Biology subjects

Sanou, A.

Publications and source records attributed to Sanou, A..

4 recordsLinked to original sources

bioRxiv2026

Multi-omics analysis identifies loci associated with pyrethroid resistance across sister species in the Anopheles gambiae species complex

The Anopheles gambiae species complex includes An. gambiae, An. coluzzii, and An. arabiensis, three of the four major malaria vector species across Africa. Insecticide-based vector control remains the most critical tool in the fight against malaria, with a heavy reliance on pyrethroid insecticides. However, widespread pyrethroid resistance jeopardises the effectiveness of these methods. Currently, the number of diagnostic markers available to track pyrethroid resistance in endemic settings is limited, focusing mainly on changes at the insecticide target site. Genetic analysis of seven insecticide-resistant populations from West Africa, a region with intense insecticide resistance, reveals shared loci associated with pyrethroid resistance among the sister species of the An. gambiae complex including kdr, GSTE1-8 and the CYP6P region. Notably, a mutation in the voltage-gated sodium channel, I1527T, previously identified in An. coluzzii and An. gambiae, was detected in wild-caught An. arabiensis from Burkina Faso. Additionally, a mutation, L207I, in GSTE7 common to An. coluzzii and An. arabiensis, significantly increases survivorship to deltamethrin. With the additional integration of RNAseq and data from the Anopheles gambiae 1000 genomes project, we were able to identify putative eQTLs associated with the expression of major insecticide resistance-related transcripts, such as CYP6P3, CYP9K1 and CYP6AA1. This study reveals several potential diagnostic markers of resistance that can be implemented in endemic settings and identifies putative introgression between An. arabiensis and An. coluzzii in Burkina Faso.

genetics↗

bioRxiv2025

Do epidemiologically impactful vector control interventions disrupt mosquito population structure?

Large epidemiological impacts resulting from disease vector control interventions are typically associated with significant disruption of vector populations. While vector density is a frequently measured response, impacts on demography and connectivity are suspected but rarely quantified. We analysed low-coverage whole-genome sequence data of 893 Anopheles gambiae mosquitoes collected between 2014-2015 during a cluster-randomized control trial (cRCT) in Burkina Faso to compare a pyrethroid-only net (ITN) with a pyrethroid-pyriproxyfen (ITN-PPF) net. Despite reductions of clinical malaria by 12%, and vector density by 22% in the ITN-PPF arm, we found no significant changes in An. gambiae population genetic structure or diversity. We found remarkably low population differentiation, and a lack of discernible clustering by treatment, time, or space. Nucleotide diversity and inbreeding coefficient remained stable between treatments, and genome-wide scans showed no putative signatures of selection between trial arms. These results show that ITN-PPF did not alter An. gambiae genetic structure, possibly due to large, vagile populations in West Africa. More widely, this is first evidence that epidemiologically meaningful reductions in vector density may not impact genetic diversity or connectivity, and challenges what constitutes adequate vector control in large populations.

ecology↗

bioRxiv2024

Integrating data from across insecticide resistance bioassay types using a mechanistic model incorporating mosquito genetic variation and behaviour

Malaria claims approximately 500,000 lives each year, and insecticide-treated nets (ITNs), which kill mosquitoes that transmit the disease, remain the most effective intervention. However, resistance to pyrethroids, the primary insecticide class used in ITNs, has risen dramatically in Africa, making it difficult to assess the current public health impact of pyrethroid-ITNs. Past work has modelled the relation between pyrethroid susceptibility measured in discriminating-dose susceptibility bioassays and ITN effectiveness in experimental hut trials. Here, we introduce a new predictive approach that accounts for heterogeneity in insecticide resistance within wild mosquito populations, for example, due to genetic variability, by incorporating data from newly recommended intensity-dose susceptibility bioassays. We fit our mathematical model to a comprehensive data set that combines discriminating dose bioassays from all over Africa, intensity dose bioassays from Burkina Faso, and concurrent experimental hut trials. Our analysis estimates location- and insecticide-specific variation in resistance heterogeneity in Burkina Faso and quantifies differences in insecticide exposure in bioassays and experimental huts. By providing a mechanistic understanding of these experimental data, our approach could be integrated into malaria transmission models to account for the public health impact of insecticide resistance detected by surveillance programmes. Author summaryBednets treated with insecticides that kill mosquitoes have been responsible for major reductions in malaria burden over recent decades. However, the spread of insecticide resistance in mosquito populations threatens to slow or reverse these gains. It is therefore important to be able to gauge insecticide resistance in local mosquito populations and the remaining effectiveness of bednets. Important tools for quantifying insecticide resistance include susceptibility bioassays, which expose mosquitoes to specific insecticide doses and measure mortality, and experimental hut trials, which aim to mimic how mosquitoes interact with insecticides on bednets in the field. Here, we develop a mathematical model that incorporates mechanistic features of how mosquitoes interact with insecticides in both types of experiments. We show that this model can accurately predict mosquito mortality in experimental hut trials using data from intensity-dose susceptibility bioassays. These bioassays are more sensitive than traditional discriminating-dose assays while being less costly and logistically demanding than experimental hut trials. Our model provides a more granular understanding of insecticide resistance measurements and could be embedded into malaria transmission models to predict the public health impact of insecticide resistance measured by surveillance programmes.

bioinformatics↗

bioRxiv2018

Infection of highly insecticide-resistant malaria vector Anopheles coluzzii with an environmentally friendly entomopathogenic bacteria Chromobacterium violaceum reduces its survival, blood feeding propensity and fecundity

This is now a concern that malaria eradication will not be achieved without the introduction of novel control tools. Microbiological control might be able to make a greater contribution to vector control in the future. Here, we studied the impact of Chromobacterium violaceum infections isolated from wild caught Anopheles gambiae s.l. mosquitoes in Burkina Faso on mosquito survival, blood feeding and fecundity propensy. C. violaceum kills pyrethroid resistant mosquitoes An. coluzzii (LT80 ~ at 108 bacteria cell/ml of sugar meal). Interestingly, this bacterium had other negative effects on mosquito lifespan by significantly reducing (~59%, P<0.001) the mosquito feeding willingness from day 4-post infection to 9-day post infection. Moreover, C.violaceum considerably jeopardized the mosquito egg laying and hatching of mosquitoes by ~77.93% and ~22 % respectively. Mosquitoes infected with C. violaceum also showed significantly higher retention rates of immature eggs and follicles. These data showed important entomopathogenic properties of Burkina Faso C. violaceum strains. However, additional studies as the sequencing of C. violaceum genome and the potential toxins secreted will certainly provide useful information render it a potential candidate for the biological control strategies of malaria.

microbiology↗