Water eDNA metabarcoding is effective in detecting non-native species in marinas, but detection errors still hinder its use for passive monitoring

Abstract

Marinas are high-priority targets for marine non-indigenous species (NIS), where they compose a large portion of the biofouling communities. The practicality of water samples collection makes environmental DNA (eDNA) metabarcoding an interesting tool for routine NIS surveys. Here the effectiveness of water-eDNA-metabarcoding to identify biofouling NIS, in 10 marinas from western France, was examined. Morphological identification of specimens collected in quadrats brought out 18 sessile benthic NIS beneath floating pontoons. Water-eDNA-metabarcoding detected two thirds of them, failing to detect important NIS. However, sampling and bioinformatics filtering steps can be optimized to identify more species. In addition, this method allowed the detection of additional NIS from neighboring micro-habitats. Caution should, however, be taken when reporting putative novel NIS, because of errors in species assignment. This work highlights that water-eDNA-metabarcoding is effective for active (targeted) NIS surveys and could be significantly improved for its further use in marine NIS passive surveys.

Keywords:

• Biological invasions
• environmental DNA
• metabarcoding
• morphology
• ports
• quadrats

Acknowledgements

The authors thank the Diving and Marine core service from the Roscoff Biological Station, particularly Yann Fontana, Wilfried Thomas and Mathieu Camusat for the quadrat sampling, and Jérôme Coudret and Stéphane Loisel for their help for the field work. We thank Gwenn Tanguy from the Biogenouest Genomer Platform for advice and access to the sequencing facilities, and the Biogenouest ABIMS Platform for access to the calculation and storage resources.

Disclosure statement

The authors report that there are no competing interests to declare.

Data availability statement

Raw sequences were deposited on NCBI SRA: BioProject PRJNA744352. The metabarcoding and analyses scripts used in this study are available at https://github.com/joarwrie/benthic_NIS_detection

Funding

This project was supported by the TOTAL Foundation (project AquaNIS2.0). MC acknowledges a PhD grant by Région Bretagne (ENIGME ARED project) and Sorbonne Université (ED 227 ‘Sciences de la Nature et de l’Homme’).