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Identification of fish species using the next generation sequencing (NGS) technology

https://doi.org/10.21323/2618-9771-2022-5-2-80-93

Abstract

The laws relating to fish and fishery product labeling that require indication of the information about fish species exist in many world countries. These rules are conditioned by a significant growth in the number of the economic fraud cases in the field of production and trade of fishery products. The widespread ways of fraud are replacement and mislabeling of a product as confirmed by many studies. Analysis of scientific works shows that mislabeling in fishery product manufacture occurs in 30–70% of cases in different countries. The existing legislation about food traceability is insufficient for their prevention, which suggests a necessity of taking strict control measures ensuring effective species identification of fish and fishery products. At present, various laboratory tests are used for their species identification. They are based, mainly, on analysis of unique DNA profiles found in different species. In this work, we present the method for detection of fish species using next generation sequencing (NGS). NGS is an advanced technology in the field of quality control of fishery products, especially for fish species identification in multicomponent products, which contain DNA fragments of other species besides the target DNA. NGS was carried out on the platform Ion Torrent Ion GeneStudio S5 System. Twenty samples were analyzed: 17 commercial samples and three prepared experimental samples consisted of the mixture of two and more species. The universal primers, which were able to amplify the fragment 16S rRNA of the commercial fish species, were selected and prepared. In general, DNA of 11 families, 15 genera and 16 species was identified in the course of the analysis. The obtained result of NGS of 17 commercial samples confirmed the results of identification by other molecular diagnostic methods. Mislabeling was revealed in four samples. In three samples, all fish species present in the composition were identified. Possible reasons for fish replacement were assessed.

About the Authors

T. A. Fomina
V. M. Gorbatov Federal Research Center for Food Systems; National Centre for Safety of Aquatic Fisheries Products and Aquaculture
Russian Federation

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., 109316, Moscow; 14–1, Grafskiy per., 129626, Moscow



M. G. Kuleshova
V. M. Gorbatov Federal Research Center for Food Systems; National Centre for Safety of Aquatic Fisheries Products and Aquaculture
Russian Federation

Mariya G.  Kuleshova, Graduate Student, Laboratory of Molecular Biology and Bioinformatics, V. M. Gorbatov Federal Research Center for Food Systems; Molecular Biologist, Department of Molecular Diagnostic Research at the Testing Reference Laboratory, National Centre for Safety of Aquatic Fisheries Products and Aquaculture


26, Talalikhina str., 109316, Moscow; 14–1, Grafskiy per., 129626, Moscow



M. Yu. Minaev
V. M. Gorbatov Federal Research Center for Food Systems
Russian Federation

Mikhail Yu. Minaev, Candidate of Technical Sciences, Head of Laboratory of Molecular Biology and Bioinformatics, V. M. Gorbatov Federal Research

Center for Food Systems 26, Talalikhina str., 109316, Moscow



E. A. Konorov
V. M. Gorbatov Federal Research Center for Food Systems
Russian Federation

Evgeniy А. Konorov, Candidate of Technical Sciences, Senior Research Scientist, Laboratory of Molecular Biology and Bioinformatics, V. M. Gorbatov Federal Research Center for Food Systems

26, Talalikhina str., 109316, Moscow



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For citations:


Fomina T.A., Kuleshova M.G., Minaev M.Yu., Konorov E.A. Identification of fish species using the next generation sequencing (NGS) technology. Food systems. 2022;5(2):80-93. (In Russ.) https://doi.org/10.21323/2618-9771-2022-5-2-80-93

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ISSN 2618-9771 (Print)
ISSN 2618-7272 (Online)