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Patient-based transcriptome-wide analysis identify interferon and ubiquination pathways as potential predictors of Influenza A disease severity

ABSTRACT: Transcriptional profile in influenza infected patients with different clinical outcomes were investigated.

ORGANISM(S): Homo sapiens

PROVIDER: GSE61821 | GEO | 2014/09/28

SECONDARY ACCESSION(S): PRJNA262463

REPOSITORIES: GEO

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Project description:Classical antiviral therapy inhibit viral proteins and are subject to resistance. To counteract this emergence, alternative strategy has been developed that target cellular factors. We hypothesized that such approach could also be useful to identify broad antivirals. Influenza A virus was used as a model for viral diversity and need for therapy against unpredictable viruses as recently underlined by the H1N1 pandemic. We proposed to identify a gene-expression signature associated with infection with different influenza A virus subtypes which could help to identify potential antiviral drugs with broad spectrum. Cellular gene expression response to infection with five different human and avian influenza viruses strains was analyzed and 300 genes were determined as differentially expressed between infected and non-infected samples. Strikingly, only a few genes were induced by infection and related to immune response. A more concise list was used to screen connectivity map, a database of drug-associated gene expression profiles, for molecules with inverse profiles than the signature of infection. We hypothesized that such compounds would induce an unfavorable cellular environment for influenza virus replication. Eight potential antivirals including ribavirin were identified, and six inhibited influenza viral growth in vitro. The new pandemic H1N1 virus, which was not used to define the gene expression signature of infection, was inhibited by five of the eight identified molecules, demonstrating that this strategy could help to identify broad spectrum antivirals. This is the first study showing that a gene expression based-screening can be used to identify antivirals. Such approaches could accelerate the drug discovery progress and could be extended to other pathogens. A549 (human lung epithelial cells) were infected with 5 different influenza A strains (A/New Caledonia/20/99 (H1N1), A/Moscow/10/99 (H3N2), A/Lyon/969/09 (H1N1 SOI-V), A/Turkey/582/2006 (H5N1), A/Finch/England/2051/94 (H5N2), and A/Chicken/Italy/2076/99 (H7N1)) or mock infected. Five independant replicates were done and hybridized on a different microarray. The overall design is thus composed of 5 mock samples, and 5x5 infected samples.

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Patient-based transcriptome-wide analysis identify interferon and ubiquination pathways as potential predictors of Influenza A disease severity

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