E-GEOD-5450 - Transcription profiling of human alveolar epithelial cell line infected with EBV (A-Akata) revals alveolar epithelial cell injury with EBV upregulates TGF-beta1 expression
Submitted on 3 August 2006, released on 13 June 2008, last updated on 10 June 2011
Idiopathic pulmonary fibrosis (IPF) is a refractory and lethal interstitial lung disease characterized by alveolar epithelial cells apoptosis, fibroblast proliferation and extra-cellular matrix proteins deposition. Epstein - Barr virus (EBV) has previously been localised to alveolar epithelial cells of IPF patients. In this study we utilised a microarray based differential gene expression analysis strategy to identify potential molecular drivers of EBV associated lung fibrosis. We employed an alveolar epithelial cell line infected with EBV (A-Akata). Lytic phase infection induced in the A-Akata cells by TPA/BA treatment resulted in increase of TGFbeta1 and TIEG1 mRNA expression. Treatment of the A-Akata cells with ganciclovir,; resulted in a down regulation of both TIEG1 and TGFbeta1 expression, accompanied by a suppression of the EBV early response genes, Rta and Zta. This suppression of cell turnover mediators was correlated with an increase in cell activity index. To identify a possible role for Rta in driving apoptotic gene expression, we inhibited the Rta gene expression by silencing RNA, resulting in a decrease in TGFbeta1 and TIEG1 expression. This study identifies an apoptotic role of the EBV early response genes, as enhancer factors of TIEG1 and TGFbeta1 in EBV infected alveolar epithelial cells, potentially providing a possible mechanism for the role of EBV infection in pulmonary fibrosis. Experiment Overall Design: RNA isolation, cDNA synthesis, in vitro transcription and microarray analysis of A549, EBV infected A549 (AAKata) and A549 +TGFbeta1 10ng/ml 4hours were performed as previously reported. All analysis were microarrayed in duplicate. Image files were obtained through Affymetrix GeneChip software (MAS5). Subsequently robust multichip analysis (RMA) was performed. Expression data was compared to control by ANOVA analysis, p<0.05 correlated values and a signal log ratio of 0.6 or greater (equivalent to a fold change in expression of 1.5 or greater) were taken to identify significant differential regulation. All the SLRs data resulting from the comparative analyses were reported in a graph to determine the reliability of the assay and the linearity by r2. For all the microarray assays r2 value was higher than 0.98. Using gene expression values normalised by RMA, Average Linkage Hierarchical Cluster Analysis was performed and the results visualized by TreeView software.
transcription profiling by array, unknown experiment type