Research on food sources through DNA metabarcoding is being used for various organisms based on high resolution and reproducibility. In the study, we investigated the difference in food sources between pre and post-starving in the three bivalve species (Anemina acaeformis, Anodonta woodiana, and Unio douglasiae) through DNA metabarcoding using 18S rRNA V9 primer. The food source of pre-starving appeared in 87 genera, 71 families, 51 orders, 35 classes, and 22 phyla. The primary food sources were the zoo and phytoplankton, including Chlamydomonadales, Euglenales, Ploima, Sphaeropleales, and Stephanodiscales. However, all zoo and phytoplankton were not observed after starving except Schizopyrenida and Rotifera. In Levin’s niche breadth analysis, the Bi index of A. woodiana is 0.3, which was higher than A. acaeformis (0.14) and U. douglasiae (0.21), indicating that they feed on various food sources. The niche overlap of A. acaeformis was measured as 0.78 in A. woodiana, 0.7 in U. douglasiae showing a relative high value compared to other bivalves. The trophic level of A. acaeformis, A. woodiana, and U. douglasiae based on the food source information were investigated as 2.0, 2.0, and 2.5, respectively. The results of the previous study on the trophic level using stable isotopes showed 1.8 to 2.4 values were similar to the results of this study. These results suggest that DNA metabarcoding can be an effective analyzing tool for the gut content in the bivalves.

Gut contents analysis is essential to predict the impact of organisms on food source changes due to variations of the habitat environment. Previous studies of gut content analysis have been conducted using traditional methods, such as visual observation. However, these studies are limited in analyzing food sources because of the digestive process in gut organ. DNA metabarcoding analysis is a useful method to analyze food sources by supplementing these limitations. We sampled marine fish of Pennahia argentata, Larimichthys polyactis, Crangon affinis, Loligo beka and Sepia officinalis from Gwangyang Bay and Yeosu fisheries market for analyzing gut contents by applying DNA metabarcoding analysis. 18S rRNA v9 primer was used for analyzing food source by DNA metabarcoding. Network and two-way clustering analyses characterized the relationship between organisms and food sources. As a result of comparing metabarcoding of gut contents for P. argentata between sampled from Gwangyang Bay and the fisheries market, fish and Copepoda were analyzed as common food sources. In addition, Decapoda and Copepoda were analyzed as common food sources for L. polyactis and C. affinis, respectively. Copepoda was analyzed as the primary food source for L. beka and S. officinalis. These study results demonstrated that gut contents analysis using DNA metabarcoding reflects diverse and detailed information of biological food sources in the aquatic environment. In addition, it will be possible to provide biological information in the gut to identify key food sources by applying it to the research on the food web in the ecosystem.

메타바코딩을 이용한 환경 DNA 분석은 검출 감도가 높아 어류의 생물다양성 평가 및 멸종위기종의 검출에 유용 한 기술이다. 이번 연구는 메타바코딩을 이용해 우리나라 담수어류를 대상으로 높은 검출 효율을 보일 수 있는 적합 한 분석방법을 확인하기 위해 4가지 분석조건별, 즉 필터 (cellulose nitrate filter, glass fiber filter), 추출 키트 (DNeasy® Blood & Tissue Kit, DNeasy® PowerWater Kit), 프라이머 조합 (12S rDNA, 16S rDNA) 그리고 PCR 방법 (conventional PCR, touchdown PCR)로 나타나는 Operational Taxonomic Units (OTUs) 수와 종 조성을 비교하였다. Glass fiber filter와 DNeasy® Tissue & Blood Kit를 이용해 추출한 시료는 12S rDNA와 16S rDNA 프라이머 조합에서 담수어류 OTUs가 가장 많이 검출되었다. 모든 분석조건 중 프라이머 조합에서만 조기어강 (Class Actinopterygii) 평균 OTUs 수에서 통계적으로 유의한 차이를 보였고 (Non-parametric Wilcoxon Signed Ranks Test, p=0.005), 담수어류 평균 OTUs 수는 유의하지 않았다. 종 조성 비교 결과 역시 프라이머 조합에서 유의한 차이를 보였고 (PERMANOVA, Pseudo-F=6.9489, p=0.006), 나머지 분석조건에서는 유의한 차이를 보이지 않았다. NMDS 분석 결과 종 조성은 유사도 65% 기준에서 프라이머 조합에 따라 묶였고, 16S rDNA 프라이머 세트는 주로 멸종위기종인 모래주사 (Microphysogobio koreensis), 꼬치동자개 (Pseudogobio brevicorpus)가 기여하였고, 12S rDNA 프라이머 세트는 주로 일반종인 피라미 (Zacco platypus), 꺽지 (Coreoperca herzi) 등이 기여한 것으로 나타났다. 본 연구는 국내 하천에서 채취한 시료에 대한 메타바코딩을 이용한 종 다양성 분석의 기초정보를 제공한다.