BackgroundMetabolic resistance to insecticides is the biggest threat to the continued effectiveness of malaria vector control. However, its underlying molecular basis, crucial for successful resistance management, remains poorly characterized.ResultsHere, we demonstrate that the single amino acid change L119F in an upregulated glutathione S-transferase gene, GSTe2, confers high levels of metabolic resistance to DDT in the malaria vector Anopheles funestus. Genome-wide transcription analysis revealed that GSTe2 was the most over-expressed detoxification gene in DDT and permethrin-resistant mosquitoes from Benin. Transgenic expression of GSTe2 in Drosophila melanogaster demonstrated that over-transcription of this gene alone confers DDT resistance and cross-resistance to pyrethroids. Analysis of GSTe2 polymorphism established that the point mutation is tightly associated with metabolic resistance to DDT and its geographical distribution strongly correlates with DDT resistance patterns across Africa. Functional characterization of recombinant GSTe2 further supports the role of the L119F mutation, with the resistant allele being more efficient at metabolizing DDT than the susceptible one. Importantly, we also show that GSTe2 directly metabolizes the pyrethroid permethrin. Structural analysis reveals that the mutation confers resistance by enlarging the GSTe2 DDT-binding cavity, leading to increased DDT access and metabolism. Furthermore, we show that GSTe2 is under strong directional selection in resistant populations, and a restriction of gene flow is observed between African regions, enabling the prediction of the future spread of this resistance.ConclusionsThis first DNA-based metabolic resistance marker in mosquitoes provides an essential tool to track the evolution of resistance and to design suitable resistance management strategies.

The artemisinin (ART)-based antimalarials have contributed significantly to reducing global malaria deaths over the past decade, but we still do not know how they kill parasites. To gain greater insight into the potential mechanisms of ART drug action, we developed a suite of ART activity-based protein profiling probes to identify parasite protein drug targets in situ. Probes were designed to retain biological activity and alkylate the molecular target(s) of Plasmodium falciparum 3D7 parasites in situ. Proteins tagged with the ART probe can then be isolated using click chemistry before identification by liquid chromatography-MS/MS. Using these probes, we define an ART proteome that shows alkylated targets in the glycolytic, hemoglobin degradation, antioxidant defense, and protein synthesis pathways, processes essential for parasite survival. This work reveals the pleiotropic nature of the biological functions targeted by this important class of antimalarial drugs.

The fight against diseases spread by mosquitoes and other insects has enormous environmental, economic and social consequences. Chemical insecticides remain the first line of defence but the control of diseases, especially malaria and dengue fever, is being increasingly undermined by insecticide resistance. Mosquitoes have a large repertoire of P450s (over 100 genes). By pinpointing the key enzymes associated with insecticide resistance we can begin to develop new tools to aid the implementation of control interventions and reduce their environmental impact on Earth. Recent technological advances are helping us to build a functional profile of the P450 determinants of insecticide metabolic resistance in mosquitoes. Alongside, the cross-responses of mosquito P450s to insecticides and pollutants are also being investigated. Such research will provide the means to produce diagnostic tools for early detection of P450s linked to resistance. It will also enable the design of new insecticides with optimized efficacy in different environments.

This new resistance will have serious effects on malaria control.

Phasor measurement units (PMUs) are considered as a promising tool for future monitoring, protection and control of power systems. In this paper, a unified approach is proposed in order to determine the optimal number and locations of PMUs to make the system measurement model observable and thereby can be used for power system state estimation. The PMU placement problem is formulated as a binary integer linear programming (BILP), in which the binary decision variables (0, 1) determine whether to install a PMU at each bus, while preserving the system observability and lowest system metering economy. The proposed approach integrates the impacts of both existing conventional power injection/flow measurements (if any) and the possibility of single or multiple PMU loss into the decision strategy of the optimal PMU allocation. Unlike other available techniques, the network topology remains unaltered for the inclusion of conventional measurements, and therefore the network connectivity matrix is built only once based on the original network topology. The mathematical formulation of the problem maintains the original bus ordering of the system under study, and therefore the solution directly points at the optimal PMU locations. Simulations using Matlab are conducted on a simple testing seven-bus system, as well as on different IEEE systems (14-bus, 30-bus, 57-bus, and 118-bus) to prove the validity of the proposed method. The results obtained in this paper are compared with those published before in literature.