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.

The phosphatidylserine receptor TIM1 promotes infection of enveloped hepatitis E virus

The hepatitis E virus (HEV) is an underestimated RNA virus of which the viral life cycle and pathogenicity remain partially understood and for which specific antivirals are lacking. The virus exists in two forms: nonenveloped HEV that is shed in feces and transmits between hosts; and membrane-associated, quasi-enveloped HEV that circulates in the blood. It is suggested that both forms employ different mechanisms for cellular entry and internalization but little is known about the exact mechanisms. Interestingly, the membrane of enveloped HEV is enriched with phosphatidylserine, a natural ligand for the T-cell immunoglobulin and mucin domain-containing protein 1 (TIM1) during apoptosis and involved in 'apoptotic mimicry', a process by which viruses hijack the apoptosis pathway to promote infection. We here investigated the role of TIM1 in the entry process of HEV. We determined that HEV infection with particles derived from culture supernatant, which are cloaked by host-derived membranes (eHEV), was significantly impaired after knockout of TIM1, whereas infection with intracellular HEV particles (iHEV) was unaffected. eHEV infection was restored upon TIM1 expression; and enhanced after ectopic TIM1 expression. The significance of TIM1 during entry was further confirmed by viral binding assay, and point mutations of the PS-binding pocket diminished eHEV infection. In addition, Annexin V, a PS-binding molecule also significantly reduced infection. Taken together, our findings support a role for TIM1 in eHEV-mediated cell entry, facilitated by the PS present on the viral membrane, a strategy HEV may use to promote viral spread throughout the infected body.

Next-generation large-scale binary protein interaction network for Drosophila melanogaster

Generating reference maps of interactome networks illuminates genetic studies by providing a protein-centric approach to finding new components of existing pathways, complexes, and processes. We apply state-of-the-art methods to identify binary protein-protein interactions (PPIs) for Drosophila melanogaster. Four all-by-all yeast two-hybrid (Y2H) screens of > 10,000 Drosophila proteins result in the 'FlyBi' dataset of 8723 PPIs among 2939 proteins. Testing subsets of data from FlyBi and previous PPI studies using an orthogonal assay allows for normalization of data quality; subsequent integration of FlyBi and previous data results in an expanded binary Drosophila reference interaction network, DroRI, comprising 17,232 interactions among 6511 proteins. We use FlyBi data to generate an autophagy network, then validate in vivo using autophagy-related assays. The deformed wings (dwg) gene encodes a protein that is both a regulator and a target of autophagy. Altogether, these resources provide a foundation for building new hypotheses regarding protein networks and function.

Prolyl endopeptidase-like is a (thio)esterase involved in mitochondrial respiratory chain function

Deficiency of the serine hydrolase prolyl endopeptidase-like (PREPL) causes a recessive metabolic disorder characterized by neonatal hypotonia, feeding difficulties, and growth hormone deficiency. The pathophysiology of PREPL deficiency and the physiological substrates of PREPL remain largely unknown. In this study, we connect PREPL with mitochondrial gene expression and oxidative phosphorylation by analyzing its protein interactors. We demonstrate that the long PREPLL isoform localizes to mitochondria, whereas PREPLS remains cytosolic. Prepl KO mice showed reduced mitochondrial complex activities and disrupted mitochondrial gene expression. Furthermore, mitochondrial ultrastructure was abnormal in a PREPL-deficient patient and Prepl KO mice. In addition, we reveal that PREPL has (thio)esterase activity and inhibition of PREPL by Palmostatin M suggests a depalmitoylating function. We subsequently determined the crystal structure of PREPL, thereby providing insight into the mechanism of action. Taken together, PREPL is a (thio)esterase rather than a peptidase and PREPLL is involved in mitochondrial homeostasis.

Bcl-xL acts as an inhibitor of IP3R channels, thereby antagonizing Ca2+-driven apoptosis

Anti-apoptotic Bcl-2-family members not only act at mitochondria but also at the endoplasmic reticulum, where they impact Ca²⁺ dynamics by controlling IP₃ receptor (IP₃R) function. Current models propose distinct roles for Bcl-2 vs. Bcl-xL, with Bcl-2 inhibiting IP₃Rs and preventing pro-apoptotic Ca²⁺ release and Bcl-xL sensitizing IP₃Rs to low [IP₃] and promoting pro-survival Ca²⁺ oscillations. We here demonstrate that Bcl-xL too inhibits IP₃R-mediated Ca²⁺ release by interacting with the same IP₃R regions as Bcl-2. Via in silico superposition, we previously found that the residue K87 of Bcl-xL spatially resembled K17 of Bcl-2, a residue critical for Bcl-2's IP₃R-inhibitory properties. Mutagenesis of K87 in Bcl-xL impaired its binding to IP₃R and abrogated Bcl-xL's inhibitory effect on IP₃Rs. Single-channel recordings demonstrate that purified Bcl-xL, but not Bcl-xL^K87D, suppressed IP₃R single-channel openings stimulated by sub-maximal and threshold [IP₃]. Moreover, we demonstrate that Bcl-xL-mediated inhibition of IP₃Rs contributes to its anti-apoptotic properties against Ca²⁺-driven apoptosis. Staurosporine (STS) elicits long-lasting Ca²⁺ elevations in wild-type but not in IP₃R-knockout HeLa cells, sensitizing the former to STS treatment. Overexpression of Bcl-xL in wild-type HeLa cells suppressed STS-induced Ca²⁺ signals and cell death, while Bcl-xL^K87D was much less effective in doing so. In the absence of IP₃Rs, Bcl-xL and Bcl-xL^K87D were equally effective in suppressing STS-induced cell death. Finally, we demonstrate that endogenous Bcl-xL also suppress IP₃R activity in MDA-MB-231 breast cancer cells, whereby Bcl-xL knockdown augmented IP₃R-mediated Ca²⁺ release and increased the sensitivity towards STS, without altering the ER Ca²⁺ content. Hence, this study challenges the current paradigm of divergent functions for Bcl-2 and Bcl-xL in Ca²⁺-signaling modulation and reveals that, similarly to Bcl-2, Bcl-xL inhibits IP₃R-mediated Ca²⁺ release and IP₃R-driven cell death. Our work further underpins that IP₃R inhibition is an integral part of Bcl-xL's anti-apoptotic function.

A reference map of the human binary protein interactome

Global insights into cellular organization and genome function require comprehensive understanding of the interactome networks that mediate genotype-phenotype relationships^1,2. Here, we present a human “all-by-all” reference interactome map of human binary protein interactions, or “HuRI”. With ~53,000 high-quality protein-protein interactions (PPIs), HuRI has approximately four times more such interactions than high-quality curated interactions from small-scale studies. Integrating HuRI with genome³, transcriptome⁴, and proteome⁵ data enables the study of cellular function within most physiological or pathological cellular contexts. We demonstrate the utility of HuRI in identifying specific subcellular roles of PPIs. Inferred tissue-specific networks reveal general principles for the formation of cellular context-specific functions and elucidate potential molecular mechanisms underlying tissue-specific phenotypes of Mendelian diseases. HuRI represents a systematic proteome-wide reference linking genomic variation to phenotypic outcomes.

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.

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.

MAPPI-DAT: data management and analysis for protein-protein interaction data from the high-throughput MAPPIT cell microarray platform

Summary

Protein-protein interaction (PPI) studies have dramatically expanded our knowledge about cellular behaviour and development in different conditions. A multitude of high-throughput PPI techniques have been developed to achieve proteome-scale coverage for PPI studies, including the microarray based Mammalian Protein-Protein Interaction Trap (MAPPIT) system. Because such high-throughput techniques typically report thousands of interactions, managing and analysing the large amounts of acquired data is a challenge. We have therefore built the MAPPIT cell microArray Protein Protein Interaction-Data management & Analysis Tool (MAPPI-DAT) as an automated data management and analysis tool for MAPPIT cell microarray experiments. MAPPI-DAT stores the experimental data and metadata in a systematic and structured way, automates data analysis and interpretation, and enables the meta-analysis of MAPPIT cell microarray data across all stored experiments.

Availability and Implementation

MAPPI-DAT is developed in Python, using R for data analysis and MySQL as data management system. MAPPI-DAT is cross-platform and can be ran on Microsoft Windows, Linux and OS X/macOS. The source code and a Microsoft Windows executable are freely available under the permissive Apache2 open source license at https://github.com/compomics/MAPPI-DAT.

Supplementary information

Supplementary data are available at Bioinformatics online.

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.

Abstract 3850: First-in-class cell-penetrating proteins targeting Mcl-1 induce tumor cell apoptosis and inhibition of tumor growth in vivo

We have developed Cell Penetrating Alphabodies (CPABs), a novel and unique therapeutic class of proteins engineered to efficiently enter cells. In vitro, uptake in a range of tumor and non-tumor cell types occurs rapidly with cytosol levels of up to 1 μM concentration after 2 hours of CPAB exposure. Early forms of these CPABs suffered from rapid serum clearance, thereby limiting their efficacy in vivo and amenability to drug development. The incorporation of an albumin binding region in the body of the protein has allowed extension of serum half-life in mice from a few minutes to more than one hour. These CPABs have been shown to be efficiently delivered to xenograft tumors in mice after IV bolus injection by tissue ELISA and immunohistochemistry. CPABs can be used to target and interfere with intracellular protein-protein interactions involved in tumor survival in a highly specific way.

The anti-apoptotic protein Myeloid Cell Leukaemia-1 (Mcl-1) promotes through its interaction with Bak, the survival of a range of different tumor types including myeloid leukemia, breast cancer and non-small cell lung cancer. Moreover, Mcl-1 overexpression is often associated with chemotherapeutic resistance and disease relapse. Mcl-1, however, has proven difficult to target using the conventional small molecule approach.

Alphabodies which bind to Mcl-1 were engineered by a combination of rational design and phage display library screening. The affinities for Mcl-1 ranged between 18 pM and 750 pM with binding to the closely related proteins Bcl-2 and Bcl-XL being below the limit of detection for the assay. In a Mammalian Two Hybrid assay, these Alphabodies inhibited Bak-Mcl-1 but not Bak-Bcl-XL interactions. Anti-Mcl-1 CPABs were shown to efficiently kill the Mcl-1 dependent multiple myeloma cell line NCI-H929 with IC50s ranging from 0.5 μM to 2 μM as monitored in cell viability assays. The dose responsive cell killing correlated with caspase-3/7 activation in NCI-H929 cells. Other Mcl-1 dependent tumor cell types including non-small cell lung cancer (NCI-H23) and Burkitt's lymphoma (Raji) or tumor cell types with high Mcl-1 expression such as ovarian cancer (A2780) and colorectal adenocarcinoma (COLO-320DM) were also killed efficiently using anti-Mcl-1 CPABs. Despite its short half-life, daily intraperitoneal administration of a prototype Mcl-1 targeting CPAB (without half-life extension) at 30 mg/kg for 14 days resulted in tumor inhibition of 33% as compared to vehicle control. Experiments are underway in mouse models using the more optimal CPABs with extended serum half-life and tumor exposure.

CPABs represent the best-in-class cell penetrating protein therapeutics both in terms of efficiency of uptake and amenability to conversion to viable drugs opening unprecedented opportunities to tackle intracellular protein-protein interactions critical to diseases with unmet medical need.

Citation Format: Sabrina Deroo, Sophie Thiolloy, Johan Desmet, Franky Baatz, Stefan Loverix, Karen Vandenbroucke, Eric Lorent, Paula Henderikx, Irma Lemmens, Philippe Alard, Ignace Lasters, Yvonne McGrath. First-in-class cell-penetrating proteins targeting Mcl-1 induce tumor cell apoptosis and inhibition of tumor growth in vivo. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3850.

A combined binary interaction and phenotypic map of C. elegans cell polarity proteins

The establishment of cell polarity is an essential process for the development of multicellular organisms and the functioning of cells and tissues. Here, we combine large-scale protein interaction mapping with systematic phenotypic profiling to study the network of physical interactions that underlies polarity establishment and maintenance in the nematode Caenorhabditis elegans. Using a fragment-based yeast two-hybrid strategy, we identified 439 interactions between 296 proteins, as well as the protein regions that mediate these interactions. Phenotypic profiling of the network resulted in the identification of 100 physically interacting protein pairs for which RNAi-mediated depletion caused a defect in the same polarity-related process. We demonstrate the predictive capabilities of the network by showing that the physical interaction between the RhoGAP PAC-1 and PAR-6 is required for radial polarization of the C. elegans embryo. Our network represents a valuable resource of candidate interactions that can be used to further our insight into cell polarization.

Ryanodine receptors are targeted by anti-apoptotic Bcl-XL involving its BH4 domain and Lys87 from its BH3 domain

Anti-apoptotic B-cell lymphoma 2 (Bcl-2) family members target several intracellular Ca(2+)-transport systems. Bcl-2, via its N-terminal Bcl-2 homology (BH) 4 domain, inhibits both inositol 1,4,5-trisphosphate receptors (IP3Rs) and ryanodine receptors (RyRs), while Bcl-XL, likely independently of its BH4 domain, sensitizes IP3Rs. It remains elusive whether Bcl-XL can also target and modulate RyRs. Here, Bcl-XL co-immunoprecipitated with RyR3 expressed in HEK293 cells. Mammalian protein-protein interaction trap (MAPPIT) and surface plasmon resonance (SPR) showed that Bcl-XL bound to the central domain of RyR3 via its BH4 domain, although to a lesser extent compared to the BH4 domain of Bcl-2. Consistent with the ability of the BH4 domain of Bcl-XL to bind to RyRs, loading the BH4-Bcl-XL peptide into RyR3-overexpressing HEK293 cells or in rat hippocampal neurons suppressed RyR-mediated Ca(2+) release. In silico superposition of the 3D-structures of Bcl-2 and Bcl-XL indicated that Lys87 of the BH3 domain of Bcl-XL could be important for interacting with RyRs. In contrast to Bcl-XL, the Bcl-XL(K87D) mutant displayed lower binding affinity for RyR3 and a reduced inhibition of RyR-mediated Ca(2+) release. These data suggest that Bcl-XL binds to RyR channels via its BH4 domain, but also its BH3 domain, more specific Lys87, contributes to the interaction.

Spatiotemporal 16p11.2 protein network implicates cortical late mid-fetal brain development and KCTD13-Cul3-RhoA pathway in psychiatric diseases

The psychiatric disorders autism and schizophrenia have a strong genetic component, and copy number variants (CNVs) are firmly implicated. Recurrent deletions and duplications of chromosome 16p11.2 confer a high risk for both diseases, but the pathways disrupted by this CNV are poorly defined. Here we investigate the dynamics of the 16p11.2 network by integrating physical interactions of 16p11.2 proteins with spatiotemporal gene expression from the developing human brain. We observe profound changes in protein interaction networks throughout different stages of brain development and/or in different brain regions. We identify the late mid-fetal period of cortical development as most critical for establishing the connectivity of 16p11.2 proteins with their co-expressed partners. Furthermore, our results suggest that the regulation of the KCTD13-Cul3-RhoA pathway in layer 4 of the inner cortical plate is crucial for controlling brain size and connectivity and that its dysregulation by de novo mutations may be a potential determinant of 16p11.2 CNV deletion and duplication phenotypes.

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.

A proteome-scale map of the human interactome network

Just as reference genome sequences revolutionized human genetics, reference maps of interactome networks will be critical to fully understand genotype-phenotype relationships. Here, we describe a systematic map of ?14,000 high-quality human binary protein-protein interactions. At equal quality, this map is ?30% larger than what is available from small-scale studies published in the literature in the last few decades. While currently available information is highly biased and only covers a relatively small portion of the proteome, our systematic map appears strikingly more homogeneous, revealing a "broader" human interactome network than currently appreciated. The map also uncovers significant interconnectivity between known and candidate cancer gene products, providing unbiased evidence for an expanded functional cancer landscape, while demonstrating how high-quality interactome models will help "connect the dots" of the genomic revolution.

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.

Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism

Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases.

Host-pathogen interactome mapping for HTLV-1 and -2 retroviruses

BACKGROUND

Human T-cell leukemia virus type 1 (HTLV-1) and type 2 both target T lymphocytes, yet induce radically different phenotypic outcomes. HTLV-1 is a causative agent of Adult T-cell leukemia (ATL), whereas HTLV-2, highly similar to HTLV-1, causes no known overt disease. HTLV gene products are engaged in a dynamic struggle of activating and antagonistic interactions with host cells. Investigations focused on one or a few genes have identified several human factors interacting with HTLV viral proteins. Most of the available interaction data concern the highly investigated HTLV-1 Tax protein. Identifying shared and distinct host-pathogen protein interaction profiles for these two viruses would enlighten how they exploit distinctive or common strategies to subvert cellular pathways toward disease progression.

RESULTS

We employ a scalable methodology for the systematic mapping and comparison of pathogen-host protein interactions that includes stringent yeast two-hybrid screening and systematic retest, as well as two independent validations through an additional protein interaction detection method and a functional transactivation assay. The final data set contained 166 interactions between 10 viral proteins and 122 human proteins. Among the 166 interactions identified, 87 and 79 involved HTLV-1 and HTLV-2 -encoded proteins, respectively. Targets for HTLV-1 and HTLV-2 proteins implicate a diverse set of cellular processes including the ubiquitin-proteasome system, the apoptosis, different cancer pathways and the Notch signaling pathway.

CONCLUSIONS

This study constitutes a first pass, with homogeneous data, at comparative analysis of host targets for HTLV-1 and -2 retroviruses, complements currently existing data for formulation of systems biology models of retroviral induced diseases and presents new insights on biological pathways involved in retroviral infection.

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.

Strategies towards high-quality binary protein interactome maps

Many processes in a cell depend on protein-protein interactions (PPIs) and perturbations of these interactions can lead to diseases. Comprehensive knowledge of PPI networks will not only give us information on how the cell is organized, but will also provide new drug targets. Current binary PPI networks are mainly generated by high-throughput yeast two-hybrid. Due to the small overlap of these maps, it has long been assumed that these maps are of low quality containing many false positives. However, by using an orthogonal two-hybrid method, MAPPIT (mammalian protein-protein interaction trap), these maps were shown to be of high quality suggesting that the limited overlap is likely due to low sensitivity and not to low specificity.

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.

MAPPIT (mammalian protein-protein interaction trap) analysis of early steps in toll-like receptor signalling

The mammalian protein-protein interaction trap (MAPPIT) is a two-hybrid technique founded on type I cytokine signal transduction. Thereby, bait and prey proteins are linked to signalling deficient cytokine receptor chimeras. Interaction of bait and prey and ligand stimulation restores functional JAK (Janus kinase)-STAT (signal transducers and activators of transcription) signalling, which ultimately leads to the transcription of a reporter or marker gene under the control of the STAT3-responsive rPAP1 promoter. In the subsequent protocol, we describe the use of MAPPIT to study early events in Toll-like receptor (TLR) signalling. We here demonstrate a "signalling interaction cascade" from TLR4 to IRAK-1.

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.

An empirical framework for binary interactome mapping

Several attempts have been made at systematically mapping protein-protein interaction, or “interactome” networks. However, it remains difficult to assess the quality and coverage of existing datasets. 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 are superior in precision to literature-curated interactions supported by only 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 ~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 critical to establish the magnitude of the task of comprehensive human interactome mapping and to illuminate a path towards this goal.

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.

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.

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.

Reverse MAPPIT detects disruptors of protein-protein interactions in human cells

Reverse mammalian protein-protein interaction trap (MAPPIT) is a mammalian reverse two-hybrid technology. The method is adapted from the forward MAPPIT technique, a two-hybrid complementation system in which the interaction between a bait-fusion protein and a prey-fusion protein restores ligand-dependent cytokine receptor signaling. In the reverse mode described in detail here, a positive readout is generated on disruption of the designated protein-protein interactions. Reverse MAPPIT functions in intact human cells, facilitating simultaneous analysis of disruption, toxicity and permeability of the tested compounds, making it particularly suitable for screening for molecules that target therapeutically interesting protein-protein interactions or for mapping the interaction interface between proteins. The total handling time of a typical reverse MAPPIT experiment is approximately 9 h and is spread over 4-5 d.

Analysis of leptin signalling in hematopoietic cells using an adapted MAPPIT strategy

The adipocyte-secreted hormone leptin participates in the regulation of hematopoiesis and enhances proliferation of hematopoietic cells. We used an adaptation of the MAPPIT mammalian two-hybrid method to study leptin signalling in a hematopoietic setting. We confirmed the known interactions of suppressor of cytokine signalling 3 (SOCS3) and STAT5 with the Y985 and Y1077 motifs of the leptin receptor, respectively. We also provide evidence for novel interactions at the Y1077 motif, including phospholipase C gamma and several members of the SOCS protein family, further underscoring the important role of the Y1077 motif in leptin signalling.

Two-hybrid and its recent adaptations

Interactions between proteins play a pivotal role in virtually all cellular processes, and many of these interactions represent interesting targets for drug development. Among the wide array of interactor-hunting technologies that has emerged, genetic two-hybrid methods account for a large amount of the currently available interaction data and is being successfully applied in interactome-scale mapping projects. Reverse two-hybrid approaches have been developed that allow selected interactions to be assayed for disrupting compounds.:

A systematic scan of interactions with tyrosine motifs in the erythropoietin receptor using a mammalian 2-hybrid approach

Signaling via the erythropoietin receptor (EpoR) depends on the interaction of several proteins with phosphorylated tyrosine-containing motifs in its cytosolic domain. Detailed mapping of these interactions is required for an accurate insight into Epo signaling. We recently developed a mammalian protein-protein interaction trap (MAPPIT), a cytokine receptor-based 2-hybrid method that operates in intact Hek293-T mammalian cells. As baits, we used intracellular segments of the EpoR containing 1 or 2 tyrosines. Several known signaling molecules, including cytokine-inducible SH2-containing protein (CIS), suppressor of cytokine signaling-2 (SOCS2), phosphatidylinositol 3′-kinase (PI3-K), phospholipase C-γ (PLC-γ), and signal transducer and activator of transcription 5 (STAT5) were used as prey. We also extended the MAPPIT method to enable interaction analysis with wild-type EpoR. In this relay MAPPIT approach, instead of using isolated EpoR fragments as bait, we used the full-length EpoR itself as a “receptor bait.” Finally, we introduced MAPPIT in the erythroleukemic TF-1 cell line, which is a more natural setting of the EpoR. With these strategies several known interactions with the EpoR were analyzed and evidence for new interactions was obtained.

Reverse MAPPIT: screening for protein-protein interaction modifiers in mammalian cells

Interactions between proteins are at the heart of the cellular machinery. It is therefore not surprising that altered interaction profiles caused by aberrant protein expression patterns or by the presence of mutations can trigger cellular dysfunction, eventually leading to disease. Moreover, many viral and bacterial pathogens rely on protein-protein interactions to exert their damaging effects. Interfering with such interactions is an obvious pharmaceutical goal, but detailed insights into the protein binding properties as well as efficient screening platforms are needed. In this report, we describe a cytokine receptor-based assay with a positive readout to screen for disrupters of designated protein-protein interactions in intact mammalian cells and evaluate this concept using polypeptides as well as small organic molecules. These reverse mammalian protein-protein interaction trap (MAPPIT) screens were developed to monitor interactions between the erythropoietin receptor (EpoR) and suppressors of cytokine signaling (SOCS) proteins, between FKBP12 and ALK4, and between MDM2 and p53.

Heteromeric MAPPIT: a novel strategy to study modification-dependent protein-protein interactions in mammalian cells

We recently reported a two-hybrid trap for detecting protein-protein interactions in intact mammalian cells (MAPPIT). The bait protein was fused to a STAT recruitment-deficient, homodimeric cytokine receptor and the prey protein to functional STAT recruitment sites. In such a configuration, STAT-dependent responses can be used to monitor a given bait-prey interaction. Using this system, we were able to demonstrate both modification-independent and tyrosine phosphorylation- dependent interactions. Protein modification in this approach is, however, strictly dependent on the receptor-associated JAK tyrosine kinases. We have now extended this concept by using extracellular domains of the heteromeric granulocyte/macrophage colony-stimulating factor receptor (GM-CSFR). Herein, the bait was fused to the (beta)c chain and its modifying enzyme to the GM-CSFRalpha chain (or vice versa). We demonstrate several serine phosphorylation-dependent interactions in the TGFbeta/Smad pathway using the catalytic domains of the ALK4 or ALK6 serine/threonine kinase receptors. In all cases tested, STAT-dependent signaling was completely abolished when mutant baits were used wherein critical serine residues were replaced by alanines. This approach operates both in transient and stable expression systems and may not be limited to serine phosphorylation but has the potential for studying various different types of protein modification-dependent interactions in intact cells.

Design and use of a mammalian protein-protein interaction trap (MAPPIT)

Identifying the interaction partners of a protein is a straightforward way to gain insight into the protein's function and to position it in an interaction network such as a signal transduction pathway. Various techniques have been developed to serve this purpose, and some are specifically designed to study posttranslational modifications in mammalian proteins and to clarify their normal physiological context. However, several intrinsic constraints limit the use of these technologies, and most are not suitable for screening for new interacting partners. In the Mammalian Protein-Protein Interaction Trap (MAPPIT) Protocol described here, knowledge of cytokine receptor signaling has been used to design a versatile genetic tool that can be used analytically and for detection of new protein-protein interactions in mammalian cells.

MAPPIT: a cytokine receptor-based two-hybrid method in mammalian cells

Identifying novel targets for therapy in allergic disease: protein interactions inside the cell Therapy of allergic disease currently relies on pharmacological manipulation of mediators or immunotherapy. Drugs have been developed to target specific mediators and their receptors: for example antihistamines blocking the H1 receptor have been refined to maximize antagonism and reduce central side-effects or adverse effects of activity on other receptors such as muscarinic cholinergic receptors. Traditional pharmacological approaches identify new surface receptors against which chemists will then design or screen compounds for activity: examples are H3 or H4 histamine receptors. With the advent of the sequenced human genome we are faced with a vast array of genes and proteins that interact to define normal physiology or indeed pathology. A major challenge to biotechnology is to evolve novel techniques to understand the function and interaction of these myriad proteins. One particular area of current interest is the signalling cascades downstream of surface receptors. For many years pathways have appeared overlapping and to offer little chance of specific intervention. However, greater understanding of the complexity and integration of signalling, together with the possibility of directing drugs to specific cells has aroused considerable interest in this area for novel therapeutics. Indeed, targeting events within the cell has been done for many years with steroids. Here, Jan Tavernier and colleagues describe some signalling pathways relevant to allergic disease and potential methods for understanding protein interactions that allow mapping of the cascades. In particular they describe an elegant new system of analysis of protein-protein interactions in a mammalian system, which they have developed, termed MAPPIT. The basis of the system is an engineered receptor with JAK kinase but which lacks STAT activation sites. To the cytoplasmic end of the receptor is added a bait protein of interest, and the cell line can then be transduced with plasmid containing 'prey' cDNA from a library of interest linked to an active STAT binding site. If this cDNA encodes a protein which, upon expression, is activated and recruited to the membrane complex, it will bind to the receptor via the bait, then STAT activation will occur and activate a reporter gene system such as luciferase or puromycin resistance. This novel system allows study of known protein-protein interactions by targeted mutagenesis, or screening for novel interactions. It has the advantage over existing systems such as yeast 2 hybrid that it uses mammalian cells and thus can reproduce the physiological conditions for protein processing or activation. As new genes and proteins are linked to the atopic phenotypes, systems such as this hold promise of rapidly defining their function and interacting proteins and may be important in linking genomics and proteomics with function and pharmacology in the future.

Design and application of a cytokine-receptor-based interaction trap

Ligand-induced clustering of type I cytokine receptor subunits leads to trans-phosphorylation and activation of associated cytosolic janus kinases (JAKs). In turn, JAKs phosphorylate tyrosine residues in the receptor tails, leading to recruitment and activation of signalling molecules. Among these, signal transducers and activators of transcription (STATs) are important in the direct transmission of signals to the nucleus. Here, we show that incorporation of an interaction trap in a signalling-deficient receptor allows the identification of protein-protein interactions, using a STAT-dependent complementation assay. Mammalian protein-protein interaction trap (MAPPIT) adds to existing yeast two-hybrid procedures, as originally explored by Fields and Song, and permits the detection of both modification-independent and of phosphorylation-dependent interactions in intact human cells. We also demonstrate that MAPPIT can be used to screen complex complementary DNA libraries, and using this approach, we identify cytokine-inducible SH2-containing protein (CIS) and suppressor of cytokine signalling-2 (SOCS-2) as interaction partners of the phosphotyrosine 402 (Tyr 402)-binding motif in the erythropoietin receptor (EpoR). Importantly, this approach places protein-protein interactions in their normal physiological context, and is especially applicable to the in situ analysis of signal transduction pathways.

Characterization of the mouse Men1 gene and its expression during development

The gene responsible for multiple endocrine neoplasia type 1 (MEN1), a heritable predisposition to endocrine tumours in man, has recently been identified. Here we have characterized the murine homologue with regard to cDNA sequence, genomic structure, expression pattern and chromosomal localisation. The murine Men1 gene spans approximately 6.7 kb of genomic DNA and is comprised of 10 exons with similar genomic structure to the human locus. It was mapped to the pericentromeric region of mouse chromosome 19, which is conserved with the human 11q13 band where MEN1 is located. The predicted protein is 611 amino acids in length and overall is 97% homologous to the human orthologue. The 45 reported MEN1 mutations which alter or delete a single amino acid in human all occur at conserved residues, thereby supporting their functional significance. Two transcripts of approximately 3.2 and 2.8 kb were detected in both embryonal and adult murine tissues, resulting from alternative splicing of intron 1. By RNA in situ hybridization and Northern analysis the spatiotemporal expression pattern of Men1 was determined during mouse development. Men1 gene activity was detected already at gestational day 7. At embryonic day 14 expression was generally high throughout the embryo, while at day 17 the thymus, skeletal muscle, and CNS showed the strongest signal. In selected tissues from postnatal mouse Men1 was detected in all tissues analysed and was expressed at high levels in cerebral cortex, hippocampus, testis, and thymus. In brain the menin protein was detected mainly in nerve cell nuclei, whereas in testis it appeared perinuclear in spermatogonia. These results show that Men1 expression is not confined to organs affected in MEN1, suggesting that Men1 has a significant function in many different cell types including the CNS and testis.

A putative human zinc-finger gene (ZFPL1) on 11q13, highly conserved in the mouse and expressed in exocrine pancreas. The European Consortium on MEN 1

In the process of identification of the multiple endocrine neoplasia type 1 gene, which was recently published, we isolated a novel gene in the 11q13 region. This gene (named ZFPL1, for zinc-finger protein-like 1) is expressed strongly in the exocrine pancreas as a 1.4-kb polyadenylated RNA encoding a putative protein of 310 amino acids. A mouse EST contig predicts an equally sized murine protein with 91% amino acid sequence identity to the human protein. No significant homology with known proteins could be found through database screening. However, zinc-finger-like domains and leucine-zipper-like motifs in the predicted ZFPL1 protein were identified, suggesting the presence of DNA-binding and dimerization domains possibly involved in transcription regulation. This notion is supported by the presence of a putative bipartite nuclear localization signal. This paper presents the full-length cDNA sequence for this gene, its genomic structure and chromosomal orientation, and expression studies by Northern blot hybridization and RNA in situ hybridization.

Construction of a 1.2-Mb sequence-ready contig of chromosome 11q13 encompassing the multiple endocrine neoplasia type 1 (MEN1) gene. The European Consortium on MEN1

Multiple endocrine neoplasia type 1 (MEN1) is an autosomal dominant familial cancer syndrome characterized by parathyroid, pancreatic, and anterior pituitary tumors. The MEN1 locus has been previously localized to chromosome 11q13, and a 2-Mb gene-rich region flanked by D11S1883 and D11S449 has been defined. We have pursued studies to facilitate identification of the MEN1 gene by narrowing this critical region to a 900-kb interval between the VRF and D11S1783 loci through melotic mapping. This was achieved by investigating 17 cosmids for microsatellite polymorphisms, which defined two novel polymorphisms at the VRF and A0138 loci, and utilizing these to characterize recombinants in MEN1 families. In addition, we have established a 1200-kb sequence-ready contig consisting of 26 cosmids, eight BACs, and eight PACs that encompass this region. The precise locations for 19 genes and three ESTs within this contig have been determined, and three gene clusters consisting of a centromeric group (VRF, FKBP2, PNG, and PLCB3), a middle group (PYGM, ZFM1, SCG1, SCG2 (which proved to be the MEN1 gene), and PPP2R5B), and a telomeric group (H4B, ANG3, ANG2, ANG1, FON, FAU, NOF, NON, and D11S2196E) were observed. These results represent a valuable transcriptional map of chromosome 11q13 that will help in the search for disease genes in this region.

Identification of the multiple endocrine neoplasia type 1 (MEN1) gene. The European Consortium on MEN1

Multiple endocrine neoplasia type 1 (MEN1) is an autosomal dominant disorder characterised by tumours of the parathyroids, pancreas and anterior pituitary that represents one of the familial cancer syndromes. The MEN1 locus has been previously localised to chromosome 11q13, and a <300 kb gene-rich region flanked centromerically by PYGM and telomerically by D11S1783 defined by combined meiotic and tumour deletion mapping studies. Two candidate genes, ZFM1 and PPP2R5B, from this region have been previously excluded, and in order to identify additional candidate genes we used a BAC to isolate cDNAs from a bovine parathyroid cDNA library by direct selection. One of the novel genes that we identified, SCG2, proved to be identical to the recently published MEN1 gene, which is likely to be a tumour suppressor gene. The SCG2 transcript was 2.9 kb in all tissues with an additional 4.2 kb transcript also being present in the pancreas and thymus. Mutational analysis of SCG2 in 10 unrelated MEN1 families identified one polymorphism and nine different heterozygous mutations (one missense, four non-sense, one insertional and three deletional frameshifts) that segregated with the disease, hence providing an independent confirmation for the identification of the MEN1 gene.