Quantitative insertion-site sequencing (QIseq) for high throughput phenotyping of transposon mutants

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

Uncovering the essential genes of the human malaria parasite Plasmodium falciparum by saturation mutagenesis

Malaria is caused by eukaryotic Plasmodium spp. parasites that classically infect red blood cells. These are difficult organisms to investigate genetically because of their AT-rich genomes. Zhang et al. have exploited this peculiarity by using piggyBac transposon insertion sites to achieve saturation-level mutagenesis for identifying and ranking essential genes and drug targets (see the Perspective by White and Rathod). Genes that are current candidates for drug targets were identified as essential, in contrast to many vaccine target genes. Notably, the proteasome degradation pathway was confirmed as a target for developing therapeutic interventions because of the several essential genes involved and the link to the mechanism of action of the current frontline drug, artemisinin

Phenotypic Screens Identify Parasite Genetic Factors Associated with Malarial Fever Response in Plasmodium falciparum piggyBac Mutants

ABSTRACT Malaria remains one of the most devastating parasitic diseases worldwide, with 90% of the malaria deaths in Africa in 2013 attributable to Plasmodium falciparum. The clinical symptoms of malaria include cycles of fever, corresponding to parasite rupture from red blood cells every 48 h. Parasite pathways involved in the parasite’s ability to survive the host fever response, and indeed, the functions of ~40% of P. falciparum genes as a whole, are still largely unknown. Here, we evaluated the potential of scalable forward-genetic screening methods to identify genes involved in the host fever response. We performed a phenotypic screen for genes linked to the parasite response to febrile temperatures by utilizing a selection of single-disruption P. falciparum mutants generated via random piggyBac transposon mutagenesis in a previous study. We identified several mutants presenting significant phenotypes in febrile response screens compared to the wild type, indicating possible roles for the disrupted genes in this process. We present these initial studies as proof that forward genetics can be used to gain insight into critical factors associated with parasite biology. IMPORTANCE Though the P. falciparum genome sequence has been available for many years, ~40% of its genes do not have informative annotations, as they show no detectable homology to those of studied organisms. More still have not been evaluated via genetic methods. Scalable forward-genetic approaches that allow interrogation of gene function without any pre-existing knowledge are needed to hasten understanding of parasite biology, which will expedite the identification of drug targets and the development of future interventions in the face of spreading resistance to existing frontline drugs. In this work, we describe a new approach to pursue forward-genetic phenotypic screens for P. falciparum to identify factors associated with virulence. Future large-scale phenotypic screens developed to probe other such interesting phenomena, when considered in parallel, will prove a powerful tool for functional annotation of the P. falciparum genome, where so much remains undiscovered

Artemisinin resistance phenotypes and K13 inheritance in a Plasmodium falciparum cross and Aotus model

Concerns about malaria parasite resistance to treatment with artemisinin drugs (ARTs) have grown with findings of prolonged parasite clearance t1/2s (>5 h) and their association with mutations in Plasmodium falciparum Kelch-propeller protein K13. Here, we describe a P. falciparum laboratory cross of K13 C580Y mutant with C580 wild-type parasites to investigate ART response phenotypes in vitro and in vivo. After genotyping >400 isolated progeny, we evaluated 20 recombinants in vitro: IC50 measurements of dihydroartemisinin were at similar low nanomolar levels for C580Y- and C580-type progeny (mean ratio, 1.00; 95% CI, 0.62–1.61), whereas, in a ring-stage survival assay, the C580Y-type progeny had 19.6-fold (95% CI, 9.76–39.2) higher average counts. In splenectomized Aotus monkeys treated with three daily doses of i.v. artesunate, t1/2 calculations by three different methods yielded mean differences of 0.01 h (95% CI, −3.66 to 3.67), 0.80 h (95% CI, −0.92 to 2.53), and 2.07 h (95% CI, 0.77–3.36) between C580Y and C580 infections. Incidences of recrudescence were 57% in C580Y (4 of 7) versus 70% in C580 (7 of 10) infections (−13% difference; 95% CI, −58% to 35%). Allelic substitution of C580 in a C580Y-containing progeny clone (76H10) yielded a transformant (76H10C580Rev) that, in an infected monkey, recrudesced regularly 13 times over 500 d. Frequent recrudescences of ART-treated P. falciparum infections occur with or without K13 mutations and emphasize the need for improved partner drugs to effectively eliminate the parasites that persist through the ART component of combination therapy

On Cartan matrices with two parameters (Cohomology theory of finite groups and related topics)

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

Metabolomic and chemogenomic profiling.

<p>(A) Metabolic profiling: Heat map showing metabolic fingerprints of 80 Malaria Box compounds and atovaquone control. Parasite extracts were analyzed by LC-MS, and changes in metabolite pools were calculated for drug-treated parasites as compared to untreated controls. Hierarchical clustering was performed on ²log-fold changes in metabolites (data in <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1005763#ppat.1005763.s003" target="_blank">S2 Table</a>), scaled from -3 to +3. Six of seven compounds (indicated in red) reported to target <i>Pf</i>ATP4 [<a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1005763#ppat.1005763.ref025" target="_blank">25</a>] showed a distinct metabolic response characterized by the accumulation of dNTPs and a decrease in hemoglobin-derived peptides. A large cluster of compounds (indicated in blue) clustered with the atovaquone control (indicated in orange), and exhibit an atovaquone-like signature characterized by dysregulation of pyrimidine biosynthesis, and showed a distinct metabolic response characterized by the accumulation of dNTPs and a decrease in hemoglobin-derived peptides. (B) Chemogenomic profiling: A collection of 35 <i>P</i>. <i>falciparum</i> single insertion <i>piggyBac</i> mutants were profiled with 53 MMV compounds and 3 artemisinin (ART) compounds [Artesunate (AS), Artelinic acid (AL) and Artemether (AM)] for changes in IC₅₀ relative to the wild-type parent NF54 (data in <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1005763#ppat.1005763.s004" target="_blank">S3 Table</a>, genes queried in <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1005763#ppat.1005763.s005" target="_blank">S4 Table</a>). Clone PB58 carried a <i>piggyBac</i> insertion in the promoter region of the K13 gene and has an increased sensitivity to ART compounds as do PB54 and PB55 [<a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1005763#ppat.1005763.ref033" target="_blank">33</a>]. Drug-drug relationships based on similarities in IC₅₀ deviations of compounds generated with <i>piggyBac</i> mutants created chemogenomic profiles used to define drug-drug relationships. The significance of similarity in MoA between Malaria Box compounds and ART was evaluated by Pearson’s correlation calculations from pairwise comparisons. The X axis shows the chemogenomic profile correlation between a Malaria Box compound and AS, the Y axis with AM; the color gradient indicates the average correlation with all ART derivatives tested. Five Malaria Box compounds (MMV006087, MMV006427, MMV020492, MMV665876, MMV396797) were identified as having similar drug-drug chemogenomic profiles to the ART sensitivity cluster.</p

Antiprotozoal Malaria Box compounds with activity in biological assays and lacking toxicity at therapeutic levels.

<p>Selectivity Index, SI, is toxicity level/activity level; p, probe-like; d, drug-like.</p

Malaria Box Heatmap.

<p>Shown are selected data from the HeatMap (<a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1005763#ppat.1005763.s002" target="_blank">S1 Table</a>) for the 400 Malaria Box compounds. Each column represents an assay (grouped by category), compounds are represented in rows. The red-green gradient represents higher to lower activity. Favorable PK activities are scored green. <i>Pf</i>: <i>Plasmodium falciparum</i>, <i>Pb</i>: <i>Plasmodium berghei</i>, PK: pharmacokinetics, sol.: solubility, hERG: human ether-a-go-go channel inhibition, DDI: drug-drug interactions (predicted).</p