Optimization of environmental DNA-based methods: a case study for detecting brook trout (Salvelinus fontinalis)

The utility of eDNA for fish species and community monitoring is well-established using targeted amplification (i.e., qPCR and ddPCR) and sequencing approaches (i.e., metabarcoding). However, the lack of optimized and standardized methods across the eDNA workflow reduces the sensitivity of eDNA surveys and precludes the reliable comparison of findings across studies, respectively. DNA extraction is a prime target for optimization efforts because the extraction method is highly variable across eDNA studies despite being one of the most influential factors in detection efficiency across the entire post-collection workflow. Sequence analysis is arguably the least standardized step in the workflow, with new bioinformatics pipelines frequently emerging in the literature and being implemented with innumerable unique combinations of parameter values. The current study aimed to support the optimization and standardization of eDNA methods for fish detection by assessing two commercial DNA extraction kits. The kits, manufactured by Qiagen and Macherey-Nagel, were evaluated based on cost, time, and performance specifications and the success of brook trout detection by metabarcoding across three bioinformatics pipelines, qPCR, and ddPCR. Our protocols were effective in detecting brook trout in all 20 samples analyzed. Brook trout eDNA was detected by ddPCR in nine (90%) Qiagen extracts but only seven (70%) Macherey-Nagel extracts. The concentration of target DNA determined by ddPCR was significantly greater in Qiagen extracts. In comparison, detection success was equal across the two extraction kits using qPCR (70%) and metabarcoding (100% across all three bioinformatics pipelines). The concentration of target DNA determined by qPCR was not significantly different between Qiagen extracts and Macherey-Nagel extracts; however, the number of target DNA reads determined by metabarcoding was significantly greater in Qiagen extracts using MetaWorks, but no significant difference was found using the MiFish Pipeline. Under our experimental conditions, the Qiagen kit was selected as the preferred kit; while slightly more time-intensive, performance was equal or superior across all analysis methods at a substantially lower cost than the Macherey-Nagel kit. We present this method optimization as a case study which can be applied as a framework for eDNA practitioners to facilitate the evaluation of novel eDNA extraction kits as they become available, against established methods in the field.