Severe malaria is caused by the apicomplexan parasite Plasmodium falciparum. Despite decades of research the unique biology of these parasites has made it challenging to establish high throughput genetic approaches for identification of therapeutic targets. Using transposon mutagenesis of P. falciparum in an approach that exploited its AT-rich genome we generated >38,000 mutants, saturating the genome and defining fitness costs for 95% of genes. Of 5,399 genes we found ~3,000 genes are essential for optimal growth of asexual blood-stages in vitro. Our study defines ∼1000 essential genes, including genes associated with drug resistance, vaccine candidates, and conserved proteins of unknown function. We validated this approach by testing proteasome pathways for individual mutants associated with artemisinin sensitivity.

A major cause of the paucity of new starting points for drug discovery is the lack of interaction between academia and industry. Much of the global resource in biology is present in universities, whereas the focus of medicinal chemistry is still largely within industry. Open source drug discovery, with sharing of information, is clearly a first step towards overcoming this gap. But the interface could especially be bridged through a scale-up of open sharing of physical compounds, which would accelerate the finding of new starting points for drug discovery. The Medicines for Malaria Venture Malaria Box is a collection of over 400 compounds representing families of structures identified in phenotypic screens of pharmaceutical and academic libraries against the Plasmodium falciparum malaria parasite. The set has now been distributed to almost 200 research groups globally in the last two years, with the only stipulation that information from the screens is deposited in the public domain. This paper reports for the first time on 236 screens that have been carried out against the Malaria Box and compares these results with 55 assays that were previously published, in a format that allows a meta-analysis of the combined dataset. The combined biochemical and cellular assays presented here suggest mechanisms of action for 135 (34%) of the compounds active in killing multiple life-cycle stages of the malaria parasite, including asexual blood, liver, gametocyte, gametes and insect ookinete stages. In addition, many compounds demonstrated activity against other pathogens, showing hits in assays with 16 protozoa, 7 helminths, 9 bacterial and mycobacterial species, the dengue fever mosquito vector, and the NCI60 human cancer cell line panel of 60 human tumor cell lines. Toxicological, pharmacokinetic and metabolic properties were collected on all the compounds, assisting in the selection of the most promising candidates for murine proof-of-concept experiments and medicinal chemistry programs. The data for all of these assays are presented and analyzed to show how outstanding leads for many indications can be selected. These results reveal the immense potential for translating the dispersed expertise in biological assays involving human pathogens into drug discovery starting points, by providing open access to new families of molecules, and emphasize how a small additional investment made to help acquire and distribute compounds, and sharing the data, can catalyze drug discovery for dozens of different indications. Another lesson is that when multiple screens from different groups are run on the same library, results can be integrated quickly to select the most valuable starting points for subsequent medicinal chemistry efforts.

Genetic screening using random transposon insertions has been a powerful tool for uncovering biology in prokaryotes, where whole-genome saturating screens have been performed in multiple organisms. In eukaryotes, such screens have proven more problematic, in part because of the lack of a sensitive and robust system for identifying transposon insertion sites. We here describe quantitative insertion-site sequencing, or QIseq, which uses custom library preparation and Illumina sequencing technology and is able to identify insertion sites from both the 5 ′ and 3 ′ ends of the transposon, providing an inbuilt level of validation. The approach was developed using piggyBac mutants in the human malaria parasite Plasmodium falciparum but should be applicable to many other eukaryotic genomes. QIseq proved accurate, confirming known sites in >100 mutants, and sensitive, identifying and monitoring sites over a >10,000-fold dynamic range of sequence counts. Applying QIseq to uncloned parasites shortly after transfections revealed multiple insertions in mixed populations and suggests that >4000 independent mutants could be generated from relatively modest scales of transfection, providing a clear pathway to genome-scale screens in P. falciparum. QIseq was also used to monitor the growth of pools of previously cloned mutants and reproducibly differentiated between deleterious and neutral mutations in competitive growth. Among the mutants with fitness defects was a mutant with a piggyBac insertion immediately upstream of the kelch protein K13 gene associated with artemisinin resistance, implying mutants in this gene may have competitive fitness costs. QIseq has the potential to enable the scale-up of piggyBac-mediated genetics across multiple eukaryotic systems.