Project description:Control of malaria is threatened by emerging parasite resistance to artemisinin drug (ART) therapies. The molecular details of how Plasmodium malaria parasites response to ART and how this relates to resistance is not clear. To determine how parasites respond to ART by altering gene expression, we performed a transcriptomic study of dihydroartemisinin (DHA) response in P. falciparum K1 strain and in P. berghei ANKA strain. Microarray data from DHA-treated P. falciparum trophozoite stage parasites were compared with data from other ART treatments. Genes with consistent changes in expression were identified, which includes notably down-regulation of cytosolic ribosomal protein genes. RNA-seq data revealed a similar pattern of transcriptomic change, although the pattern was much clearer in that more than one-third of P. falciparum trophozoite genes are differentially expressed with greater statistical support for down-regulation of ribosomal protein genes. The poor overlap of differentially-expressed genes between microarray and RNA-seq and less-well defined patterns for the former suggests that the accuracy of microarray is limited by technological bias. The trophozoite response to DHA is overall âring-likeâ and less âtrophozoite-likeâ, which is consistent with previous findings that Plasmodium can enter a quiescent ring-like state to resist ART. RNA-seq data from DHA-treated P. falciparum rings reveal a more muted response, although there is considerable overlap of differentially expressed genes with DHA-treated trophozoites. In contrast, P. falciparum schizonts are unresponsive to DHA, suggesting that the protective response acts mainly to arrest parasite development through the G2/M checkpoint. The transcriptional response of P. berghei to DHA treatment in vivo in infected mice is strikingly similar to the P. falciparum in vitro ring and trophozoite responses, in which ribosomal protein genes are notably down-regulated. These results suggest Plasmodium species respond to DHA in the same way. This knowledge could be applied to outwit the parasite to deliver more effective artemisinin therapies, and maybe hinder the development of drug resistance. Two condition drug-treatment experiment, Dihydroartemisinin vs. Vehicle control treatment with matched reference untreated controls. Biological replicates: 5 independently grown and harvested experimental culture replicates. One replicate of treatment/reference time-point per array.

Project description:To determine the transcriptional effects of a novel plant-based compound, dehydrobrachylaenolide, on P. falciparum, parasite cultures were treated with the compound over time. Samples were taken for analysis 2, 6, and 12 hours post-invasion of human red blood cells. Control cultures were treated simultaneously with DMSO, and samples isolated at 2, 6, and 12 hours for transcriptional analysis. Background Antimalarial drug resistance threatens to undermine efforts to eliminate this deadly disease. The resulting omnipresent requirement for drugs with novel modes of action prompted a national consortium initiative to discover new antiplasmodial agents from South African medicinal plants. One of the plants selected for investigation was Dicoma anomala subsp. gerrardii, based on its ethnomedicinal profile. Methods Standard phytochemical analysis techniques including solvent-solvent extraction, thin-layer and column chromatography, were used to isolate the main active constituent of Dicoma anomala subsp. gerrardii. The crystallised pure compound was identified using nuclear magnetic resonance spectroscopy, mass spectrometry and X-ray crystallography. The compound was tested in vitro on Plasmodium falciparum cultures using the parasite lactate dehydrogenase assay. The effects of treatment on the P. falciparum transcriptome were subsequently investigated by treating ring-stage parasites (alongside untreated controls) with the pure compound, followed by oligonucleotide microarray and data analysis. Results The main active constituent was identified as dehydrobrachylaenolide, a eudesmanolide-type sesquiterpene lactone. The compound demonstrated an in vitro IC50 of 245.6 nM, which was comparable to the IC50 of chloroquine, against a chloroquine-resistant strain (K1) of P. falciparum. Microarray data analysis identified a cluster of unique genes that were differentially expressed as a result of the treatment and gene ontology analysis identified various biological processes that were significantly affected. Comparison of the dehydrobrachylaenolide treatment transcriptional dataset with a published artesunate (also a sesquiterpene lactone) dataset revealed little overlap. This suggests differentiated modes of action between the two compounds. Conclusions Dehydrobrachylaenolide could play a valuable role as a drug candidate to generate new antimalarial compounds with novel modes of action and favourable ADMET properties. Reference design. Transcriptional analysis was performed as described in GSE18075 with the following modification. Profiles from parasite cultures isolated 2hrs after drug treatment during early ring-stage development were contrasted against untreated control cultures isolated at this timepoint. Profiles from parasites isolated 6 and 12 hours following drug treatment were contrasted to against untreated control cultures isolated at 6 hours. A detailed description of the statistical methodology used for this dataset is outlined in the accompanying manuscript. A reference design was employed for array hybridisation, utilising the URR pool described previously in the NCBI GEO Series GSE18075 dataset. All solvent-control and drug-treated samples were hybridised to Operon slides, along with the URR. In contrast to the hybridisation protocol described in GSE18075, 40 pmoles of each dye was hybridised to each array, utilising Cy3 (sample) and Cy5 (reference) dyes from GE Healthcare (#RPN5661), specifically optimised for nucleic acid labelling. A total of nineteen slides were processed in the study. Two independent cDNA samples (biological replicates) were prepared for each untreated and drug-treated sample at each time point. One of the biological replicate cDNA samples were additionally hybridised to a third slide (representing the technical replicate). In the case of the 2 hour DMSO treated control culture, an additional technical microarray replicate was included for quality control purposes. GenePix results (gpr) files were generated using GenePix 6.0 (Molecular Devices) software, without normalization. For clustering analyses, results files were normalized with DNMAD (Diagnosis and Normalization for MicroArray Data) using print-tip loess. The normalized values were subsequently downloaded and analyzed with the Multiexperiment Viewer (MeV) in the TM4 software suite. Hierarchical Clustering (HCL, average linkage) was performed to estimate technical and biological variation between samples and at which point cytostasis most likely occurred for comparative purposes in downstream analyses. Intensity data for individual slides were imported into LIMMA (linear models for microarray data) in the R computing environment. Pre- and post-normalization diagnostic plots were performed using MARRAY. Data from each microarray slide was normalized using print-tip loess. Data between microarrays was normalized using R-Quantile normalisation. Pearson correlations were computed in MS Excel to estimate variation between technical and biological replicates. Spots excluded from slide correlations and normalisation were those weighted by the limma script or flagged in the genepix results file (gpr). Additionally, spots termed Alien, Empty, Null and Operon Use Only were excluded from the correlation analyses. These spots were similarly excluded for correlations between untreated and treated samples at each time point following normalisation. Results from biological and slide replicates within each of the time points were collated, and linear models were computed to contrast gene expression between time points. A two-fold change in gene expression was used as cut-off, in conjunction with correction for false discovery (false discovery rate (FDR) = 5%). Analysis of differentially expressed genes was performed in MADIBA (Micro Array Data Interface for Biological Annotation).

Project description:Transcriptional profiling of P. falciparum cultures treated with cyclohexylamine over time (18, 25 and 30 hours post invasion) A control experiment was also set up in which P. falciparum was not treated with cyclohexylamine, and samples were taken at 18, 25 and 30 h post invasion). Background Plasmodium falciparum, the causative agent of severe human malaria, has evolved to become resistant to previously successful antimalarial chemotherapies, most notably chloroquine and the antifolates. The prevalence of resistant strains has necessitated the discovery and development of new chemical entities with novel modes-of-action. Although much effort has been invested in the creation of analogues based on existing drugs and the screening of chemical and natural compound libraries, a crucial shortcoming in current Plasmodial drug discovery efforts remains the lack of an extensive set of novel, validated drug targets. A requirement of these targets (or the pathways in which they function) is that they prove essential for parasite survival. The polyamine biosynthetic pathway, responsible for the metabolism of highly abundant amines crucial for parasite growth, proliferation and differentiation, is currently under investigation as an antimalarial target. Chemotherapeutic strategies targeting this pathway have been successfully utilized for the treatment of Trypanosomes causing West African sleeping sickness. In order to further evaluate polyamine depletion as possible antimalarial intervention, the consequences of inhibiting P. falciparum spermidine synthase (PfSpdSyn) were examined on a morphological, transcriptomic, proteomic and metabolic level. Results Morphological analysis of P. falciparum 3D7 following application of the PfSpdSyn inhibitor cyclohexylamine confirmed that parasite development was completely arrested at the early trophozoite stage. This is in contrast to untreated parasites which progressed to late trophozoites at comparable time points. Global gene expression analyses confirmed a transcriptional arrest in the parasite. Several of the differentially expressed genes mapped to the polyamine biosynthetic and associated metabolic pathways. Differential expression of corresponding parasite proteins involved in polyamine biosynthesis was also observed. Most notably, uridine phosphorylase, adenosine deaminase, lysine decarboxylase (LDC) and S-adenosylmethionine synthetase were differentially expressed at the transcript and/or protein level. Several genes in associated metabolic pathways (purine metabolism and various methyltransferases) were also affected. The specific nature of the perturbation was additionally reflected by changes in polyamine metabolite levels. Conclusions This study details the malaria parasite’s response to PfSpdSyn inhibition on the transcriptomic, proteomic and metabolic levels. The results corroborate and significantly expand previous functional genomics studies relating to polyamine depletion in this parasite. Moreover, they confirm the role of transcriptional regulation in P. falciparum, particularly in this pathway. The findings promote this essential pathway as a target for antimalarial chemotherapeutic intervention strategies. Keywords: Time course experiment in response to a drug treatment Reference design. All timepoints compared with t = 18 hours (untreated) post invasion. Two biological replicates and one technical sample per treatment and per time point. A reference design was employed for array hybridisation, utilising the URR pool described previously. All solvent-control and drug-treated sampled were hybridised to Operon slides, along with the URR. For each time point and each untreated/treated sample, three microarray slides were processed, such that a total of eighteen slides were processed in the study. Two independent cDNA samples (biological replicates) were prepared for each untreated and drug-treated sample at each time point. One of the biological replicate cDNA samples were additionally hybridised to a third slide (representing the technical replicate). GenePix results (gpr) files were generated using GenePix 6.0 (Molecular Devices) software, without normalization. For clustering analyses, results files were normalized with DNMAD (Diagnosis and Normalization for MicroArray Data) using print-tip loess. The normalized values were subsequently downloaded and analyzed with the Multiexperiment Viewer (MeV) in the TM4 software suite. Hierarchical Clustering (HCL, average linkage) was performed to estimate technical and biological variation between samples and at which point cytostasis most likely occurred for comparative purposes in downstream analyses. Intensity data for individual slides were imported into LIMMA (linear models for microarray data) in the R computing environment. Pre- and post-normalization diagnostic plots were performed using MARRAY. Data from each microarray slide was normalized using print-tip loess. Data between microarrays was normalized using rquantile normalisation. Pearson correlations were computed in ExCel to estimate variation between technical and biological replicates. Spots excluded from slide correlations and normalisation were those weighted by the limma script or flagged in the genepix results file (gpr). Additionally, spots termed Alien, Empty, Null and Operon Use Only were excluded from the correlation analyses. These spots were similarly excluded for correlations between untreated and treated samples at each time point following normalisation. Results from biological and slide replicates within each of the time points were collated, and linear models were computed to contrast gene expression between time points. A two-fold change in gene expression was used as cut-off, in conjunction with correction for false discovery (false discovery rate (FDR) = 5%). Normalised data was deposited in the Gene Expression Omnibus (GEO) database, number GSE18075. Analysis of differentially expressed genes was performed in MADIBA (Micro Array Data Interface for Biological Annotation).

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Global gene expression profiling of Plasmodium falciparum in response to the anti-malarial drug pyronaridine

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