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  • 1
    Language: English
    In: BMC bioinformatics, 20 December 2011, Vol.12, pp.485
    Description: High-content, high-throughput RNA interference (RNAi) offers unprecedented possibilities to elucidate gene function and involvement in biological processes. Microscopy based screening allows phenotypic observations at the level of individual cells. It was recently shown that a cell's population context significantly influences results. However, standard analysis methods for cellular screens do not currently take individual cell data into account unless this is important for the phenotype of interest, i.e. when studying cell morphology. We present a method that normalizes and statistically scores microscopy based RNAi screens, exploiting individual cell information of hundreds of cells per knockdown. Each cell's individual population context is employed in normalization. We present results on two infection screens for hepatitis C and dengue virus, both showing considerable effects on observed phenotypes due to population context. In addition, we show on a non-virus screen that these effects can be found also in RNAi data in the absence of any virus. Using our approach to normalize against these effects we achieve improved performance in comparison to an analysis without this normalization and hit scoring strategy. Furthermore, our approach results in the identification of considerably more significantly enriched pathways in hepatitis C virus replication than using a standard analysis approach. Using a cell-based analysis and normalization for population context, we achieve improved sensitivity and specificity not only on a individual protein level, but especially also on a pathway level. This leads to the identification of new host dependency factors of the hepatitis C and dengue viruses and higher reproducibility of results.
    Keywords: RNA Interference ; Dengue -- Genetics ; Hepatitis C -- Genetics ; Phosphotransferases -- Genetics ; Single-Cell Analysis -- Methods
    E-ISSN: 1471-2105
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  • 2
    Language: English
    In: The Journal of biological chemistry, 05 August 2011, Vol.286(31), pp.27278-87
    Description: RIG-I is a major innate immune sensor for viral infection, triggering an interferon (IFN)-mediated antiviral response upon cytosolic detection of viral RNA. Double-strandedness and 5'-terminal triphosphates were identified as motifs required to elicit optimal immunological signaling. However, very little is known about the response dynamics of the RIG-I pathway, which is crucial for the ability of the cell to react to diverse classes of viral RNA while maintaining self-tolerance. In the present study, we addressed the molecular mechanism of RIG-I signal detection and its translation into pathway activation. By employing highly quantitative methods, we could establish the length of the double-stranded RNA (dsRNA) to be the most critical determinant of response strength. Size exclusion chromatography and direct visualization in scanning force microscopy suggested that this was due to cooperative oligomerization of RIG-I along dsRNA. The initiation efficiency of this oligomerization process critically depended on the presence of high affinity motifs, like a 5'-triphosphate. It is noteworthy that for dsRNA longer than 200 bp, internal initiation could effectively compensate for a lack of terminal triphosphates. In summary, our data demonstrate a very flexible response behavior of the RIG-I pathway, in which sensing and integration of at least two distinct signals, initiation efficiency and double strand length, allow the host cell to mount an antiviral response that is tightly adjusted to the type of the detected signal, such as viral genomes, replication intermediates, or small by-products.
    Keywords: Immunity, Innate ; Dead-Box RNA Helicases -- Physiology
    E-ISSN: 1083-351X
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