6 research outputs found

    Potential metabolic resistance mechanisms to ivermectin in Anopheles gambiae: a synergist bioassay study.

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    BACKGROUND Despite remarkable success obtained with current malaria vector control strategies in the last 15 years, additional innovative measures will be needed to achieve the ambitious goals for malaria control set for 2030 by the World Health Organization (WHO). New tools will need to address insecticide resistance and residual transmission as key challenges. Endectocides such as ivermectin are drugs that kill mosquitoes which feed on treated subjects. Mass administration of ivermectin can effectively target outdoor and early biting vectors, complementing the still effective conventional tools. Although this approach has garnered attention, development of ivermectin resistance is a potential pitfall. Herein, we evaluate the potential role of xenobiotic pumps and cytochrome P450 enzymes in protecting mosquitoes against ivermectin by active efflux and metabolic detoxification, respectively. METHODS We determined the lethal concentration 50 for ivermectin in colonized Anopheles gambiae; then we used chemical inhibitors and inducers of xenobiotic pumps and cytochrome P450 enzymes in combination with ivermectin to probe the mechanism of ivermectin detoxification. RESULTS Dual inhibition of xenobiotic pumps and cytochromes was found to have a synergistic effect with ivermectin, greatly increasing mosquito mortality. Inhibition of xenobiotic pumps alone had no effect on ivermectin-induced mortality. Induction of xenobiotic pumps and cytochromes may confer partial protection from ivermectin. CONCLUSION There is a clear pathway for development of ivermectin resistance in malaria vectors. Detoxification mechanisms mediated by cytochrome P450 enzymes are more important than xenobiotic pumps in protecting mosquitoes against ivermectin

    Detection of Plasmodium falciparum infected Anopheles gambiae using near-infrared spectroscopy

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    Background: Large-scale surveillance of mosquito populations is crucial to assess the intensity of vector-borne disease transmission and the impact of control interventions. However, there is a lack of accurate, cost-effective and high-throughput tools for mass-screening of vectors. Methods: A total of 750 Anopheles gambiae (Keele strain) mosquitoes were fed Plasmodium falciparum NF54 gametocytes through standard membrane feeding assay (SMFA) and afterwards maintained in insectary conditions to allow for oocyst (8 days) and sporozoite development (14 days). Thereupon, each mosquito was scanned using near infra-red spectroscopy (NIRS) and processed by quantitative polymerase chain reaction (qPCR) to determine the presence of infection and infection load. The spectra collected were randomly assigned to either a training dataset, used to develop calibrations for predicting oocyst- or sporozoite-infection through partial least square regressions (PLS); or to a test dataset, used for validating the calibration’s prediction accuracy. Results: NIRS detected oocyst- and sporozoite-stage P. falciparum infections with 88% and 95% accuracy, respectively. This study demonstrates proof-of-concept that NIRS is capable of rapidly identifying laboratory strains of human malaria infection in African mosquito vectors. Conclusions: Accurate, low-cost, reagent-free screening of mosquito populations enabled by NIRS could revolutionize surveillance and elimination strategies for the most important human malaria parasite in its primary African vector species. Further research is needed to evaluate how the method performs in the field following adjustments in the training datasets to include data from wild-caught infected and uninfected mosquitoes

    Correction to: Detection of Plasmodium falciparum infected Anopheles gambiae using near-infrared spectroscopy

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    Following publication of the original article [1], it was flagged that the name of the author Lisa Ranford-Cartwright had been (incorrectly) given as ‘Lisa-Ranford Cartwright

    Replication Data for: Near infrared spectra and calibration for detection of malaria infection in Anopheles gambiae (Keele strain)

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    Anopheles gambiae (Keele Strain) mosquitoes were infected in the lab with cultured Plasmodium falciparum gametocytes (PfN54) to generate oocyst and sporozoite infected vectors. Controls, uninfected mosquitoes, were generated by feeding mosquitoes on the same blood after gametogenesis had occurred which was triggered by dropping the temperature in the glass feeders to below 30 degrees Celsius. After feeding, mosquitoes were kept for 7 and 14 days to allow parasite development after which each individual mosquito was scanned with near infrared spectroscopy (NIRS) and stored at -20 until processed by qPCR (quantitative polymerase chain reaction) for confirmation of infection and quantification of parasite load. The data shared is composed of all the spectra that were collected (in .spc format for GRAMS IQ software) labeled with a unique identifier which links to the STATA files where the mean number of parasite genomes and age for each individual mosquito are listed. The files used to generate the calibration through partial least square (PLS) regression on GRAMS IQ have also been shared (.tfdx) along with the calibration file (.cal) for uploading on IQ Predict software. We have also shared the prediction outputs of the independent samples that were predicted with the calibrations here developed.</p

    A chromosomal reference genome sequence for the malaria mosquito, Anopheles moucheti, Evans, 1925

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    International audienceWe present a genome assembly from an individual male Anopheles moucheti (the malaria mosquito; Arthropoda; Insecta; Diptera; Culicidae), from a wild population in Cameroon. The genome sequence is 271 megabases in span. The majority of the assembly is scaffolded into three chromosomal pseudomolecules with the X sex chromosome assembled. The complete mitochondrial genome was also assembled and is 15.5 kilobases in length
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