Identifying the proportion of muscle tissue by biomarker peptides using quadrupole chromatography-mass spectrometry

D.V. Khvostov*, N.L. Vostrikova**, I.M. Chernukha***, A.V. Kulikovskii****

V.M. Gorbatov Federal Research Center for Food Systems, Russian Academy of Sciences, Moscow, 109316 Russia

E-mail: *d.hvostov@fncps.ru, **n.vostrikova@fncps.ru,***imcher@inbox.ru,

 ****a.kulikovskii@fncps.ru

Received October 10, 2018

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DOI: 10.26907/2542-064X.2019.3.490-499

For citation: Khvostov D.V., Vostrikova N.L., Chernukha I.M., Kulikovskii A.V. Identifying the proportion of muscle tissue by biomarker peptides using quadrupole chromatography-mass spectrometry. Uchenye Zapiski Kazanskogo Universiteta. Seriya Estestvennye Nauki, 2019, vol. 161, no. 3, pp. 490–499. doi: 10.26907/2542-064X.2019.3.490-499. (In Russian)

Abstract

Current laboratory practices in determining the quality and safety of foodstuffs face a constant expansion of the list of controlled indicators, for the meat industry in particular. Thus, new standardized and certified methods based on in-depth studies of the biochemical indicators of meat and meat products are needed. For this purpose, we developed a highly symmetric analysis relying on the multiple-reactions monitoring (MRM) method, i.e., identification of the proportion of muscle tissues in multicomponent meat products (not subjected to heat treatment). The high-flux system with ultra-high performance (LC) and the triple quadrupole mass spectrometer (Agilent 6410) increased the reliability of the analysis. The analysis (25 min long) used four stable peptides to quantify two putative biomarkers of muscle tissues in minced meat (beef (Bos taurus) and pork (Sus scrofa)). Up to 5% of impurities of either beef or pork muscle tissues in fresh minced meat can be detected with the help of the developed method. The MRM protein assays presented in this paper may soon overtake the ELISA methodology as a variant of multiplexed protein assay.

Keywords: biomarker, prototypic peptides, MRM, muscle tissue, quantitation

Acknowledgments. The study was supported by the Russian Science Foundation (project no. 16-16-10073).

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