Elucidating mechanisms of carbamate resistance and carbamate/pyrethroid cross resistance in An. funestus in Africa

Malaria remains one of the most debilitating tropical diseases with more than 90% of cases in Africa among children under five and pregnant women. Resistance observed against the main insecticides used in public health sector in major vectors such as Anopheles funestus is threatening the success of vector control interventions. To improve the design of suitable resistance management strategies, it is crucial to elucidate the underlining molecular basis of resistance or cross-resistance between insecticides and also establish patterns of gene flow between populations to predict the speed and direction of spread of resistance genes. To address these questions, this study has investigated the molecular basis of resistance to carbamates and cross/resistance to carbamates/pyrethroids in a population of An. funestus from Malawi. This study has revealed that metabolic resistance is the main mechanism driving carbamate resistance through the over-expression of Cytochrome P450 genes. Genome-wide microarray-based transcription analyses consistently revealed that the duplicated P450 genes CYP6P9a and CYP6P9b were among the most up-regulated genes (>2-fold;

The P450 CYP6Z1 confers carbamate/pyrethroid cross-resistance in a major African malaria vector beside a novel carbamate-insensitive N485I acetylcholinesterase-1 mutation

Carbamates are increasingly used for vector control notably in areas with pyrethroid resistance. However, a cross-resistance between these insecticides in major malaria vectors such as Anopheles funestus could severely limit available resistance management options. Unfortunately, the molecular basis of such cross-resistance remains uncharacterized in An. funestus, preventing effective resistance management. Here, using a genome-wide transcription profiling, we revealed that metabolic resistance through up-regulation of cytochrome P450 genes is driving carbamate resistance. The P450s CYP6P9a, CYP6P9b and CYP6Z1 were the most up-regulated detoxification genes in the multiple resistant mosquitoes. However, in silico docking simulations predicted CYP6Z1 to metabolise both pyrethroids and carbamates, whereas CYP6P9a and CYP6P9b were predicted to metabolise only the pyrethroids. Using recombinant enzyme metabolism and inhibition assays we demonstrated that CYP6Z1 metabolizes bendiocarb and pyrethroids, whereas CYP6P9a and CYP6P9b metabolise only the pyrethroids. Other up-regulated gene families in resistant mosquitoes included several cuticular protein genes suggesting a possible reduced penetration resistance mechanism. Investigation of the target-site resistance in acetylcholinesterase 1 (ace-1) gene detected and established the association between the new N485I mutation and bendiocarb resistance (Odds ratio 7.3; P<0.0001). The detection of multiple haplotypes in single mosquitoes after cloning suggested the duplication of ace-1. A TaqMan genotyping of the N485I in nine countries revealed that the mutation is located only in Southern Africa with frequency of 10-15% suggesting its recent occurrence. These findings will help in monitoring the spread and evolution of carbamate resistance and improve the design of effective resistance management strategies to control this malaria vector

Genomic Footprints of Selective Sweeps from Metabolic Resistance to Pyrethroids in African Malaria Vectors Are Driven by Scale up of Insecticide-Based Vector Control

Insecticide resistance in mosquito populations threatens recent successes in malaria prevention. Elucidating patterns of genetic structure in malaria vectors to predict the speed and direction of the spread of resistance is essential to get ahead of the `resistance curve' and to avert a public health catastrophe. Here, applying a combination of microsatellite analysis, whole genome sequencing and targeted sequencing of a resistance locus, we elucidated the continent-wide population structure of a major African malaria vector, Anopheles funestus. We identified a major selective sweep in a genomic region controlling cytochrome P450-based metabolic resistance conferring high resistance to pyrethroids. This selective sweep occurred since 2002, likely as a direct consequence of scaled up vector control as revealed by whole genome and fine-scale sequencing of pre- and post-intervention populations. Fine-scaled analysis of the pyrethroid resistance locus revealed that a resistanceassociated allele of the cytochrome P450 monooxygenase CYP6P9a has swept through southern Africa to near fixation, in contrast to high polymorphism levels before interventions, conferring high levels of pyrethroid resistance linked to control failure. Population structure analysis revealed a barrier to gene flow between southern Africa and other areas, which may prevent or slow the spread of the southern mechanism of pyrethroid resistance to other regions. By identifying a genetic signature of pyrethroid-based interventions, we have demonstrated the intense selective pressure that control interventions exert on mosquito populations. If this level of selection and spread of resistance continues unabated, our ability to control malaria with current interventions will be compromised

The highly polymorphic CYP6M7 cytochrome P450 gene partners with the directionally selected CYP6P9a and CYP6P9b genes to expand the pyrethroid resistance front in the malaria vector Anopheles funestus in Africa

Background: Pyrethroid resistance in the major malaria vector Anopheles funestus is rapidly expanding across Southern Africa. It remains unknown whether this resistance has a unique origin with the same molecular basis or is multifactorial. Knowledge of the origin, mechanisms and evolution of resistance are crucial to designing successful resistance management strategies. Results: Here, we established the resistance profile of a Zambian An. funestus population at the northern range of the resistance front. Similar to other Southern African populations, Zambian An. funestus mosquitoes are resistant to pyrethroids and carbamate, but in contrast to populations in Mozambique and Malawi, these insects are also DDT resistant. Genome-wide microarray-based transcriptional profiling and qRT-PCR revealed that the cytochrome P450 gene CYP6M7 is responsible for extending pyrethroid resistance northwards. Indeed, CYP6M7 is more over-expressed in Zambia [fold-change (FC) 37.7; 13.2 for qRT-PCR] than CYP6P9a (FC15.6; 8.9 for qRT-PCR) and CYP6P9b (FC11.9; 6.5 for qRT-PCR), whereas CYP6P9a and CYP6P9b are more highly over-expressed in Malawi and Mozambique. Transgenic expression of CYP6M7 in Drosophila melanogaster coupled with in vitro assays using recombinant enzymes and assessments of kinetic properties demonstrated that CYP6M7 is as efficient as CYP6P9a and CYP6P9b in conferring pyrethroid resistance. Polymorphism patterns demonstrate that these genes are under contrasting selection forces: the exceptionally diverse CYP6M7 likely evolves neutrally, whereas CYP6P9a and CYP6P9b are directionally selected. The higher variability of CYP6P9a and CYP6P9b observed in Zambia supports their lesser role in resistance in this country. Conclusion: Pyrethroid resistance in Southern Africa probably has multiple origins under different evolutionary forces, which may necessitate the design of different resistance management strategies

Directionally selected cytochrome P450 alleles are driving the spread of pyrethroid resistance in the major malaria vector Anopheles funestus

Pyrethroid insecticides are critical for malaria control in Africa. However, resistance to this insecticide class in the malaria vector Anopheles funestus is spreading rapidly across Africa, threatening the success of ongoing and future malaria control programs. The underlying resistance mechanisms driving the spread of this resistance in wild populations remain largely unknown. Here, we show that increased expression of two tandemly duplicated P450 genes, CYP6P9a and CYP6P9b, is themain mechanism driving pyrethroid resistance in Malawi and Mozambique, two southern African countries where this insecticide class forms the mainstay of malaria control. Genome-wide transcription analysis using microarray and quantitative RT-PCR consistently revealed that CYP6P9a and CYP6P9b are the two genes most highly overexpressed (>50-fold; q < 0.01) in permethrin-resistant mosquitoes. Transgenic expression of CYP6P9a and CYP6P9b in Drosophila melanogaster demonstrated that elevated expression of either of these genes confers resistance to both type I (permethrin) and type II (deltamethrin) pyrethroids. Functional characterization of recombinant CYP6P9b confirmed that this protein metabolized both type I (permethrin and bifenthrin) and type II (deltamethrin and Lambda-cyhalothrin) pyrethroids but not DDT. Variability analysis identified that a single allele of each of these genes is predominantly associated with pyrethroid resistance in field populations from both countries, which is suggestive of a single origin of this resistance that has since spread across the region. Urgent resistance management strategies should be implemented in this region to limit a further spread of this resistance and minimize its impact on the success of ongoing malaria control programs

Africa-wide population structure analysis.

<p><b>A)</b> Gene diversity of 11 microsatellites from throughout the genome, showing a loss of diversity at the telomeric end of chromosome 2R. <b>B)</b> Gene diversity of 8 microsatellites on chromosome 2R (including AFUB6, FunR and FunO) shows that the loss of diversity is restricted to AFUB6 and FunR, the microsatellites located near the pyrethroid resistance QTL <i>rp1</i>. <b>C)</b> Neighbor-Joining tree based on pairwise <i>F</i>_<i>st</i> among population samples, estimated using 9 neutrally evolving microsatellites from throughout the genome (excluding AFUB6 and FunR on chromosome 2R, which may be evolving under positive selection). <b>D)</b> Barplot of assignment probabilities of individual genotypes to two ancestral clusters (the most likely number estimated from the data) estimated using Bayesian population structure analysis under an admixture model. Each bar is an individual genotype for 9 neutrally evolving microsatellites from throughout the genome (excluding AFUB6 and FunR). In panel A, points from left to right represent the following microsatellites: FunQ (on chromosome X); AFUB6, FunR, FunO (on 2R); AFUB11, FunL, AFUB10 (on 2L); AFND7, AFND19 (on 3R); FunF and AFUB12 (on 3L). In panel B, points from left to right represent AFUB3, AFND40, AFUB6, FunR, AFND6, AFND30, AFND32 and FunO (all on 2R).</p

The selective sweep at <i>rp1</i> in southern Africa coincides with the scale-up in pyrethroid use in malaria control.

<p><b>A)</b> Gene diversity at microsatellites on chromosome 2R in mosquitoes collected before widespread pyrethroid-based intervention in Malawi, 2002 (purple) and Mozambique, 2002 (red), and ‘post-intervention’ in Malawi, 2010 (green) and Mozambique, 2009 (yellow). <b>B)</b> Fine-scale nucleotide sequence analysis of the 120kb <i>rp1</i> locus in Cameroon (orange) or pre-intervention samples (Malawi (CKW2002) = brown and Mozambique (MOZ2009) = pink) compared to Post intervention samples from Chikwawa (green), Salima (light blue), Nkhotakota (blue) Malawi, Chokwe (purple) Mozambique, and Kaoma (dark blue) Zambia. <b>C)</b> TCS haplotype network at ‘BAC25’. Haplotypes including sequences from more than one location are denoted by an H and include the frequency, haplotypes from one location Malawi (blue) and Mozambique (yellow) are only present in pre-intervention samples. <b>D)</b> Change in average pairwise diversity (Pi) in the <i>CYP6P9a</i> gene pre- <i>vs</i>. post-intervention in Malawi and Mozambique. <b>E)</b> Phylogeny of <i>CYP6P9a</i> sequences including both Malawi (Ckw) and Mozambique (Moz) shows that post-intervention samples (red) are almost completely homogenous while pre-intervention samples (black) are diverse.</p

Africa-wide analysis of genetic diversity across the <i>rp1</i> pyrethroid resistance locus.

<p><b>A)</b> Genetic diversity (pi) across the 120kb <i>rp1</i> in Cameroon (orange), Malawi (blue), and Mozambique (green). <b>B)</b> Phylogeny of the ‘BAC25’ fragment (located 25kb along the BAC sequence and 9kb upstream of the <i>CYP6P9a</i> gene), which shows the most extreme difference in diversity between Cameroon (orange) and southern populations Malawi (blue) and Mozambique (green), which form a single clade. <b>C)</b> Phylogeny of the <i>CYP6P9a</i> gene sampled from throughout Africa, showing clear geographical divergence between southern Africa (Malawi and Mozambique; 100% bootstrap support), East Africa (Uganda; 87% bootstrap support) and West/Central Africa (Ghana, Benin, Cameroon; 78% bootstrap support). <b>D)</b> Haplotype network for Non-synonymous nucleotide variants in <i>CYP6P9a</i>. Light blue = haplotype shared between Malawi and Mozambique (MAL/MOZ); pink = haplotype shared between Benin, Cameroon and Ghana (BN/CAM/GH); teal = Benin (BN); red = Ghana (GH); orange = Cameroon (CAM); green = Mozambique (MOZ); blue = Malawi (MAL); purple = Uganda (UG). The size of the shapes is proportional to the frequency of the haplotype and numbers on each branch show the mutational steps separating haplotypes.</p