Ichthyoplankton metabarcoding: an efficient tool for early detection of invasive species establishment

Detection of invasive species is critical for management but is often limited by challenges associated with capture, processing, and identification of early life stages. DNA metabarcoding facilitates large-scale monitoring projects to detect establishment early. Here, we test the use of DNA metabarcoding to monitor invasive species by sequencing over 5000 fishes in bulk ichthyoplankton samples (larvae and eggs) from four rivers of ecological and cultural importance in southern Canada. We were successful in detecting species known from each river, and three invasive species in two of the four rivers. This includes the first detection of early life-stage rudd in the Credit River. We evaluated whether sampling gear affected detection of invasive species and estimates of species richness and found that light traps outperform bongo nets in both cases. We also found that the primers used for amplification of target sequences and the number of sequencing reads generated per sample, affect the consistency of species detections. However, these factors have less impact on detections and species richness estimates than the number of samples collected and analyzed.  Our analyses also show that incomplete reference databases can result in incorrectly attributing DNA sequences to invasive species. Overall, we conclude that DNA metabarcoding is an efficient tool for monitoring the early establishment of invasive species by detecting evidence of reproduction, but requires careful consideration of sampling design and the primers used to amplify, sequence, and classify the diversity of native and potential invasive species. 

Methods
DNA extracted from homogenized bulk ichthyoplankton samples using salt extraction protocol, 1st PCR amplification using MiFish 12S or modified PS1 Teleost Primers with heterogeneity spacers and Nextera adaptor sequences, 2nd PCR using combinatorial Nextera i5/i7 indices, purified using Ampure XP magnetic beads and quantification via QuBit broad range kit, Illumina MiSeq using the V2 (150bp x 2). 

Sequencing data were processed using the Qiime2 software package, utilizing the following algorithms (cudadapt / DADA2 / Vsearch). Processed sequencing data were analyzed using custom scripts in R and software packages VEGAN, MUSCLE, APE, and DECIPHER. Plots were generated using ggplot2.