MODELING THE INNATE IMMUNE RESPONSE NETWORK

Scripps Research Institute, La Jolla CA

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Abstract

Integrative modeling of the innate immune response will predict system behaviors to enable the modulation of the TLR-dependent pro-inflammatory signaling network. Our modeling methods are based on the modular structure and function of biological systems. We will extend our methods and contribute implementations of these to the Cytoscape network-modeling platform of the Bioinformatics Core. In collaboration with the Underhill Bridging Project, we will inform the selection of signaling protein candidates for interaction profiling in the Proteomics Core. We will integrate these interaction data with genome-scale mRNA and protein expression data gathered in the Underhill, Steinman, Ravetch, and Aderem Bridging Projects. With this combination of global data types, we will construct models of the innate immune response network in two states, unstimulated, and after stimulation by lipopolysaccharide (LPS). Based on the modular structure of the network, the expression of local subnetworks, and the changes in network structure from the unstimulated to the stimulated state, we will predict the effects of specific network perturbations. In collaboration with the Animal Models and Forward Genetics Cores, we will test these predictions by assessing the susceptibilities of mutant mice to infection. With the Aderem Bridging Project and the Genomics Core, macrophages derived from these mice will be assayed for gene-expression responses to LPS and other pathogen-associated molecular patterns (PAMPs). Of particular interest will be the modulation of the innate immune response and the creation of tailored responses.