Prediction of species composition ratios in pooled specimens of the Anopheles Hyrcanus group using quantitative sequencing.

Background: Plasmodium vivax is transmitted by members of the Anopheles Hyrcanus Group that includes six species in the Republic of Korea: Anopheles sinensis sensu stricto (s.s.), Anopheles pullus, Anopheles kleini, Anopheles belenrae, Anopheles lesteri, and Anopheles sineroides. Individual Anopheles species within the Hyrcanus Group demonstrate differences in their geographical distributions, vector competence and insecticide resistance, making it crucial for accurate species identification. Conventional species identification conducted using individual genotyping (or barcoding) based on species-specific molecular markers requires extensive time commitment and financial resources.

Results: A population-based quantitative sequencing (QS) protocol developed in this study provided a rapid estimate of species composition ratios among pooled mosquitoes as a cost-effective alternative to individual genotyping. This can be accomplished by using species- or group-specific nucleotide sequences of the mitochondrial cytochrome C oxidase subunit I (COI) and the ribosomal RNA internal transcribed spacer 2 (ITS2) region as species identification alleles in a two-step prediction protocol. Standard genomic DNA fragments of COI and ITS2 genes were amplified from each Anopheles species using group-specific universal primer sets. Following sequencing of the COI or ITS2 amplicons generated from sets of standard DNA mixtures, equations were generated via linear regression to predict species-specific nucleotide sequence frequencies at different positions. Species composition ratios between An. sineroides, An. pullus and An. lesteri were estimated from QS of the COI amplicons based on the mC.260A, mC.122C and mC.525C alleles at the first step, followed by the prediction of species composition ratios between An. sinensis, An. kleini and An. belenrae based on QS of the ITS2 amplicons using the rI.370G and rI.389T alleles. The COI copy number was not significantly different between species, suggesting the reliability of COI-based prediction. In contrast, ITS2 showed a slightly but significantly higher copy number in An. belenrae, requiring an adjustment of its predicted composition ratio. A blind test proved that predicted species composition ratios either from pooled DNA specimens or pooled mosquito specimens were not statistically different from the actual values, demonstrating that the QS-based prediction is accurate and reliable.

Conclusions: This two-step prediction protocol will facilitate rapid estimation of the species composition ratios in field-collected Anopheles Hyrcanus Group populations and is particularly useful for studying the vector ecology of Anopheles population and epidemiology of malaria.