RESUMEN
One of the key obstacles to malaria elimination is largely attributed to Plasmodium vivax's ability to form resilient hypnozoites in the host liver that cause relapsing infections. As a result, interruption of P. vivax transmission is difficult. P. vivax transmission occurs in Duffy-positive individuals and have been mainly thought to be absent in Africa. However, increasing studies using molecular tools detected P. vivax among Duffy-negative individuals in various African countries. Studies on the African P. vivax has been severely limited because most of malaria control program focus mainly on falciparum malaria. In addition, there is a scarcity of laboratory infrastructures to overcome the biological obstacles posed by P. vivax. Herein, we established field transmission of Ethiopian P. vivax for routine sporozoite supply followed by liver stage infection in Mali. Furthermore, we evaluated local P. vivax hypnozoites and schizonts susceptibilities to reference antimalarial drugs. The study enabled the assessment of local African P. vivax hypnozoite production dynamics. Our data displayed the ability of the African P. vivax to produce hypnozoite forms ex-vivo at different rates per field isolate. We report that while tafenoquine (1µM) potently inhibited both hypnozoites and schizont forms; atovaquone (0.25µM) and the phosphatidylinositol-4-OH kinase (PI4K)-specific inhibitor KDU691 (0.5µM) showed no activity against hypnozoites forms. Unlike hypnozoites forms, P. vivax schizont stages were fully susceptible to both atovaquone (0.25µM) and the (PI4K)-specific inhibitor KDU691 (0.5µM). Together, the data revealed the importance of the local platform for further biological investigation and implementation of drug discovery program on the African P. vivax clinical isolates.
Asunto(s)
Antimaláricos , Malaria Vivax , Humanos , Antimaláricos/farmacología , Antimaláricos/uso terapéutico , Plasmodium vivax , Atovacuona , Malaria Vivax/tratamiento farmacológico , MalíRESUMEN
Imidazolopiperazine (IPZ), KAF156, a close analogue of GNF179, is a promising antimalarial candidate. IPZ is effective against Plasmodium falciparum and Plasmodium vivax clinical malaria in human with transmission blocking property in animal models and effective against liver stage parasites. Despite these excellent drug efficacy properties, in vitro parasites have shown resistance to IPZ. However, the mechanism of action and resistance of IPZ remained not fully understood. Here, we used transcriptomic analysis to elucidate mode of action of IPZs. We report, in wild-type parasites GNF179 treatment down regulated lipase enzymes, two metabolic pathways: the hydrolysis of Phosphoinositol 4,5-bipohosphate (PIP2) that produce diacyglycerol (DAG) and the cytosolic calcium Ca2+ homeostasis which are known to be essential for P. falciparum survival and proliferation, as well for membrane permeability and protein trafficking. Furthermore, in wild-type parasites, GNF179 repressed expression of Acyl CoA Synthetase, export lipase 1 and esterase enzymes. Thus, in wild-type parasites only, GNF179 treatment affected enzymes leading lipid metabolism, transport, and synthesis. Lastly, our data revealed that IPZs did not perturb known IPZ resistance genes markers pfcarl, pfact, and pfugt regulations, which are all instead possibly involved in the drug resistance that disturb membrane transport targeted by IPZ.
Asunto(s)
Malaria Falciparum , Malaria Vivax , Parásitos , Animales , Humanos , Plasmodium falciparum , Malaria Falciparum/parasitología , Perfilación de la Expresión Génica , Lipasa/metabolismoRESUMEN
We report an analysis of the propensity of the antimalarial agent cabamiquine, a Plasmodium-specific eukaryotic elongation factor 2 inhibitor, to select for resistant Plasmodium falciparum parasites. Through in vitro studies of laboratory strains and clinical isolates, a humanized mouse model, and volunteer infection studies, we identified resistance-associated mutations at 11 amino acid positions. Of these, six (55%) were present in more than one infection model, indicating translatability across models. Mathematical modelling suggested that resistant mutants were likely pre-existent at the time of drug exposure across studies. Here, we estimated a wide range of frequencies of resistant mutants across the different infection models, much of which can be attributed to stochastic differences resulting from experimental design choices. Structural modelling implicates binding of cabamiquine to a shallow mRNA binding site adjacent to two of the most frequently identified resistance mutations.
Asunto(s)
Antimaláricos , Parásitos , Animales , Ratones , Antimaláricos/farmacología , Aminoácidos , Sitios de Unión , Modelos Animales de EnfermedadRESUMEN
Microarray technology is widely used for gene expression research targeting the development of new drug treatments. In the case of a two-color microarray, the process starts with labeling DNA samples with fluorescent markers (cyanine 635 or Cy5 and cyanine 532 or Cy3), then mixing and hybridizing them on a chemically treated glass printed with probes, or fragments of genes. The level of hybridization between a strand of labeled DNA and a probe present on the array is measured by scanning the fluorescence of spots in order to quantify the expression based on the quality and number of pixels for each spot. The intensity data generated from these scans are subject to errors due to differences in fluorescence efficiency between Cy5 and Cy3, as well as variation in human handling and quality of the sample. Consequently, data have to be normalized to correct for variations which are not related to the biological phenomena under investigation. Among many existing normalization procedures, we have implemented the quantile adjustment method using the python computer language, and produced a module which can be run via an HTML dynamic form. This module is composed of different functions for data files reading, intensity and ratio computations and visualization. The current version of the HTML form allows the user to visualize the data before and after normalization. It also gives the option to subtract background noise before normalizing the data. The output results of this module are in agreement with the results of other normalization tools.