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

Area of Science:

• Entomology and Molecular Ecology
• Public Health and Vector Surveillance

Background:

• Canada faces increasing public health risks from endemic mosquito-borne diseases (MBD) like West Nile Virus (WNV) and Eastern Equine Encephalitis (EEE).
• The establishment of exotic mosquito species, such as Aedes albopictus, exacerbates these risks.
• Traditional mosquito identification methods can be time-consuming and may not capture the full diversity of species present.

Purpose of the Study:

• To evaluate the efficacy of DNA metabarcoding as a tool for identifying and quantifying mosquito species from light-trap collections in Canada.
• To determine the optimal biomass and number of replicates required for reliable species detection using DNA metabarcoding.
• To assess the potential of DNA metabarcoding for early detection of emerging mosquito-borne disease threats.

Main Methods:

• Mosquitoes were collected using CDC light traps from two sites in eastern Canada.
• DNA metabarcoding was performed by amplifying the cytochrome c oxidase subunit I (CO1) gene using two primer pairs (BF2-BR2 and F230).
• High-throughput sequencing on an Illumina MiSeq platform and subsequent species identification using a QIIME 1.9 bioinformatics pipeline against GenBank were employed.

Main Results:

• The DNA metabarcoding approach identified 33 mosquito species, compared to 24 identified by traditional key identification from the same collections.
• A dried biomass of 76 mg (approximately 72 mosquitoes) was found to be sufficient for identifying the majority of species.
• Reliable detection of most species in collections of 144-215 mosquitoes required at least two replicates, while collections >215 mosquitoes benefited from three replicates.

Conclusions:

• DNA metabarcoding is a powerful and accurate tool for comprehensive mosquito surveillance in Canada.
• This method can effectively identify both native and exotic mosquito species, including those of public health concern.
• The findings support the integration of DNA metabarcoding into routine surveillance programs to monitor and mitigate risks associated with mosquito-borne diseases.