From qualitative to quantitative insect metabarcoding: an in tandem multilocus mosquito identification methodology

Abstract

AbstractIn the era of emergence and re-emergence of vector-borne diseases, a high throughput trap-based insect monitoring is essential for the identification of invasive species, study of mosquito populations and risk assessment of disease outbreaks. Insect DNA metabarcoding technology has emerged as a highly promising methodology for unbiased and large-scale surveillance. Despite significant attempts to introduce DNA metabarcoding in mosquito or other insect surveillance qualitative and quantitative metabarcoding remains a challenge. In the present study, we have developed a methodology of in-tandem identification and quantification using cytochrome oxidase subunit I (COI) combined with a secondary multilocus identification and quantification involving three loci of 28S ribosomal DNA. The presented methodology was able to identify individual species in pools of mosquitoes with 95.94% accuracy and resolve with high accuracy (p = 1, χ2 = 2.55) mosquito population composition providing a technology capable of revolutionizing mosquito surveillance through metabarcoding. The methodology, given the respective dataset, has the potential to be applied to various small animal populations.