Metabarcoding of freshwater invertebrates to detect the effects of a pesticide spill
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Accepted version
Author(s)
Type
Journal Article
Abstract
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.
Date Issued
2017-12-29
Date Acceptance
2017-10-16
Citation
Molecular Ecology, 2017, 27 (1), pp.146-166
ISSN
0962-1083
Publisher
Wiley
Start Page
146
End Page
166
Journal / Book Title
Molecular Ecology
Volume
27
Issue
1
Copyright Statement
© 2017 John Wiley & Sons Ltd. This is the peer reviewed version of the article, which has been published in final form at https://dx.doi.org/10.1111/mec.14410
Sponsor
Natural Environment Research Council (NERC)
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000424111400011&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Grant Number
NE/L008491/1
Subjects
Science & Technology
Life Sciences & Biomedicine
Biochemistry & Molecular Biology
Ecology
Evolutionary Biology
Environmental Sciences & Ecology
biomonitoring
community ecology
DNA barcoding
freshwater ecosystems
invertebrates
BAETIS-RHODANI EPHEMEROPTERA
16S RIBOSOMAL-RNA
TAXONOMIC RESOLUTION
BIODIVERSITY ASSESSMENT
SPECIES DELIMITATION
CRYPTIC DIVERSITY
BETA DIVERSITY
SEQUENCE DATA
DNA
BARCODE
Publication Status
Published