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The Taub Faculty of Computer Science Events and Talks

Bioinformatics Forum: Stochastic Effects in Viral-infected Dendritic Cells Lead to Efficient Immune Response Activation
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Yishai Shimoni (Andrea Califano's Lab, Center for Computational Biology and Bioinformatics (C2B2), Columbia University, New York)
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Wednesday, 16.02.2011, 15:30
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Taub 701
When monocyte-derived human dendritic cells (DCs) are infected by Newcastle disease virus, the virus is known to be detected by RIG-I proteins, which induces interferon production. Interferon activates a host of genes, including the gene coding RIG-I. Single cell measurements is DCs show large cell to cell variation of 3-4 orders of magnitude at 6-10 hours after infection. In order analyze early times after infection, when reliable direct single cell data cannot be obtained, an agent-based mathematical model was developed. The model was correlated with biochemical time-course measurements of the levels of IFNB1 and DDX58 (RIG-I). Simulations showed that a high level of variation and the presence at early times of a small number of early responder cells is necessary for explaining the experimental data as well as for efficient and controlled activation of the IFNB1-DDX58 positive feedback loop. The model generated testable predictions that were confirmed by single cell experiments. The results suggest that large cell-to-cell response variation plays a significant role in the early innate immune response, and that the variability is in fact essential to the efficient activation of the IFNB1 based feedback loop.