blood-stage

Malaria is a disease affecting hundreds of millions of people across the world, mainly in developing countries and especially in sub-Saharan Africa. It is the cause of hundreds of thousands of deaths each year and there is an ever-present need to identify and develop effective new therapies to tackle the disease and overcome increasing drug resistance. Here, we extend a previous study in which a number of partners collaborated to develop a consensus in silico model that can be used to identify novel molecules that may have antimalarial properties.

Dihydroartemisinin-piperaquine is a recommended first-line artemisinin combination therapy for falciparum malaria. Piperaquine is also under consideration for other antimalarial combination therapies. The aim of this study was to develop a pharmacokinetic-pharmacodynamic model that could be used to optimize the use of piperaquine in new antimalarial combination therapies. The pharmacokinetic-pharmacodynamic model was developed using data from a previously reported dose-ranging study where 24 healthy volunteers were inoculated 1,800 blood-stage Plasmodium falciparum parasites.

Antibodies play a critical protective role in the host response to blood-stage malaria infection. The role of cytokines in shaping the antibody response to blood-stage malaria is unclear. Interferon lambda (IFNλ), a type III interferon, is a cytokine produced early during blood-stage malaria infection that has an unknown physiological role during malaria infection.

Sequencing technology advancements opened new opportunities to use transcriptomics for studying malaria pathology and epidemiology. Even though in recent years the study of whole parasite transcriptome proved to be essential in understanding parasite biology there is no compiled up-to-date reference protocol for the efficient generation of transcriptome data from growing number of samples. Here, a comprehensive methodology on how to preserve, extract, amplify, and sequence full-length mRNA transcripts from Plasmodium-infected blood samples is presented that can be fully streamlined for high-throughput studies.