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Effect of the human cytomegalovirus IE86 protein on expression of E2F-responsive genes: a DNA microarray analysis.

ABSTRACT: We have previously reported that the immediate early (IE)-86 protein of human cytomegalovirus (HCMV) pushes the cell cycle toward S phase but inhibits cell division [Murphy, E. A., Streblow, D. N., Nelson, J. A. & Stinski, M. F. (2000) J. Virol. 74, 7108-7118]. We determined the cellular genes activated by the IE86 protein in permissive human fibroblast cells. A 4-fold or greater increase in the steady-state RNA from many cellular genes that regulate the cell cycle, the enzymes for DNA precursor synthesis, and the initiation of cellular DNA replication was detected by high-density DNA microarray analysis. Northern blot analysis confirmed the DNA microarray data. The viral IE86 protein induced a significant increase in the cellular steady-state RNA level from the B-myb, cyclin E, cdk-2, E2F-1, ribonucleotide reductase 1, ribonucleotide reductase 2, thymidylate synthetase, MCM3, and MCM7 genes, but actin RNA was not affected. Cellular genes regulated by the E2F transcription factors were strongly activated by the IE86 protein. In most cases, the cellular genes induced by the IE86 protein were also induced by HCMV infection. This study demonstrates the global array of cellular genes activated by the IE86 protein that pushes progression of the cell cycle from G0/G1 toward the G1/S transition point.

SUBMITTER: Song YJ

PROVIDER: S-EPMC122434 | biostudies-literature | 2002 Mar

REPOSITORIES: biostudies-literature

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Effect of the human cytomegalovirus IE86 protein on expression of E2F-responsive genes: a DNA microarray analysis.

Song Yoon-Jae YJ Stinski Mark F MF

Proceedings of the National Academy of Sciences of the United States of America 20020226 5

We have previously reported that the immediate early (IE)-86 protein of human cytomegalovirus (HCMV) pushes the cell cycle toward S phase but inhibits cell division [Murphy, E. A., Streblow, D. N., Nelson, J. A. & Stinski, M. F. (2000) J. Virol. 74, 7108-7118]. We determined the cellular genes activated by the IE86 protein in permissive human fibroblast cells. A 4-fold or greater increase in the steady-state RNA from many cellular genes that regulate the cell cycle, the enzymes for DNA precursor ...[more]

PMID: 11867723

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Project description:BackgroundA common observation in the analysis of gene expression data is that many genes display similarity in their expression patterns and therefore appear to be co-regulated. However, the variation associated with microarray data and the complexity of the experimental designs make the acquisition of co-expressed genes a challenge. We developed a novel method for Extracting microarray gene expression Patterns and Identifying co-expressed Genes, designated as EPIG. The approach utilizes the underlying structure of gene expression data to extract patterns and identify co-expressed genes that are responsive to experimental conditions.ResultsThrough evaluation of the correlations among profiles, the magnitude of variation in gene expression profiles, and profile signal-to-noise ratio's, EPIG extracts a set of patterns representing co-expressed genes. The method is shown to work well with a simulated data set and microarray data obtained from time-series studies of dauer recovery and L1 starvation in C. elegans and after ultraviolet (UV) or ionizing radiation (IR)-induced DNA damage in diploid human fibroblasts. With the simulated data set, EPIG extracted the appropriate number of patterns which were more stable and homogeneous than the set of patterns that were determined using the CLICK or CAST clustering algorithms. However, CLICK performed better than EPIG and CAST with respect to the average correlation between clusters/patterns of the simulated data. With real biological data, EPIG extracted more dauer-specific patterns than CLICK. Furthermore, analysis of the IR/UV data revealed 18 unique patterns and 2661 genes out of approximately 17,000 that were identified as significantly expressed and categorized to the patterns by EPIG. The time-dependent patterns displayed similar and dissimilar responses between IR and UV treatments. Gene Ontology analysis applied to each pattern-related subset of co-expressed genes revealed underlying biological processes affected by IR- and/or UV- induced DNA damage.ConclusionEPIG competed with CLICK and performed better than CAST in extracting patterns from simulated data. EPIG extracted more biological informative patterns and co-expressed genes from both C. elegans and IR/UV-treated human fibroblasts. Using Gene Ontology analysis of the genes in the patterns extracted by EPIG, several key biological categories related to p53-dependent cell cycle control were revealed from the IR/UV data. Among them were mitotic cell cycle, DNA replication, DNA repair, cell cycle checkpoint, and G0-like status transition. EPIG can be applied to data sets from a variety of experimental designs.

Dataset Information

Effect of the human cytomegalovirus IE86 protein on expression of E2F-responsive genes: a DNA microarray analysis.

Publications

Effect of the human cytomegalovirus IE86 protein on expression of E2F-responsive genes: a DNA microarray analysis.

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