The implementation of long-lasting insecticidal bed nets has differential effects on the genetic structure of the African malaria vectors in the Anopheles gambiae complex in Dielmo, Senegal

Abstract Background Mosquitoes belonging to the Anopheles gambiae complex are the main vectors of malaria in sub-Saharan Africa. Among these, An. gambiae, Anopheles coluzzii and Anopheles arabiensis are the most efficient vectors and are largely distributed in sympatric locations. However, these species present ecological and behavioural differences that impact their vectorial capacity and complicate vector-control efforts, mainly based on long-lasting insecticidal bed nets (LLINs) and indoor residual spraying (IRS). In this study, the genetic structure of these three species in a Senegalese village (Dielmo) was investigated using microsatellite data in samples collected in 2006 before implementation of LLINs, in 2008, when they were introduced, and in 2010, 2 years after the use of LLINs. Results In this study 611 individuals were included, namely 136 An. coluzzii, 101 An. gambiae, 6 An. coluzzii/An. gambiae hybrids and 368 An. arabiensis. According to the species, the effect of the implementation of LLINs in Dielmo is differentiated. Populations of the sister species An. coluzzii and An. gambiae regularly experienced bottleneck events, but without significant inbreeding. The Fst values suggested in 2006 a breakdown of assortative mating resulting in hybrids, but the introduction of LLINs was followed by a decrease in the number of hybrids. This suggests a decrease in mating success of hybrids, ecological maladaptation, or a lesser probability of mating between species due to a decrease in An. coluzzii population size. By contrast, the introduction of LLINs has favoured the sibling species An. arabiensis. In this study, some spatial and temporal structuration between An. arabiensis populations were detected, especially in 2008, and the higher genetic diversity observed could result from a diversifying selection. Conclusions This work demonstrates the complexity of the malaria context and shows the need to study the genetic structure of Anopheles populations to evaluate the effectiveness of vector-control tools and successful management of malaria vector control.