Harnessing eDNA metabarcoding for mosquito surveillance: a pilot study in Ethiopia's Great Rift Valley

Vector-borne diseases account for over 17% of all infectious diseases worldwide, with malaria and mosquito-borne arboviruses emerging as a significant and escalating threat. In Ethiopia, malaria and arboviruses such as Dengue and Yellow fever viruses pose substantial public health challenges; however, surveillance efforts are hindered by traditional methods that are costly and labor-intensive, yet unable to identify cryptic species. Environmental DNA (eDNA) metabarcoding presents a promising alternative, facilitating noninvasive and high-throughput detection of vector species directly from environmental samples.

This pilot study evaluated the utility of eDNA metabarcoding for mosquito identification in Ethiopia's Great Rift Valley. A total of 29 water and soil samples were collected from diverse mosquito breeding habitats in August 2023. For eDNA extraction, samples were pooled into 13 groups to maximize yield and reduce sequencing costs, using the NucleoSpin^® eDNA Water and Soil kits. The eDNA was amplified with universal primers targeting the mitochondrial COI gene, primarily for mosquito detection. Targeted amplicon sequencing was performed on an in-house Illumina platform. For phylogenetic analysis, sequences were aligned with MAFFT, and trees were constructed using the neighbor-joining method with a Tamura-Nei model in Geneious Prime. Species identification was carried out using the BOLD System and NCBI BLAST. Out of 13 pooled environmental samples analyzed, eight (61.5%) tested positive for mosquito DNA, identifying three species: Anopheles coustani, Culex poicilipes, and Mansonia uniformis. Notably, this marks the first documented detection of Cx. poicilipes in Ethiopia, a known vector for Rift Valley Fever Virus (RVFV). The positive samples were collected from various habitats, including a water storage container, a ditch, a discarded tire, a flooded river, and a swampy area, showcasing the method's adaptability to diverse sample types.

eDNA metabarcoding is a scalable tool for mosquito surveillance in resource-limited settings. This approach can strengthen national surveillance programs by enabling the early detection of medically important species and expanding coverage to logistically challenging habitats. Future studies should integrate pathogen screening to assess direct transmission risks and expand seasonal sampling for longitudinal monitoring.