Application of Metabarcoding for Fish Species Identification

Abstract

The identification of raw materials in processed foods is a major issue in food safety management. Substitution of an expensive species by an inexpensive one (i.e., fraudulent labeling) is illegal and provides unfair profits to the manufacturer. Identification of species by their morphological characteristics is sufficient to identify fresh fish, but cannot easily be applied to processed foods (fish fillets, canned foods), which comprise a large proportion of the seafood consumed worldwide. Molecular technology has been widely used in recent years to overcome the limitations of morphology-based identification methods. Especially, DNA metabarcoding is a potentially useful method for quick assessing of the abundance of taxa in complex environments. Metabarcoding using next generation sequencing (NGS) provides a good representation of species diversity. Here, the advantages and limitations of using NGS for fish species identification from seafood products were evaluated. Two universal primer sets were designed based on the mitochondrial cytochrome c oxidase subunit I (COI) gene to amplify a barcode region of ~650 bp. Eleven seafood products were analyzed using the two primer sets in separate experiments; 56 and 32 fish species were identified. Similar amounts of the main species (e.g., Alaska Pollock and golden thread) were detected in most products by both primer sets. These new primer sets for metabarcdoing studies by NGS have shown that they can be used for species identification of processed seafood products. NGS yields accurate results, but it is not considered cost-effective for practical use. For that reason, the denaturing gradient gel electrophoresis (DGGE) fingerprinting technology has been applied to the metabarcoding analysis of seafood products. DGGE uses a reduction in electrophoretic mobility according to the denaturation characteristics of amplicons to facilitate in-gel separation. Therefore, various fish species in seafood products can be identified by DGGE fingerprinting. A universal primer set was designed based on the COI gene to amplify a 214 bp fragment, and the fish species in various seafood products were identified using DGGE fingerprinting. A total of 30 bands were identified, and 20 species were identified from 20 seafood products. A smaller number of fish species were identified in comparison with former NGS results, but the major species were almost the same. Therefore, DGGE fingerprinting is suitable for the detection of various raw materials at a reasonable cost in seafood products. Finally, a study was conducted a quantitative analysis of Alaska pollock, which is the most commonly used fish in processed seafood products. Droplet digital PCR (ddPCR) technology was used to determine the content of Alaska pollock. This technique enables the absolute quantification of the number of copies of a target DNA sequence in a sample. A universal primer set and specific probes were designed based on the mitochondrial 16S rRNA gene. This gene was chosen because it exhibits low intraspecific genetic variation; thus, false-negative results due to genetic variation can be avoided. The linear relationship between sample weight and DNA concentration for both Alaska pollock and cutlassfish was analyzed. In addition, a linear relationship was observed between the DNA copy numbers obtained by ddPCR technology. These results enabled us to devise a formula for determining the weight of Alaska pollock based on the DNA copy number, and the content of Alaska pollock in 15 seafood products was successfully measured.