Estimating female malaria mosquito age by quantifying Y-linked genes in stored male spermatozoa

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作者
Damian Madan
Rafael Rivera
Corrie Ortega
Justin C. Touchon
Corinna Kimball
Geert-Jan van Gemert
Wouter Graumans
Stephanie Matsuura
Sean S. Parghi
David Bell
Teun Bousema
Chris Drakeley
Katharine A. Collins
Thomas R. Burkot
机构
[1] Global Health Labs,Department of Medical Microbiology
[2] Intellectual Ventures Global Good Fund,School of Medicine
[3] Vassar College,undefined
[4] Radbound University Nimegen Medical Centre,undefined
[5] Department of Infection Biology,undefined
[6] School of Hygiene and Tropical Medicine,undefined
[7] Australian Institute of Tropical Health and Medicine,undefined
[8] James Cook University,undefined
[9] Anavasi Diagnostics,undefined
[10] Ozette,undefined
[11] University of Hawaii,undefined
[12] Gilead Sciences,undefined
[13] Inc,undefined
[14] Independent Consultant,undefined
来源
Scientific Reports | / 12卷
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摘要
Vector control strategies are among the most effective measures to combat mosquito-borne diseases, such as malaria. These strategies work by altering the mosquito age structure through increased mortality of the older female mosquitoes that transmit pathogens. However, methods to monitor changes to mosquito age structure are currently inadequate for programmatic implementation. Female mosquitoes generally mate a single time soon after emergence and draw down spermatozoa reserves with each oviposition cycle. Here, we demonstrate that measuring spermatozoa quantity in female Anopheles mosquitoes is an effective approach to assess mosquito age. Using multiplexed qPCR targeted at male spermatozoa, we show that Y-linked genes in female mosquitoes are exclusively found in the spermatheca, the organ that houses spermatozoa, and the quantity of these gene sequences significantly declines with age. The method can accurately identify mosquitoes more than 10 days old and thus old enough to potentially transmit pathogens harbored in the salivary glands during blood feeding. Furthermore, mosquito populations that differ by 10% in daily survivorship have a high likelihood of being distinguished using modest sample sizes, making this approach scalable for assessing the efficacy of vector intervention control programs.
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