The adapter protein Nck: Role of individual SH3 and SH2 binding modules for protein interactions in T lymphocytes

Nck is a ubiquitously expressed, primarily cytosolic adapter protein consisting of one SH2 domain and three SH3 domains. It links receptor and nonreceptor tyrosine kinases to actin cytoskeleton reorganizing proteins. In T lymphocytes, Nck is a crucial component of signaling pathways for T cell activation and effector function. It recruits actin remodeling proteins to T cell receptor (TCR)‐associated activation clusters and thereby initiates changes in cell polarity and morphology. Moreover, Nck is crucial for the TCR‐induced mobilization of secretory vesicles to the cytotoxic immunological synapse. To identify the interactome of Nck in human T cells, we performed a systematic screen for interaction partners in untreated or pervanadate‐treated cells. We used GST fusion proteins containing full length Nck, the combined SH3 domains or the individual SH3 and SH2 domains to precipitate putative Nck interactors from cellular lysates. Protein bands were excised from gels, processed by tryptic in‐gel digestion and analyzed by mass spectrometry. Using this approach, we confirmed previously established interactions (e.g., with Slp76, CD3ε, WASP, and WIPF1) and identified several novel putative Nck‐binding proteins. We subsequently verified the SH2 domain binding to the actin‐binding protein HIP55 and to FYB/ADAP, and the SH3‐mediated binding to the nuclear proteins SFPQ/NONO. Using laser scanning microscopy, we provide new evidence for a nuclear localization of Nck in human T cells. Our data highlight the fundamental role of Nck in the TCR‐to‐cytoskeleton crosstalk and point to yet unknown nuclear functions of Nck also in T lymphocytes.     

A Highlights from MBoC Selection: Systematic identification of pathological lamin A interactors

Laminopathies are a collection of phenotypically diverse diseases that include muscular dystrophies, cardiomyopathies, lipodystrophies, and premature aging syndromes. Laminopathies are caused by >300 distinct mutations in the LMNA gene, which encodes the nuclear intermediate filament proteins lamin A and C, two major architectural elements of the mammalian cell nucleus. The genotype–phenotype relationship and the basis for the pronounced tissue specificity of laminopathies are poorly understood. Here we seek to identify on a global scale lamin A–binding partners whose interaction is affected by disease-relevant LMNA mutations. In a screen of a human genome–wide ORFeome library, we identified and validated 337 lamin A–binding proteins. Testing them against 89 known lamin A disease mutations identified 50 disease-associated interactors. Association of progerin, the lamin A isoform responsible for the premature aging disorder Hutchinson–Gilford progeria syndrome, with its partners was largely mediated by farnesylation. Mapping of the interaction sites on lamin A identified the immunoglobulin G (IgG)–like domain as an interaction hotspot and demonstrated that lamin A variants, which destabilize the Ig-like domain, affect protein–protein interactions more globally than mutations of surface residues. Analysis of a set of LMNA mutations in a single residue, which result in three phenotypically distinct diseases, identified disease-specific interactors. The results represent a systematic map of disease-relevant lamin A interactors and suggest loss of tissue-specific lamin A interactions as a mechanism for the tissue-specific appearance of laminopathic phenotypes.     

Prediction of interaction partners for orphan nuclear receptors by prior-based protein sequence profiles

We present a prior-based profile method for the prediction of protein-protein interaction partners that is here applied to the nuclear receptor superfamily. In this method, the diagnostic features are locally encoded in the physicochemical properties of residues in the interaction surface that are conserved in all proteins belonging to the defining set. The procedure models the positional variation based on that observed in the defining set and a prior-based substitution matrix derived from over 20,000 highly conserved positions in a set of 147 functional protein families. The method clusters sets of nuclear receptors known to interact with retinoid X receptor or corepressor proteins with predictive sets of receptors in C. elegans and higher metazoans. The method effectively reduces the search space of all possible interactions and yields experimentally testable predictions. Applications of this novel approach extend to interaction prediction problems in general, particularly to those that are not amenable to analysis by the rigid-body approximation.     

Comprehensive Analysis of Host Cellular Interactions with Human Papillomavirus E6 Proteins Identifies New E6 Binding Partners and Reflects Viral Diversity

We have begun to define the human papillomavirus (HPV)-associated proteome for a subset of the more than 120 HPV types that have been identified to date. Our approach uses a mass spectrometry-based platform for the systematic identification of interactions between human papillomavirus and host cellular proteins, and here we report a proteomic analysis of the E6 proteins from 16 different HPV types. The viruses included represent high-risk, low-risk, and non-cancer-associated types from genus alpha as well as viruses from four different species in genus beta. The E6 interaction data set consists of 153 cellular proteins, including several previously reported HPV E6 interactors such as p53, E6AP, MAML1, and p300/CBP and proteins containing PDZ domains. We report the genus-specific binding of E6s to either E6AP or MAML1, define the specific HPV E6s that bind to p300, and demonstrate several new features of interactions involving beta HPV E6s. In particular, we report that several beta HPV E6s bind to proteins containing PDZ domains and that at least two beta HPV E6s bind to p53. Finally, we report the newly discovered interaction of proteins of E6 of beta genus, species 2, with the Ccr4-Not complex, the first report of a viral protein binding to this complex. This data set represents a comprehensive survey of E6 binding partners that provides a resource for the HPV field and will allow continued studies on the diverse biology of the human papillomaviruses.     

Targeted tandem affinity purification of PSD‐95 recovers core postsynaptic complexes and schizophrenia susceptibility proteins

The molecular complexity of mammalian proteomes demands new methods for mapping the organization of multiprotein complexes. Here, we combine mouse genetics and proteomics to characterize synapse protein complexes and interaction networks. New tandem affinity purification (TAP) tags were fused to the carboxyl terminus of PSD‐95 using gene targeting in mice. Homozygous mice showed no detectable abnormalities in PSD‐95 expression, subcellular localization or synaptic electrophysiological function. Analysis of multiprotein complexes purified under native conditions by mass spectrometry defined known and new interactors: 118 proteins comprising crucial functional components of synapses, including glutamate receptors, K⁺ channels, scaffolding and signaling proteins, were recovered. Network clustering of protein interactions generated five connected clusters, with two clusters containing all the major ionotropic glutamate receptors and one cluster with voltage‐dependent K⁺ channels. Annotation of clusters with human disease associations revealed that multiple disorders map to the network, with a significant correlation of schizophrenia within the glutamate receptor clusters. This targeted TAP tagging strategy is generally applicable to mammalian proteomics and systems biology approaches to disease.     

Systematic prediction of human membrane receptor interactions

Membrane receptor‐activated signal transduction pathways are integral to cellular functions and disease mechanisms in humans. Identification of the full set of proteins interacting with membrane receptors by high‐throughput experimental means is difficult because methods to directly identify protein interactions are largely not applicable to membrane proteins. Unlike prior approaches that attempted to predict the global human interactome, we used a computational strategy that only focused on discovering the interacting partners of human membrane receptors leading to improved results for these proteins. We predict specific interactions based on statistical integration of biological data containing highly informative direct and indirect evidences together with feedback from experts. The predicted membrane receptor interactome provides a system‐wide view, and generates new biological hypotheses regarding interactions between membrane receptors and other proteins. We have experimentally validated a number of these interactions. The results suggest that a framework of systematically integrating computational predictions, global analyses, biological experimentation and expert feedback is a feasible strategy to study the human membrane receptor interactome.     

Towards the prediction of protein interaction partners using physical docking

Deciphering the whole network of protein interactions for a given proteome (‘interactome’) is the goal of many experimental and computational efforts in Systems Biology. Separately the prediction of the structure of protein complexes by docking methods is a well‐established scientific area. To date, docking programs have not been used to predict interaction partners. We provide a proof of principle for such an approach. Using a set of protein complexes representing known interactors in their unbound form, we show that a standard docking program can distinguish the true interactors from a background of 922 non‐redundant potential interactors. We additionally show that true interactions can be distinguished from non‐likely interacting proteins within the same structural family. Our approach may be put in the context of the proposed ‘funnel‐energy model’; the docking algorithm may not find the native complex, but it distinguishes binding partners because of the higher probability of favourable models compared with a collection of non‐binders. The potential exists to develop this proof of principle into new approaches for predicting interaction partners and reconstructing biological networks.     

EBIMed--text crunching to gather facts for proteins from Medline

To allow efficient and systematic retrieval of statements from Medline we have developed EBIMed, a service that combines document retrieval with co-occurrence-based analysis of Medline abstracts. Upon keyword query, EBIMed retrieves the abstracts from EMBL-EBI's installation of Medline and filters for sentences that contain biomedical terminology maintained in public bioinformatics resources. The extracted sentences and terminology are used to generate an overview table on proteins, Gene Ontology (GO) annotations, drugs and species used in the same biological context. All terms in retrieved abstracts and extracted sentences are linked to their entries in biomedical databases. We assessed the quality of the identification of terms and relations in the retrieved sentences. More than 90% of the protein names found indeed represented a protein. According to the analysis of four protein-protein pairs from the Wnt pathway we estimated that 37% of the statements containing such a pair mentioned a meaningful interaction and clarified the interaction of Dkk with LRP. We conclude that EBIMed improves access to information where proteins and drugs are involved in the same biological process, e.g. statements with GO annotations of proteins, protein-protein interactions and effects of drugs on proteins. AVAILABILITY: Available at http://www.ebi.ac.uk/Rebholz-srv/ebimed     

Identifying true protein complex constituents in interaction proteomics: The example of the DMXL2 protein complex

A typical high-sensitivity antibody affinity purification-mass spectrometry experiment easily identifies hundreds of protein interactors. However, most of these are non-valid resulting from multiple causes other than interaction with the bait protein. To discriminate true interactors from off-target recognition, we propose to differentially include an (peptide) antigen during the antibody incubation in the immuno-precipitation experiment. This contrasts the specific antibody-bait protein interactions, versus all other off-target protein interactions. To exemplify the power of the approach, we studied the DMXL2 interactome. From the initial six immuno-precipitations, we identified about 600 proteins. When filtering for interactors present in all anti-DMXL2 antibody immuno-precipitation experiments, absent in the bead controls, and competed off by the peptide antigen, this hit list is reduced to ten proteins, including known and novel interactors of DMXL2. Together, our approach enables the use of a wide range of available antibodies in large-scale protein interaction proteomics, while gaining specificity of the interactions.     

Rac1 activation inhibits E-cadherin-mediated adherens junctions via binding to IQGAP1 in pancreatic carcinoma cells

Nck is a ubiquitously expressed adapter protein that is almost exclusively built of one SH2 domain and three SH3 domains. The two isoproteins of Nck are functionally redundant in many aspects and differ in only few amino acids that are mostly located in the linker regions between the interaction modules. Nck proteins connect receptor and non-receptor tyrosine kinases to the machinery of actin reorganisation. Thereby, Nck regulates activation-dependent processes during cell polarisation and migration and plays a crucial role in the signal transduction of a variety of receptors including for instance PDGF-, HGF-, VEGF- and Ephrin receptors. In most cases, the SH2 domain mediates binding to the phosphorylated receptor or associated phosphoproteins, while SH3 domain interactions lead to the formation of larger protein complexes. In T lymphocytes, Nck plays a pivotal role in the T cell receptor (TCR)-induced reorganisation of the actin cytoskeleton and the formation of the immunological synapse. However, in this context, two different mechanisms and adapter complexes are discussed. In the first scenario, dependent on an activation-induced conformational change in the CD3ε subunits, a direct binding of Nck to components of the TCR/CD3 complex was shown. In the second scenario, Nck is recruited to the TCR complex via phosphorylated Slp76, another central constituent of the membrane proximal activation complex. Over the past years, a large number of putative Nck interactors have been identified in different cellular systems that point to diverse additional functions of the adapter protein, e.g. in the control of gene expression and proliferation.     

Domains of the human androgen receptor and glucocorticoid receptor involved in binding to the nuclear matrix

Steroid receptors have been reported to bind to the nuclear matrix. The nuclear matrix is operationally defined as the residual nuclear structure that remains after extraction of most of the chromatin and all soluble and loosely bound componnets. To obtain insight in the molecular mechanism of the interaction of steroid receptors with the nuclear matrix, we studied the binding of several deletion mutants of the human androgen receptor (hAR) and the human glucocorticoid receptor (hGR) to the nuclear matrix. Receptor binding was tested for two different nuclear matrix preparations: complete matrices, in which most matrix proteins are retained during the isolation procedure, and depleted matrices, which consist of only a subset of these proteins. The results show that the C-terminal domain of the hAR binds tightly to both depleted and complete matrices. In addition, at least one other domain of the hAR binds to complete matrices but not to depleted matrices. In contrast to the hAR, the hGR binds only to complete matrices. For this interaction both the DNA-binding domain and the C-terminal domain of the hGR are required, whereas the N-terminal domain is not. We conclude that specific protein domains of the hAR and the hGR are involved in binding to the nuclear matrix. In addition, our results indicate that the hAR and the hGR are attached to the nuclear matrix through different molecular interactions.     

Interaction proteomics of the AMPA receptor: towards identification of receptor sub-complexes

AMPA receptors (AMPAR) are the main ligand-gated ion channels responsible for the fast excitatory synaptic transmission in the mammalian brain. Whereas a number of proteins that interact with AMPAR are known to be involved in the trafficking and localization of the receptor and/or the regulation of receptor channel properties, the protein composition of the AMPAR supra-complexes are largely unclear. Recent interaction proteomics report the presence of up to 34 proteins as high-confidence constituents of the AMPAR. It was proposed that the inner core of the receptor complex consists of the GluA tetramer and four auxiliary proteins comprising transmembrane AMPA receptor regulatory proteins and/or cornichons. The other AMPAR interactors, present in lower amount, may form the outer shell of the AMPAR with a range in size and variability.     

An interaction map of proteasome subunits

Despite the central role of the 26 S proteasome in eukaryotic cells, many facets of its structural organization and functioning are still poorly understood. To learn more about the interactions between its different subunits, as well as its possible functional partners in cells, we performed, with Marc Vidal's laboratory (Dana-Farber Cancer Institute, Boston, MA, U.S.A.), a systematic two-hybrid analysis using Caenorhaditis elegans 26 S proteasome subunits as baits [Davy, Bello, Thierry-Mieg, Vaglio, Hitti, Doucette-Stamm, Thierry-Mieg, Reboul, Boulton, Walhout et al. (2001) EMBO Rep. 2, 821-828]. A pair-wise matrix of all subunit combinations allowed us to detect numerous possible intra-complex interactions, among which some had already been reported by others and eight were novel. Interestingly, four new interactions were detected between two ATPases of the 19 S regulatory complex and three alpha-subunits of the 20 S proteolytic core. Possibly, these interactions participate in the association of these two complexes to form the 26 S proteasome. Proteasome subunit sequences were also used to screen a cDNA library to identify new interactors of the complex. Among the interactors found, most (58) have no clear connection to the proteasome, and could be either substrates or potential cofactors of this complex. Few interactors (7) could be directly or indirectly linked to proteolysis. The others (12) interacted with more than one proteasome subunit, forming 'interaction clusters' of potential biological interest.