Development and validation of targeted environmental DNA (eDNA) metabarcoding for early detection of 69 invasive fishes and aquatic invertebrates

Invasive species are of concern due to their impacts on ecosystems and economies, but they pose significant control challenges. Environmental DNA (eDNA) is a powerful tool in the detection of aquatic organisms at low densities due to high detection sensitivity and relative ease of sample collection. Aquatic eDNA analyses have increased worldwide and are generally either applied to few target species (quantitative PCR), or for broad taxonomic applications (metabarcoding). Here, we describe the development and testing of a hybrid approach that utilized high-sensitivity PCR primer sets and high-throughput sequencing (HTS), referred to as targeted metabarcoding, to detect 69 fishes and invertebrates. We identified target species based on reports of globally important invasive species and developed two independent PCR primers for each species (CO1 and a second mtDNA region). We assessed sensitivity and eDNA interference for all 138 primers (2 per species and 69 species) using standard end-point PCR and tested them on 10 eDNA samples spiked with various amounts of one or more of the target species DNA. The sensitivity of the 138 primer sets ranged between 1.5 x 10(-5) and 2.64 ng template DNA (mean = 0.069 ng). Primers were also tested for interference effects using plankton eDNA to simulate field conditions. The inclusion of interfering plankton DNA reduced the sensitivity for most primer sets by one or more orders of magnitude (range 0-3). Overall, our targeted metabarcoding resulted in the detection of similar to 98% of species in the DNA spiked samples, and perhaps more importantly, the HTS read count was positively related to the quantity of spiked DNA (p < 0.002). We envision this technique being particularly useful for the early detection of species at low population densities; however, there are diverse applications of targeted metabarcoding for monitoring aquatic community composition and to quantify ecosystem change and health.