Metabarcoding of freshwater invertebrates to detect the effects of a pesticide spill

Biomonitoring underpins the environmental assessment of freshwater ecosystems and guides management and conservation. Current methodology for surveys of (macro)invertebrates uses coarse taxonomic identification where species-level resolution is difficult to obtain. Next-generation sequencing of entire assemblages (metabarcoding) provides a new approach for species detection, but requires further validation. We used metabarcoding of invertebrate assemblages with two fragments of the cox1 “barcode” and partial nuclear ribosomal (SSU) genes, to assess the effects of a pesticide spill in the River Kennet (southern England). Operational taxonomic unit (OTU) recovery was tested under 72 parameters (read denoising, filtering, pair merging and clustering). Similar taxonomic profiles were obtained under a broad range of parameters. The SSU marker recovered Platyhelminthes and Nematoda, missed by cox1, while Rotifera were only amplified with cox1. A reference set was created from all available barcode entries for Arthropoda in the BOLD database and clustered into OTUs. The River Kennet metabarcoding produced matches to 207 of these reference OTUs, five times the number of species recognized with morphological monitoring. The increase was due to the following: greater taxonomic resolution (e.g., splitting a single morphotaxon “Chironomidae” into 55 named OTUs); splitting of Linnaean binomials into multiple molecular OTUs; and the use of a filtration-flotation protocol for extraction of minute specimens (meiofauna). Community analyses revealed strong differences between “impacted” vs. “control” samples, detectable with each gene marker, for each major taxonomic group, and for meio- and macrofaunal samples separately. Thus, highly resolved taxonomic data can be extracted at a fraction of the time and cost of traditional nonmolecular methods, opening new avenues for freshwater invertebrate biodiversity monitoring and molecular ecology.This study was funded by NERC grant NE/M021955 to DYW, APV and KB.Peer Reviewe