Scanning amplicons with CRISPR-Dx detects endangered amphibians in environmental DNA

Abstract

More efficient methods for extensive biodiversity monitoring are required to support rapid measures to address the biodiversity crisis. While environmental DNA (eDNA) metabarcoding and quantitative PCR (qPCR) methods offer advantages over traditional monitoring approaches, their large-scale application is limited by the time and labour required for developing assays and/or for analysis. CRISPR (clustered regularly interspaced short palindromic repeats) diagnostic technologies (Dx) may overcome some of these limitations, but they have been used solely with species-specific primers, restricting their versatility for biodiversity monitoring. Here, we demonstrate the feasibility of designing species-specific CRISPR-Dx assays in silico within a short metabarcoding fragment using a general primer set, a methodology we term 'ampliscanning', for 18 of the 22 amphibian species in Switzerland. We sub-selected nine species, including three classified as regionally endangered, to test the methodology using eDNA sampled from ponds at nine sites. We compared the ampliscanning detections to data from traditional monitoring at these sites. Ampliscanning was successful at detecting target species with different prevalences across the landscape. With only one visit, we detected more species per site than three traditional monitoring visits (visual and acoustic detections by trained experts), in particular more elusive species and previously undocumented but expected populations. Ampliscanning detected 25 species/site combinations compared to 12 with traditional monitoring. Sensitivity analyses showed that larger numbers of field visits and PCR replicates are more important for reliable detection than many technical replicates at the CRISPR-Dx assay level. Given the reduced sampling and analysis effort, our results highlight the benefits of eDNA and CRISPR-Dx combined with universal primers for large-scale monitoring of multiple endangered species across landscapes to inform conservation measures.