Protein-protein Interaction Screening Research Articles

The Hippo signaling pathway interactome.

The Hippo pathway controls metazoan organ growth by regulating cell proliferation and apoptosis. Many components have been identified, but our knowledge of the composition and structure of this pathway is still incomplete. Using existing pathway components as baits, we generated by mass spectrometry a high-confidence Drosophila Hippo protein-protein interaction network (Hippo-PPIN) consisting of 153 proteins and 204 interactions. Depletion of 67% of the proteins by RNA interference regulated the transcriptional coactivator Yorkie (Yki) either positively or negatively. We selected for further characterization a new member of the alpha-arrestin family, Leash, and show that it promotes degradation of Yki through the lysosomal pathway. Given the importance of the Hippo pathway in tumor development, the Hippo-PPIN will contribute to our understanding of this network in both normal growth and cancer.

MEGADOCK: An All-to-All Protein-Protein Interaction Prediction System Using Tertiary Structure Data

The elucidation of protein-protein interaction (PPI) networks is important for understanding cellular structure and function and structure-based drug design. However, the development of an effective method to conduct exhaustive PPI screening represents a computational challenge. We have been investigating a protein docking approach based on shape complementarity and physicochemical properties. We describe here the development of the protein-protein docking software package “MEGADOCK” that samples an extremely large number of protein dockings at high speed. MEGADOCK reduces the calculation time required for docking by using several techniques such as a novel scoring function called the real Pairwise Shape Complementarity (rPSC) score. We showed that MEGADOCK is capable of exhaustive PPI screening by completing docking calculations 7.5 times faster than the conventional docking software, ZDOCK, while maintaining an acceptable level of accuracy. When MEGADOCK was applied to a subset of a general benchmark dataset to predict 120 relevant interacting pairs from 120 x 120 = 14,400 combinations of proteins, an F-measure value of 0.231 was obtained. Further, we showed that MEGADOCK can be applied to a large-scale protein-protein interaction-screening problem with accuracy better than random. When our approach is combined with parallel high-performance computing systems, it is now feasible to search and analyze protein-protein interactions while taking into account three-dimensional structures at the interactome scale. MEGADOCK is freely available at http://www.bi.cs.titech.ac.jp/megadock.

Negative Feedback Control of Jasmonate Signaling by an Alternative Splice Variant of JAZ10

The plant hormone jasmonate (JA) activates gene expression by promoting ubiquitin-dependent degradation of jasmonate ZIM domain (JAZ) transcriptional repressor proteins. A key feature of all JAZ proteins is the highly conserved Jas motif, which mediates both JAZ degradation and JAZ binding to the transcription factor MYC2. Rapid expression of JAZ genes in response to JA is thought to attenuate JA responses, but little is known about the mechanisms by which newly synthesized JAZ proteins exert repression in the presence of the hormone. Here, we show in Arabidopsis (Arabidopsis thaliana) that desensitization to JA is mediated by an alternative splice variant (JAZ10.4) of JAZ10 that lacks the Jas motif. Unbiased protein-protein interaction screens identified three related basic helix-loop-helix transcription factors (MYC2, MYC3, and MYC4) and the corepressor NINJA as JAZ10.4-binding partners. We show that the amino-terminal region of JAZ10.4 contains a cryptic MYC2-binding site that resembles the Jas motif and that the ZIM motif of JAZ10.4 functions as a transferable repressor domain whose activity is associated with the recruitment of NINJA. Functional studies showed that the expression of JAZ10.4 from the native JAZ10 promoter complemented the JA-hypersensitive phenotype of a jaz10 mutant. Moreover, treatment of these complemented lines with JA resulted in the rapid accumulation of JAZ10.4 protein. Our results provide an explanation for how the unique domain architecture of JAZ10.4 links transcription factors to a corepressor complex and suggest how JA-induced transcription and alternative splicing of JAZ10 premessenger RNA creates a regulatory circuit to attenuate JA responses.

Development and application of a DNA microarray-based yeast two-hybrid system

The yeast two-hybrid (Y2H) system is the most widely applied methodology for systematic protein–protein interaction (PPI) screening and the generation of comprehensive interaction networks. We developed a novel Y2H interaction screening procedure using DNA microarrays for high-throughput quantitative PPI detection. Applying a global pooling and selection scheme to a large collection of human open reading frames, proof-of-principle Y2H interaction screens were performed for the human neurodegenerative disease proteins huntingtin and ataxin-1. Using systematic controls for unspecific Y2H results and quantitative benchmarking, we identified and scored a large number of known and novel partner proteins for both huntingtin and ataxin-1. Moreover, we show that this parallelized screening procedure and the global inspection of Y2H interaction data are uniquely suited to define specific PPI patterns and their alteration by disease-causing mutations in huntingtin and ataxin-1. This approach takes advantage of the specificity and flexibility of DNA microarrays and of the existence of solid-related statistical methods for the analysis of DNA microarray data, and allows a quantitative approach toward interaction screens in human and in model organisms.

Transcriptional divergence plays a role in the rewiring of protein interaction networks after gene duplication

Gene duplication plays a key role in the evolution of protein-protein interaction (PPI) networks. After a gene duplication event, paralogous proteins may diverge through the gain and loss of PPIs. This divergence can be explained by two non-exclusive mechanisms. First, mutations may accumulate in the coding sequences of the paralogs and affect their protein sequences, which can modify, for instance, their binding interfaces and thus their interaction specificity. Second, mutations may accumulate in the non-coding region of the genes and affect their regulatory sequences. The resulting changes in expression profiles can lead to paralogous proteins being differentially expressed and occurring in the cell with different sets of potential interaction partners. These changes could also alter splicing regulation and lead to the inclusion or exclusion of alternative exons. The evolutionary role of these regulatory mechanisms remains largely unexplored. We use bioinformatics analyses of existing PPI data and proteome-wide PPI screening to show that the divergence of transcriptional regulation between paralogs plays a significant role in determining their PPI specificity. Because many gene duplication events are followed by rapid changes in transcriptional regulation, our results suggest that PPI networks may be rewired by gene duplication, without the need for protein to diverge in their binding specificities. This article is part of a Special Issue entitled: From protein structures to clinical applications.

Development of an Influenza virus Protein Array Using Sortagging Technology

Protein array technology is an emerging tool that enables high-throughput screening of protein-protein or protein-lipid interactions and identification of immunodominant antigens during the course of a bacterial or viral infection. In this work, we developed an Influenza virus protein array using the sortase-mediated transpeptidation reaction known as "Sortagging". LPETG-tagged Influenza virus proteins from bacterial and eukaryotic cellular extracts were immobilized at their carboxyl-termini onto a preactivated amine-glass slide coated with a Gly3 linker. Immobilized proteins were revealed by specific antibodies, and the newly generated Sortag-protein chip can be used as a device for antigen and/or antibody screening. The specificity of the Sortase A (SrtA) reaction avoids purification steps in array building and allows immobilization of proteins in an oriented fashion. Previously, this versatile technology has been successfully employed for protein labeling and protein conjugation. Here, the tool is implemented to covalently link proteins of a viral genome onto a solid support. The system could readily be scaled up to proteins of larger genomes in order to develop protein arrays for high-throughput screening.

Patterns and rates of exonic de novo mutations in autism spectrum disorders

Autism spectrum disorders (ASD) are believed to have genetic and environmental origins, yet in only a modest fraction of individuals can specific causes be identified1,2. To identify further genetic risk factors, we assess the role of de novo mutations in ASD by sequencing the exomes of ASD cases and their parents (n= 175 trios). Fewer than half of the cases (46.3%) carry a missense or nonsense de novo variant and the overall rate of mutation is only modestly higher than the expected rate. In contrast, there is significantly enriched connectivity among the proteins encoded by genes harboring de novo missense or nonsense mutations, and excess connectivity to prior ASD genes of major effect, suggesting a subset of observed events are relevant to ASD risk. The small increase in rate of de novo events, when taken together with the connections among the proteins themselves and to ASD, are consistent with an important but limited role for de novo point mutations, similar to that documented for de novo copy number variants. Genetic models incorporating these data suggest that the majority of observed de novo events are unconnected to ASD, those that do confer risk are distributed across many genes and are incompletely penetrant (i.e., not necessarily causal). Our results support polygenic models in which spontaneous coding mutations in any of a large number of genes increases risk by 5 to 20-fold. Despite the challenge posed by such models, results from de novo events and a large parallel case-control study provide strong evidence in favor of CHD8 and KATNAL2 as genuine autism risk factors.

Self-Assembled Nanometer Scale Lipid Bilayers for Elucidating the Structure and Function of Membrane Proteins

One of the most challenging problems in biochemical science are studies of integral membrane proteins. Using designed amphipathic helical peptides, termed membrane scaffold proteins (MSPs) we have developed a simple and robust system that self-assembles phospholipids into soluble discoidal phospholipid bilayers 8-10 nm in diameter, termed Nanodiscs. Importantly, the same self-assembly process can be used to directly incorporate a variety of integral membrane proteins into these nanobilayers. The result is a native-like environment that provides stability and full functionality for these integral membrane protein targets. Using MSPs of varying lengths, the size and composition of the Nanodiscs can also control the oligomerization state of incorporated targets. During my presentation I will relay our most recent results in the incorporation of integral membrane enzymes, channels, transporters and receptors into Nanodiscs as well as the structural, biophysical and biochemical characterization of these nanostructures. We have also demonstrated that this same self-assembly process can be used to form Soluble Membrane Protein Libraries (SMPL) which can be used as the basis for high-throughput screening of protein-protein, cell-cell and cell-viral interactions. Supported by grants from the National Institutes of Health.

Proteome-wide Detection of Abl1 SH3-binding Peptides by Integrating Computational Prediction and Peptide Microarray

Protein-protein interactions are essential for regulating almost all aspects of cellular functions. Many of these interactions are mediated by weak and transient protein domain-peptide binding, but they are often under-represented in high throughput screening of protein-protein interactions using techniques such as yeast two-hybrid and mass spectrometry. On the other hand, computational predictions and in vitro binding assays are valuable in providing clues of in vivo interactions. We present here a systematic approach that integrates computer modeling and a peptide microarray technology to identify binding peptides of the SH3 domain of the tyrosine kinase Abl1 in the human proteome. Our study provides a comprehensive list of candidate interacting partners for the Abl1 protein, among which the presence of numerous methyltransferases and RNA splicing proteins may suggest a novel function of Abl1 in chromatin remodeling and RNA processing. This study illustrates a powerful approach for integrating computational and experimental methods to detect protein interactions mediated by domain-peptide recognition.

Construction of high quality Gateway™ entry libraries and their application to yeast two-hybrid for the monocot model plant Brachypodium distachyon

BackgroundMonocots, especially the temperate grasses, represent some of the most agriculturally important crops for both current food needs and future biofuel development. Because most of the agriculturally important grass species are difficult to study (e.g., they often have large, repetitive genomes and can be difficult to grow in laboratory settings), developing genetically tractable model systems is essential. Brachypodium distachyon (hereafter Brachypodium) is an emerging model system for the temperate grasses. To fully realize the potential of this model system, publicly accessible discovery tools are essential. High quality cDNA libraries that can be readily adapted for multiple downstream purposes are a needed resource. Additionally, yeast two-hybrid (Y2H) libraries are an important discovery tool for protein-protein interactions and are not currently available for Brachypodium.ResultsWe describe the creation of two high quality, publicly available Gateway™ cDNA entry libraries and their derived Y2H libraries for Brachypodium. The first entry library represents cloned cDNA populations from both short day (SD, 8/16-h light/dark) and long day (LD, 20/4-h light/dark) grown plants, while the second library was generated from hormone treated tissues. Both libraries have extensive genome coverage (~5 × 107 primary clones each) and average clone lengths of ~1.5 Kb. These entry libraries were then used to create two recombination-derived Y2H libraries. Initial proof-of-concept screens demonstrated that a protein with known interaction partners could readily re-isolate those partners, as well as novel interactors.ConclusionsAccessible community resources are a hallmark of successful biological model systems. Brachypodium has the potential to be a broadly useful model system for the grasses, but still requires many of these resources. The Gateway™ compatible entry libraries created here will facilitate studies for multiple user-defined purposes and the derived Y2H libraries can be immediately applied to large scale screening and discovery of novel protein-protein interactions. All libraries are freely available for distribution to the research community.

Meta-analysis of heterogeneous data sources for genome-scale identification of risk genes in complex phenotypes

Meta-analyses of large-scale association studies typically proceed solely within one data type and do not exploit the potential complementarities in other sources of molecular evidence. Here, we present an approach to combine heterogeneous data from genome-wide association (GWA) studies, protein-protein interaction screens, disease similarity, linkage studies, and gene expression experiments into a multi-layered evidence network which is used to prioritize the entire protein-coding part of the genome identifying a shortlist of candidate genes. We report specifically results on bipolar disorder, a genetically complex disease where GWA studies have only been moderately successful. We validate one such candidate experimentally, YWHAH, by genotyping five variations in 640 patients and 1,377 controls. We found a significant allelic association for the rs1049583 polymorphism in YWHAH (adjusted P = 5.6e-3) with an odds ratio of 1.28 [1.12-1.48], which replicates a previous case-control study. In addition, we demonstrate our approach's general applicability by use of type 2 diabetes data sets. The method presented augments moderately powered GWA data, and represents a validated, flexible, and publicly available framework for identifying risk genes in highly polygenic diseases. The method is made available as a web service at www.cbs.dtu.dk/services/metaranker.

Novel screening system for protein–protein interactions by bimolecular fluorescence complementation in Saccharomyces cerevisiae

For high-throughput screening of protein-protein interactions, we have developed a novel yeast screening system using Bimolecular fluorescence complementation (BiFC). Two yeast plasmids, in which genes of heterodimerized peptides LZA and LZB were each fused with those of non-fluorescent half fragments of Kusabira-Green mutant (mKG2), were transformed into a- and α-type yeast, respectively. Mating of them gave a library, which was screened by following green fluorescence resulted from LZA-LZB interaction. The method showed potential ability to detect the positive clones from a model library, in which green-fluorescent and non-fluorescent yeast was mixed in a ratio of 1:675.

Robo4 Maintains Vessel Integrity and Inhibits Angiogenesis by Interacting with UNC5B

Robo4 is an endothelial cell-specific member of the Roundabout axon guidance receptor family. To identify Robo4 binding partners, we performed a protein-protein interaction screen with the Robo4 extracellular domain. We find that Robo4 specifically binds to UNC5B, a vascular Netrin receptor, revealing unexpected interactions between two endothelial guidance receptors. We show that Robo4 maintains vessel integrity by activating UNC5B, which inhibits signaling downstream of vascular endothelial growth factor (VEGF). Function-blocking monoclonal antibodies against Robo4 and UNC5B increase angiogenesis and disrupt vessel integrity. Soluble Robo4 protein inhibits VEGF-induced vessel permeability and rescues barrier defects in Robo4(-/-) mice, but not in mice treated with anti-UNC5B. Thus, Robo4-UNC5B signaling maintains vascular integrity by counteracting VEGF signaling in endothelial cells, identifying a novel function of guidance receptor interactions in the vasculature.

A Bacterial Two-Hybrid System that Utilizes Gateway Cloning for Rapid Screening of Protein-Protein Interactions

Comprehensive clone sets representing the entire genome now exist for a large number of organisms. The Gateway entry clone sets are a particularly useful means to study gene function, given the ease of introduction into any Gateway-suitable destination vector. We have adapted a bacterial two-hybrid system for use with Gateway entry clone sets, such that potential interactions between proteins encoded within these clone sets can be determined by new destination vectors. We show that utilizing the Gateway clone sets for Francisella tularensis and Vibrio cholerae, known interactions between F. tularensis IglA and IglB and V. cholerae VipA and VipB could be confirmed with these destination vectors. Moreover, the introduction of unique tags into each vector allowed for visualization of the expressed hybrid proteins via Western immunoblot. This Gateway-suitable bacterial two-hybrid system provides a new tool for rapid screening of protein-protein interactions.

Coupled Yeast 2-Hybrid–Mammalian 2-Hybrid Reading-Frame-Independent and Site-Specific Recombinational Cloning Vector System

The yeast 2-hybrid (Y2H) system is a powerful method for identifying protein-protein interactions (PPIs), requiring minimal prior information of the putative interactors. Currently available automated versions of the Y2H system are sufficiently developed to allow facile genome-wide PPI screening to compile extensive inter-actome data. A limitation of the Y2H approach, however, is that all primary hits have to be technically verified and biologically evaluated by complementary methods, which is time-consuming, costly, and laborious. Furthermore, the yeast intracellular environment can lead to spurious results for proteins of other organisms, for example because of differences in post-translational modifications or the presence/absence of bridging proteins. Many researchers now confirm PPIs found in the Y2H system by retesting the candidates in the mammalian 2-hybrid system (M2H). However, although such combined Y2H-M2H testing is desirable and perhaps necessary, recloning of Y2H candidates into M2H vectors, especially on a large scale, is time-consuming and costly. To address this shortcoming, we introduce here a new site-specific recombination-capable M2H vector system that is fully compatible with the site-specific Y2H system that we recently described in Biotechniques [2008;45(3):235-244]. The results show that the new vectors are: (a) Gateway®, compatible and suitable for fast cloning; (b) fully functional in the M2H system without influencing the capacity of the selection system or creating autoactivators; and (c) directly compatible with the existing site-specific Y2H vector system, as demonstrated by confirmation of Y2H PPI candidates in the M2H system.

Global Approaches To Study Protein–Protein Interactions Among Viruses and Hosts

While high-throughput protein-protein interaction screens were first published approximately 10 years ago, systematic attempts to map interactions among viruses and hosts started only a few years ago. HIV-human interactions dominate host-pathogen interaction databases (with approximately 2000 interactions) despite the fact that probably none of these interactions have been identified in systematic interaction screens. Recently, combinations of protein interaction data with RNAi and other functional genomics data allowed researchers to model more complex interaction networks. The rapid progress in this area promises a flood of new data in the near future, with clinical applications as soon as structural and functional genomics catches up with next-generation sequencing of human variation and structure-based drug design.

Computational approaches for detecting protein complexes from protein interaction networks: a survey

BackgroundMost proteins form macromolecular complexes to perform their biological functions. However, experimentally determined protein complex data, especially of those involving more than two protein partners, are relatively limited in the current state-of-the-art high-throughput experimental techniques. Nevertheless, many techniques (such as yeast-two-hybrid) have enabled systematic screening of pairwise protein-protein interactions en masse. Thus computational approaches for detecting protein complexes from protein interaction data are useful complements to the limited experimental methods. They can be used together with the experimental methods for mapping the interactions of proteins to understand how different proteins are organized into higher-level substructures to perform various cellular functions.ResultsGiven the abundance of pairwise protein interaction data from high-throughput genome-wide experimental screenings, a protein interaction network can be constructed from protein interaction data by considering individual proteins as the nodes, and the existence of a physical interaction between a pair of proteins as a link. This binary protein interaction graph can then be used for detecting protein complexes using graph clustering techniques. In this paper, we review and evaluate the state-of-the-art techniques for computational detection of protein complexes, and discuss some promising research directions in this field.ConclusionsExperimental results with yeast protein interaction data show that the interaction subgraphs discovered by various computational methods matched well with actual protein complexes. In addition, the computational approaches have also improved in performance over the years. Further improvements could be achieved if the quality of the underlying protein interaction data can be considered adequately to minimize the undesirable effects from the irrelevant and noisy sources, and the various biological evidences can be better incorporated into the detection process to maximize the exploitation of the increasing wealth of biological knowledge available.

Biotin tagging coupled with amino acid‐coded mass tagging for efficient and precise screening of interaction proteome in mammalian cells

In mammalian cells, when tandem affinity purification approach is employed, the existence of untagged endogenous target protein and repetitive washing steps together result in overall low yield of purified/stable complexes and the loss of weakly and transiently interacting partners of biological significance. To avoid the trade-offs involving in methodological sensitivity, precision, and throughput, here we introduce an integrated method, biotin tagging coupled with amino acid-coded mass tagging, for highly sensitive and accurate screening of mammalian protein-protein interactions. Without the need of establishing a stable cell line, using a short peptide tag which could be specifically biotinylated in vivo, the biotin-tagged target/bait protein was then isolated along with its associates efficiently by streptavidin magnetic microbeads in a single step. In a pulled-down complex amino acid-coded mass tagging serves as "in-spectra" quantitative markers to distinguish those bait-specific interactors from non-specific background proteins under stringent criteria. Applying this biotin tagging coupled with amino acid-coded mass tagging approach, we first biotin-tagged in vivo a multi-functional protein family member, 14-3-3epsilon, which was expressed at close to endogenous level. Starting with approximately 20 millions of 293T cells which were significantly less than what needed for a tandem affinity purification run, 266 specific interactors of 14-3-3epsilon were identified in high confidence.

High quality protein microarray using in situprotein purification

BackgroundIn the postgenomic era, high throughput protein expression and protein microarray technologies have progressed markedly permitting screening of therapeutic reagents and discovery of novel protein functions. Hexa-histidine is one of the most commonly used fusion tags for protein expression due to its small size and convenient purification via immobilized metal ion affinity chromatography (IMAC). This purification process has been adapted to the protein microarray format, but the quality of in situ His-tagged protein purification on slides has not been systematically evaluated. We established methods to determine the level of purification of such proteins on metal chelate-modified slide surfaces. Optimized in situ purification of His-tagged recombinant proteins has the potential to become the new gold standard for cost-effective generation of high-quality and high-density protein microarrays.ResultsTwo slide surfaces were examined, chelated Cu2+ slides suspended on a polyethylene glycol (PEG) coating and chelated Ni2+ slides immobilized on a support without PEG coating. Using PEG-coated chelated Cu2+ slides, consistently higher purities of recombinant proteins were measured. An optimized wash buffer (PBST) composed of 10 mM phosphate buffer, 2.7 mM KCl, 140 mM NaCl and 0.05% Tween 20, pH 7.4, further improved protein purity levels. Using Escherichia coli cell lysates expressing 90 recombinant Streptococcus pneumoniae proteins, 73 proteins were successfully immobilized, and 66 proteins were in situ purified with greater than 90% purity. We identified several antigens among the in situ-purified proteins via assays with anti-S. pneumoniae rabbit antibodies and a human patient antiserum, as a demonstration project of large scale microarray-based immunoproteomics profiling. The methodology is compatible with higher throughput formats of in vivo protein expression, eliminates the need for resin-based purification and circumvents protein solubility and denaturation problems caused by buffer exchange steps and freeze-thaw cycles, which are associated with resin-based purification, intermittent protein storage and deposition on microarrays.ConclusionAn optimized platform for in situ protein purification on microarray slides using His-tagged recombinant proteins is a desirable tool for the screening of novel protein functions and protein-protein interactions. In the context of immunoproteomics, such protein microarrays are complimentary to approaches using non-recombinant methods to discover and characterize bacterial antigens.

Polyplexed Flow Cytometry Protein Interaction Assay: A Novel High-Throughput Screening Paradigm for RGS Protein Inhibitors

Intracellular signaling cascades are a series of regulated protein-protein interactions that may provide a number of targets for potential drug discovery. Here, the authors examine the interaction of regulators of G-protein signaling (RGS) proteins with the G-protein Galphao, using a flow cytometry protein interaction assay (FCPIA). FCPIA accurately measures nanomolar binding constants of this protein-protein interaction and has been used in high-throughput screening. This report focuses on 5 RGS proteins (4, 6, 7, 8, and 16). To increase the content of screens, the authors assessed high-throughput screening of these RGS proteins in multiplex, by establishing binding constants of each RGS with Galphao in isolation, and then in a multiplex format with 5 RGS proteins present. To use this methodology as a higher-content multiplex protein-protein interaction screen, they established Z-factor values for RGS proteins in multiplex of 0.73 to 0.92, indicating this method is suitable for screening using FCPIA. To increase throughput, they also compressed a set of 8000 compounds by combining 4 compounds in a single assay well. Subsequent deconvolution of the compounds mixtures verified the identification of active compounds at specific RGS targets in their mixtures using the polyplexed FCPIA method.