Evaluation of Fish Species Detection in the Northwestern Pacific using eDNA Metabarcoding: A Mock Community Approach

Metabarcoding of environmental DNA (eDNA), a technique using high-throughput sequencing, has transformed biodiversity monitoring by identifying organisms from DNA fragments present in the environment. This method, particularly useful for aquatic ecosystems, allows for non-invasive species monitoring, helping to provide insight into ecosystem composition and taxonomic diversity. The objective of this study was to assess the efficacy of eDNA metabarcoding for fish species identification in a model community from the northeast Pacific Ocean using 12S ribosomal RNA (12S rRNA) marker.

Water samples were collected from the tank of the Primorsky Aquarium, which contains fish species from the Sea of Japan, Sea of Okhotsk, and Bering Sea. DNA was extracted using syringe filters and enriched with polymerase chain reaction (PCR) of mitochondrial 12S rRNA fragment, followed by sequencing on Illumina platform. The resulting reads were processed using the bayesian generalized uncertainty modeling (BEGUM) pipeline and their taxonomic diversity was assessed by basic local alignment search tool (BLAST) search. Using in silico PCR, we also assessed the possible association of detection failures of some species with the presence of primer-to-target sequence mismatches.

From a fish community of only 20 species in the tank, we identified 56 operational taxonomic units (OTUs) corresponding to 28 genera. Among these OTUs, 20 species were unambiguously classified by BLAST-based analysis, though only 9 of them corresponded to the species actually present in the tank. Significant problems included inconsistent reference data and marker biases that affected the accuracy of species identification. In addition to DNA contamination from feed, contamination from the water source may have introduced extraneous DNA into the samples. Also, using in silico PCR analysis with a small number of available reference sequences, we demonstrated a significantly higher number of primer mismatches for species that were not identified.

This study highlights the relative efficacy of eDNA metabarcoding for fish species identification, but also highlights the need to improve reference databases and minimise contamination, searching for references and primers to improve accuracy. Further research should focus on optimising marker selection and controlling methodological bias to ensure robust biodiversity estimates.