A system view on the differential activities of hu.. (IFNaction)
A system view on the differential activities of human type I interferons
Start date: Jan 1, 2009,
End date: Dec 31, 2012
Type I interferons (IFNs) form a restricted network of highly related immune cytokines that elicit differential biological responses through a single cell surface receptor comprised of the subunits IFNAR1 and IFNAR2. We have shown that differential signal activation correlates with differential interaction and conformational dynamics of the receptor induced by binding of different member of the IFN family. The goal of this project is to employ a systems biology approach to identify the molecular and cellular mechanisms responsible for translating receptor dynamics into differential cellular responses by combining biochemical, biophysical and genetic analysis of the signaling outputs. We will collect quantitative data describing type I interferon signaling from ligand recognition until phenomenological cellular responses in a number of well defined cell lines. Based on detailed structure functions studies, we will generate a set of IFN mutants with highly differential cellular responses. Based on this sub-family of ligands, we will explore the molecular and cellular dynamics of the signaling complex on the plasma membrane, as well as the receptor trafficking upon activation. Moreover, we will analyze the protein-protein interaction network involved in signal transduction and obtain a spatio-temporal picture of key signaling pathways. These studies will be flanked by extensive analyses of gene transcription levels and correlated with cellular responses. Using these data sets, input and output signals will be correlated on different levels by various mathematical approaches to understand how the processing of differential input signals is translated within the cell to produce different responses to binding the same surface receptors. In order to test the validity of these models, experimental and theoretical studies will be tightly coupled, for example, in designing network perturbations. As a proof-of-concept for this approach, we will design IFNs with optimized potencies for medical application, such as the ex vivo differentiation of monocytes into dendritic cell for application as cancer vaccines.
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