Abstract

AbstractEnvironmental DNA (eDNA) metabarcoding has shown great promise as an effective, non‐invasive monitoring method for marine biomes. However, long filtration times and the need for state‐of‐the‐art laboratories are restricting sample replication and in situ species detections. Methodological innovations, such as passive filtration and self‐contained DNA extraction protocols, have the potential to alleviate these issues. We explored the implementation of passive sampling and a self‐contained DNA extraction protocol by comparing fish diversity obtained from active filtration (1 L; 0.45 μm cellulose nitrate [CN] filters) to five passive substrates, including 0.45 μm CN filters, 5 μm nylon filters, 0.45 μm positively charged nylon filters, artificial sponges, and fishing net. Fish diversity was then compared between the PDQeX Nucleic Acid Extractor and the conventional Qiagen DNeasy Blood & Tissue protocol. Experiments were conducted in both a controlled mesocosm and in situ at the Portobello Marine Laboratory, New Zealand. No significant differences in fish diversity were observed among active filtration and more porous passive materials (artificial sponges and fishing net) for both the mesocosm and harbor waters. For the in situ comparison, all passive filter membranes detected a significantly lower number of fish species, resulting from partial sample drop‐out. While no significant differences in fish eDNA signal diversity were observed between either DNA extraction methods in the mesocosm, the PDQeX system was less effective at detecting fish for the in situ comparison. Our results demonstrate that a passive sampling approach using porous substrates can be effectively implemented to capture eDNA from seawater, eliminating vacuum filtration processing. The large variation in efficiency observed among the five substrate types, however, warrants further optimization of the passive sampling approach for routine eDNA applications. The PDQeX system can extract high‐abundance DNA in a mesocosm with further optimization to detect low‐abundance eDNA from the marine environment.

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