Periodic Report Summary - IFNACTION (A system view on the differential activities of human type I interferons)
Publishable summary
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 signalling outputs. We will collect quantitative data describing type I interferon signalling from ligand recognition until phenomenological cellular responses in a number of well defined cell lines.
Using these data sets, input and output signals are 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. As a proof-of-concept for this approach, we design IFNs with optimised potencies for medical application, such as the ex vivo differentiation of monocytes into dendritic cell for application as cancer vaccines.
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 signalling outputs. We will collect quantitative data describing type I interferon signalling from ligand recognition until phenomenological cellular responses in a number of well defined cell lines.
Using these data sets, input and output signals are 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. As a proof-of-concept for this approach, we design IFNs with optimised potencies for medical application, such as the ex vivo differentiation of monocytes into dendritic cell for application as cancer vaccines.
