Understanding mosquito host choice behaviour: a new and cost-effective method of identifying the sex of human hosts in mosquito blood meals

Background: Mosquito-borne diseases are a global health problem, causing hundreds of thousands of deaths/year. Pathogens are transmitted by mosquitoes taking blood from an infected host and then feeding on a new host. Monitoring mosquito host-choice behaviour can help in many aspects of vector-borne disease control. Currently, it is possible to determine the host species and the individual human host using genotyping to match the blood profile of local inhabitants to the blood-meal found in mosquitoes. Epidemiological models generally assume biting behaviour is random, however, numerous studies have shown that certain individuals are more attractive to mosquitoes than others, due to e.g., genetic makeup and profiles of skin microbiota. Analysing blood-meals and illuminating host choice behaviour will help re-evaluate and optimise disease transmission models. Methods: We describe a new blood-meal assay that identifies the sex of the person a mosquito has bitten. The amelogenin locus (AMEL), a sex marker located on both X and Y chromosomes, was amplified by PCR in DNA extracted from Aedes aegypti and Anopheles coluzzii blood-meals. Results: Our results show that AMEL successfully amplifies up to 36 hours after a blood-meal in 63% of An. coluzzii and 80% of Ae. aegypti blood-meals, revealing the sex of humans that were fed on by individual mosquitoes, which enables further exploration of vector mosquito host preferences. This method was successfully tested in both Anopheles coluzzii and Aedes aegypti, important vectors of malaria and arboviruses, respectively. Conclusions: This method, developed with mosquitoes fed on volunteers, can be applied to field-caught mosquitoes where the host species, the biological sex of the human host and host diversity within blood-meals can be determined. Two important vector species were tested successfully in our laboratory experiments, demonstrating the potential of this technique to improve epidemiological models of vector-borne diseases. This viable and highly cost-effective approach has the capacity to improve our understanding of vector-borne disease transmission, specifically gender differences in exposure and attractiveness to mosquitoes. The data gathered from field-studies using our method will shape new transmission models and aid in the implementation of more effective and targeted vector control strategies by better understanding the drivers of vector-host interactions

Improved species assignments across the entire Anopheles genus using targeted sequencing

Accurate species identification of the mosquitoes in the genus Anopheles is of crucial importance to implement malaria control measures and monitor their effectiveness. We use a previously developed amplicon panel (ANOSPP) that retrieves sequence data from multiple short nuclear loci for any species in the genus. Species assignment is based on comparison of samples to a reference index using k-mer distance. Here, we provide a protocol to generate version controlled updates of the reference index and present its latest release, NNv2, which contains 91 species, compared to 56 species represented in its predecessor NNv1. With the updated reference index, we are able to assign samples to species level that previously could not be assigned. We discuss what happens if a species is not represented in the reference index and how this can be addressed in a future update. To demonstrate the increased power of NNv2, we showcase the assignments of 1789 wild-caught mosquitoes from Madagascar and demonstrate that we can detect within species population structure from the amplicon sequencing data

Improved species assignments across the entire Anopheles genus using targeted sequencing.

Peer reviewed: TrueAcknowledgements: In tribute to our colleague and co-author Tatamo, who died conducting field work. We thank Edel Sheerin for general logistic support for ANOSPP. We thank Petra Korlević for valuable suggestions and Nil Rahola for providing information on morphological keys used in taxonomic information. We thank the Medical Entomology Research Unit from the Institut Pasteur de Madagascar, VectorLink and the National Program for the Fight Against Malaria (PNLP) for sample collection and identification in this country. We also thank the Vector Biology and Control Section from the Department of Entomology at the Armed Forces Research Institute of Medical Sciences for sample collection and identification in Thailand. We thank the teams of the Entomology, Malaria and Laboratory departments of the Shoklo Malaria Research Unit for their help with sample collection, processing and management. For field sampling in Uganda we would like to thank Target Malaria Uganda. For sample collection in Ghana we would like to thank Richardson Kwesi Egyirifa, Christopher Dorcoo and Sampson Otoo. We thank Sanger’s Scientific Operation Teams for carrying out all PCRs, library generation, and sequencing on data presented here and Catherine McCarthy for her support in ensuring all samples are compliant with Access and Benefit Sharing of sequence data as laid out by the Nagoya Protocol. ThermaStop was provided to the Wellcome Sanger Institute by ThermaGenix Inc. (Natick Massachusetts, USA) free of charge.Accurate species identification of the mosquitoes in the genus Anopheles is of crucial importance to implement malaria control measures and monitor their effectiveness. We use a previously developed amplicon panel (ANOSPP) that retrieves sequence data from multiple short nuclear loci for any species in the genus. Species assignment is based on comparison of samples to a reference index using k-mer distance. Here, we provide a protocol to generate version controlled updates of the reference index and present its latest release, NNv2, which contains 91 species, compared to 56 species represented in its predecessor NNv1. With the updated reference index, we are able to assign samples to species level that previously could not be assigned. We discuss what happens if a species is not represented in the reference index and how this can be addressed in a future update. To demonstrate the increased power of NNv2, we showcase the assignments of 1789 wild-caught mosquitoes from Madagascar and demonstrate that we can detect within species population structure from the amplicon sequencing data