eDNA in a bottleneck: obstacles to fish metabarcoding studies in megadiverse freshwater systems

ABSTRACT The current capacity of environmental DNA (eDNA) to provide accurate insights into the biodiversity of megadiverse regions (e.g., the Neotropics) requires further evaluation to ensure its reliability for long-term monitoring. In this study, we first evaluated the taxonomic resolution capabilities of a short fragment from the 12S rRNA gene widely used in fish eDNA metabarcoding studies, and then compared eDNA metabarcoding data from water samples with traditional sampling using nets. For the taxonomic discriminatory power analysis, we used a specifically curated reference dataset consisting of 373 sequences from 264 neotropical fish species (including 47 newly generated sequences) to perform a genetic distance-based analysis of the amplicons targeted by the MiFish primer set. We obtained an optimum delimitation threshold value of 0.5% due to lowest cumulative errors. The barcoding gap analysis revealed only a 50.38% success rate in species recovery (133/264), highlighting a poor taxonomic resolution from the targeted amplicon. To evaluate the empirical performance of this amplicon for biomonitoring, we assessed fish biodiversity using eDNA metabarcoding from water samples collected from the Amazon (Adolpho Ducke Forest Reserve and two additional locations outside the Reserve). From a total of 84 identified Molecular Operational Taxonomic Units (MOTUs), only four could be assigned to species level using a fixed threshold. Measures of α-diversity analyses within the Reserve showed similar patterns in each site between the number of MOTUs (eDNA dataset) and species (netting data) found. However, β-diversity revealed contrasting patterns between the methods. We therefore suggest that a new approach is needed, underpinned by sound taxonomic knowledge, and a more thorough evaluation of better molecular identification procedures such as multi-marker metabarcoding approaches and tailor-made (i.e., order-specific) taxonomic delimitation thresholds.