Gene expression-based biomarkers for Anopheles gambiae age grading.
Information on population age structure of mosquitoes under natural conditions is fundamental to the understanding of vectorial capacity and crucial for assessing the impact of vector control measures on malaria transmission. Transcriptional profiling has been proposed as a method for predicting mosquito age for Aedes and Anopheles mosquitoes, however, whether this new method is adequate for natural conditions is unknown. This study tests the applicability of transcriptional profiling for age-grading of Anopheles gambiae, the most important malaria vector in Africa. The transcript abundance of two An. gambiae genes, AGAP009551 and AGAP011615, was measured during aging under laboratory and field conditions in three mosquito strains. Age-dependent monotonic changes in transcript levels were observed in all strains evaluated. These genes were validated as age-grading biomarkers using the mark, release and recapture (MRR) method. The MRR method determined a good correspondence between actual and predicted age, and thus demonstrated the value of age classifications derived from the transcriptional profiling of these two genes. The technique was used to establish the age structure of mosquito populations from two malaria-endemic areas in western Kenya. The population age structure determined by the transcriptional profiling method was consistent with that based on mosquito parity. This study demonstrates that the transcription profiling method based on two genes is valuable for age determination of natural mosquitoes, providing a new approach for determining a key life history trait of malaria vectors.
Program in Public Health, University of California Irvine, Irvine, California, United States of America.
Mei-Hui
MH
Wang
Osvaldo
O
Marinotti
Daibin
D
Zhong
Anthony A
AA
James
Edward
E
Walker
Tom
T
Guda
Eliningaya J
EJ
Kweka
John
J
Githure
Guiyun
G
Yan
D000375:Aging / Q000235:genetics*; D000818:Animals; D000852:Anopheles / Q000235:genetics* / Q000254:growth & development*; D015415:Biomarkers / Q000378:metabolism*; D005260:Female; D020869:Gene Expression Profiling; D007630:Kenya; D008297:Male; D012333:RNA, Messenger / Q000235:genetics / Q000378:metabolism; D059467:Transcriptome / Q000235:genetics
D015415:Biomarkers; D012333:RNA, Messenger