Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcription profiling of human A549 epithelial cells infected with polio virus or mock infected to compare Nanostring and Affymetrix technologies

ABSTRACT: Mock and poliovirus infected A549 cells were used as model system to assess Nanostring's technology for detecting mRNA transcripts, linearity of signal, reproducibility and fold change measurements. As a comparison, the same samples were measured using Affymetrix U133 2.0 plus arrays and several genes were followed up using RT-PCR. All samples for all platforms were performed in triplicate

ORGANISM(S): Homo sapiens

SUBMITTER: Gary Geiss

PROVIDER: E-MEXP-1072 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Direct multiplexed measurement of gene expression with color-coded probe pairs.

Geiss Gary K GK Bumgarner Roger E RE Birditt Brian B Dahl Timothy T Dowidar Naeem N Dunaway Dwayne L DL Fell H Perry HP Ferree Sean S George Renee D RD Grogan Tammy T James Jeffrey J JJ Maysuria Malini M Mitton Jeffrey D JD Oliveri Paola P Osborn Jennifer L JL Peng Tao T Ratcliffe Amber L AL Webster Philippa J PJ Davidson Eric H EH Hood Leroy L Dimitrov Krassen K

Nature biotechnology 20080217 3

We describe a technology, the NanoString nCounter gene expression system, which captures and counts individual mRNA transcripts. Advantages over existing platforms include direct measurement of mRNA expression levels without enzymatic reactions or bias, sensitivity coupled with high multiplex capability, and digital readout. Experiments performed on 509 human genes yielded a replicate correlation coefficient of 0.999, a detection limit between 0.1 fM and 0.5 fM, and a linear dynamic range of ove ...[more]

PMID: 18278033

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Project description:MicroRNAs (miRNAs) repress the expression levels of genes by binding to mRNA transcripts, acting as master regulators of cellular processes. Differential expression of miRNAs has been linked to viral-associated diseases involving members of the hepacivirus, herpesvirus, and retrovirus families. In contrast, limited biological and molecular information has been reported on the potential role of cellular miRNAs in the lifecycle of influenza A viruses (infA). In this study, we hypothesize that elucidating the miRNA expression signatures induced by low-pathogenic swine-origin influenza A virus (S-OIV) pandemic H1N1 (2009) and highly pathogenic avian-origin (A-OIV) H7N7 (2003) infections could reveal temporal and strain-specific miRNA fingerprints during the viral lifecycle, shedding important insights into the potential role of cellular miRNAs in host-infA interactions. Using a microfluidic microarray platform, we profiled cellular miRNA expression in human A549 cells infected with S- and A-OIVs at multiple time-points during the viral lifecycle, including global gene expression profiling during S-OIV infection. Using target prediction and pathway enrichment analyses, we identified the key cellular pathways associated with the differentially expressed miRNAs and predicted mRNA targets during infA infection, including immune system, cell proliferation, apoptosis, cell cycle, and DNA replication and repair. By identifying the specific and dynamic molecular phenotypic changes (microRNAome) triggered by S- and A-OIV infection in human cells, we provide experimental evidence demonstrating a series of temporal- and strain-specific host molecular responses involving different combinatorial contributions of multiple cellular miRNAs. Our results also identify novel potential exosomal miRNA biomarkers associated with pandemic S-OIV and deadly A-OIV-host infection. Control (mock-infected) samples: 12 (2 technical replicates, averaged), Infected samples: 6, for each time-point (0, 4, 8, 24, 48 and 72 hours post infection). The experiment was performed in six replicates.

Dataset Information

Transcription profiling of human A549 epithelial cells infected with polio virus or mock infected to compare Nanostring and Affymetrix technologies

Publications

Direct multiplexed measurement of gene expression with color-coded probe pairs.

Similar Datasets

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