Mosquito Identification From Bulk Samples Using DNA Metabarcoding: a Protocol to Support Mosquito-Borne Disease Surveillance in Canada

Abstract

Approximately 80 species of mosquitoes (Diptera: Culicidae) have been documented in Canada. Exotic species such as Aedes albopictus (Skuse) (Diptera: Culicidae) are becoming established. Recently occurring endemic mosquito-borne diseases (MBD) in Canada including West-Nile virus (WNV) and Eastern Equine Encephalitis (EEE) are having significant public health impacts. Here we explore the use of DNA metabarcoding to identify mosquitoes from CDC light-trap collections from two locations in eastern Canada. Two primer pairs (BF2-BR2 and F230) were used to amplify regions of the cytochrome c oxidase subunit I (CO1) gene. High throughput sequencing was conducted using an Illumina MiSeq platform and GenBank-based species identification was applied using a QIIME 1.9 bioinformatics pipeline. From a site in southeastern Ontario, Canada, 26 CDC light trap collections of 72 to >300 individual mosquitoes were used to explore the capacity of DNA metabarcoding to identify and quantify captured mosquitoes. The DNA metabarcoding method identified 33 species overall while 24 species were identified by key. Using replicates from each trap, the dried biomass needed to identify the majority of species was determined to be 76 mg (equivalent to approximately 72 mosquitoes), and at least two replicates from the dried biomass would be needed to reliably detect the majority of species in collections of 144-215 mosquitoes and three replicates would be advised for collections with >215 mosquitoes. This study supports the use of DNA metabarcoding as a mosquito surveillance tool in Canada which can help identify the emergence of new mosquito-borne disease potential threats.

Keywords: DNA metabarcoding; biodiversity; mosquito; taxonomy; vector-borne disease.