Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcriptomic analysis of host response to mouse-adapted SARS virus in wild type, STAT1 -/-, and IFNAR1 -/- mouse genetic backgrounds

ABSTRACT: The mechanisms by which pulmonary lesions and fibrosis are generated during SARS-CoV infection are not known. Using high-throughput mRNA profiling, we examined the transcriptional response of wild-type (WT), type I interferon receptor knockout (IFNAR1−/−), and STAT1 knockout (STAT1−/−) mice infected with a recombinant mouse-adapted SARS-CoV (rMA15) to better understand the contribution of specific gene expression changes to disease progression. Ten week old 129S6/SvEv wild-type, STAT1−/− (Taconic Farms, Germantown, NY), and IFNAR1−/− mice bred on a 129SvEv background were anesthetized with a ketamine and infected intranasally with either phosphate-buffered saline (PBS) alone (Invitrogen, Carlsbad, CA) or 1 × 10^5 PFU rMA15-PBS. Mice were euthanized and left lungs were harvested from individual mice (a total of 3 infected mice from each strain) at days 2, 5, and 9 postinfection (dpi) for microarray analyses. Lung samples were taken from mock-infected animals from each of the strains at 5 dpi.

ORGANISM(S): Mus musculus

SUBMITTER: Richard Green

PROVIDER: E-GEOD-36016 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Transcriptomic analysis reveals a mechanism for a prefibrotic phenotype in STAT1 knockout mice during severe acute respiratory syndrome coronavirus infection.

Zornetzer Gregory A GA Frieman Matthew B MB Rosenzweig Elizabeth E Korth Marcus J MJ Page Carly C Baric Ralph S RS Katze Michael G MG

Journal of virology 20100811 21

Severe acute respiratory syndrome coronavirus (SARS-CoV) infection can cause the development of severe end-stage lung disease characterized by acute respiratory distress syndrome (ARDS) and pulmonary fibrosis. The mechanisms by which pulmonary lesions and fibrosis are generated during SARS-CoV infection are not known. Using high-throughput mRNA profiling, we examined the transcriptional response of wild-type (WT), type I interferon receptor knockout (IFNAR1-/-), and STAT1 knockout (STAT1-/-) mic ...[more]

PMID: 20702617

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Project description:We investigated the ability of HDAC inhibitors (HDACi) to target CML stem cells. Treatment with HDACi combined with IM effectively induced apoptosis in quiescent CML progenitors resistant to elimination by IM alone, and eliminated CML stem cells capable of engrafting immunodeficient mice. In vivo administration of HDACi with IM markedly diminished LSC in a transgenic mouse model of CML. The interaction of IM and HDACi inhibited genes regulating hematopoietic stem cell maintenance and survival. HDACi treatment represents a novel and effective strategy to target LSC in CML patients receiving tyrosine kinase inhibitors. CML CD34+CD38- cells were selected using flow cytometry sorting and treated with IM, LBH and the combination of IM and LBH or cultured without exposure to drugs (controls) for 24 hours (n=3 each). Total RNA from 5000 cells was extracted using the RNeasy kit (Qiagen), amplified and labeled using GeneChip Two-Cycle Target Labeling and Control Reagents (Affymetrix, Santa Clara, CA). 15 Âµg cRNA from each sample was hybridized to Affymetrix GeneChip Human Genome U133 Plus 2.0 Arrays. Microarray data analyses were performed using R (version 2.9) with genomic analysis packages from Bioconductor (version 2.4). Expression data were normalized using the robust multiarray average (RMA) algorithm, with background adjustment, quantile normalization and median polish summarization. Probesets with low expression levels or low variability across samples were filtered. For genes with multiple probesets, the gene level expression was set to be the median of the probesets. Linear regression was used to model the gene expression with the consideration of 2x2 factorial design and matched samples. Differentially expressed genes were identified by calculating empirical Bayes moderated t-statistic, and p-values were adjusted by FDR using the âLIMMAâ package. Gene Set Enrichment Analyses (GSEA) was performed using GSEA software version 2.04 [http://www.broadinstitute.org/gsea/] to detect enrichment of predetermined gene sets using t-scores and gene sets in C2 (curated gene sets) category from the Molecular Signature Database (MsigDB). Gene sets representing common functional categories were categorized and grouped. We also analyzed enrichment of gene sets with common transcription factor binding sites (586 sets) from MsigDB.

Dataset Information

Transcriptomic analysis of host response to mouse-adapted SARS virus in wild type, STAT1 -/-, and IFNAR1 -/- mouse genetic backgrounds

Publications

Transcriptomic analysis reveals a mechanism for a prefibrotic phenotype in STAT1 knockout mice during severe acute respiratory syndrome coronavirus infection.

Similar Datasets

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