High-throughput detection of eukaryotic parasites and arboviruses in mosquitoes
Matthew V. Cannon,
Haikel N. Bogale,
Devika Bhalerao,
Kalil Keita,
Denka Camara,
Yaya Barry,
Moussa Keita,
Drissa Coulibaly,
Abdoulaye K. Kone,
Ogobara K. Doumbo,
Mahamadou A. Thera,
Christopher V. Plowe,
Mark A. Travassos,
Seth R. Irish,
Joshua Yeroshefsky,
Jeannine Dorothy,
Brian Prendergast,
Brandyce St. Laurent,
Megan L. Fritz,
David Serre
Affiliations
Matthew V. Cannon
Institute for Genome Sciences, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, USA
Haikel N. Bogale
Institute for Genome Sciences, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, USA
Devika Bhalerao
Institute for Genome Sciences, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, USA
Kalil Keita
Programme National de Lutte contre le Paludisme, Guinea
Denka Camara
Programme National de Lutte contre le Paludisme, Guinea
Yaya Barry
Programme National de Lutte contre le Paludisme, Guinea
Moussa Keita
Programme National de Lutte contre le Paludisme, Guinea
Drissa Coulibaly
Malaria Research and Training Center, University Science, Techniques and Technologies of Bamako, Mali
Abdoulaye K. Kone
Malaria Research and Training Center, University Science, Techniques and Technologies of Bamako, Mali
Ogobara K. Doumbo
Malaria Research and Training Center, University Science, Techniques and Technologies of Bamako, Mali
Mahamadou A. Thera
Malaria Research and Training Center, University Science, Techniques and Technologies of Bamako, Mali
Christopher V. Plowe
Malaria Research Program, Department of Medicine, Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD 21201, USA
Mark A. Travassos
Malaria Research Program, Department of Medicine, Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD 21201, USA
Seth R. Irish
U.S. President's Malaria Initiative and Entomology Branch, Division of Parasitic Diseases and Malaria, Center for Global Health, Centers for Disease Control and Prevention, Atlanta, GA 30333, USA
Joshua Yeroshefsky
Department of Entomology, University of Maryland College Park, College Park, MD 20742, USA
Jeannine Dorothy
Mosquito Control Program, Maryland Department of Agriculture, Annapolis, MD 21401, USA
Brian Prendergast
Mosquito Control Program, Maryland Department of Agriculture, Annapolis, MD 21401, USA
Brandyce St. Laurent
Laboratory of Malaria and Vector Research, National Institute of Allergy and Infectious Diseases, Rockville, MD 20852, USA
Megan L. Fritz
Department of Entomology, University of Maryland College Park, College Park, MD 20742, USA
David Serre
Institute for Genome Sciences, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, USA
Vector-borne pathogens cause many human infectious diseases and are responsible for high mortality and morbidity throughout the world. They can also cause livestock epidemics with dramatic social and economic consequences. Due to its high costs, vector-borne disease surveillance is often limited to current threats, and the investigation of emerging pathogens typically occurs after the reports of clinical cases. Here, we use high-throughput sequencing to detect and identify a wide range of parasites and viruses carried by mosquitoes from Cambodia, Guinea, Mali and the USA. We apply this approach to individual Anopheles mosquitoes as well as pools of mosquitoes captured in traps; and compare the outcomes of this assay when applied to DNA or RNA. We identified known human and animal pathogens and mosquito parasites belonging to a wide range of taxa, as well as DNA sequences from previously uncharacterized organisms. Our results also revealed that analysis of the content of an entire trap could be an efficient approach to monitor and identify rare vector-borne pathogens in large surveillance studies. Overall, we describe a high-throughput and easy-to-customize assay to screen for a wide range of pathogens and efficiently complement current vector-borne disease surveillance approaches.