Transcriptomes of microglia in experimental cerebral malaria in mice in the presence and absence of Type I Interferon signaling
journal contributionposted on 14.09.2020, 10:29 by Carlos Talavera-López, Barbara Capuccini, Richard Mitter, Jing Wen Lin, Jean Langhorne
OBJECTIVES: Plasmodium berghei ANKA infection in mice is a model for human cerebral malaria, the most severe complication of Plasmodium falciparum infection. Responses of brain microglia have been little investigated, and may contribute to the pathogenesis of cerebral malaria. We showed previously that microglia are activated in P. berghei infections, and that Type 1-Interferon signaling is important for activation. This dataset compares transcriptomic profiles of brain microglia of infected mice in the presence and absence of Type 1 interferon signaling, with the aim of identifying genes in microglia in this pathway during experimental cerebral malaria. DATA DESCRIPTION: We documented global gene expression from microglial RNA from uninfected and P berghei-infected wild-type C57BL/6 and IFNA Receptor Knock-out mice using Illumina Beadarrays. Principal component analysis showed 4 groups of samples corresponding to naïve wild-type, naïve IFNA Receptor knock-out, infected wild-type, and IFNA Receptor knock-out mice. Differentially-expressed genes of microglia from the two groups of infected mice are documented. Gene set enrichment analysis showing the top 500 genes assigned to Reactome pathways from infected IFNA Receptor knock-out versus naïve, and infected WT versus naïve has been generated. These data will be useful for those interested in microglia cells, and in experimental cerebral malaria.
Experimental cerebral malariaMalariaMicroarrayMicrogliaPlasmodium bergheiType I InterferonsAnimalsBrainDisease Models, AnimalFemaleInterferon Type IMalaria, CerebralMiceMice, Inbred C57BLMice, KnockoutReceptor, Interferon alpha-betaSignal TransductionTranscriptomeLanghorne FC001101CBBRF-ackAS-ackFC-ack1199 Other Medical and Health Sciences0601 Biochemistry and Cell BiologyBioinformatics