Abstract
Adulteration of meat products is a major concern not only for economic fraud, but also for ethical reasons. In this study, we presented a parallel reaction monitoring (PRM) mass spectrometry approach for detection of trace pork in meat mixtures (chicken, sheep, and beef). Specific peptides were identified and screened by a shotgun proteomic approach based on tryptic digests of certain protein. Five surrogate peptides from myosin were screened and then used for pork detection by PRM of Orbitrap MS. When the most sensitive peptide was selected, the LOD in mixed meat can be up to 0.5%. The RSD values between detected and designated pork levels (1%, 5% and 50%) were 4–15%. The targeted method developed can be applied to identify and quantify the pork in meat mixture.
Highlights
Meat authentication is of great interest for the scienti c community, consumers and researchers.[1]
As described by Kumar et al.,[21] data dependent acquisition is a mode of data collection in tandem mass spectrometry in which a xed number of peaks selected from a survey scan using predetermined rules, and the 125 peptides for myosin-4 and myosin-1 were identi ed (Table 1), these peptides cannot be directly used for marker peptides
We selected ve peptides (HKYEETQAELEASQK, KLETDISQIQGEMEDIVQEAR, LETDISQIQGEMEDIVQEAR, KLETDISQIQGEMEDIIQEAR and LETDISQIQGEMEDIIQEAR) as the potential surrogate peptides, which are not included in sheep, beef or chicken muscle (Table 2)
Summary
Meat authentication is of great interest for the scienti c community, consumers and researchers.[1]. ELISA and PCR are two common methods used for species authentication. Immunoassays are not exempt from some limitations such as the need for speci c antibodies. When antibodies are not highly speci c of particular species and/or tissue, it may give rise to false positive cases in terms of crossreactions.[4] PCR methods show some limits, especially in authentication of processed meat. The aggressive conditions in the meat processing such as high temperature and pH change can lead to the disruption of DNA. Another important limitation is that the molecular information obtained is limited and datamining cannot be performed in post-analysis.[5]
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