Review of new technologies used for meat identification
https://doi.org/10.21323/2414-438X-2022-7-2-131-137
Аннотация
The present article represents an analysis of trends in development of test-systems for identification of meat. These test systems are commonly used in food production and research laboratories. The relevance of development of methods for identification of meat kinds is related not only to the food restrictions, which are practiced in some religions and related to consumption of certain types of meat, but also with the hygienic aspects of food production. Also, this research is inspired also by the acute issue of food products adulteration and the replacement of one type of meat with another one. The article considers the trends in the develop ment of microanalysis method that use immunochromatic research, i. e. methods based on molecular biology. Also this article considers the devices that do not use chromatographic methods of analysis. Examples of the development of test systems based on various methods of analysis for the identification of meat are given below. Attention is focused on the prospects of combining these methods, including colorimetric methods for identification of meat. It is also specified that the emergence of new dyes and new enzyme systems, suitable for use in enzyme-immunoassay, can enhance the sensitivity of these test systems. It is also noted that the development of technologies associated with sorbents can contribute to a better separation of the test substrates and this way to increase the sensitivity of the test in case of small amounts of test substrate. It is also noted that the use of various types of iso thermal amplification can reduce the analysis time necessary for meat identification. Various schemes of devices for microanalysis are given; their advantages and disadvantages are listed. An example of proteomes application for meat identification is given. It is shown that this method can also be applied in the heat treatment of meat. The prospects for the development of such devices are analyzed. It is concluded that the development of systems for microanalysis in the form of quick tests is quite relevant and promis ing. It is indicated that theoretically in the future such analytical systems, due to the use of microfluidic technologies, will be able to combine several methods. The authors proposed to use machine-aided cognition methods to analyze data obtained from similar test systems in order to increase their sensitivity.
Об авторах
V. Yu. KornienkoРоссия
Vladimir Yu. Kornienko, Candidate of Biological Sciences, Senior Researcher, Laboratory of Molecular Biology and Bioinformatics
26, Talalikhina Str., Moscow, 109316
T. А. Fomina
Россия
Tatyana A. Fomina, Candidate of Technical Sciences, Senior Research Scientist, Laboratory of Molecular Biology and Bioinformatics, V. M. Gorbatov Federal Research Center for Food Systems. Head of the Department of Molecular Diagnostic Research at the Testing Reference Laboratory, National Centre for Safety of Aquatic Fisheries Products and Aquaculture
26, Talalikhina Str., Moscow, 109316,
14–1, Grafskiy per., 129626, Moscow
M. Yu. Minaev
Россия
Mihail Yu. Minaev, Candidate of Technical Sciences, Head of Laboratory of Molecular Biology and Bioinformatics
26, Talalikhina Str., Moscow, 109316
Список литературы
1. Kumar, Y., Narsaiah, K. (2021). Quick point-of-care testing methods/devices for meat species identification: A review. Comprehensive Reviews in Food Science and Food Safety, 20(1), 900– 923. https://doi.org/10.1111/1541–4337.12674
2. Boyacı, İ. H., Temiz, H. T., Uysal, R. S., Velioğlu, H. M., Yadegari, R. J., Rishkan, M. M. (2014). A novel method for discrimination of beef and horsemeat using Raman spectroscopy. Food Chemistry, 148, 37–41. https://doi.org/10.1016/j.foodchem.2013.10.006
3. Quinto, C. A., Tinoco, R., Hellberg, R. S. (2016). DNA barcoding reveals mislabeling of game meat species on the U.S. commercial market. Food Control, 59, 386–392. https://doi.org/10.1016/j.Foodcont.2015.05.043
4. Chuah, L.-O., He, X. B., Effarizah, M. E., Syahariza, Z. A., Shamila-Syuhada, A. K., Rusul, G. (2016). Mislabelling of beef and poultry products sold in Malaysia. Food Control, 62, 157–164. https://doi.org/10.1016/j.foodcont.2015.10.030
5. Cawthorn, D.-M., Steinman, H. A., Hoffman, L. C. (2013). A high incidence of species substitution and mislabelling detected in meat products sold in South Africa. Food Control, 32(2), 440– 449. https://doi.org/10.1016/j.foodcont.2013.01.008
6. Kane, D. E., Hellberg, R. S. (2016). Identification of species in ground meat products sold on the U.S. commercial market using DNA-based methods. Food Control, 59, 158–163. https://doi.org/10.1016/j.foodcont.2015.05.020
7. Naaum, A. M., Shehata, H. R., Chen, S., Li, J., Tabujara, N., Awmack, D. et al. (2018). Complementary molecular methods detect undeclared species in sausage products at retail markets in Canada. Food Control, 84, 339–344. https://doi.org/10.1016/j.foodcont.2017.07.040
8. Abdullahi, U. F., Naim, R., Wan Taib, W. R., Saleh, A., Muazu, A., Aliyu, S. et al. (2015). Loop-mediated isothermal amplification (LAMP), an innovation in gene amplification: Bridging the gap in molecular diagnostics; a review. Indian Journal of Science and Technology, 8(17), 1–12. https://doi.org/10.17485/ijst/2015/v8i17/55767
9. Kornienko, V. Yu., Zakharova, M.V., Kovalevskaya, Zh.I. (2019). World trends in meat species identification. Meat Industry, 11, 28–32. (In Russian)
10. Furutani, S., Hagihara, Y., Nagai, H. (2017). On-site identification of meat species in processed foods by a quick real-time polymerase chain reaction system. Meat Science, 131, 56–59. https://doi.org/10.1016/j.meatsci.2017.04.009
11. Danthanarayana, A. N., Finley, E., Vu, B., Kourentzi, K., Willson, R. C., Brgoch, J. (2020). A multicolor multiplex lateral flow assay for high-sensitivity analyte detection using persistent luminescent nanophosphors. Analytical Methods, 12(3), 272–280. https://doi.org/10.1039/C9AY02247C
12. Zvereva, E. A., Kovalev, L. I., Ivanov, A. V., Kovaleva, M. A., Zherdev, A. V., Shishkin, S. S. et al. (2015). Enzyme immunoassay and proteomic characterization of troponin I as a marker of mammalian muscle compounds in raw meat and some meat products. Meat Science, 105, 46–52. https://doi.org/10.1016/j.meatsci.2015.03.001
13. Fornal, E., Montowska, M. (2019). Species-specific peptide-based liquid chromatography–mass spectrometry monitoring of three poultry species in processed meat products. Food Chemistry, 283, 489–498. https://doi.org/10.1016/j.foodchem.2019.01.074
14. Montowska, M., Pospiech, E. (2013). Species-specific expression of various proteins in meat tissue: Proteomic analysis of raw and cooked meat and meat products made from beef, pork and selected poultry species. Food Chemistry, 136(3–4), 1461– 1469. https://doi.org/10.1016/j.foodchem.2012.09.072
15. Nalazek-Rudnicka, K., Kłosowska-Chomiczewska, I. E., Brockmeyer, J., Wasik, A., Macierzanka, A. (2022). Relative quantification of pork and beef in meat products using global and species-specific peptide markers for the authentication of meat composition. Food Chemistry, 389, Article 133066. https://doi.org/10.1016/j.foodchem.2022.133066
16. Vanegas, D. C., Gomes, C. L., Cavallaro, N. D., Giraldo-Escobar, D., McLamore, E. S. (2017). Emerging biorecognition and transduction schemes for quick detection of pathogenic bacteria in food. Comprehensive Reviews in Food Science and Food Safety, 16(6), 1188–1205. https://doi.org/10.1111/1541-4337.12294
17. Zubik, A. N., Rudnitskaya, G.E., Evstrapov, A.A. (2021). Loopmediated isothermal amplification (lamp) technique in microdevice format (Review). Nauchnoe Priborostroenie, 31(1), 3–43. https://doi.org/10.18358/np-31–1-i343 (In Russian)
18. Feng, T., Li, S., Wang, S., Pan, J. (2018). Cross priming amplification with nucleic acid test strip analysis of mutton in meat mixtures. Food Chemistry, 245, 641–645. https://doi.org/10.1016/j.foodchem.2017.08.107
19. Cao, Y., Zheng, K., Jiang, J., Wu, J., Shi, F., Song, X. et al. (2018). A novel method to detect meat adulteration by recombinase polymerase amplification and SYBR green I. Food Chemistry, 266, 73–78. https://doi.org/10.1016/j.foodchem.2018.05.115
20. Liu, R., Wang, X., Wang, X., Shi, Y., Shi, C., Wang, W. et al. (2019). A simple isothermal nucleic acid amplification method for the effective on-site identification for adulteration of pork source in mutton. Food Control, 98, 297–302. https://doi.org/10.1016/j.foodcont.2018.11.040
21. Girish, P. S., Anjaneyulu, A. S. R., Viswas, K. N., Anand, M., Rajkumar, N., Shivakumar, B. M. et al. (2004). Sequence analysis of mitochondrial 12S rRNA gene can identify meat species. Meat Science, 66(3), 551–556. https://doi.org/10.1016/S0309-1740(03)00158-X
22. Park, J., Shin, J. H., Park, J.-K. (2016). Pressed paper-based dipstick for detection of foodborne pathogens with multistep reactions. Analytical Chemistry, 88(7), 3781–3788. https://doi.org/10.1021/acs.analchem.5b04743
23. Yew, C.-H. T., Azari, P., Choi, J. R., Li, F., Pingguan-Murphy, B. (2018). Electrospin-coating of nitrocellulose membrane enhances sensitivity in nucleic acid-based lateral flow assay. Analytica Chimica Acta, 1009, 81–88. https://doi.org/10.1016/j.aca.2018.01.016
24. Ahmad, A. L., Low, S. C., Shukor, S. R. A., Fernando, W. J. N., Ismail, A. (2010). Hindered diffusion in lateral flow nitrocellulose membrane: Experimental and modeling studies. Journal of Membrane Science, 357(1–2), 178–184. https://doi.org/10.1016/j.memsci.2010.04.018
25. Ding, Y., Hua, X., Chen, H., Liu, F., González-Sapien, G., Wang, M. (2018). Recombinant peptidomimetic-nano luciferase tracers for sensitive single-step immunodetection of small molecules. Analytical Chemistry, 90(3), 2230–2237. https://doi.org/10.1021/acs.analchem.7b04601
26. Jauset-Rubio, M., Svobodová, M., Mairal, T., McNeil, C., Keegan, N., El-Shahawi, M. S. et al. (2016). Aptamer lateral flow assays for ultrasensitive detection of β-conglutin combining recombinase polymerase amplification and tailed primers. Analytical Chemistry, 88(21), 10701–10709. https://doi.org/10.1021/acs.analchem.6b03256
27. Xu, Y., Wei, Y., Cheng, N., Huang, K., Wang, W., Zhang, L. et al. (2018). Nucleic acid biosensor synthesis of an all-in-one universal blocking linker recombinase polymerase amplification with a peptide nucleic acid-based lateral flow device for ultrasensitive detection of food pathogens. Analytical Chemistry, 90(1), 708– 715. https://doi.org/10.1021/acs.analchem.7b01912
28. Di Nardo, F., Alladio, E., Baggiani, C., Cavalera, S., Giovannoli, C., Spano, G. et al. (2019). Colour-encoded lateral flow immunoassay for the simultaneous detection of aflatoxin B1 and type-B fumonisins in a single Test line. Talanta, 192, 288–294. https://doi.org/10.1016/j.talanta.2018.09.037
29. Shen, H., Xie, K., Huang, L., Wang, L., Ye, J., Xiao, M. et al. (2019). A novel SERS‑based lateral flow assay for differential diagnosis of wild-type pseudorabies virus and gE-deleted vaccine. Sensors and Actuators B: Chemical, 282, 152–157. https://doi.org/10.1016/j.snb.2018.11.065
30. Lee, S. H., Hwang, J., Kim, K., Jeon, J., Lee, S., Ko, J. et al. (2019). Quantitative serodiagnosis of scrub typhus using surface-enhanced Raman scattering-based lateral flow assay platforms. Analytical Chemistry, 91(19), 12275–12282. https://doi.org/10.1021/acs.analchem.9b02363
31. Fu, X., Wen, J., Li, J., Lin, H., Liu, Y., Zhuang, X. et al. (2019). Highly sensitive detection of prostate cancer specific PCA3 mimic DNA using SERS‑based competitive lateral flow assay. Nanoscale, 11(33), 15530–15536. https://doi.org/10.1039/c9nr04864b
32. Wang, X., Choi, N., Cheng, Z., Ko, J., Chen, L., Choo, J. (2017). Simultaneous detection of dual nucleic acids using a SERS-based lateral flow assay biosensor. Analytical Chemistry, 89(2), 1163– 1169. https://doi.org/10.1021/acs.analchem.6b03536
33. Montowska, M., Pospiech, E. (2010). Authenticity determination of meat and meat products on the protein and DNA basis. Food Reviews International, 27(1), 84–100. https://doi.org/10.1080/87559129.2010.518297
34. Zhao, L., Wang, K., Yan, C., Xiao, J., Wu, H., Zhang, H. et al. (2020). A PCR‑based lateral flow assay for the detection of Turkey ingredient in food products. Food Control, 107, Article 106774. https://doi.org/10.1016/j.foodcont.2019.106774
35. Yin, R., Sun, Y., Wang, K., Feng, N., Zhang, H., Xiao, M. (2020). Development of a PCR‑based lateral flow strip assay for the simple, quick, and accurate detection of pork in meat and meat products. Food Chemistry, 318, Article 126541. https://doi.org/10.1016/j.foodchem.2020.126541
36. Sul, S., Kim, M.-J., Lee, J.-M., Kim, S.-Y., Kim, H.-Y. (2020). Development of a quick on-site method for the detection of chicken meat in processed ground meat products using a direct ultrafast PCR System. Journal of Food Protection, 83(6), 984–990. https://doi.org/10.4315/jfp-19–583
37. Yin, R., Sun, Y., Yu, S., Wang, Y., Zhang, M., Xu, Y. et al. (2016). A validated strip-based lateral flow assay for the confirmation of sheep-specific PCR products for the authentication of meat. Food Control, 60, 146–150. https://doi.org/10.1016/j.foodcont.2015.07.030
38. Qin, P., Qiao, D., Xu, J., Song, Q., Yao, L., Lu, J. et al. (2019). Quick visual sensing and quantitative identification of duck meat in adulterated beef with a lateral flow strip platform. Food Chemistry, 294, 224–230. https://doi.org/10.1016/j.foodchem.2019.05.030
39. Magiati, M., Myridaki, V. M., Christopoulos, T. K., Kalogianni, D. P. (2019). Lateral flow test for meat authentication with visual detection. Food Chemistry, 274, 803–807. https://doi.org/10.1016/j.foodchem.2018.09.063
40. Li, Y.-J., Fan, J.-Y. (2017). Quick visual identification of bovine meat by loop mediated isothermal amplification combined with immunochromatographic strip. BioChip Journal, 11(1), 8–13. https://doi.org/10.1007/s13206–016–1102-y
41. Shi, Y., Feng, Y., Xu, C., Xu, Z., Cheng, D., Lu, Y. (2017). Loopmediated isothermal amplification assays for the quick identification of duck-derived ingredients in adulterated meat. Food Analytical Methods, 10(7), 2325–2331. https://doi.org/10.1007/s12161–016–0767–0
42. Yayla, M. E. A., Karakaya, F., Akcael, E., Yucel, F. (2016). Development of a lateral flow immunoassay for the detection of pork components in raw meat. Journal of Biotechnology, 231, S50. https://doi.org/10.1016/j.jbiotec.2016.05.191
43. Kuswandi, B., Gani, A. A., Ahmad, M. (2017). Immuno strip test for detection of pork adulteration in cooked meatballs. Food Bioscience, 19, 1–6. https://doi.org/10.1016/j.fbio.2017.05.001
44. Masiri, J., Benoit, L., Thienes, C., Kainrath, C., Barrios-Lopez, B., Agapov, A. et al. (2017). A quick, semi-quantitative test for detection of raw and cooked horse meat residues. Food Control, 76, 102–107. https://doi.org/10.1016/j.foodcont.2017.01.015
45. Seddaoui, N., Amine, A. (2020). A sensitive colorimetric immunoassay based on poly(dopamine) modified magnetic nanoparticles for meat authentication. LWT — Food Science and Technology, 122, Article 109045. https://doi.org/10.1016/j.lwt.2020.109045
46. Wu, H., Qian, C., Wang, R., Wu, C., Wang, Z., Wang, L. et al. (2020). Identification of pork in raw meat or cooked meatballs within 20 min using quick PCR coupled with visual detection. Food Control, 109, Article 106905. https://doi.org/10.1016/j.foodcont.2019.106905
47. Skouridou, V., Tomaso, H., Rau, J., Bashammakh, A. S., El-Shahawi, M. S., Alyoubi, A. O. et al. (2019). Duplex PCR-ELONA for the detection of pork adulteration in meat products. Food Chemistry, 287, 354–362. https://doi.org/10.1016/j.foodchem.2019.02.095
48. Lee, S.-Y., Kim, M.-J., Hong, Y., Kim, H.-Y. (2016). Development of a quick on-site detection method for pork in processed meat products using real-time loop-mediated isothermal amplification. Food Control, 66, 53–61. https://doi.org/10.1016/j.foodcont.2016.01.041
49. Wang, J., Wan, Y., Chen, G., Liang, H., Ding, S., Shang, K. (2019). Colorimetric detection of horse meat based on loop-mediated isothermal amplification (LAMP). Food Analytical Methods, 12(11), 2535–2541. https://doi.org/10.1007/s12161–019–01590–9
50. Yan, C., Wang, X., Zhao, X., Wei, M., Shi, C., Ma, C. (2020). Development of a direct and visual isothermal method for meat adulteration detection in low resource settings. Food Chemistry, 319, Article 126542. https://doi.org/10.1016/j.foodchem.2020.126542
51. Wang, X., Yan, C., Wei, M., Shi, C., Niu, S., Ma, C. (2019). Onsite method for beef detection based on strand exchange amplification. Analytical Sciences, 35(3), 337–341. https://doi.org/10.2116/analsci.18P425
Рецензия
Для цитирования:
Kornienko V.Yu., Fomina T.А., Minaev M.Yu. Review of new technologies used for meat identification. Теория и практика переработки мяса. 2022;7(2):131-137. https://doi.org/10.21323/2414-438X-2022-7-2-131-137
For citation:
Kornienko V.Yu., Fomina T.A., Minaev M.Yu. Review of new technologies used for meat identification. Theory and practice of meat processing. 2022;7(2):131-137. https://doi.org/10.21323/2414-438X-2022-7-2-131-137