Project description:Recent advances in high throughput sequencing methodologies allow the opportunity to probe in depth the transcriptomes of organisms including important human pathogens. In this project, we are using Illumina sequencing technology to analyze the transcriptome (RNA-Seq) of experimentally accessible stages of the mouse malaria parasite, P. berghei ANKA. The aim is to make transcriptional landscape maps of different life cycle stages of P. berghei ANKA at single base pairs resolution. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/
Project description:We have used cDNA microarrays to compare gene expression profiles in brains from normal mice to those infected with the Anka strain of Plasmodium berghei, a model of cerebral malaria. For each of three brains in each group, we computed ratios of all quantifiable genes with a composite reference sample and then computed ratios of gene expression in infected brains with untreated controls. Of the almost 12,000 unigenes adequateluy quantified in all arrays, about 3% were significantly downregulated (p<0.05, >50% fold change) and about 7% were upregulated. Upon inspection of the lists of regulated genes, we identified a high number encoding proteins of importance to normal brain function or associated with neuropathology. These results emphasize the important impact of malarial infection on gene expression in brain and provide tentative target biomarkers that might provide novel therapeutic targets for neurological sequelae of disease.
Project description:Cerebral malaria (CM) is a severe complication of Plasmodium falciparum infection, predominantly experienced by children and non-immune adults, which results in great mortality and long-term sequelae. Recent reports based on histology of post-mortem brain tissue suggest that CM may be the common end point for a range of syndromes. Here, we have analysed the gene expression profiles in brain tissue taken from experimental CM (ECM)-susceptible, Plasmodium berghei ANKA (PbA)-infected C57BL/6 (B6) and CBA/CaH (CBA) mice with ECM. Gene expression profiles were largely heterogeneous between the two ECM-susceptible strains. These results, combined with experimental data, support the existence of distinct pathogenic pathways in CM. Keywords: disease state analysis
Project description:Cerebral malaria (CM) is a severe complication of Plasmodium falciparum infection, predominantly experienced by children and non-immune adults, which results in great mortality and long-term sequelae. Recent reports based on histology of post-mortem brain tissue suggest that CM may be the common end point for a range of syndromes. Here, we have analysed the gene expression profiles in brain tissue taken from experimental CM (ECM)-susceptible, Plasmodium berghei ANKA (PbA)-infected C57BL/6 (B6) and CBA/CaH (CBA) mice with ECM. Gene expression profiles were largely heterogeneous between the two ECM-susceptible strains. These results, combined with experimental data, support the existence of distinct pathogenic pathways in CM. Experiment Overall Design: C57BL/6 and CBA/CaH mice were infected with 10e5 Plasmodium berghei ANKA-infected RBCs and monitored for ECM development. At onset of ECM symptoms, infected mice and naive controls were culled, perfused (in order to remove non-adherent circulating cells), and brains were removed. Total RNA was extracted from these brains and pooled (n=6 mice/ group). Pooled RNA samples were converted to cDNA and antisense cRNA, labelled and hybridized to GeneChip Mouse Genome 430 2.0 Arrays (Affymetrix, Surrey Hills, Australia). Arrays were scanned using the GeneChip Scanner 3000 (Affymetrix) and GeneChip Operating Software v1.1.1 (Affymetrix). Normalisation and initial analyses were carried out in GeneSpring v7 (Agilent Technologies). Values below 0.01 were set to 0.01. Each measurement was divided by the 50th percentile of all measurements in that sample. The data was filtered for genes flagged as present, which had at least an expression level of 50. Following this, a threshold of 2.5 fold up-regulation or down-regulation of genes differentially expressed during ECM was set.