The use of transcriptional profiles to predict adult mosquito age under field conditions

Age is a critical determinant of an adult female mosquito's ability to transmit a range of human pathogens. Despite its central importance, relatively few methods exist with which to accurately determine chronological age of field-caught mosquitoes. This fact is a major constraint on our ability to fully understand the relative importance of vector longevity to disease transmission in different ecological contexts. It also limits our ability to evaluate novel disease control strategies that specifically target mosquito longevity. We report the development of a transcriptional profiling approach to determine age of adult female Aedes aegypti under field conditions. We demonstrate that this approach surpasses current cuticular hydrocarbon methods for both accuracy of predicted age as well as the upper limits at which age can be reliably predicted. The method is based on genes that display age-dependent expression in a range of dipteran insects and, as such, is likely to be broadly applicable to other disease vectors

Predicting the age of mosquitoes using transcriptional profiles

The use of transcriptional profiles for predicting mosquito age is a novel solution for the longstanding problem of determining the age of field-caught mosquitoes. Female mosquito age is of central importance to the transmission of a range of human pathogens. The transcriptional age-grading protocol we present here was developed in Aedes aegypti, principally as a research tool. Age predictions are made on the basis of transcriptional data collected from mosquitoes of known age. The abundance of eight candidate gene transcripts is quantified relative to a reference gene using quantitative reverse transcriptase-PCR (RT-PCR). Normalized gene expression (GE) measures are analyzed using canonical redundancy analysis to obtain a multivariate predictor of mosquito age. The relationship between the first redundancy variate and known age is used as the calibration model. Normalized GE measures are quantified for wild-caught mosquitoes, and ages are then predicted using this calibration model. Rearing of mosquitoes to specific ages for calibration data can take up to 40 d. Molecular analysis of transcript abundance, and subsequent age predictions, should take similar to 3-5 d for 100 individuals