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The primary means of reducing malaria transmission is through reduction in longevity in days of the adult female stage of the Anopheles vector. However, assessing chronological age is limited to crude physiologic methods which categorize the females binomially as either very young (nulliparous) or not very young (parous). Yet the epidemiologically relevant reduction in life span falls within the latter category. Age-grading methods that delineate chronological age, using accurate molecular surrogates based upon gene expression profiles, will allow quantification of the longevity-reducing effects of vector control tools aimed at the adult, female mosquito. In this study, microarray analyses of gene expression profiles in the African malaria vector Anopheles gambiae were conducted during natural senescence of females in laboratory conditions. Results showed that detoxification-related and stress-responsive genes were up-regulated as mosquitoes aged. A total of 276 transcripts had age-dependent expression, independently of blood feeding and egg laying events. Expression of 112 (40.6%) of these transcripts increased or decreased monotonically with increasing chronologic age. Seven candidate genes for practical age assessment were tested by quantitative gene amplification in the An. gambiae G3 strain in a laboratory experiment and the Mbita strain in field enclosures set up in western Kenya under conditions closely resembling natural ones. Results were similar between experiments, indicating that senescence is marked by changes in gene expression and that chronological age can be gauged accurately and repeatedly with this method. These results indicate that the method may be suitable for accurate gauging of the age in days of field-caught, female An. gambiae.

Original publication

DOI

10.1371/journal.pone.0013359

Type

Journal article

Journal

PLoS One

Publication Date

13/10/2010

Volume

5

Keywords

Aging, Animals, Anopheles, Female, Gene Expression Profiling, Genome, Insect Vectors, Oligonucleotide Array Sequence Analysis, Transcription, Genetic