Array MAPPIT: high-throughput interactome analysis in mammalian cells

Crosstalk interactions between transcription factors ERRα and PPARα assist PPARα-mediated gene expression

OBJECTIVE

The peroxisome proliferator-activated receptor α (PPARα) is a transcription factor driving target genes involved in fatty acid β-oxidation. To what extent various PPARα interacting proteins may assist its function as a transcription factor is incompletely understood. An ORFeome-wide unbiased mammalian protein-protein interaction trap (MAPPIT) using PPARα as bait revealed a PPARα-ligand-dependent interaction with the orphan nuclear receptor estrogen-related receptor α (ERRα). The goal of this study was to characterize the nature of the interaction in depth and to explore whether it was of physiological relevance.

METHODS

We used orthogonal protein-protein interaction assays and pharmacological inhibitors of ERRα in various systems to confirm a functional interaction and study the impact of crosstalk mechanisms. To characterize the interaction surfaces and contact points we applied a random mutagenesis screen and structural overlays. We pinpointed the extent of reciprocal ligand effects of both nuclear receptors via coregulator peptide recruitment assays. On PPARα targets revealed from a genome-wide transcriptome analysis, we performed an ERRα chromatin immunoprecipitation analysis on both fast and fed mouse livers.

RESULTS

Random mutagenesis scanning of PPARα's ligand-binding domain and coregulator profiling experiments supported the involvement of (a) bridging coregulator(s), while recapitulation of the interaction in vitro indicated the possibility of a trimeric interaction with RXRα. The PPARα·ERRα interaction depends on 3 C-terminal residues within helix 12 of ERRα and is strengthened by both PGC1α and serum deprivation. Pharmacological inhibition of ERRα decreased the interaction of ERRα to ligand-activated PPARα and revealed a transcriptome in line with enhanced mRNA expression of prototypical PPARα target genes, suggesting a role for ERRα as a transcriptional repressor. Strikingly, on other PPARα targets, including the isolated PDK4 enhancer, ERRα behaved oppositely. Chromatin immunoprecipitation analyses demonstrate a PPARα ligand-dependent ERRα recruitment onto chromatin at PPARα-binding regions, which is lost following ERRα inhibition in fed mouse livers.

CONCLUSIONS

Our data support the coexistence of multiple layers of transcriptional crosstalk mechanisms between PPARα and ERRα, which may serve to finetune the activity of PPARα as a nutrient-sensing transcription factor.

Screening for molecular glues - Challenges and opportunities

Molecular glues are small molecules, typically smaller than PROTACs, and usually with improved physicochemical properties that aim to stabilise the interaction between two proteins. Most often this approach is used to improve or induce an interaction between the target and an E3 ligase, but other interactions which stabilise interactions to increase activity or to inhibit binding to a natural effector have also been demonstrated. This review will describe the effects of induced proximity, discuss current methods used to identify molecular glues and introduce approaches that could be adapted for molecular glue screening.

Virus-Host Protein Interaction Network of the Hepatitis E Virus ORF2-4 by Mammalian Two-Hybrid Assays

Throughout their life cycle, viruses interact with cellular host factors, thereby influencing propagation, host range, cell tropism and pathogenesis. The hepatitis E virus (HEV) is an underestimated RNA virus in which knowledge of the virus-host interaction network to date is limited. Here, two related high-throughput mammalian two-hybrid approaches (MAPPIT and KISS) were used to screen for HEV-interacting host proteins. Promising hits were examined on protein function, involved pathway(s), and their relation to other viruses. We identified 37 ORF2 hits, 187 for ORF3 and 91 for ORF4. Several hits had functions in the life cycle of distinct viruses. We focused on SHARPIN and RNF5 as candidate hits for ORF3, as they are involved in the RLR-MAVS pathway and interferon (IFN) induction during viral infections. Knocking out (KO) SHARPIN and RNF5 resulted in a different IFN response upon ORF3 transfection, compared to wild-type cells. Moreover, infection was increased in SHARPIN KO cells and decreased in RNF5 KO cells. In conclusion, MAPPIT and KISS are valuable tools to study virus-host interactions, providing insights into the poorly understood HEV life cycle. We further provide evidence for two identified hits as new host factors in the HEV life cycle.

An Unexpected Encounter: Respiratory Syncytial Virus Nonstructural Protein 1 Interacts with Mediator Subunit MED25

Innate immune responses, including the production of type I and III interferons, play a crucial role in the first line of defense against RSV infection. However, only a poor induction of type I IFNs is observed during RSV infection, suggesting that RSV has evolved mechanisms to prevent type I IFN expression by the infected host cell.

Revealing protein-protein interactions at the transcriptome scale by sequencing

We describe PROPER-seq (protein-protein interaction sequencing) to map protein-protein interactions (PPIs) en masse. PROPER-seq first converts transcriptomes of input cells into RNA-barcoded protein libraries, in which all interacting protein pairs are captured through nucleotide barcode ligation, recorded as chimeric DNA sequences, and decoded at once by sequencing and mapping. We applied PROPER-seq to human embryonic kidney cells, T lymphocytes, and endothelial cells and identified 210,518 human PPIs (collected in the PROPER v.1.0 database). Among these, 1,365 and 2,480 PPIs are supported by published co-immunoprecipitation (coIP) and affinity purification-mass spectrometry (AP-MS) data, 17,638 PPIs are predicted by the prePPI algorithm without previous experimental validation, and 100 PPIs overlap human synthetic lethal gene pairs. In addition, four previously uncharacterized interaction partners with poly(ADP-ribose) polymerase 1 (PARP1) (a critical protein in DNA repair) known as XPO1, MATR3, IPO5, and LEO1 are validated in vivo. PROPER-seq presents a time-effective technology to map PPIs at the transcriptome scale, and PROPER v.1.0 provides a rich resource for studying PPIs.

Decoding Protein-protein Interactions: An Overview

Drug discovery has focused on the paradigm "one drug, one target" for a long time. However, small molecules can act at multiple macromolecular targets, which serves as the basis for drug repurposing. In an effort to expand the target space, and given advances in X-ray crystallography, protein-protein interactions have become an emerging focus area of drug discovery enterprises. Proteins interact with other biomolecules and it is this intricate network of interactions that determines the behavior of the system and its biological processes. In this review, we briefly discuss networks in disease, followed by computational methods for protein-protein complex prediction. Computational methodologies and techniques employed towards objectives such as protein-protein docking, protein-protein interactions, and interface predictions are described extensively. Docking aims at producing a complex between proteins, while interface predictions identify a subset of residues on one protein that could interact with a partner, and protein-protein interaction sites address whether two proteins interact. In addition, approaches to predict hot spots and binding sites are presented along with a representative example of our internal project on the chemokine CXC receptor 3 B-isoform and predictive modeling with IP10 and PF4.

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.

Maximizing binary interactome mapping with a minimal number of assays

Complementary assays are required to comprehensively map complex biological entities such as genomes, proteomes and interactome networks. However, how various assays can be optimally combined to approach completeness while maintaining high precision often remains unclear. Here, we propose a framework for binary protein-protein interaction (PPI) mapping based on optimally combining assays and/or assay versions to maximize detection of true positive interactions, while avoiding detection of random protein pairs. We have engineered a novel NanoLuc two-hybrid (N2H) system that integrates 12 different versions, differing by protein expression systems and tagging configurations. The resulting union of N2H versions recovers as many PPIs as 10 distinct assays combined. Thus, to further improve PPI mapping, developing alternative versions of existing assays might be as productive as designing completely new assays. Our findings should be applicable to systematic mapping of other biological landscapes.

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.

Discovering cellular protein-protein interactions: Technological strategies and opportunities

The analysis of protein interaction networks is one of the key challenges in the study of biology. It connects genotypes to phenotypes, and disruption often leads to diseases. Hence, many technologies have been developed to study protein-protein interactions (PPIs) in a cellular context. The expansion of the PPI technology toolbox however complicates the selection of optimal approaches for diverse biological questions. This review gives an overview of the binary and co-complex technologies, with the former evaluating the interaction of two co-expressed genetically tagged proteins, and the latter only needing the expression of a single tagged protein or no tagged proteins at all. Mass spectrometry is crucial for some binary and all co-complex technologies. After the detailed description of the different technologies, the review compares their unique specifications, advantages, disadvantages, and applicability, while highlighting opportunities for further advancements.

The Prader-Willi syndrome proteins MAGEL2 and necdin regulate leptin receptor cell surface abundance through ubiquitination pathways

In Prader-Willi syndrome (PWS), obesity is caused by the disruption of appetite-controlling pathways in the brain. Two PWS candidate genes encode MAGEL2 and necdin, related melanoma antigen proteins that assemble into ubiquitination complexes. Mice lacking Magel2 are obese and lack leptin sensitivity in hypothalamic pro-opiomelanocortin neurons, suggesting dysregulation of leptin receptor (LepR) activity. Hypothalamus from Magel2-null mice had less LepR and altered levels of ubiquitin pathway proteins that regulate LepR processing (Rnf41, Usp8, and Stam1). MAGEL2 increased the cell surface abundance of LepR and decreased their degradation. LepR interacts with necdin, which interacts with MAGEL2, which complexes with RNF41 and USP8. Mutations in the MAGE homology domain of MAGEL2 suppress RNF41 stabilization and prevent the MAGEL2-mediated increase of cell surface LepR. Thus, MAGEL2 and necdin together control LepR sorting and degradation through a dynamic ubiquitin-dependent pathway. Loss of MAGEL2 and necdin may uncouple LepR from ubiquitination pathways, providing a cellular mechanism for obesity in PWS.

KISS: A Mammalian Two-Hybrid Method for In Situ Analysis of Protein-Protein Interactions

KISS (KInase Substrate Sensor) is a recently developed two-hybrid technology that allows in situ analysis of protein-protein interactions in intact mammalian cells. In this method, which is derived from MAPPIT (mammalian protein-protein interaction trap), the bait protein is coupled to the kinase domain of TYK2, while the prey protein is fused to a fragment of the gp130 cytokine receptor chain. Bait and prey interaction leads to phosphorylation of the gp130 anchor by TYK2, followed by recruitment and activation of STAT3, resulting in transcription of a STAT3-dependent reporter system. This approach enables the identification of interactions between proteins, including transmembrane and cytosolic proteins, and their modulation in response to physiological or pharmacological challenges. Here, we describe a detailed step-by-step protocol for the detection of an interaction between two proteins of interest using KISS.

Glucocorticoid Receptor-mediated transactivation is hampered by Striatin-3, a novel interaction partner of the receptor

The transcriptional activity of the glucocorticoid receptor (GR) is co-determined by its ability to recruit a vast and varying number of cofactors. We here identify Striatin-3 (STRN3) as a novel interaction partner of GR that interferes with GR’s ligand-dependent transactivation capacity. Remarkably, STRN3 selectively affects only GR-dependent transactivation and leaves GR-dependent transrepression mechanisms unhampered. We found that STRN3 down-regulates GR transactivation by an additional recruitment of the catalytic subunit of protein phosphatase 2A (PPP2CA) to GR. We hypothesize the existence of a functional trimeric complex in the nucleus, able to dephosphorylate GR at serine 211, a known marker for GR transactivation in a target gene-dependent manner. The presence of STRN3 appears an absolute prerequisite for PPP2CA to engage in a complex with GR. Herein, the C-terminal domain of GR is essential, reflecting ligand-dependency, yet other receptor parts are also needed to create additional contacts with STRN3.

Compound A influences gene regulation of the Dexamethasone-activated glucocorticoid receptor by alternative cofactor recruitment

The glucocorticoid receptor (GR) is a transcription factor of which the underlying gene regulatory mechanisms are complex and incompletely understood. The non-steroidal anti-inflammatory Compound A (CpdA), a selective GR modulating compound in various cell models, has been shown to favour GR-mediated gene repression but not GR-mediated gene activation. Shifting balances towards only a particular subset of GR gene regulatory events may be of benefit in the treatment of inflammatory diseases. We present evidence to support that the combination of CpdA with Dexamethasone (DEX), a classic steroidal GR ligand, can shape GR function towards a unique gene regulatory profile in a cell type-dependent manner. The molecular basis hereof is a changed GR phosphorylation status concomitant with a change in the GR cofactor recruitment profile. We subsequently identified and confirmed the orphan nuclear receptor SHP as a coregulator that is specifically enriched at GR when CpdA and DEX are combined. Combining CpdA with DEX not only leads to stronger suppression of pro-inflammatory gene expression, but also enhanced anti-inflammatory GR target gene expression in epithelial cells, making ligand combination strategies in future a potentially attractive alternative manner of skewing and fine-tuning GR effects towards an improved therapeutic benefit.

RNF41 interacts with the VPS52 subunit of the GARP and EARP complexes

RNF41 (Ring Finger Protein 41) is an E3 ubiquitin ligase involved in the intracellular sorting and function of a diverse set of substrates. Next to BRUCE and Parkin, RNF41 can directly ubiquitinate ErbB3, IL-3, EPO and RARα receptors or downstream signaling molecules such as Myd88, TBK1 and USP8. In this way it can regulate receptor signaling and routing. To further elucidate the molecular mechanism behind the role of RNF41 in intracellular transport we performed an Array MAPPIT (Mammalian Protein-Protein Interaction Trap) screen using an extensive set of proteins derived from the human ORFeome collection. This paper describes the identification of VPS52, a subunit of the GARP (Golgi-Associated Retrograde Protein) and the EARP (Endosome-Associated Recycling Protein) complexes, as a novel interaction partner of RNF41. Through interaction via their coiled coil domains, RNF41 ubiquitinates and relocates VPS52 away from VPS53, a common subunit of the GARP and EARP complexes, towards RNF41 bodies.

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.

Chromatin recruitment of activated AMPK drives fasting response genes co-controlled by GR and PPARα

Adaptation to fasting involves both Glucocorticoid Receptor (GRα) and Peroxisome Proliferator-Activated Receptor α (PPARα) activation. Given both receptors can physically interact we investigated the possibility of a genome-wide cross-talk between activated GR and PPARα, using ChIP- and RNA-seq in primary hepatocytes. Our data reveal extensive chromatin co-localization of both factors with cooperative induction of genes controlling lipid/glucose metabolism. Key GR/PPAR co-controlled genes switched from transcriptional antagonism to cooperativity when moving from short to prolonged hepatocyte fasting, a phenomenon coinciding with gene promoter recruitment of phosphorylated AMP-activated protein kinase (AMPK) and blocked by its pharmacological inhibition. In vitro interaction studies support trimeric complex formation between GR, PPARα and phospho-AMPK. Long-term fasting in mice showed enhanced phosphorylation of liver AMPK and GRα Ser211. Phospho-AMPK chromatin recruitment at liver target genes, observed upon prolonged fasting in mice, is dampened by refeeding. Taken together, our results identify phospho-AMPK as a molecular switch able to cooperate with nuclear receptors at the chromatin level and reveal a novel adaptation mechanism to prolonged fasting.

Trapping mammalian protein complexes in viral particles

Cell lysis is an inevitable step in classical mass spectrometry–based strategies to analyse protein complexes. Complementary lysis conditions, in situ cross-linking strategies and proximal labelling techniques are currently used to reduce lysis effects on the protein complex. We have developed Virotrap, a viral particle sorting approach that obviates the need for cell homogenization and preserves the protein complexes during purification. By fusing a bait protein to the HIV-1 GAG protein, we show that interaction partners become trapped within virus-like particles (VLPs) that bud from mammalian cells. Using an efficient VLP enrichment protocol, Virotrap allows the detection of known binary interactions and MS-based identification of novel protein partners as well. In addition, we show the identification of stimulus-dependent interactions and demonstrate trapping of protein partners for small molecules. Virotrap constitutes an elegant complementary approach to the arsenal of methods to study protein complexes.

A large portion of the proteome carries out its cellular function as part of macromolecular complexes. Here the authors describe Virotrap, a novel lysis-free approach for the isolation and identification of biologically relevant protein-protein and small molecule-protein interactions.

Ubiquitin D Regulates IRE1α/c-Jun N-terminal Kinase (JNK) Protein-dependent Apoptosis in Pancreatic Beta Cells

Pro-inflammatory cytokines contribute to pancreatic beta cell apoptosis in type 1 diabetes at least in part by inducing endoplasmic reticulum (ER) stress and the consequent unfolded protein response (UPR). It remains to be determined what causes the transition from "physiological" to "apoptotic" UPR, but accumulating evidence indicates that signaling by the ER transmembrane protein IRE1α is critical for this transition. IRE1α activation is regulated by both intra-ER and cytosolic cues. We evaluated the role for the presently discovered cytokine-induced and IRE1α-interacting protein ubiquitin D (UBD) on the regulation of IRE1α and its downstream targets. UBD was identified by use of a MAPPIT (mammalian protein-protein interaction trap)-based IRE1α interactome screen followed by comparison against functional genomic analysis of human and rodent beta cells exposed to pro-inflammatory cytokines. Knockdown of UBD in human and rodent beta cells and detailed signal transduction studies indicated that UBD modulates cytokine-induced UPR/IRE1α activation and apoptosis. UBD expression is induced by the pro-inflammatory cytokines interleukin (IL)-1β and interferon (IFN)-γ in rat and human pancreatic beta cells, and it is also up-regulated in beta cells of inflamed islets from non-obese diabetic mice. UBD interacts with IRE1α in human and rodent beta cells, modulating IRE1α-dependent activation of JNK and cytokine-induced apoptosis. Our data suggest that UBD provides a negative feedback on cytokine-induced activation of the IRE1α/JNK pro-apoptotic pathway in cytokine-exposed beta cells.

OTUB1 triggers lung cancer development by inhibiting RAS monoubiquitination

Activation of the RAS oncogenic pathway, frequently ensuing from mutations in RAS genes, is a common event in human cancer. Recent reports demonstrate that reversible ubiquitination of RAS GTPases dramatically affects their activity, suggesting that enzymes involved in regulating RAS ubiquitination may contribute to malignant transformation. Here, we identified the de-ubiquitinase OTUB1 as a negative regulator of RAS mono- and di-ubiquitination. OTUB1 inhibits RAS ubiquitination independently of its catalytic activity resulting in sequestration of RAS on the plasma membrane. OTUB1 promotes RAS activation and tumorigenesis in wild-type RAS cells. An increase of OTUB1 expression is commonly observed in non-small-cell lung carcinomas harboring wild-type KRAS and is associated with increased levels of ERK1/2 phosphorylation, high Ki67 score, and poorer patient survival. Our results strongly indicate that dysregulation of RAS ubiquitination represents an alternative mechanism of RAS activation during lung cancer development.

Fundamentals of protein interaction network mapping

Studying protein interaction networks of all proteins in an organism (“interactomes”) remains one of the major challenges in modern biomedicine. Such information is crucial to understanding cellular pathways and developing effective therapies for the treatment of human diseases. Over the past two decades, diverse biochemical, genetic, and cell biological methods have been developed to map interactomes. In this review, we highlight basic principles of interactome mapping. Specifically, we discuss the strengths and weaknesses of individual assays, how to select a method appropriate for the problem being studied, and provide general guidelines for carrying out the necessary follow‐up analyses. In addition, we discuss computational methods to predict, map, and visualize interactomes, and provide a summary of some of the most important interactome resources. We hope that this review serves as both a useful overview of the field and a guide to help more scientists actively employ these powerful approaches in their research.

A combined "omics" approach identifies N-Myc interactor as a novel cytokine-induced regulator of IRE1 protein and c-Jun N-terminal kinase in pancreatic beta cells

Type 1 diabetes is an autoimmune disease with a strong inflammatory component. The cytokines interleukin-1β and interferon-γ contribute to beta cell apoptosis in type 1 diabetes. These cytokines induce endoplasmic reticulum stress and the unfolded protein response (UPR), contributing to the loss of beta cells. IRE1α, one of the UPR mediators, triggers insulin degradation and inflammation in beta cells and is critical for the transition from "physiological" to "pathological" UPR. The mechanisms regulating inositol-requiring protein 1α (IRE1α) activation and its signaling for beta cell "adaptation," "stress response," or "apoptosis" remain to be clarified. To address these questions, we combined mammalian protein-protein interaction trap-based IRE1α interactome and functional genomic analysis of human and rodent beta cells exposed to pro-inflammatory cytokines to identify novel cytokine-induced regulators of IRE1α. Based on this approach, we identified N-Myc interactor (NMI) as an IRE1α-interacting/modulator protein in rodent and human pancreatic beta cells. An increased expression of NMI was detected in islets from nonobese diabetic mice with insulitis and in rodent or human beta cells exposed in vitro to the pro-inflammatory cytokines interleukin-1β and interferon-γ. Detailed mechanistic studies demonstrated that NMI negatively modulates IRE1α-dependent activation of JNK and apoptosis in rodent and human pancreatic beta cells. In conclusion, by using a combined omics approach, we identified NMI induction as a novel negative feedback mechanism that decreases IRE1α-dependent activation of JNK and apoptosis in cytokine-exposed beta cells

MAPPIT, a mammalian two-hybrid method for in-cell detection of protein-protein interactions

MAPPIT (MAmmalian Protein-Protein Interaction Trap) is a two-hybrid technology that facilitates the detection and analysis of interactions between proteins in living mammalian cells. The system is based on type 1 cytokine receptor signaling. The bait protein of interest is fused to a chimeric signaling-deficient cytokine receptor, the signaling competence of which is restored upon recruitment of a prey protein that is coupled to a functional cytokine receptor domain. MAPPIT exhibits an excellent signal-to-noise ratio, detects a wide variety of protein-protein interactions (PPIs) including transient and indirect interactions, and has been shown to be highly complementary to other two-hybrid methods with respect to the interactions it can detect. Variants of the method were developed to allow large-scale PPI screening, mapping of protein interaction interfaces, PPI inhibitor screening and drug profiling. This chapter describes a basic 4-day MAPPIT protocol for the analysis of interaction between two designated proteins.

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 β-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.

Using proteomics to identify the HBx interactome in hepatitis B virus: how can this inform the clinic?

Hepatitis B virus (HBV) is a small and enveloped DNA virus, of which chronic infection is the main risk factor of liver cirrhosis and hepatocellular carcinoma. Hepatitis B virus X protein (HBx) is a multifunctional protein encoded by HBV genome, which have significant effects on HBV replication and pathogenesis. Through directly interacting with cellular proteins, HBx is capable to promote HBV replication, regulate transcription of host genes, disrupt protein degradation, modulate signaling pathway, manipulate cell death and deregulate cell cycle. In this review, we briefly discuss the diversified effects of HBx-interactome and their potential clinical significances.

Exploring mitochondrial system properties of neurodegenerative diseases through interactome mapping

Mitochondria are double membraned, dynamic organelles that are required for a large number of cellular processes, and defects in their function have emerged as causative factors for a growing number of human disorders and are highly associated with cancer, metabolic, and neurodegenerative (ND) diseases. Biochemical and genetic investigations have uncovered small numbers of candidate mitochondrial proteins (MPs) involved in ND disease, but given the diversity of processes affected by MP function and the difficulty of detecting interactions involving these proteins, many more likely remain unknown. However, high-throughput proteomic and genomic approaches developed in genetically tractable model prokaryotes and lower eukaryotes have proven to be effective tools for querying the physical (protein-protein) and functional (gene-gene) relationships between diverse types of proteins, including cytosolic and membrane proteins. In this review, we highlight how experimental and computational approaches developed recently by our group and others can be effectively used towards elucidating the mitochondrial interactome in an unbiased and systematic manner to uncover network-based connections. We discuss how the knowledge from the resulting interaction networks can effectively contribute towards the identification of new mitochondrial disease gene candidates, and thus further clarify the role of mitochondrial biology and the complex etiologies of ND disease.

BIOLOGICAL SIGNIFICANCE

Biochemical and genetic investigations have uncovered small numbers of candidate mitochondrial proteins (MPs) involved in neurodegenerative (ND) diseases, but given the diversity of processes affected by MP function and the difficulty of detecting interactions involving these proteins, many more likely remain unknown. Large-scale proteomic and genomic approaches developed in model prokaryotes and lower eukaryotes have proven to be effective tools for querying the physical (protein-protein) and functional (gene-gene) relationships between diverse types of proteins. Extension of this new framework to the mitochondrial sub-system in human will likewise provide a universally informative systems-level view of the physical and functional landscape for exploring the evolutionary principles underlying mitochondrial function. In this review, we highlight how experimental and computational approaches developed recently by our group and others can be effectively used towards elucidating the mitochondrial interactome in an unbiased and systematic manner to uncover network-based connections. We anticipate that the knowledge from these resulting interaction networks can effectively contribute towards the identification of new mitochondrial disease gene candidates, and thus foster a deeper molecular understanding of mitochondrial biology as well as the etiology of mitochondrial diseases. This article is part of a Special Issue: Can Proteomics Fill the Gap Between Genomics and Phenotypes?

The deubiquitylase USP33 discriminates between RALB functions in autophagy and innate immune response

The RAS-like GTPase RALB mediates cellular responses to nutrient availability or viral infection by respectively engaging two components of the exocyst complex, EXO84 and SEC5. RALB employs SEC5 to trigger innate immunity signalling, whereas RALB-EXO84 interaction induces autophagocytosis. How this differential interaction is achieved molecularly by the RAL GTPase remains unknown. We found that whereas GTP binding turns on RALB activity, ubiquitylation of RALB at Lys 47 tunes its activity towards a particular effector. Specifically, ubiquitylation at Lys 47 sterically inhibits RALB binding to EXO84, while facilitating its interaction with SEC5. Double-stranded RNA promotes RALB ubiquitylation and SEC5-TBK1 complex formation. In contrast, nutrient starvation induces RALB deubiquitylation by accumulation and relocalization of the deubiquitylase USP33 to RALB-positive vesicles. Deubiquitylated RALB promotes the assembly of the RALB-EXO84-beclin-1 complexes driving autophagosome formation. Thus, ubiquitylation within the effector-binding domain provides the switch for the dual functions of RALB in autophagy and innate immune responses.

Tracking context-specific transcription factors regulating hox activity

BACKGROUND

Hox proteins are key developmental regulators involved in almost every embryonic tissue for specifying cell fates along longitudinal axes or during organ formation. It is thought that the panoply of Hox activities relies on interactions with tissue-, stage-, and/or cell-specific transcription factors. High-throughput approaches in yeast or cell culture systems have shown that Hox proteins bind to various types of nuclear and cytoplasmic components, illustrating their remarkable potential to influence many different cell regulatory processes. However, these approaches failed to identify a relevant number of context-specific transcriptional partners, suggesting that these interactions are hard to uncover in non-physiological conditions. Here we discuss this problematic.

RESULTS

In this review, we present intrinsic Hox molecular signatures that are probably involved in multiple (yet specific) interactions with transcriptional partners. We also recapitulate the current knowledge on Hox cofactors, highlighting the difficulty to tracking context-specific cofactors through traditional large-scale approaches.

CONCLUSION

We propose experimental approaches that will allow a better characterisation of interaction networks underlying Hox contextual activities in the next future.

A "clickable" MTX reagent as a practical tool for profiling small-molecule-intracellular target interactions via MASPIT

We present a scalable synthesis of a versatile MTX reagent with an azide ligation handle that allows rapid γ-selective conjugation to yield MTX fusion compounds (MFCs) appropriate for MASPIT, a three-hybrid system that enables the identification of mammalian cytosolic proteins that interact with a small molecule of interest. We selected three structurally diverse pharmacologically active compounds (tamoxifen, reversine, and FK506) as model baits. After acetylene functionalization of these baits, MFCs were synthesized via a CuAAC reaction, demonstrating the general applicability of the MTX reagent. In analytical mode, MASPIT was able to give concentration-dependent reporter signals for the established target proteins. Furthermore, we demonstrate that the sensitivity obtained with the new MTX reagent was significantly stronger than that of a previously used non-regiomeric conjugate mixture. Finally, the FK506 MFC was explored in a cellular array screen for targets of FK506. Out of a pilot collection of nearly 2000 full-length human ORF preys, FKBP12, the established target of FK506, emerged as the prey protein that gave the highest increase in luciferase activity. This indicates that our newly developed synthetic strategy for the straightforward generation of MFCs is a promising asset to uncover new intracellular targets using MASPIT cellular array screening.

Reciprocal cross-regulation between RNF41 and USP8 controls cytokine receptor sorting and processing

The mechanisms controlling the steady-state cytokine receptor cell surface levels, and consequently the cellular response to cytokines, remain poorly understood. The number of surface-exposed receptors is a dynamic balance of de novo synthesis, transport to the plasma membrane, internalization, recycling, degradation and ectodomain shedding. We previously reported that the E3 ubiquitin ligase Ring Finger Protein 41 (RNF41) inhibits basal lysosomal degradation and enhance ectodomain shedding of JAK2-associated cytokine receptors. Ubiquitin-specific protease 8 (USP8), an RNF41 interacting deubiquitinating enzyme (DUB) stabilizes RNF41 and is involved in trafficking of various transmembrane proteins. The present study identifies USP8 as a substrate of RNF41 and reveals that loss of USP8 explains the aforementioned RNF41 effects. RNF41 redistributes and ubiquitinates USP8, and reduces USP8 levels. In addition, USP8 knockdown functionally matches the effects of RNF41 ectopic expression on the model leptin and leukemia inhibitory factor (LIF) receptors. Moreover, RNF41 indirectly destabilizes the ESCRT-0 complex via USP8 suppression. Collectively, our findings demonstrate that RNF41 controls JAK2-associated cytokine receptor trafficking by acting as a key regulator of USP8 and ESCRT-0 stability. Balanced reciprocal cross-regulation between RNF41 and USP8 thus decides if receptors are sorted for lysosomal degradation or recycling, this way regulating basal cytokine receptor levels.

High-throughput analysis of peptide-binding modules

Modular protein interaction domains (PIDs) that recognize linear peptide motifs are found in hundreds of proteins within the human genome. Some PIDs such as SH2, 14-3-3, Chromo, and Bromo domains serve to recognize posttranslational modification (PTM) of amino acids (such as phosphorylation, acetylation, methylation, etc.) and translate these into discrete cellular responses. Other modules such as SH3 and PSD-95/Discs-large/ZO-1 (PDZ) domains recognize linear peptide epitopes and serve to organize protein complexes based on localization and regions of elevated concentration. In both cases, the ability to nucleate-specific signaling complexes is in large part dependent on the selectivity of a given protein module for its cognate peptide ligand. High-throughput (HTP) analysis of peptide-binding domains by peptide or protein arrays, phage display, mass spectrometry, or other HTP techniques provides new insight into the potential protein-protein interactions prescribed by individual or even whole families of modules. Systems level analyses have also promoted a deeper understanding of the underlying principles that govern selective protein-protein interactions and how selectivity evolves. Lastly, there is a growing appreciation for the limitations and potential pitfalls associated with HTP analysis of protein-peptide interactomes. This review will examine some of the common approaches utilized for large-scale studies of PIDs and suggest a set of standards for the analysis and validation of datasets from large-scale studies of peptide-binding modules. We will also highlight how data from large-scale studies of modular interaction domain families can provide insight into systems level properties such as the linguistics of selective interactions.

Interactome mapping for analysis of complex phenotypes: insights from benchmarking binary interaction assays

Protein interactions mediate essentially all biological processes and analysis of protein-protein interactions using both large-scale and small-scale approaches has contributed fundamental insights to the understanding of biological systems. In recent years, interactome network maps have emerged as an important tool for analyzing and interpreting genetic data of complex phenotypes. Complementary experimental approaches to test for binary, direct interactions, and for membership in protein complexes are used to explore the interactome. The two approaches are not redundant but yield orthogonal perspectives onto the complex network of physical interactions by which proteins mediate biological processes. In recent years, several publications have demonstrated that interactions from high-throughput experiments can be equally reliable as the high quality subset of interactions identified in small-scale studies. Critical for this insight was the introduction of standardized experimental benchmarking of interaction and validation assays using reference sets. The data obtained in these benchmarking experiments have resulted in greater appreciation of the limitations and the complementary strengths of different assays. Moreover, benchmarking is a central element of a conceptual framework to estimate interactome sizes and thereby measure progress toward near complete network maps. These estimates have revealed that current large-scale data sets, although often of high quality, cover only a small fraction of a given interactome. Here, I review the findings of assay benchmarking and discuss implications for quality control, and for strategies toward obtaining a near-complete map of the interactome of an organism.

Diversity in genetic in vivo methods for protein-protein interaction studies: from the yeast two-hybrid system to the mammalian split-luciferase system

The yeast two-hybrid system pioneered the field of in vivo protein-protein interaction methods and undisputedly gave rise to a palette of ingenious techniques that are constantly pushing further the limits of the original method. Sensitivity and selectivity have improved because of various technical tricks and experimental designs. Here we present an exhaustive overview of the genetic approaches available to study in vivo binary protein interactions, based on two-hybrid and protein fragment complementation assays. These methods have been engineered and employed successfully in microorganisms such as Saccharomyces cerevisiae and Escherichia coli, but also in higher eukaryotes. From single binary pairwise interactions to whole-genome interactome mapping, the self-reassembly concept has been employed widely. Innovative studies report the use of proteins such as ubiquitin, dihydrofolate reductase, and adenylate cyclase as reconstituted reporters. Protein fragment complementation assays have extended the possibilities in protein-protein interaction studies, with technologies that enable spatial and temporal analyses of protein complexes. In addition, one-hybrid and three-hybrid systems have broadened the types of interactions that can be studied and the findings that can be obtained. Applications of these technologies are discussed, together with the advantages and limitations of the available assays.

Random mutagenesis MAPPIT analysis identifies binding sites for Vif and Gag in both cytidine deaminase domains of Apobec3G

The mammalian two-hybrid system MAPPIT allows the detection of protein-protein interactions in intact human cells. We developed a random mutagenesis screening strategy based on MAPPIT to detect mutations that disrupt the interaction of one protein with multiple protein interactors simultaneously. The strategy was used to detect residues of the human cytidine deaminase Apobec3G that are important for its homodimerization and its interaction with the HIV-1 Gag and Vif proteins. The strategy is able to identify the previously described head-to-head homodimerization interface in the N-terminal domain of Apobec3G. Our analysis further detects two new potential interaction surfaces in the N-and C-terminal domain of Apobec3G for interaction with Vif and Gag or for Apobec3G dimerization.

The use of mammalian two-hybrid technologies for high-throughput drug screening

Developing agents that target protein-protein interactions (PPIs) is an emerging field in drug discovery. Although this target class has hitherto remained underexplored, it holds exceptional promise related to the large amount of potential PPI targets compared to single protein targets and it offers important opportunities to increase the specificity of therapeutic molecules. While several PPI modulating therapeutics have recently been reported and a number of these are in clinical trial, progress in the field has been hampered by the lack of efficient screening systems. Recently, a number of cellular approaches have been developed that complement classical in vitro screening methods and which exhibit a number of important assets related to the physiological context they provide. Here we discuss the utility of two-hybrid technologies towards high-throughput screening for PPI inhibitors, in particular those that operate in a mammalian cellular background. We review a number of cases where mammalian two-hybrids have been successfully applied to identify small molecule disruptors of PPIs and zoom in further on the MAPPIT (Mammalian Protein-Protein Interaction Trap) technology platform. The value of this approach for drug discovery is illustrated by recent data from MAPPIT-based screening projects.

Network approaches to the functional analysis of microbial proteins

Large amounts of detailed biological data have been generated over the past few decades. Much of these data is freely available in over 1000 online databases; an enticing, but frustrating resource for microbiologists interested in a systems-level view of the structure and function of microbial cells. The frustration engendered by the need to trawl manually through hundreds of databases in order to accumulate information about a gene, protein, pathway, or organism of interest can be alleviated by the use of computational data integration to generated network views of the system of interest. Biological networks can be constructed from a single type of data, such as protein-protein binding information, or from data generated by multiple experimental approaches. In an integrated network, nodes usually represent genes or gene products, while edges represent some form of interaction between the nodes. Edges between nodes may be weighted to represent the probability that the edge exists in vivo. Networks may also be enriched with ontological annotations, facilitating both visual browsing and computational analysis via web service interfaces. In this review, we describe the construction, analysis of both single-data source and integrated networks, and their application to the inference of protein function in microbes.

MAPPIT: a protein interaction toolbox built on insights in cytokine receptor signaling

MAPPIT (mammalian protein-protein interaction trap) is a two-hybrid interaction mapping technique based on functional complementation of a type I cytokine receptor signaling pathway. Over the last decade, the technology has been extended into a platform of complementary assays for the detection of interactions among proteins and between chemical compounds and proteins, and for the identification of small molecules that interfere with protein-protein interactions. Additionally, several screening approaches have been developed to broaden the utility of the platform. In this review we provide an overview of the different components of the MAPPIT toolbox and highlight a number of applications in interactomics, drug screening and compound target profiling.

Large-scale protein interactome mapping: strategies and opportunities

Interactions between proteins are central to any cellular process, and mapping these into a protein network is informative both for the function of individual proteins and the functional organization of the cell as a whole. Many strategies have been developed that are up to this task, and the last 10 years have seen the high-throughput application of a number of those in large-scale, sometimes proteome-wide, interactome mapping efforts. Although initially the quality of the data produced in these screening campaigns has been questioned, quality standards and empirical validation schemes are now in place to ensure high-quality data generation. Through their integration with other 'omics' data, interactomics datasets have proven highly valuable towards applications in different areas of clinical importance.

Literature curation of protein interactions: measuring agreement across major public databases

Literature curation of protein interaction data faces a number of challenges. Although curators increasingly adhere to standard data representations, the data that various databases actually record from the same published information may differ significantly. Some of the reasons underlying these differences are well known, but their global impact on the interactions collectively curated by major public databases has not been evaluated. Here we quantify the agreement between curated interactions from 15 471 publications shared across nine major public databases. Results show that on average, two databases fully agree on 42% of the interactions and 62% of the proteins curated from the same publication. Furthermore, a sizable fraction of the measured differences can be attributed to divergent assignments of organism or splice isoforms, different organism focus and alternative representations of multi-protein complexes. Our findings highlight the impact of divergent curation policies across databases, and should be relevant to both curators and data consumers interested in analyzing protein-interaction data generated by the scientific community.

Database URL:http://wodaklab.org/iRefWeb

Mammalian two-hybrids come of age

A diverse series of mammalian two-hybrid technologies for the detection of protein-protein interactions have emerged in the past few years, complementing the established yeast two-hybrid approach. Given the mammalian background in which they operate, these assays open new avenues to study the dynamics of mammalian protein interaction networks, i.e. the temporal, spatial and functional modulation of protein-protein associations. In addition, novel assay formats are available that enable high-throughput mammalian two-hybrid applications, facilitating their use in large-scale interactome mapping projects. Finally, as they can be applied in drug discovery and development programs, these techniques also offer exciting new opportunities for biomedical research.