Islands and stepping-stones: comparative population structure of Anopheles gambiae sensu stricto and Anopheles arabiensis in Tanzania and implications for the spread of insecticide resistance.

Deodatus Maliti,Khamis Haji,Gerald Killeen,David Weetman,Juma Mcha,William Kisinza,Stephen Magesa,Hilary Ranson,Igor V. Sharakhov

doi:10.1371/journal.pone.0110910

Abstract

Population genetic structures of the two major malaria vectors Anopheles gambiae s.s. and An. arabiensis, differ markedly across Sub-Saharan Africa, which could reflect differences in historical demographies or in contemporary gene flow. Elucidation of the degree and cause of population structure is important for predicting the spread of genetic traits such as insecticide resistance genes or artificially engineered genes. Here the population genetics of An. gambiae s.s. and An. arabiensis in the central, eastern and island regions of Tanzania were compared. Microsatellite markers were screened in 33 collections of female An. gambiae s.l., originating from 22 geographical locations, four of which were sampled in two or three years between 2008 and 2010. An. gambiae were sampled from six sites, An. arabiensis from 14 sites, and both species from two sites, with an additional colonised insectary sample of each species. Frequencies of the knock-down resistance (kdr) alleles 1014S and 1014F were also determined. An. gambiae exhibited relatively high genetic differentiation (average pairwise FST = 0.131), significant even between nearby samples, but without clear geographical patterning. In contrast, An. arabiensis exhibited limited differentiation (average FST = 0.015), but strong isolation-by-distance (Mantel test r = 0.46, p = 0.0008). Most time-series samples of An. arabiensis were homogeneous, suggesting general temporal stability of the genetic structure. An. gambiae populations from Dar es Salaam and Bagamoyo were found to have high frequencies of kdr 1014S (around 70%), with almost 50% homozygote but was at much lower frequency on Unguja Island, with no. An. gambiae population genetic differentiation was consistent with an island model of genetic structuring with highly restricted gene flow, contrary to An. arabiensis which was consistent with a stepping-stone model of extensive, but geographically-restricted gene flow.

Highlights

In sub-Saharan Africa, a dramatic increase in household ownership of long-lasting insecticidal nets (LLINs), is considered one of the major factors contributing to the fall in malaria cases over the last decade [1]
Ethics statement All mosquitoes were either collected through routine physiological surveillance activities of the National Institute for Medical Research (NIMR) of Tanzania and the Zanzibar National Malaria Elimination Programme (ZAMEP), or through research protocols implemented by the Ifakara Health Institute (IHI) that were approved by both the IHI internal institutional review board (Reference IHI/IRB/A.50) and the Medical Research Coordination Committee at NIMR (Reference NIMR/HQ/R.8a/Vol IX/ 801)
Distance and environmental adaptation have all been implicated previously as causal factors reducing gene flow in An. gambiae s.l., but few studies have compared their roles in An. gambiae s.s. and An. arabiensis

Summary

Introduction

In sub-Saharan Africa, a dramatic increase in household ownership of long-lasting insecticidal nets (LLINs), is considered one of the major factors contributing to the fall in malaria cases over the last decade [1]. Sustainability of LLINs as a frontline control strategy against malaria is threatened by growing Anopheles resistance to pyrethroids [2], the only class of insecticides licensed for LLIN treatment. Improved understanding of the mechanisms responsible for insecticide resistance in Anopheles malaria vectors, and development of reliable diagnostics (such as those available for kdr knockdown resistance mutations [3]) are considered important goals to prolong the efficacy of pyrethroids for mosquito control [4]. Genetic data can aid predictions of the spread of resistance alleles via inference of vector population structure, which can be compared to the spatial or temporal distribution of diagnostic markers for specific resistance mechanisms where these are available [5]. Vector population genetic data could potentially give insight into connectivity of disease transmission dynamics [6], and is an essential prerequisite for rational planning of vector control strategies that focus on release of sterilised or genetically manipulated mosquitoes [7]

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Conclusion