Background New strategies to eliminate dengue have been proposed that specifically target older Aedes aegypti mosquitoes, the proportion of the vector population that is potentially capable of transmitting dengue viruses. Evaluation of these strategies will require accurate and high-throughput methods of predicting mosquito age. We previously developed an age prediction assay for individual Ae. aegypti females based on the transcriptional profiles of a selection of age responsive genes. Here we conducted field testing of the method on Ae. aegypti that were entirely uncaged and free to engage in natural behavior. Methodology/Principal Findings We produced “free-range” test specimens by releasing 8007 adult Ae. aegypti inside and around an isolated homestead in north Queensland, Australia, and recapturing females at two day intervals. We applied a TaqMan probe-based assay design that enabled high-throughput quantitative RT-PCR of four transcripts from three age-responsive genes and a reference gene. An age prediction model was calibrated on mosquitoes maintained in small sentinel cages, in which 68.8% of the variance in gene transcription measures was explained by age. The model was then used to predict the ages of the free-range females. The relationship between the predicted and actual ages achieved an R2 value of 0.62 for predictions of females up to 29 days old. Transcriptional profiles and age predictions were not affected by physiological variation associated with the blood feeding/egg development cycle and we show that the age grading method could be applied to differentiate between two populations of mosquitoes having a two-fold difference in mean life expectancy. Conclusions/Significance The transcriptional profiles of age responsive genes facilitated age estimates of near-wild Ae. aegypti females. Our age prediction assay for Ae. aegypti provides a useful tool for the evaluation of mosquito control interventions against dengue where mosquito survivorship or lifespan reduction are crucial to their success. The approximate cost of the method was US$7.50 per mosquito and 60 mosquitoes could be processed in 3 days. The assay is based on conserved genes and modified versions are likely to support similar investigations of several important mosquito and other disease vectors.
References
[1]
Knox TB, Kay BH, Hall RA, Ryan PA (2003) Enhanced vector competence of Aedes aegypti (Diptera: Culicidae) from the Torres Strait compared with mainland Australia for dengue 2 and 4 viruses. J Med Entomol 40: 950–956. doi: 10.1603/0022-2585-40.6.950
[2]
Macdonald G (1952) The objectives of residual insecticide campaigns. Trans R Soc Trop Med Hyg 46: 227–235. doi: 10.1016/0035-9203(52)90070-9
[3]
Garrett-Jones C (1964) Prognosis for interruption of malaria transmission through assessment of the mosquito's vectorial capacity. Nature 204: 1173–1175. doi: 10.1038/2041173a0
Sinkins SP, O'Neill S L (2000) Wolbachia as a vehicle to modify insect populations. In: Handler AM, James AA, editors. Insect transgenesis: methods and applications. Boca Raton: CRC Press. pp. 271–287.
[6]
Brownstein JS, Hett E, O'Neill SL (2003) The potential of virulent Wolbachia to modulate disease transmission by insects. J Invertebr Pathol 84: 24–29. doi: 10.1016/S0022-2011(03)00082-X
[7]
Thomas MB, Read AF (2007) Can fungal biopesticides control malaria? Nat Rev Microbiol 5: 377–383. doi: 10.1038/nrmicro1638
[8]
Cook PE, McMeniman CJ, O'Neill SL (2008) Modifying insect population age structure to control vector-borne disease. Adv Exp Med Biol 627: 126–140. doi: 10.1007/978-0-387-78225-6_11
[9]
McMeniman CJ, Lane RV, Cass BN, Fong AW, Sidhu M, et al. (2009) Stable introduction of a life-shortening Wolbachia infection into the mosquito Aedes aegypti. Science 323: 141–144. doi: 10.1126/science.1165326
[10]
Hugo LE, Quick-Miles S, Kay BH, Ryan PA (2008) Evaluations of mosquito age grading techniques based on morphological changes. J Med Entomol 45: 353–369. doi: 10.1603/0022-2585(2008)45[353:EOMAGT]2.0.CO;2
[11]
Desena ML, Clark JM, Edman JD, Symington SB, Scott TW, et al. (1999) Potential for aging female Aedes aegypti (Diptera: Culicidae) by gas chromatographic analysis of cuticular hydrocarbons, including a field evaluation. J Med Entomol 36: 811–823.
[12]
Desena ML, Edman JD, Clark JM, Symington SB, Scott TW (1999) Aedes aegypti (Diptera: Culicidae) age determination by cuticular hydrocarbon analysis of female legs. J Med Entomol 36: 824–830.
[13]
Gerade BB, Lee SH, Scott TW, Edman JD, Harrington LC, et al. (2004) Field validation of Aedes aegypti (Diptera: Culicidae) age estimation by analysis of cuticular hydrocarbons. J Med Entomol 41: 231–238. doi: 10.1603/0022-2585-41.2.231
[14]
Cook PE, Hugo LE, Iturbe-Ormaetxe I, Williams CR, Chenoweth SF, et al. (2006) The use of transcriptional profiles to predict adult mosquito age under field conditions. Proc Natl Acad Sci U S A 103: 18060–18065. doi: 10.1073/pnas.0604875103
[15]
Cook PE, Hugo LE, Iturbe-Ormaetxe I, Williams CR, Chenoweth SF, et al. (2007) Predicting the age of mosquitoes using transcriptional profiles. Nat Protoc 2: 2796–2806. doi: 10.1038/nprot.2007.396
[16]
Dana AN, Hong YS, Kern MK, Hillenmeyer ME, Harker BW, et al. (2005) Gene expression patterns associated with blood-feeding in the malaria mosquito Anopheles gambiae. BMC Genomics 6: 5. doi: 10.1186/1471-2164-6-5
[17]
Marinotti O, Calvo E, Nguyen QK, Dissanayake S, Ribeiro JM, et al. (2006) Genome-wide analysis of gene expression in adult Anopheles gambiae. Insect Mol Biol 15: 1–12. doi: 10.1111/j.1365-2583.2006.00610.x
[18]
Marinotti O, Nguyen QK, Calvo E, James AA, Ribeiro JM (2005) Microarray analysis of genes showing variable expression following a blood meal in Anopheles gambiae. Insect Mol Biol 14: 365–373. doi: 10.1111/j.1365-2583.2005.00567.x
[19]
Dana AN, Hillenmeyer ME, Lobo NF, Kern MK, Romans PA, et al. (2006) Differential gene expression in abdomens of the malaria vector mosquito, Anopheles gambiae, after sugar feeding, blood feeding and Plasmodium berghei infection. BMC Genomics 7: 119. doi: 10.1186/1471-2164-7-119
[20]
Heid CA, Stevens J, Livak KJ, Williams PM (1996) Real time quantitative PCR. Genome Res 6: 986–994. doi: 10.1101/gr.6.10.986
[21]
Christophers SR (1911) The development of the egg follicle in anophelines. Paludism 2: 73–88.
[22]
Detinova TS (1962) Age-grouping methods in Diptera of medical importance with special reference to some vectors of malaria. Geneva: World Health Organization.
[23]
Nasci RS (1990) Relationship of wing length to adult dry weight in several mosquito species (Diptera: Culicidae). J Med Entomol 27: 716–719.
[24]
Lunn DJ, Thomas A, Best N (2000) WinBUGS - a Bayesian modelling framework: concepts, structure, and extensibility. Stat Comput 10: 325–337.
