Population genetic structure of the malaria vector Anopheles nili in sub-Saharan Africa

<p>Abstract</p> <p>Background</p> <p><it>Anopheles nili </it>is a widespread efficient vector of human malaria parasites in the humid savannas and forested areas of sub-Saharan Africa. Understanding <it>An. nili </it>population structure and gene flow patterns could be useful for the development of locally-adapted vector control measures.</p> <p>Methods</p> <p>Polymorphism at eleven recently developed microsatelitte markers, and sequence variation in four genes within the 28s rDNA subunit (ITS2 and D3) and mtDNA (COII and ND4) were assessed to explore the level of genetic variability and differentiation among nine populations of <it>An. nili </it>from Senegal, Ivory Coast, Burkina Faso, Nigeria, Cameroon and the Democratic Republic of Congo (DRC).</p> <p>Results</p> <p>All microsatellite loci successfully amplified in all populations, showing high and very similar levels of genetic diversity in populations from West Africa and Cameroon (mean Rs = 8.10-8.88, mean He = 0.805-0.849) and much lower diversity in the Kenge population from DRC (mean Rs = 5.43, mean He = 0.594). Bayesian clustering analysis of microsatellite allelic frequencies revealed two main genetic clusters in the dataset. The first one included only the Kenge population and the second grouped together all other populations. High Fst estimates based on microsatellites (Fst > 0.118, P < 0.001) were observed in all comparisons between Kenge and all other populations. By contrast, low Fst estimates (Fst < 0.022, P < 0.05) were observed between populations within the second cluster. The correlation between genetic and geographic distances was weak and possibly obscured by demographic instability. Sequence variation in mtDNA genes matched these results, whereas low polymorphism in rDNA genes prevented detection of any population substructure at this geographical scale.</p> <p>Conclusion</p> <p>Overall, high genetic homogeneity of the <it>An. nili </it>gene pool was found across its distribution range in West and Central Africa, although demographic events probably resulted in a higher level of genetic isolation in the marginal population of Kenge (DRC). The role of the equatorial forest block as a barrier to gene flow and the implication of such findings for vector control are discussed.</p

Population structure of the malaria vector Anopheles moucheti in the equatorial forest region of Africa

<p>Abstract</p> <p>Background</p> <p><it>Anopheles moucheti </it>is a major malaria vector in forested areas of Africa. However, despite its important epidemiological role, it remains poorly known and insufficiently studied. Here, levels of genetic differentiation were estimated between different <it>A. moucheti </it>populations sampled throughout its distribution range in Central Africa.</p> <p>Methods</p> <p>Polymorphism at ten microsatellite markers was compared in mosquitoes sampled in Cameroon, the Democratic Republic of Congo and an island on Lake Victoria in Uganda. Microsatellite data were used to estimate genetic diversity within populations, their relative long-term effective population size, and the level of genetic differentiation between them.</p> <p>Results</p> <p>All specimens collected in Tsakalakuku (Democratic Republic of Congo) were identified as <it>A. m. bervoetsi </it>while other samples consisted of <it>A. m. moucheti</it>. Successful amplification was obtained at all microsatellite loci within all <it>A. m. moucheti </it>samples while only six loci amplified in <it>A. m. bervoetsi</it>. Allelic richness and heterozygosity were high for all populations except the island population of Uganda and <it>A. m. bervoetsi</it>. High levels of genetic differentiation were recorded between <it>A. m. bervoetsi </it>and each <it>A. m. moucheti </it>sample as well as between the island population of <it>A. m. moucheti </it>and mainland populations. Significant isolation by distance was evidenced between mainland populations.</p> <p>Conclusion</p> <p>High levels of genetic differentiation supports complete speciation of <it>A. m. bervoetsi </it>which should henceforth be recognized as a full species and named <it>A. bervoetsi</it>. Isolation by distance is the main force driving differentiation between mainland populations of <it>A. m. moucheti</it>. Genetically and geographically isolated populations exist on Lake Victoria islands, which might serve as relevant field sites for evaluation of innovative vector control strategies.</p

A pre-intervention study of malaria vector abundance in Rio Muni, Equatorial Guinea: Their role in malaria transmission and the incidence of insecticide resistance alleles

BACKGROUND: Following the success of the malaria control intervention on the island of Bioko, malaria control by the use of indoor residual spraying (IRS) and long-lasting insecticide-treated nets (LLITN) was extended to Rio Muni, on the mainland part of Equatorial Guinea. This manuscript reports on the malaria vectors present and the incidence of insecticide resistant alleles prior to the onset of the programme. METHODS: Anopheles mosquitoes were captured daily using window traps at 30 sentinel sites in Rio Muni, from December 2006 to July 2007. The mosquitoes were identified to species and their sporozoite rates, knockdown resistance (kdr) and acetylcholinesterase (AChE) sensitivity measured, to define the role of vector species in malaria transmission and their potential susceptibility to insecticides. RESULTS: A total of 6,162 Anopheles mosquitoes were collected of which 4,808 were morphologically identified as Anopheles gambiae s.l., 120 Anopheles funestus, 1,069 Anopheles moucheti, and 165 Anopheles nili s.l.. Both M and S molecular forms of Anopheles gambiae s.s. and Anopheles melas were identified. Anopheles ovengensis and Anopheles carnevalei were the only two members of the An. nili group to be identified. Using the species-specific sporozoite rates and the average number of mosquitoes per night, the number of infective mosquitoes per trap per 100 nights for each species complex was calculated as a measure of transmission risk. Both kdr-w and kdr-e alleles were present in the S-form of An. gambiae s.s. (59% and 19% respectively) and at much lower frequencies in the M-form (9.7% and 1.8% respectively). The kdr-w and kdr-e alleles co-occurred in 103 S-form and 1 M-form specimens. No insensitive AChE was detected. CONCLUSION: Anopheles gambiae s.s, a member of the Anopheles gambiae complex was shown to be the major vector in Rio Muni with the other three groups playing a relatively minor role in transmission. The demonstration of a high frequency of kdr alleles in mosquito populations before the onset of a malaria control programme shows that continuous entomological surveillance including resistance monitoring will be of critical importance to ensure the chosen insecticide remains effective

Age-structured gametocyte allocation links immunity to epidemiology in malaria parasites

Background Despite a long history of attempts to model malaria epidemiology, the over-riding conclusion is that a detailed understanding of host-parasite interactions leading to immunity is required. It is still not known what governs the duration of an infection and how within-human parasite dynamics relate to malaria epidemiology. Presentation of the hypothesis Immunity to Plasmodium falciparum develops slowly and requires repeated exposure to the parasite, which thus generates age-structure in the host-parasite interaction. An age-structured degree of immunity would present the parasite with humans of highly variable quality. Evolutionary theory suggests that natural selection will mould adaptive phenotypes that are more precise (less variant) in "high quality" habitats, where lifetime reproductive success is best. Variability in malaria parasite gametocyte density is predicted to be less variable in those age groups who best infect mosquitoes. Thus, the extent to which variation in gametocyte density is a simple parasite phenotype reflecting the complex within-host parasite dynamics is addressed. Testing the hypothesis Gametocyte densities and corresponding infectiousness to mosquitoes from published data sets and studies in both rural and urban Cameroon are analysed. The mean and variation in gametocyte density according to age group are considered and compared with transmission success (proportion of mosquitoes infected). Across a wide range of settings endemic for malaria, the age group that infected most mosquitoes had the least variation in gametocyte density, i.e. there was a significant relationship between the variance rather than the mean gametocyte density and age-specific parasite transmission success. In these settings, the acquisition of immunity over time was evident as a decrease in asexual parasite densities with age. By contrast, in an urban setting, there were no such age-structured relationships either with variation in gametocyte density or asexual parasite density. Implications of the hypothesis Gametocyte production is seemingly predicted by evolutionary theory, insofar as a reproductive phenotype (gametocyte density) is most precisely expressed (i.e. is most invariant) in the most infectious human age group. This human age group would thus be expected to be the habitat most suitable for the parasite. Comprehension of the immuno-epidemiology of malaria, a requisite for any vaccine strategies, remains poor. Immunological characterization of the human population stratified by parasite gametocyte allocation would be a step forward in identifying the salient immunological pathways of what makes a human a good habitat

The dominant Anopheles vectors of human malaria in Africa, Europe and the Middle East: occurrence data, distribution maps and bionomic précis

<p>Abstract</p> <p>Background</p> <p>This is the second in a series of three articles documenting the geographical distribution of 41 dominant vector species (DVS) of human malaria. The first paper addressed the DVS of the Americas and the third will consider those of the Asian Pacific Region. Here, the DVS of Africa, Europe and the Middle East are discussed. The continent of Africa experiences the bulk of the global malaria burden due in part to the presence of the <it>An. gambiae </it>complex. <it>Anopheles gambiae </it>is one of four DVS within the <it>An. gambiae </it>complex, the others being <it>An. arabiensis </it>and the coastal <it>An. merus </it>and <it>An. melas</it>. There are a further three, highly anthropophilic DVS in Africa, <it>An. funestus</it>, <it>An. moucheti </it>and <it>An. nili</it>. Conversely, across Europe and the Middle East, malaria transmission is low and frequently absent, despite the presence of six DVS. To help control malaria in Africa and the Middle East, or to identify the risk of its re-emergence in Europe, the contemporary distribution and bionomics of the relevant DVS are needed.</p> <p>Results</p> <p>A contemporary database of occurrence data, compiled from the formal literature and other relevant resources, resulted in the collation of information for seven DVS from 44 countries in Africa containing 4234 geo-referenced, independent sites. In Europe and the Middle East, six DVS were identified from 2784 geo-referenced sites across 49 countries. These occurrence data were combined with expert opinion ranges and a suite of environmental and climatic variables of relevance to anopheline ecology to produce predictive distribution maps using the Boosted Regression Tree (BRT) method.</p> <p>Conclusions</p> <p>The predicted geographic extent for the following DVS (or species/suspected species complex*) is provided for Africa: <it>Anopheles </it>(<it>Cellia</it>) <it>arabiensis</it>, <it>An. </it>(<it>Cel.</it>) <it>funestus*</it>, <it>An. </it>(<it>Cel.</it>) <it>gambiae</it>, <it>An. </it>(<it>Cel.</it>) <it>melas</it>, <it>An. </it>(<it>Cel.</it>) <it>merus</it>, <it>An. </it>(<it>Cel.</it>) <it>moucheti </it>and <it>An. </it>(<it>Cel.</it>) <it>nili*</it>, and in the European and Middle Eastern Region: <it>An. </it>(<it>Anopheles</it>) <it>atroparvus</it>, <it>An. </it>(<it>Ano.</it>) <it>labranchiae</it>, <it>An. </it>(<it>Ano.</it>) <it>messeae</it>, <it>An. </it>(<it>Ano.</it>) <it>sacharovi</it>, <it>An. </it>(<it>Cel.</it>) <it>sergentii </it>and <it>An. </it>(<it>Cel.</it>) <it>superpictus*</it>. These maps are presented alongside a bionomics summary for each species relevant to its control.</p