Session 3 (The American Society for Biochemistry and Molecular Biology, 2014)
5.1 Resolving Sites of Protein Palmitoylation Using Quantitative Proteomics Mark Collins(1), Jyoti Choudhary(2) (1)University of Sheffield, Sheffield, GB; (2)The Wellcome Trust Sanger Institute, Hinxton, GB Protein palmitoylation (S-acylation) is a reversible lipid modification that is increasingly recognised as an important regulator of protein function including membrane association, trafficking and subcellular localization. Palmitoylated proteins may be purified using methods that selectively replace palmitoyl groups with affinity tags or by the use metabolic labelling with palmitic acid analogues that can be selectively captured. The combination of these methods with mass spectrometry has enabled the identification of many palmitoylated proteins from a range of cells, tissues and species. However, these approaches lack the resolution to identify exact sites of palmitoylation, the number of palmitoylation sites on a given protein or the potential to measure differentially regulated palmitoylation sites. We demonstrate a quantitative site-specific acyl-biotin exchange (ssABE) method that allowed the identification of 906 palmitoylation sites on 641 proteins from mouse forebrain. 46.4% of sites map to known palmitoylated proteins and high coverage of important receptors, ion channels and palmitoyl acyl transferases (PATs) was obtained. Palmitoylation sites from membrane and soluble proteins displayed distinct topological features and were associated with specific sequence motifs. Sites of palmitoylation were enriched at positions near transmembrane helices and were found to occur in regions less modified with other post-translational modifications. Using this technology we demonstrate for the first time, the large-scale quantitative analysis of the effects of global pharmacological inhibition of acyl transferases and specific inhibition of acyl protein thioesterase 1 (APT1), revealing substrates with palmitoylation site resolution. 5.2 A Novel Comprehensive Discovery Approach for SUMO Modified Proteins Jesse G. Meyer, Bing Yang, Eric Bennett, Elizabeth A. Komives University of California, San Diego, CA, USA Wild type alpha-lytic protease (WaLP) was recently shown to cleave at aliphatic residues including Threonine. We therefore sought to determine whether cleavage with WaLP would provide a way of generating the lysyl-GG remnant from SUMOylated proteins in a manner similar to the way in which trypsin is used to generate the lysyl-GG remnant from ubiquitylated proteins. The C-terminal sequence of Ub that is attached to lysines in RGG whereas the C-terminal sequence of human SUMOs attached to lysines is TGG. Since the lysyl-GG remnant generated by WaLP digestion of Sumoylated proteins is the same as the lysyl-GG remnant generated by trypsin digestion of Ubiquitylated proteins, the same antibody enrichment schemes that have already been developed for comprehensive mapping of ubiquitinylation can be used to enrich for lysyl-GG remnants from WaLP digestion of Sumoylated proteins. An important aspect of this work is the orthogonality between trypsin and WaLP such that the GG remnants generated from WaLP digestion derive only from cleavage of SUMOylated proteins whereas the GG remnants generated from trypsin digestion derive only from cleavage of Ubiquitylated proteins. Here we show that WaLP can, indeed, be used for comprehensive global mapping of SUMOylated proteins. We compare results from the same cell samples digested with trypsin or with WaLP. WaLP, therefore, provides a new way to comprehensively determine SUMOylated proteins without the need for introduction of mutations. 5.3 NeuCode Mass Spectrometry Unveils New Roles for Ubiquitin Machinery in Metabolic Homeostasis Joshua M. Baughman(1), Chris M. Rose(9), Ganesh Kolumam(7), Joshua Webster(3), Anna E. Merrill(9), Daisy Bustos(1), Paula Katavolos(4), Christian Cunningham(2), Lillian Phu(1), Joy Tea(8), Justin Lesch(5), Raymond Asuncion(6), Melanie Domeyer(6), Jose Zavala-Solorio(2), Jason deVoss(5), Baris Bingol(8), Anwesha Dey(2), Joshua Coon(9), Donald Kirkpatrick(1) (1) Departments of Protein Chemistry, (2)Translational Oncology, (3)Pathology, (4)Safety assessment, (5)Translational immunology, (6)Dixon, (7)Biomedical Imaging, (8)Neuroscience. Genentech, Inc., South San Francisco, CA, (9) University of Wisconsin-Madison, WI, USA Disruptions in metabolic homeostasis are linked to a variety of common disorders ranging from diabetes to cancer and even Parkinson's disease. Genetic approaches have exposed key roles for ubiquitination machinery in regulating disease-relevant metabolic networks. Currently, we do not have a complete proteomic picture of these “metabolic proteostasis” pathways. To build such a picture, we must know the specific targets and pertinent biological pathways influenced by ubiquitin enzymes involved in metabolism. Recent advances in mass spectrometry now allow for deep interrogation of post-translational modifications (PTMs), including ubiquitin, and have facilitated analyses of ubiquitin enzymes and their relevant substrates. However, studies of ubiquitin involvement in metabolism require techniques that are simultaneously compatible with in vivo metabolic models, lysine PTM immunoaffinity enrichment and time course experiments. To overcome these hurdles, we have adopted a NeuCode multiplexing strategy. We metabolically label lysines in cell lines with up to four NeuCode isotopes and demonstrate compatibility with immunoaffinity enrichment of K-GG (ubiquitinated) peptides. We have applied our technique to study a ubiquitination cascade following mitochondrial depolarization that is relevant to Parkinson's disease. To test whether NeuCode labeling can be used in vivo, we generated a NeuCode mouse model, in which we have metabolically labeled the lysines of wild-type mice and mice lacking a deubiquitinating enzyme called BAP1. Our NeuCode mouse data reveals that loss of BAP1 perturbs liver and pancreas metabolic pathways ultimately leading to misregulation of glucose and lipid homeostasis. 5.4 Functional Glycomics - Defining Glycan Recognition by Proteins Richard D. Cummings, David F. Smith, Xuezheng Song Emory University School of Medicine, Atlanta, GA, USA Glycosylation of proteins is a common post-translational modification resulting in thousands of different glycan structures attached to specific amino acid residues, including the most common modifications of asparagine (N-glycans), and serine/threonine (O-glycans). Glycan structures are elaborated by several hundred gene products that define the site and structure of glycoprotein. Glycans serve two key roles in glycoproteins; as both integral structural components to participate in protein folding, oligomerization, stability, etc, and as key recognition components for glycan-binding proteins (GBPs). We have explored the recognition of glycans by GBPs from humans, animals, and pathogens, using glycan microarray technologies, whereby glycans are derivatized, and covalently printed on surfaces for interrogation by individual GBPs using fluorescence-based techniques. Since human and animal glycomes contain many thousands of glycan species, we have used a “shotgun glycomic” approach, whereby glycans are chemically released from proteins and lipids or present as free glycans in body fluids, e.g. human milk, and the glycan mixtures are derivatized with fluorescent tags. The tagged glycans are purified by multiple chromatographic strategies and individual glycans are then covalently printed in nanograms quantities for microarray studies. Glycans of interest that are identified and recognized by specific GBPs are then further structurally defined using mass spectrometry and other metadata-assisted approaches. Our studies have focused on natural glycans isolated from human and animal cells and tissues, and have revealed novel glycans recognized by many different human GBPs as well as GBPs in human pathogens. The presentation will focus on the functional aspects of glycomics where structural analyses are coupled to studies on glycan recognition. [Supported by NIH Grants to RDC: P41GM103694, R24GM09879, and AI101982.] 6.1 Dynamic Profiling of the Protein Life Cycle Reveals Two Distinct Strategies for Controlling Differential Expression of Immune and Housekeeping Protein Levels in Response to Pathogens Marko Jovanovic,(1) Michael Rooney(1), Philipp Mertins(1), Dariusz Przybylski(1), Nicolas Chevrier(2), Rahul Satija(1), Schraga Schwartz(1), Raktima Raychowdhury(1), Max Mumbach(1), Thomas Eisenhaure(1), Michal Rabani(1), Dave Gennert(1), Diana Lu(1), Toni Delorey(1), Steven A. Carr(1), Nir Hacohen(1), Aviv Regev(1) (1)The Broad Institute of MIT and Harvard, Cambridge, MA, USA; (2)Harvard FAS Center for Systems Biology, Boston, MA, USA Protein expression is tightly regulated by the interplay between production and degradation of mRNAs and proteins, but it is still debated whether changes in mRNA levels are primary or minor drivers of protein changes during dynamic responses. Here, we combine pulsed SILAC proteomics measurements of protein production and degradation and data on RNA dynamics with a novel computational approach to build a quantitative, genome-scale model of the temporal differential regulation of gene expression in the model system of LPS stimulated dendritic cells (DCs). We find that upon LPS stimulation, changes in RNA abundance play a dominant role in determining most dynamic fold changes in protein levels, especially for strongly induced immune response proteins. Nevertheless, the preexisting proteome of housekeeping proteins is functionally remodeled primarily through changes in protein production or degradation, accounting for half of the absolute change in protein molecules in the cell. In particular, there is enhanced degradation of mitochondrial proteins, which may contribute to a metabolic shift in stimulated DCs, and a selective increase in the translation of some ribosomal proteins, including Rps11, a protein we show is required for the LPS response. Our findings support a model where the cellular proteome is dynamically regulated through two strategies: induction of novel cellular functions by transcriptional changes, and remodeling of pre-existing functions by changes in protein production or degradation of abundant proteins. 6.2 High-Throughput Proteomic Mapping of Protein Interaction Networks: Toward a Global View of the Human Interactome Edward Huttlin, Lily Ting, Raphael J. Bruckner, Joao A. Paulo, Melanie P. Gygi, Ramin Rad, Deepak Kolippakkam, John Szpyt, Gabriela Zarraga, Stanley Tam, Fana Gebreab, Greg Colby, Robert A. Obar, Virginia Guarani-Pereira, Timothy Harris, Spyros Artavanis-Tsakonas, Mathew E. Sowa, J. Wade Harper, Steven P. Gygi Harvard Medical School, Boston, MA, USA Because a cell's phenotype reflects its underlying proteome, mass-spectrometry-enabled proteomic studies can provide essential biological insights. Whereas surveys of protein expression and select post-translational modifications have achieved near-comprehensive scope, mass-spectrometry-based protein interaction profiles have typically examined small protein families while leaving vast swaths of the interaction landscape unexplored. To achieve more comprehensive examination, we have established a high-throughput pipeline capable of elucidating interactions for several hundred baits per month and are now systematically mapping human protein interactions at unparalleled depth and breadth. The emerging interaction network is providing unique insights into both normal and pathological biological processes by revealing novel functions for familiar proteins and providing tantalizing clues into roles of unknown proteins. Our high-throughput platform for protein interaction profiling relies upon expressing HA-tagged versions of up to 13,000 human proteins within HEK293T cells; following immunoprecipitation, the baits and their interacting partners are identified using Q-Exactive mass spectrometers aided by customized data analysis techniques. To date we have completed analysis of over 2500 bait proteins and their interacting partners, defining an interaction network that spans 24000 interactions among nearly 8000 proteins. The resulting network reveals clusters matching known subcellular structures such as the proteasome, signalsome, and mediator complexes, while suggesting biological functions for unknown proteins and highlighting shared functional and regulatory clusters across the interactome. Whether viewed individually or in aggregate, these interaction profiles offer unique insights into both known and unknown proteins while also illuminating larger patterns of proteomic regulation.