生物
多路复用
库蚊
淡色库蚊
动物
病毒学
生态学
遗传学
幼虫
作者
Thamyris Sampaio Vilela,Nathália Alves de Senne,Patrícia Gonzaga Paulino,Thamires Rezende Araújo,Pamella Pryscila de Alvarenga Bissoli Maciel de Lima,Natália Pedra Gonçalves,Daniel da Silva Guedes‐Junior,Isabele da Costa Angelo,Carlos Luiz Massard,Maristela Peckle Peixoto,Huarrisson Azevedo Santos
摘要
Culex species, such as Culex quinquefasciatus and Culex nigripalpus display a range of feeding habits and act as vectors for pathogens that can cause diseases in both humans and animals. Understanding their feeding habits is pivotal for enhancing disease prevention strategies. The present study introduces the application of two multiplex real-time PCR (qPCR) followed by high-resolution melting (HRM) as a cost-effective and time-efficient alternative. This investigation involved the development of two multiplex qPCR-HRM: assay 1 detects human, dog and chicken, while assay 2 detects cat, cattle and horse in Culex sp. engorged female mosquitoes. The qPCR-HRM reactions showed a detection limit of one copy of genomic DNA when performed as single and multiplex qPCR-HRM. The reaction efficiencies were 97.96% for human, 100.60% for dog, 99.03% for chicken, 99.92% for feline, 99.18% for cattle and 97.68% for horse. The qPCR-HRM method, employing multiplex 1 and 2, was applied to field-collected mosquitoes and demonstrated the ability to detect DNA from multiple blood sources within a single sample. By analysing both multiplexes, it was possible to identify up to five distinct blood sources in Cx. quinquefasciatus and Cx. nigripalpus, and up to two sources in Culex coronatus. Sequencing corroborated the qPCR-HRM results, confirming the presence of DNA from one to four different blood sources with 100% accuracy. The development of these molecular methods may contribute for identification of blood-feeding patterns in mosquitoes. It contributes to studies on the dissemination and transmission of pathogens among various animals and humans, thereby bridging the gap between epidemiology and vector monitoring.
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