only for producers and consumers but also for the regulatory bodies, as consequently, some analytical methods capable of detecting the adulteration practice and quantifying the adulterants are needed [ 7 ]. These methods included ultraperformance liquid chromatography-tandem triple quadrupole mass spectrometry (UPLC-TOF MS) by determining the peptide markers [ 8 ] and metabolomics approach [ 9 ], LC-MS based on ion-trap for proteomics [ 10 ] and peptide analyses [ 11 ], GC-MS and GC-FID by determining fatty acid composition [ 12 ], differential scanning calorimetry (DSC) coupled with machine learning detecting the thermal profile of authentic and adulterated milk [ 13 ], and ICP-MS discriminating milk by geographical origin clustering [ 14 ]. Chromatographic-based techniques coupled with MS detectors are widely used detection methods, despite these methods being expensive, involving sophisticated instruments, and needing competent analysts.…”