“Deciphering the topology of molecular interaction networks is critical to understanding what goes wrong when cells become diseased.”
–Jeff Ranish, PhD, Professor
A particular focus of the research done by Jeff Ranish and his colleagues has been the complexes that control expression of protein coding genes at the level of transcription. These complexes can be very large and their composition often changes in response to cellular and environmental conditions. For example, in macrophages, the liver X receptor (LXR) transcription factors regulate expression of target genes in response to different stimuli by interacting with co-activator or co-repressor proteins. To understand how LXR protein complexes control expression of cholesterol efflux genes, the Ranish group developed a promoter enrichment-quantitative mass spectrometry approach to characterize the composition of complexes that assemble at the regulatory elements of these genes under different conditions. This led to the discovery of a number of LXR interacting proteins that are required for proper control of cholesterol efflux genes in response to lipid and inflammatory signals. Because dysregulation of cholesterol efflux can lead to intracellular cholesterol accumulation and the formation of atherosclerosis-promoting foam cells, these proteins and their interactions may represent targets for the development of therapeutics for the treatment of atherosclerosis.
To decipher the structural basis for protein complex function, the group has developed chemical crosslinking-mass spectrometry (CLMS) technologies, including novel crosslinking reagents, methodologies, and computational programs that can provide information about subunit proximity within protein complexes. Often computational approaches are used to integrate the CLMS information with other sources of structural data to obtain models with higher resolution. These models can then be used to develop strategies to control the activity of the complexes in desired ways. The group has used this approach to determine the architecture of several large transcriptional regulatory complexes including the general transcription factor TFIIH, the TFIID co-activator complex, and the SWI-SNF chromatin remodeling complex.
The Ranish lab also is developing mass spectrometry-based approaches to systematically detect and quantify specific proteins such as transcription factors during dynamic processes such as cell differentiation. Changes in transcription factor abundance and stoichiometry drive cell state changes, in part by affecting molecular interactions. However, our understanding of these complex relationships is limited by the paucity of nuclear protein concentration information. To address this issue, the group developed a targeted mass spectrometry approach to quantify the absolute abundances of large numbers of TFs and cofactors across multiple sequential time points during human erythropoiesis. In doing so, they defined the protein concentration (copies/nucleus) for master regulators of hematopoiesis/erythropoiesis, as well as coregulators of transcription, thereby providing a quantitative scale for human TFs in the nucleus (http://apps.systemsbiology.net/app/Transcription_Factor_Protein_RNA_Erythropoiesis). In addition, comparison of protein and mRNA expression patterns suggests that many TFs are regulated by post-transcriptional mechanisms. By integrating these absolute protein abundances with mRNA measurements they generated a dynamic gene regulatory network of erythroid commitment (http://grns.biotapestry.org/HumanErythropoiesisGRN/). These data provide unique and important information for understanding the transcriptional regulatory programs controlling erythropoiesis, as well as general mechanisms that may regulate cell fate decisions in different systems.
By providing an in-depth understanding of how genes are turned on and off, the research will reveal information that is key to determining how cells function in health and disease. Understanding these processes will make it possible to reprogram the behavior of cells when the dysregulation of gene expression results in disease.
