Development and validation of a multi-locus DNA metabarcoding method to identify endangered species in complex samples

Arulandhu, Alfred J.; Staats, Martijn; Hagelaar, Rico; Voorhuijzen, Marleen M.; Prins, Theo W.; Scholtens, Ingrid; Costessi, Adalberto; Duijsings, Danny; Rechenmann, François; Gaspar, Frédéric B.; Barreto Crespo, Maria Teresa; Holst-Jensen, Arne; Birck, Matthew; Burns, Malcolm; Haynes, Edward; Hochegger, Rupert; Klingl, Alexander; Lundberg, Lisa; Natale, Chiara; Niekamp, Hauke; Perri, Elena; Barbante, Alessandra; Rosec, Jean Philippe; Seyfarth, Ralf; Sovova, Tereza; Moorleghem, Christoff Van; Ruth, Saskia van; Peelen, Tamara; Kok, Esther


DNA metabarcoding provides great potential for species identification in complex samples such as food supplements and traditional medicines. Such a method would aid Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) enforcement officers to combat wildlife crime by preventing illegal trade of endangered plant and animal species. The objective of this research was to develop a multi-locus DNA metabarcoding method for forensic wildlife species identification and to evaluate the applicability and reproducibility of this approach across different laboratories. A DNA metabarcoding method was developed that makes use of 12 DNA barcode markers that have demonstrated universal applicability across a wide range of plant and animal taxa and that facilitate the identification of species in samples containing degraded DNA. The DNA metabarcoding method was developed based on Illumina MiSeq amplicon sequencing of well-defined experimental mixtures, for which a bioinformatics pipeline with user-friendly web-interface was developed. The performance of the DNA metabarcoding method was assessed in an international validation trial by 16 laboratories, in which the method was found to be highly reproducible and sensitive enough to identify species present in a mixture at 1% dry weight content. The advanced multi-locus DNA metabarcoding method assessed in this study provides reliable and detailed data on the composition of complex food products, including information on the presence of CITES-listed species. The method can provide improved resolution for species identification, while verifying species with multiple DNA barcodes contributes to an enhanced quality assurance.