Ubiquitin: from Signaling to Disease
- Cullin-RING Ubiquitin Ligases and Cell Signaling
- Protein Interaction Networks and Quantitative Proteomics
- Macro and Selective Autophagy, including mitophagy
- 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 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. Further studies have revealed a novel component of a cristae junction complex called MICOS (eLife, 2015). The new transmembrane protein QIL1 links multiple components of MICOS together in the mitochondrial inner membrane. In collaboration with Manuel Schiff, we demonstrated that QIL1 is mutated in early onset fetal mitochondrial encephalopathy and cells from patients have disrupted cristae junctions and mitochondrial structure (eLife, 2016). Recently, we have also explored to mitichondrial unfolded protein response using proteomics and RNA-Seq, identifying roles for Pre-RNA processing in mitochondrial UPR (Munch et al., Nature, 2016). More recently, we have systematically examined the roles of the 6 ATG8 proteins in human cells using CRISPR-based gene editing, proteomics, and cell biological approaches (Pontano-Vaites et al., MCB, 2016). We have also systematically examined ribophagy under a number of distinct stress conditions, identifying stress agents that induce ribophagy and also degradation of other cytosolic proteins (An and Harper, Nature Cell Biology, 2016).
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 now extended this to the p97 network, identifying a large collection of UBDX domain containing adaptor associated proteins and a role for one of them in ciliogenesis (Raman et al., Nature Cell Biology, 2015)
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. Our 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. We have now combinded this with Tandem Mass Tagging (TMT) based quantitative proteomics to examine thousands of ubiquitylation sites in a signal-dependent manner. Using this system we have extensively mapped PARKIN-dependent ubiquitylation of mitochondria (Rose et al., Cell Systems, 2016).
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). We have extended this to identify a feed-forward mechanism for PARKIN and PINK1-dependent mitochondrial ubiquitylation, and discovered PINK1 dependent phosphoryaltion of ubiquitin to promote PARKIN recruitment to mitochondrial (Ordureau et al., Molecular Cell, 2014; Ordureau et al., PNAS 2015). We also identified an OPTN-TBK1 complex as a critical element in the recruitment of ubiquitylated mitochondria to the autophagosome (Heo et al., Molecular Cell, 2015).
Together with the Gygi lab, we have developed a large scale platform for interaction proteomics and a website allowing access to the database (http//:bioplex.hms.harvard.edu). In our initial study (Huttlin et al Cell, 2015), we determined the interaction partners for 2500 bait proteins in HEK293T cells using stable protein expression, purification, and LC-MS/MS. This work identified a network of more than 7000 proteins involving 25000 interactions. We have continued this process, producing a network originating from now 7500 bait proteins, 6000 of which were recently published in Huttlin et al., Nature 2017 (see Publications), all of which is available at the website. This data provides novel insights into the landscape of protein interactions for a large fraction of the proteome. Lenti viral expression clones from this project are available from the DF/HCC DNA Resource Core (see link on menu bar above).
Access to the BIOPLEX website (http//:bioplex.hms.harvard.edu)