Systems-Level Analysis of the Toll-like Receptor Network of Dendritic Cells
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CitationChevrier, Nicolas. 2012. Systems-Level Analysis of the Toll-like Receptor Network of Dendritic Cells. Doctoral dissertation, Harvard University.
AbstractCells detect and respond to environmental changes using intracellular networks, and defects in the wiring of these networks contribute to diseases. For example, Toll-like receptors (TLRs) sense microbial molecules and trigger pathways critical for host defense. Genetic defects in components of the TLR and other pathogen-sensing pathways have been linked to human diseases. Hence, rational targeting of these pathways should help to manipulate immune responses associated with infections, autoimmunity, or vaccines. A fundamental challenge is to dissect the intracellular networks mobilized by pathogen-sensing pathways. Here we present approaches to dissect the TLR network of innate immune dendritic cells (DCs), focusing on two regulatory layers: signaling and transcription. First, we present a strategy to systematically perturb candidate regulators and monitor cellular transcriptional responses. We apply this approach to derive regulatory networks that control the transcriptional response to TLR engagement by microbial molecules. Our approach revealed the regulatory functions of 125 transcription factors (TFs), chromatin modifiers, and RNA binding proteins, which enabled the construction of a network model consisting of 24 core regulators and 76 “fine-tuners” that help explain how TLR pathways achieve specificity. Second, we report the systematic discovery of signaling components in TLR responses. By combining transcriptional profiling, genetic and small molecule perturbations, and phosphoproteomics, we uncover 35 signaling regulators, including 16 known members of the TLR signaling pathways. In particular, we find that Polo-like kinases (Plk) 2 and 4 are essential components of antiviral pathways in vitro and in vivo and activate a signaling branch involving a dozen proteins, among which is Tnfaip2, a gene associated with autoimmune diseases but whose role was unknown. Lastly, we expand these approaches to integrate functional and physical interactions linking the ‘signaling-to-transcription’ TLR network. By combining our perturbation-based approach with measurements of physical interactions, including phosphorylation, protein complexes, and TF binding to DNA, we uncover 30 signaling regulators mechanistically linked to 19 downstream TFs. The integration of these datasets into a model reveals the organization of the TLR response. Overall, these studies illustrate the power of combining systematic measurements and perturbations to elucidate complex intracellular circuits and discover potential therapeutic targets.
Citable link to this pagehttp://nrs.harvard.edu/urn-3:HUL.InstRepos:9549940
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