Ubiquitin: from Signaling to Disease
Cullin-RING Ubiquitin Ligases and Cell Signaling
Protein Interaction Networks and Quantitative Proteomics
Macro and Selective Autophagy
Mitochondrial Quality Control and Parkinson’s Disease
Protein turnover through the ubiquitin system is a central means by which the abundance of regulatory proteins are controlled. Many such proteins are involved in signal transduction cascades linked with cell proliferation, checkpoints, and cancer. This lab employs proteomic and genetic approaches to uncover key signaling systems, ubiquitin ligases, and regulatory circuits that control various biological pathways. Broad research areas are outlined on the RESEARCH link above.
In addition to the ubiquitin system, the lab is also exploring the mechanisms underlying large-scale proteome homeostasis, including the autophagy system and mitochondrial quality control in diseases such as Parkinson’s Disease. For example, the PARKIN protein, found mutated in familial early on-set forms of Parkinson’s Disease is a ubiquitin ligase that controls the degradation of damaged mitochondria via the process of autophagy (referred to as mitophagy). Our work in this area is focused on the use of proteomic approaches to identify targets of the PARKIN ubiquitin ligase and how PARKIN activates the mitophagy process (Sarraf et al., Nature, 2013). We have also now extended our mitochondrial work towards understanding how mitochondrial networks are established and how these complexes are deregulated in mitochondrial disease. Our first publication in this area recently appeared in Molecular and Cellular Biology (Guarani et a., MCB, 2014), where we identified a novel component of the assembly apparatus for Complex I of the electron transport chain.
To aid in our proteomic studies, we have developed several proteomic tools and methods that facilitate quantitative studies of signaling pathways and protein modifications such as phosphorylation and ubiquitylation. A key system is our proteomics platform called CompPASS (Comparative Proteomics Analysis Software Suite) (Sowa et al., Cell, 2009). CompPASS is designed to help facilitate the identification of high confidence candidate interacting proteins from IP-MS/MS data. The CompPASS website contains all of the data from the Cell paper describing the deubiquitinating enzyme interactome, the autophagy interactome (Nature, 2010), and ERAD interactome (Nature Cell Biology, 2011), as well as tools for navigating this data, and a CompPASS tutorial. This software can be accessed by clicking on the CompPASS icon (below). We have used this approach to examine the interaction partners of hundreds of proteins involved in signal transduction and disease. Recently, we have developed a new method called Parallel Adaptor Capture proteomics to identify substrates of cullin-RING ligases, and have applied it to the entire SCF-FBXL family of E3s, identifying numerous candidate substrates (Tan et al., Molecular Cell, 2013).
We have recently reported in Nature the use of quantitative proteomics to systematically identify autophagosome-enriched proteins, with a major goal of identifying new cargo and cargo receptors. Among the novel autophagosomally enriched proteins was NCOA4, a cytoplasmic protein that we demonstrated to localize to autophagosomal vesicles in response to activation of autophagy. Unbiased identification of NCOA4-associated proteins revealed ferritin heavy and light chains, components of an iron-filled cage structure that protects cells from reactive iron species but is degraded via autophagy to release iron through an unknown mechanism. We found that delivery of ferritin to lysosomes required NCOA4, and an inability of NCOA4-deficient cells to degrade ferritin leads to decreased bioavailable intracellular iron. Their work identifies NCOA4 as a selective cargo receptor for autophagic turnover of ferritin (ferritinophagy) critical for iron homeostasis and provides a resource for further dissection of autophagosomal cargo-receptor connectivity.
In addition, with the Gygi Lab we have developed diGLY proteomics as an approach for identification of ubiquitylation sites in proteins in a dynamic and quantitative manner (Kim et al., Molecular Cell 2011). This system can be used to characterize the ubiquitin modified proteome and to identify sites of ubiquitylation by specific ubiquitin ligases.
Finally, we are involved in the development of multiple quantitative approaches for measuring the effects of cellular perturbations on signaling networks and post-translational modifications. One approach is called Absolute Quantification (AQUA) which employs heavily labeled reference peptides to quantify individual proteins in complexes. We have used this approach to examine the dynamics of the CRL system (Bennett et al., Cell, 2010).