Sapkota, R., Winding, A., Stæhr, P.A.U., Andersen, N.R., Buur, H., Hablutzel, P. 2023. Use of metabarcoding to detect non-indigenous species in Danish harbours: Methods comparison. Aarhus University, DCE – Danish Centre for Environment and Energy, 30 pp. Technical Report No. 267
https://dce2.au.dk/pub/TR267.pdf
This report provides a comparison of three different approaches to detect non-indigenous species (NIS) in the marine environment: conventional monitoring, and two environmental DNA (eDNA) molecular based methods: qPCR species specific detection systems and metabarcoding with three different primer sets analyzed using two different bioinformatics pipelines. Conventional NIS detection is time consuming and not efficient for early and rapid detection of NIS. eDNA based detection is proposed as an alternative, as eDNA are less invasive, are supposed to cover a larger area and potentially with a high level of detection. In 2021 NIS was monitored in six Danish harbors by conventional methods and NIS specific qPCR detection systems. During this monitoring eDNA was collected from water samples and settlement plates at three stations in each of the six harbors. In the present project, this eDNA was used for metabarcoding using three different primer sets: 18S rDNA, COI and 12S rDNA, targeting eukaryotes, invertebrates, and fish, respectively. The results show the highest number of NIS detected by metabarcoding and the lowest number by qPCR. The overlap between species detected was limited: only three NIS were found by all three methodological approaches, while metabarcoding found several species not detected with either qPCR or conventional sampling. Both eDNA methods detected fish and planktonic species, which was not possible with the conventional methods used. The metabarcoding data was analyzed using two different bioinformatics pipelines. Interestingly, more NIS (40 species) were detected by metabarcoding using the VLIZ pipeline compared to the DCE pipeline (30 species) using the Danish NIS gross list as reference. However, the VLIZ pipeline recorded NIS in much fewer samples, while the DCE pipeline as well as qPCR detected NIS at several sampling stations. Metabarcoding (DCE pipeline) detected ca 1/3 of NIS in all six harbors. A direct comparison between qPCR and metabarcoding (DCE-pipeline) showed that the level of agreement in NIS detection increased with the number of samples compared. Using a newly published European gross NIS list as reference, indicated that seven new NIS for Danish waters were detected by metabarcoding. Although metabarcoding currently appears less sensitive than qPCR for NIS detection, metabarcoding has several advantages which should be considered when implementing a monitoring strategy. Metabarcoding is the only method which enables detection of both sessile, mobile and planktonic species, it is comparatively cheaper, and it provides a fast approach to detect NIS new to a region. However, the bioinformatics pipelines should be standardized and optimized along with the reference databases of the marine species in Danish and regional waters.
