Nuclear import of the DSCAM-cytoplasmic domain drives signaling capable of inhibiting synapse formation.

DSCAM and DSCAML1 are immunoglobulin and cell adhesion-type receptors serving important neurodevelopmental functions including control of axon growth, branching, neurite self-avoidance, and neuronal cell death. The signal transduction mechanisms or effectors of DSCAM receptors, however, remain poorly characterized. We used a human ORFeome library to perform a high-throughput screen in mammalian cells and identified novel cytoplasmic signaling effector candidates including the Down syndrome kinase Dyrk1a, STAT3, USP21, and SH2D2A. Unexpectedly, we also found that the intracellular domains (ICDs) of DSCAM and DSCAML1 specifically and directly interact with IPO5, a nuclear import protein of the importin beta family, via a conserved nuclear localization signal. The DSCAM ICD is released by γ-secretase-dependent cleavage, and both the DSCAM and DSCAML1 ICDs efficiently translocate to the nucleus. Furthermore, RNA sequencing confirms that expression of the DSCAM as well as the DSCAML1 ICDs alone can profoundly alter the expression of genes associated with neuronal differentiation and apoptosis, as well as synapse formation and function. Gain-of-function experiments using primary cortical neurons show that increasing the levels of either the DSCAM or the DSCAML1 ICD leads to an impairment of neurite growth. Strikingly, increased expression of either full-length DSCAM or the DSCAM ICD, but not the DSCAML1 ICD, significantly decreases synapse numbers in primary hippocampal neurons. Taken together, we identified a novel membrane-to-nucleus signaling mechanism by which DSCAM receptors can alter the expression of regulators of neuronal differentiation and synapse formation and function. Considering that chromosomal duplications lead to increased DSCAM expression in trisomy 21, our findings may help uncover novel mechanisms contributing to intellectual disability in Down syndrome.

A protein domain-based interactome network for C. elegans early embryogenesis.

Many protein-protein interactions are mediated through independently folding modular domains. Proteome-wide efforts to model protein-protein interaction or "interactome" networks have largely ignored this modular organization of proteins. We developed an experimental strategy to efficiently identify interaction domains and generated a domain-based interactome network for proteins involved in C. elegans early-embryonic cell divisions. Minimal interacting regions were identified for over 200 proteins, providing important information on their domain organization. Furthermore, our approach increased the sensitivity of the two-hybrid system, resulting in a more complete interactome network. This interactome modeling strategy revealed insights into C. elegans centrosome function and is applicable to other biological processes in this and other organisms.

The Development of RNA-KISS, a Mammalian Three-Hybrid Method to Detect RNA-Protein Interactions in Living Mammalian Cells.

RNA-protein interactions are essential for the regulation of mRNA and noncoding RNA functions and are implicated in many diseases, such as cancer and neurodegenerative disorders. A method that can detect RNA-protein interactions in living mammalian cells on a proteome-wide scale will be an important asset to identify and study these interactions. Here we show that a combination of the mammalian two-hybrid protein-protein detection method KISS (kinase substrate sensor) and the yeast RNA three-hybrid method, utilizing the specific interaction between the MS2 RNA and MS2 coat protein, is capable of detecting RNA-protein interactions in living mammalian cells. For conceptional proof we used the subgenomic flavivirus RNA (sfRNA) of the dengue virus (DENV), a highly structured noncoding RNA derived from the DENV genome known to target host cell proteins involved in innate immunity and antiviral defense, as bait. Using RNA-KISS, we could confirm the previously established interaction between the RNA-binding domain of DDX6 and the DENV sfRNA. Finally, we performed a human proteome-wide screen for DENV sfRNA-binding host factors, identifying several known flavivirus host factors such as DDX6 and PACT, further validating the RNA-KISS method as a robust and high-throughput cell-based RNA-protein interaction screening tool.

Proteome-scale Binary Interactomics in Human Cells.

Because proteins are the main mediators of most cellular processes they are also prime therapeutic targets. Identifying physical links among proteins and between drugs and their protein targets is essential in order to understand the mechanisms through which both proteins themselves and the molecules they are targeted with act. Thus, there is a strong need for sensitive methods that enable mapping out these biomolecular interactions. Here we present a robust and sensitive approach to screen proteome-scale collections of proteins for binding to proteins or small molecules using the well validated MAPPIT (Mammalian Protein-Protein Interaction Trap) and MASPIT (Mammalian Small Molecule-Protein Interaction Trap) assays. Using high-density reverse transfected cell microarrays, a close to proteome-wide collection of human ORF clones can be screened for interactors at high throughput. The versatility of the platform is demonstrated through several examples. With MAPPIT, we screened a 15k ORF library for binding partners of RNF41, an E3 ubiquitin protein ligase implicated in receptor sorting, identifying known and novel interacting proteins. The potential related to the fact that MAPPIT operates in living human cells is illustrated in a screen where the protein collection is scanned for interactions with the glucocorticoid receptor (GR) in its unliganded versus dexamethasone-induced activated state. Several proteins were identified the interaction of which is modulated upon ligand binding to the GR, including a number of previously reported GR interactors. Finally, the screening technology also enables detecting small molecule target proteins, which in many drug discovery programs represents an important hurdle. We show the efficiency of MASPIT-based target profiling through screening with tamoxifen, a first-line breast cancer drug, and reversine, an investigational drug with interesting dedifferentiation and antitumor activity. In both cases, cell microarray screens yielded known and new potential drug targets highlighting the utility of the technology beyond fundamental biology.

Kinase Substrate Sensor (KISS), a mammalian in situ protein interaction sensor.

Probably every cellular process is governed by protein-protein interaction (PPIs), which are often highly dynamic in nature being modulated by in- or external stimuli. Here we present KISS, for KInase Substrate Sensor, a mammalian two-hybrid approach designed to map intracellular PPIs and some of the dynamic features they exhibit. Benchmarking experiments indicate that in terms of sensitivity and specificity KISS is on par with other binary protein interaction technologies while being complementary with regard to the subset of PPIs it is able to detect. We used KISS to evaluate interactions between different types of proteins, including transmembrane proteins, expressed at their native subcellular location. In situ analysis of endoplasmic reticulum stress-induced clustering of the endoplasmic reticulum stress sensor ERN1 and ligand-dependent ß-arrestin recruitment to GPCRs illustrated the method's potential to study functional PPI modulation in complex cellular processes. Exploring its use as a tool for in cell evaluation of pharmacological interference with PPIs, we showed that reported effects of known GPCR antagonists and PPI inhibitors are properly recapitulated. In a three-hybrid setup, KISS was able to map interactions between small molecules and proteins. Taken together, we established KISS as a sensitive approach for in situ analysis of protein interactions and their modulation in a changing cellular context or in response to pharmacological challenges.

Alternative reagents for methotrexate as immobilizing anchor moieties in the optimization of MASPIT: synthesis and biological evaluation.

We report the evaluation of two alternative chemical dimerizer approaches aimed at increasing the sensitivity of MASPIT, a three-hybrid system that enables small-molecule target protein profiling in intact human cells. To circumvent the potential limitations related to the binding of methotrexate (MTX) to endogenous human dihydrofolate reductase (DHFR), we explored trimethoprim (TMP) as an alternative prokaryote-specific DHFR ligand. MASPIT evaluation of TMP fusion compounds with tamoxifen, reversine, and simvastatin as model baits, resulted in dose-response curves shifted towards lower EC50 values than those of their MTX congeners. Furthermore, a scalable azido-TMP reagent was synthesized that displayed a similar improvement in sensitivity, possibly owing to increased membrane permeability relative to the MTX anchor. Applying the SNAP-tag approach to introduce a covalent bond into the system, on the other hand, produced an inferior readout than in the MTX- or TMP-tag based assay.

MX2 forms nucleoporin-comprising cytoplasmic biomolecular condensates that lure viral capsids.

Human myxovirus resistance 2 (MX2) can restrict HIV-1 and herpesviruses at a post-entry step through a process requiring an interaction between MX2 and the viral capsids. The involvement of other host cell factors, however, remains poorly understood. Here, we mapped the proximity interactome of MX2, revealing strong enrichment of phenylalanine-glycine (FG)-rich proteins related to the nuclear pore complex as well as proteins that are part of cytoplasmic ribonucleoprotein granules. MX2 interacted with these proteins to form multiprotein cytoplasmic biomolecular condensates that were essential for its anti-HIV-1 and anti-herpes simplex virus 1 (HSV-1) activity. MX2 condensate formation required the disordered N-terminal region and MX2 dimerization. Incoming HIV-1 and HSV-1 capsids associated with MX2 at these dynamic cytoplasmic biomolecular condensates, preventing nuclear entry of their viral genomes. Thus, MX2 forms cytoplasmic condensates that likely act as nuclear pore decoys, trapping capsids and inducing premature viral genome release to interfere with nuclear targeting of HIV-1 and HSV-1.

Identification of interaction sites for dimerization and adapter recruitment in Toll/interleukin-1 receptor (TIR) domain of Toll-like receptor 4.

Toll-like receptor signaling requires interactions of the Toll/IL-1 receptor (TIR) domains of the receptor and adapter proteins. Using the mammalian protein-protein interaction trap strategy, homology modeling, and site-directed mutagenesis, we identify the interaction surfaces in the TLR4 TIR domain for the TLR4-TLR4, TLR4-MyD88 adapter-like (MAL), and TLR4-TRIF-related adapter molecule (TRAM) interaction. Two binding sites are equally important for TLR4 dimerization and adapter recruitment. In a model based on the crystal structure of the dimeric TLR10 TIR domain, the first binding site mediates TLR4-TLR4 TIR-TIR interaction. Upon dimerization, two identical second binding sites of the TLR4 TIR domain are juxtaposed and form an extended binding platform for both MAL and TRAM. In our mammalian protein-protein interaction trap assay, MAL and TRAM compete for binding to this platform. Our data suggest that adapter binding can stabilize the TLR4 TIR dimerization.

An experimentally derived confidence score for binary protein-protein interactions.

Information on protein-protein interactions is of central importance for many areas of biomedical research. At present no method exists to systematically and experimentally assess the quality of individual interactions reported in interaction mapping experiments. To provide a standardized confidence-scoring method that can be applied to tens of thousands of protein interactions, we have developed an interaction tool kit consisting of four complementary, high-throughput protein interaction assays. We benchmarked these assays against positive and random reference sets consisting of well documented pairs of interacting human proteins and randomly chosen protein pairs, respectively. A logistic regression model was trained using the data from these reference sets to combine the assay outputs and calculate the probability that any newly identified interaction pair is a true biophysical interaction once it has been tested in the tool kit. This general approach will allow a systematic and empirical assignment of confidence scores to all individual protein-protein interactions in interactome networks.

Empirically controlled mapping of the Caenorhabditis elegans protein-protein interactome network.

To provide accurate biological hypotheses and elucidate global properties of cellular networks, systematic identification of protein-protein interactions must meet high quality standards.We present an expanded C. elegans protein-protein interaction network, or 'interactome' map, derived from testing a matrix of approximately 10,000 x approximately 10,000 proteins using a highly specific, high-throughput yeast two-hybrid system. Through a new empirical quality control framework, we show that the resulting data set (Worm Interactome 2007, or WI-2007) was similar in quality to low-throughput data curated from the literature. We filtered previous interaction data sets and integrated them with WI-2007 to generate a high-confidence consolidated map (Worm Interactome version 8, or WI8). This work allowed us to estimate the size of the worm interactome at approximately 116,000 interactions. Comparison with other types of functional genomic data shows the complementarity of distinct experimental approaches in predicting different functional relationships between genes or proteins

An empirical framework for binary interactome mapping.

Several attempts have been made to systematically map protein-protein interaction, or 'interactome', networks. However, it remains difficult to assess the quality and coverage of existing data sets. Here we describe a framework that uses an empirically-based approach to rigorously dissect quality parameters of currently available human interactome maps. Our results indicate that high-throughput yeast two-hybrid (HT-Y2H) interactions for human proteins are more precise than literature-curated interactions supported by a single publication, suggesting that HT-Y2H is suitable to map a significant portion of the human interactome. We estimate that the human interactome contains approximately 130,000 binary interactions, most of which remain to be mapped. Similar to estimates of DNA sequence data quality and genome size early in the Human Genome Project, estimates of protein interaction data quality and interactome size are crucial to establish the magnitude of the task of comprehensive human interactome mapping and to elucidate a path toward this goal.

Insulin receptor substrate 4 couples the leptin receptor to multiple signaling pathways.

Leptin is an adipokine that regulates food intake and energy expenditure by activating its hypothalamic leptin receptor (LR). Members of the insulin receptor substrate (IRS) family serve as adaptor proteins in the signaling pathways of several cytokines and hormones and a role for IRS2 in central leptin physiology is well established. Using mammalian protein-protein interaction trap (MAPPIT), a cytokine receptor-based two-hybrid method, in the N38 hypothalamic cell line, we here demonstrate that also IRS4 interacts with the LR. This recruitment is leptin dependent and requires phosphorylation of the Y1077 motif of the LR. Domain mapping of IRS4 revealed the critical role of the pleckstrin homology domain for full interaction. In line with its function as an adaptor protein, IRS4 interacted with the regulatory p85 subunit of the phosphatidylinositol 3-kinase, phospholipase Cgamma, and the suppressor of cytokine signaling (SOCS) family members SOCS2, SOCS6, and SOCS7 and thus can modulate LR signaling.

Mammalian protein-protein interaction trap (MAPPIT) analysis of STAT5, CIS, and SOCS2 interactions with the growth hormone receptor.

Binding of GH to its receptor induces rapid phosphorylation of conserved tyrosine motifs that function as recruitment sites for downstream signaling molecules. Using mammalian protein-protein interaction trap (MAPPIT), a mammalian two-hybrid method, we mapped the binding sites in the GH receptor for signal transducer and activator of transcription 5 (STAT5) a and b and for the negative regulators of cytokine signaling cytokine-inducible Src-homology 2 (SH2)-containing protein (CIS) and suppressor of cytokine signaling 2 (SOCS2). Y534, Y566, and Y627 are the major recruitment sites for STAT5. A non-overlapping recruitment pattern is observed for SOCS2 and CIS with positions Y487 and Y595 as major binding sites, ruling out SOCS-mediated inhibition of STAT5 activation by competition for shared binding sites. More detailed analysis revealed that CIS binding to the Y595, but not to the Y487 motif, depends on both its SH2 domain and the C-terminal part of its SOCS box, with a critical role for the CIS Y253 residue. This functional divergence of the two CIS/SOCS2 recruitment sites is also observed upon substitution of the Y+1 residue by leucine, turning the Y487, but not the Y595 motif into a functional STAT5 recruitment site.

High-quality binary protein interaction map of the yeast interactome network.

Current yeast interactome network maps contain several hundred molecular complexes with limited and somewhat controversial representation of direct binary interactions. We carried out a comparative quality assessment of current yeast interactome data sets, demonstrating that high-throughput yeast two-hybrid (Y2H) screening provides high-quality binary interaction information. Because a large fraction of the yeast binary interactome remains to be mapped, we developed an empirically controlled mapping framework to produce a "second-generation" high-quality, high-throughput Y2H data set covering approximately 20% of all yeast binary interactions. Both Y2H and affinity purification followed by mass spectrometry (AP/MS) data are of equally high quality but of a fundamentally different and complementary nature, resulting in networks with different topological and biological properties. Compared to co-complex interactome models, this binary map is enriched for transient signaling interactions and intercomplex connections with a highly significant clustering between essential proteins. Rather than correlating with essentiality, protein connectivity correlates with genetic pleiotropy.

Mapping of binding site III in the leptin receptor and modeling of a hexameric leptin.leptin receptor complex.

The leptin.leptin receptor (LR) system shows strong similarities to the long chain cytokine interleukin-6 (IL-6) and granulocyte colony-stimulating factor (G-CSF) cytokine.cytokine receptor systems. The IL-6 family cytokines interact with their receptors through three different binding sites (I-III). We demonstrated previously that leptin has similar binding sites I-III and mapped the interactions between binding site II and cytokine receptor homology domain II (CRH2) (Peelman, F., Van Beneden, K., Zabeau, L., Iserentant, H., Ulrichts, P., Defeau, D., Verhee, A., Catteeuw, D., Elewaut, D., and Tavernier, J. (2004) J. Biol. Chem. 279, 41038-41046). In this study, we built homology models for the CRH1 and Ig-like domains of the LR. The Ig-like domain shows a large conserved surface patch in the beta-sheet formed by beta-strands 3, 6, and 7. Mutations in this patch almost completely abolished the leptin-induced STAT3-dependent reporter activity. We propose that a conserved cluster of residues Leu370, Ala407, Tyr409, His417, and His418 forms the center of binding site III of the LR. We built a hexameric leptin.LR complex model based on the hexameric IL-6 complex. In this model, a conserved hydrophobic protuberance of Val36, Thr37, Phe41, and Phe43 in the A-B loop of leptin fits perfectly in the CRH2 domain, corresponding to the IL-6 alpha-receptor, and forms the center of binding site I. The 2:4 hexameric leptin.LR complex offers a rational explanation for mutagenesis studies and residue conservation.