Our lab uses integrative biochemical and genomic approaches to study gene regulation in the immune and inflammatory systems. To mount the appropriate response to a particular infection or injury, cells in the body must integrate extracellular signals and turn on the appropriate target genes. The exquisite specificity of the body’s immune response to different assaults is a hallmark of its proper function, but when it goes awry it can lead to disease.
We use computational and experimental approaches to examine gene regulation at multiple levels. At the molecular level, we examine how transcription factor proteins binding together on DNA control elements integrate signaling events and direct gene transcription. This is commonly referred to as the cis-regulatory logic. At a more global, systems level, we investigate how the molecular cis-regulatory logic operating at individual genes relates to the function and specificity of the larger gene regulatory network in a cell. For example, are sets of co-transcribed genes governed by the same cis-regulatory logic, and how does the cell specify a particular set of genes from all others in the genome?
Current projects are focused on the central immune regulator NF-kB and how interactions with other proteins modify or provide specificity to the NF-kB response. We are using protein-binding microarrays (PBMs) to characterize the binding specificity of protein complexes involving NF-kB dimers and other immune transcription factors such as HMGA1 proteins, C/EBPβ, and Irf proteins. This genome-scale binding data is integrated with in vivo binding data determined by chromatin immuno-precipitation followed by high-throughput sequencing (ChIP-seq) to construct models of the operating transcriptional regulatory logic. These models are tested in cellular assays by monitoring gene expression in wild-type cells and cells where particular genes or pathways are modified by RNAi or chemical inhibitors.
More purely computational efforts in the lab are currently focused on the integration of genomic datasets (e.g., ChIP-seq, gene expression, DNAse I hypersensitivity maps, chromatin modification data) and libraries of transcription factor binding data to predict transcriptional regulatory codes for co-transcribed gene sets. Of particular interests are transcriptional responses and codes operating in innate immune cells such as macrophages and dendritic cells, the sentinel responders in our immune system.