Plasmodium falciparum is transmitted by mosquitoes from the Anopheles gambiae sensu lato (s.l) species complex and is responsible for severe forms of malaria. The composition of the mosquitoes' microbiota plays a role in P. falciparum transmission, so we studied midgut bacterial communities of An. gambiae s.l from Burkina Faso. DNA was extracted from 17 pools of midgut of mosquitoes from the Anopheles gambiae complex from six localities in three climatic areas, including cotton-growing and cotton-free localities to include potential differences in insecticide selection pressure. The v3-v4 region of the 16S rRNA gene was targeted and sequenced using Illumina Miseq (2 × 250 nt). Diversity analysis was performed using QIIME and R software programs. The major bacterial phylum was Proteobacteria (97.2%) in all samples. The most abundant genera were Enterobacter (32.8%) and Aeromonas (29.8%), followed by Pseudomonas (11.8%), Acinetobacter (5.9%) and Thorsellia (2.2%). No statistical difference in operational taxonomic units (OTUs) was found (Kruskal-Wallis FDR-p > 0.05) among the different areas, fields or localities. Richness and diversity indexes (observed OTUs, Chao1, Simpson and Shannon indexes) showed significant differences in the cotton-growing fields and in the agroclimatic zones, mainly in the Sudano-Sahelian area. OTUs from seven bacterial species that mediate refractoriness to Plasmodium infection in An. gambiae s.l were detected. The beta diversity analysis did not show any significant difference. Therefore, a same control strategy of using bacterial species refractoriness to Plasmodium to target mosquito midgut bacterial community and affect their fitness in malaria transmission may be valuable tool for future malaria control efforts in Burkina Faso.

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In Sub-Saharan Africa, An. gambiae sensu lato (s.l.) Giles 190, largely contributes to malaria transmission. Therefore, the authors carry out a proteomic analysis to compare its metabolic state, depending on different pesticide pressures by selecting areas with/without cotton crops. The proteomes data are available via ProteomeXchange with identifier PXD016300. From a total of 1.182 identified proteins, 648 are retained for further statistical analysis and are attributed to biological functions, the most important of which being energy metabolism (120 proteins) followed by translation-biogenesis (74), cytoskeleton (71), stress response (62), biosynthetic process (60), signalling (44), cellular respiration (38), cell redox homeostasis (25), DNA processing (17), pheromone binding (10), protein folding (9), RNA processing (9), other proteins (26) and unknown functions (83). In the Sudano-Sahelian region, 421 (91.3%) proteins are found in samples from areas both with and without cotton crops. By contrast, in the Sahelian region, only 271 (55.0%) are common to both crop areas, and 233 proteins are up-regulated from the cotton area. The focus is placed on proteins with putative roles in insecticide resistance, according to literature. This study provides the first whole-body proteomic characterisation of An. gambiae s.l. in Burkina Faso, as a framework to strengthen vector control strategies.