Proteome-scale Binary Interactomics in Human Cells

Molecular glues and induced proximity: An evolution of tools and discovery

Small molecule molecular glues can nucleate protein complexes and rewire interactomes. Molecular glues are widely used as probes for understanding functional proximity at a systems level, and the potential to instigate event-driven pharmacology has motivated their application as therapeutics. Despite advantages such as cell permeability and the potential for low off-target activity, glues are still rare when compared to canonical inhibitors in therapeutic development. Their often simple structure and specific ability to reshape protein-protein interactions pose several challenges for widespread, designer applications. Molecular glue discovery and design campaigns can find inspiration from the fields of synthetic biology and biophysics to mine chemical libraries for glue-like molecules.

Chronic stress from adolescence to adulthood increases adiposity and anxiety in rats with decreased expression of Krtcap3

We previously identified Keratinocyte-associated protein 3, Krtcap3, as a novel adiposity gene, but subsequently found that its impact on adiposity may depend on environmental stress. To more thoroughly understand the connection between Krtcap3, adiposity, and stress, we exposed wild-type (WT) and Krtcap3 knock-out (KO) rats to chronic stress then measured adiposity and behavioral outcomes. We found that KO rats displayed lower basal stress than WT rats under control conditions and exhibited metabolic and behavioral responses to chronic stress exposure. Specifically, stress-exposed KO rats gained more weight, consumed more food when socially isolated, and displayed more anxiety-like behaviors relative to control KO rats. Meanwhile, there were minimal differences between control and stressed WT rats. At study conclusion stress-exposed KO rats had increased corticosterone (CORT) relative to control KO rats with no differences between WT rats. In addition, KO rats, independent of prior stress exposure, had an increased CORT response to removal of their cage-mate (psychosocial stress), which was only seen in WT rats when exposed to chronic stress. Finally, we found differences in expression of the glucocorticoid receptor, Nr3c1, in the pituitary and colon between control and stress-exposed KO rats that were not present in WT rats. These data support that Krtcap3 expression affects stress response, potentially via interactions with Nr3c1, with downstream effects on adiposity and behavior. Future work is necessary to more thoroughly understand the role of Krtcap3 in the stress response.

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.

Modulating glucocorticoid receptor actions in physiology and pathology: Insights from coregulators

Glucocorticoids (GCs) are a class of steroid hormones that regulate key physiological processes such as metabolism, immune function, and stress responses. The effects of GCs are mediated by the glucocorticoid receptor (GR), a ligand-dependent transcription factor that activates or represses the expression of hundreds to thousands of genes in a tissue- and physiological state-specific manner. The activity of GR is modulated by numerous coregulator proteins that interact with GR in response to different stimuli assembling into a multitude of DNA-protein complexes and facilitate the integration of these signals, helping GR to communicate with basal transcriptional machinery and chromatin. Here, we provide a brief overview of the physiological and molecular functions of GR, and discuss the roles of GR coregulators in the immune system, key metabolic tissues and the central nervous system. We also present an analysis of the GR interactome in different cells and tissues, which suggests tissue-specific utilization of GR coregulators, despite widespread functions shared by some of them.

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.

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.

Predicting Protein-Protein Interactions Using Symmetric Logistic Matrix Factorization

Accurate assessment of protein-protein interactions (PPIs) is critical to deciphering disease mechanisms and developing novel drugs, and with rapidly growing PPI data, the need for more efficient predictive methods is emerging. We propose here a symmetric logistic matrix factorization (symLMF)-based approach to predict PPIs, especially useful for large PPI networks. Benchmarked against two widely used datasets (Saccharomyces cerevisiae and Homo sapiens benchmarks) and their extended versions, the symLMF-based method proves to outperform most of the state-of-the-art data-driven methods applied to human PPIs, and it shows a performance comparable to those of deep learning methods despite its conceptual and technical simplicity and efficiency. Tests performed on humans, yeast, and tissue (brain and liver)- and disease (neurodegenerative and metabolic disorders)-specific datasets further demonstrate the high capability to capture the hidden interactions. Notably, many "de novo predictions" made by symLMF are verified to exist in PPI databases other than those used for training/testing the method, indicating that the method could be of broad utility as a simple, yet efficient and accurate, tool applicable to PPI datasets.

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.

The mammalian two-hybrid system as a powerful tool for high-throughput drug screening

Protein-protein interactions (PPIs) are the backbone of signaling pathways, responsible for the basis of cell communication and, when deregulated, several diseases. Consequently, identifying and modulating PPIs can unravel the pathophysiological mechanisms of diseases. The two-hybrid system, particularly the mammalian two-hybrid system (MTH), is an efficient technique to validate PPIs ex vivo. Combining MTH with high-throughput screening has a huge advantage in biomedical research. In this review, we describe methodologies developed from MTH and the role of these adaptations in PPI discovery. We also highlight the powerful contribution of MTH to the identification of disease-related PPIs and its use in the development of potential new drug screens.

Protein interactome mapping in Caenorhabditis elegans

The systematic identification of all protein-protein interactions that take place in an organism (the 'interactome') is an important goal in modern biology. The nematode Caenorhabditis elegans was one of the first multicellular models for which a proteome-wide interactome mapping project was initiated. Most Caenorhabditis elegans interactome mapping efforts have utilized the yeast two-hybrid system, yielding an extensive binary interactome, while recent developments in mass spectrometry-based approaches hold great potential for further improving our understanding of protein interactome networks in a multicellular context. For example, methods like co-fractionation, proximity labeling, and tissue-specific protein purification not only identify protein-protein interactions, but have the potential to provide crucial insight into when and where interactions take place. Here we review current standards and recent improvements in protein interaction mapping in C. elegans.

Using backbone-cyclized Cys-rich polypeptides as molecular scaffolds to target protein-protein interactions

The use of disulfide-rich backbone-cyclized polypeptides, as molecular scaffolds to design a new generation of bioimaging tools and drugs that are potent and specific, and thus might have fewer side effects than traditional small-molecule drugs, is gaining increasing interest among the scientific and in the pharmaceutical industries. Highly constrained macrocyclic polypeptides are exceptionally more stable to chemical, thermal and biological degradation and show better biological activity when compared with their linear counterparts. Many of these relatively new scaffolds have been also found to be highly tolerant to sequence variability, aside from the conserved residues forming the disulfide bonds, able to cross cellular membranes and modulate intracellular protein-protein interactions both in vitro and in vivo These properties make them ideal tools for many biotechnological applications. The present study provides an overview of the new developments on the use of several disulfide-rich backbone-cyclized polypeptides, including cyclotides, θ-defensins and sunflower trypsin inhibitor peptides, in the development of novel bioimaging reagents and therapeutic leads.

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.

LuTHy: a double-readout bioluminescence-based two-hybrid technology for quantitative mapping of protein-protein interactions in mammalian cells

Information on protein-protein interactions (PPIs) is of critical importance for studying complex biological systems and developing therapeutic strategies. Here, we present a double-readout bioluminescence-based two-hybrid technology, termed LuTHy, which provides two quantitative scores in one experimental procedure when testing binary interactions. PPIs are first monitored in cells by quantification of bioluminescence resonance energy transfer (BRET) and, following cell lysis, are again quantitatively assessed by luminescence-based co-precipitation (LuC). The double-readout procedure detects interactions with higher sensitivity than traditional single-readout methods and is broadly applicable, for example, for detecting the effects of small molecules or disease-causing mutations on PPIs. Applying LuTHy in a focused screen, we identified 42 interactions for the presynaptic chaperone CSPα, causative to adult-onset neuronal ceroid lipofuscinosis (ANCL), a progressive neurodegenerative disease. Nearly 50% of PPIs were found to be affected when studying the effect of the disease-causing missense mutations L115R and ∆L116 in CSPα with LuTHy. Our study presents a robust, sensitive research tool with high utility for investigating the molecular mechanisms by which disease-associated mutations impair protein activity in biological systems.

SMILE: a novel procedure for subcellular module identification with localisation expansion

Computational clustering methods help identify functional modules in protein–protein interaction (PPI) network, in which proteins participate in the same biological pathways or specific functions. Subcellular localisation is crucial for proteins to implement biological functions and each compartment accommodates specific portions of the protein interaction structure. However, the importance of protein subcellular localisation is often neglected in the studies of module identification. In this study, the authors propose a novel procedure, subcellular module identification with localisation expansion (SMILE), to identify super modules that consist of several subcellular modules performing specific biological functions among cell compartments. These super modules identified by SMILE are more functionally diverse and have been verified to be more associated with known protein complexes and biological pathways compared with the modules identified from the global PPI networks in both the compartmentalised PPI and InWeb_InBioMap datasets. The authors’ results reveal that subcellular localisation is a principal feature of functional modules and offers important guidance in detecting biologically meaningful results.

High-Confidence Interactome for RNF41 Built on Multiple Orthogonal Assays

Ring finger protein 41 (RNF41) is an E3 ubiquitin ligase involved in the ubiquitination and degradation of many proteins including ErbB3 receptors, BIRC6, and parkin. Next to this, RNF41 regulates the intracellular trafficking of certain JAK2-associated cytokine receptors by ubiquitinating and suppressing USP8, which, in turn, destabilizes the ESCRT-0 complex. To further elucidate the function of RNF41 we used different orthogonal approaches to reveal the RNF41 protein complex: affinity purification-mass spectrometry, BioID, and Virotrap. We combined these results with known data sets for RNF41 obtained with microarray MAPPIT and Y2H screens. This way, we establish a comprehensive high-resolution interactome network comprising 175 candidate protein partners. To remove potential methodological artifacts from this network, we distilled the data into a high-confidence interactome map by retaining a total of 19 protein hits identified in two or more of the orthogonal methods. AP2S1, a novel RNF41 interaction partner, was selected from this high-confidence interactome for further functional validation. We reveal a role for AP2S1 in leptin and LIF receptor signaling and show that RNF41 stabilizes and relocates AP2S1.

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.

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.

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.