Two-hybrid technologies in proteomics research

A fluorescence-based binding assay for proteins using the cell surface as a sensing platform

Protein-protein interaction (PPI) analysis is very important for elucidating the functions of proteins because many proteins execute their functions in living cells by interacting with one another. In PPI analysis, methods using the sensor chips are widely employed to obtain quantitative data. However, these methods require that the target proteins be immobilized on the sensor chips, and the immobilization processes can affect the binding of the target proteins to their binding partners. In the present work, we propose a PPI analysis system in which the surface of the living cells is utilized as a sensing platform. In our approach, the target protein is displayed on the cell surface by expressing it as a fusion protein with a membrane protein, and the PPI analysis is then conducted by applying its binding partner labeled with a fluorescent dye to the cell surface. We have constructed a model of this binding analysis system using the interaction between biotin protein ligase (BPL) and biotin carboxyl carrier protein (BCCP), where BCCP was displayed on the cell surface and BPL labeled with fluorescein was applied to the cell surface. Here, a red fluorescent protein, mApple, was attached to the C-terminus of the fusion protein of BCCP with a membrane protein. We evaluated the binding level of the labeled BPL by using the intensity ratios of fluorescence from fluorescein to that from mApple. We found that the binding level of the labeled BPL was stably evaluated at least across 60 min observation period and estimated the binding dissociation constant between BPL and BCCP by equilibrium analysis to be 0.33 ± 0.05 μM.

Proteomic and yeast 2-hybrid screens to identify PTEN binding partners

PTEN is a phosphoinositide lipid phosphatase and an important tumour suppressor protein. PTEN function is reduced or lost in around a third of all human cancers through diverse mechanisms, from gene deletion to changes in the function of proteins which regulate PTEN through direct protein binding. Here we present data from SILAC (Stable Isotope Labelling by Amino acids in Cell culture) proteomic screens to identify proteins which bind to PTEN. These experiments using untransformed epithelial cells and glioma cells identified several novel candidate proteins in addition to many previously identified PTEN binding partners and many proteins which are recognised as common false positives using these methods. From subsequent co-expression pull-down experiments we provide further evidence supporting the physical interaction of PTEN with MMP1, Myosin 18A and SHROOM3. We also performed yeast two-hybrid screens which identify the previously recognised PTEN binding partner MSP58 in addition to the nuclear import export receptor TNPO3. These experiments identify several novel candidate binding partners of PTEN and provide further data addressing the set of proteins that interact with this important tumour suppressor.

HrpA anchors meningococci to the dynein motor and affects the balance between apoptosis and pyroptosis

BACKGROUND

In Neisseria meningitidis the HrpA/HrpB two-partner secretion system (TPS) was implicated in diverse functions including meningococcal competition, biofilm formation, adherence to epithelial cells, intracellular survival and vacuolar escape. These diverse functions could be attributed to distinct domains of secreted HrpA.

METHODS

A yeast two-hybrid screening, in vitro pull-down assay and immunofluorescence microscopy experiments were used to investigate the interaction between HrpA and the dynein light-chain, Tctex-type 1 (DYNLT1). In silico modeling was used to analyze HrpA structure. Western blot analysis was used to investigate apoptotic and pyroptotic markers.

RESULTS

The HrpA carboxy-terminal region acts as a manganese-dependent cell lysin, while the results of a yeast two-hybrid screening demonstrated that the HrpA middle region has the ability to bind the dynein light-chain, Tctex-type 1 (DYNLT1). This interaction was confirmed by in vitro pull-down assay and immunofluorescence microscopy experiments showing co-localization of N. meningitidis with DYNLT1 in infected epithelial cells. In silico modeling revealed that the HrpA-M interface interacting with the DYNLT1 has similarity with capsid proteins of neurotropic viruses that interact with the DYNLT1. Indeed, we found that HrpA plays a key role in infection of and meningococcal trafficking within neuronal cells, and is implicated in the modulation of the balance between apoptosis and pyroptosis.

CONCLUSIONS

Our findings revealed that N. meningitidis is able to effectively infect and survive in neuronal cells, and that this ability is dependent on HrpA, which establishes a direct protein-protein interaction with DYNLTI in these cells, suggesting that the HrpA interaction with dynein could be fundamental for N. meningitidis spreading inside the neurons. Moreover, we found that the balance between apoptotic and pyroptotic pathways is heavily affected by HrpA.

Split Chloramphenicol Acetyl-Transferase Assay Reveals Self-Ubiquitylation-Dependent Regulation of UBE3B

Split reporter protein-based genetic section systems are widely used to identify and characterize protein-protein interactions (PPI). The assembly of split markers that antagonize toxins, rather than required for synthesis of missing metabolites, facilitates the seeding of high density of cells and selective growth. Here we present a newly developed split chloramphenicol acetyltransferase (split-CAT) -based genetic selection system. The N terminus fragment of CAT is fused downstream of the protein of interest and the C terminus fragment is tethered upstream to its postulated partner. We demonstrate the system's advantages for the study of PPIs. Moreover, we show that co-expression of a functional ubiquitylation cascade where the target and ubiquitin are tethered to the split-CAT fragments results in ubiquitylation-dependent selective growth. Since proteins do not have to be purified from the bacteria and due to the high sensitivity of the split-CAT reporter, detection of challenging protein cascades and post-translation modifications is enabled. In addition, we demonstrate that the split-CAT system responds to small molecule inhibitors and molecular glues (GLUTACs). The absence of ubiquitylation-dependent degradation and deubiquitylation in E. coli significantly simplify the interpretation of the results. We harnessed the developed system to demonstrate that like NEDD4, UBE3B also undergoes self-ubiquitylation-dependent inactivation. We show that self-ubiquitylation of UBE3B on K665 induces oligomerization and inactivation in yeast and mammalian cells respectively. Finally, we showcase the advantages of split-CAT in the study of human diseases by demonstrating that mutations in UBE3B that cause Kaufman oculocerebrofacial syndrome exhibit clear E. coli growth phenotypes.

Mapping, Structure and Modulation of PPI

Because of the key relevance of protein–protein interactions (PPI) in diseases, the modulation of protein-protein complexes is of relevant clinical significance. The successful design of binding compounds modulating PPI requires a detailed knowledge of the involved protein-protein system at molecular level, and investigation of the structural motifs that drive the association of the proteins at the recognition interface. These elements represent hot spots of the protein binding free energy, define the complex lifetime and possible modulation strategies. Here, we review the advanced technologies used to map the PPI involved in human diseases, to investigate the structure-function features of protein complexes, and to discover effective ligands that modulate the PPI for therapeutic intervention.

Molecular architecture of postsynaptic Interactomes

The postsynaptic density (PSD) plays an essential role in the organization of the synaptic signaling machinery. It contains a set of core scaffolding proteins that provide the backbone to PSD protein-protein interaction networks (PINs). These core scaffolding proteins can be seen as three principal layers classified by protein family, with DLG proteins being at the top, SHANKs along the bottom, and DLGAPs connecting the two layers. Early studies utilizing yeast two hybrid enabled the identification of direct protein-protein interactions (PPIs) within the multiple layers of scaffolding proteins. More recently, mass-spectrometry has allowed the characterization of whole interactomes within the PSD. This expansion of knowledge has further solidified the centrality of core scaffolding family members within synaptic PINs and provided context for their role in neuronal development and synaptic function. Here, we discuss the scaffolding machinery of the PSD, their essential functions in the organization of synaptic PINs, along with their relationship to neuronal processes found to be impaired in complex brain disorders.

Split Intein-Mediated Protein Ligation for detecting protein-protein interactions and their inhibition

Here, to overcome many limitations accompanying current available methods to detect protein-protein interactions (PPIs), we develop a live cell method called Split Intein-Mediated Protein Ligation (SIMPL). In this approach, bait and prey proteins are respectively fused to an intein N-terminal fragment (IN) and C-terminal fragment (IC) derived from a re-engineered split intein GP41-1. The bait/prey binding reconstitutes the intein, which splices the bait and prey peptides into a single intact protein that can be detected by regular protein detection methods such as Western blot analysis and ELISA, serving as readouts of PPIs. The method is robust and can be applied not only in mammalian cell lines but in animal models such as C. elegans. SIMPL demonstrates high sensitivity and specificity, and enables exploration of PPIs in different cellular compartments and tracking of kinetic interactions. Additionally, we establish a SIMPL ELISA platform that enables high-throughput screening of PPIs and their inhibitors.

Protein-protein interactions are fundamental to the regulation of protein activity and cellular phyisology. Here the authors present Split Intein-Mediated Protein Ligation, which uses bait and prey proteins fused to intein fragments to generate single intact proteins upon interaction.

Highly Modular Protein Micropatterning Sheds Light on the Role of Clathrin-Mediated Endocytosis for the Quantitative Analysis of Protein-Protein Interactions in Live Cells

Protein micropatterning is a powerful tool for spatial arrangement of transmembrane and intracellular proteins in living cells. The restriction of one interaction partner (the bait, e.g., the receptor) in regular micropatterns within the plasma membrane and the monitoring of the lateral distribution of the bait’s interaction partner (the prey, e.g., the cytosolic downstream molecule) enables the in-depth examination of protein-protein interactions in a live cell context. This study reports on potential pitfalls and difficulties in data interpretation based on the enrichment of clathrin, which is a protein essential for clathrin-mediated receptor endocytosis. Using a highly modular micropatterning approach based on large-area micro-contact printing and streptavidin-biotin-mediated surface functionalization, clathrin was found to form internalization hotspots within the patterned areas, which, potentially, leads to unspecific bait/prey protein co-recruitment. We discuss the consequences of clathrin-coated pit formation on the quantitative analysis of relevant protein-protein interactions, describe controls and strategies to prevent the misinterpretation of data, and show that the use of DNA-based linker systems can lead to the improvement of the technical platform.

Predicting Protein-Protein Interactions Using SPRINT

Understanding protein-protein interactions (PPIs) is vital to reveal the function mechanisms in cells. Thus, predicting and identifying PPIs is one of the fundamental problems in system biology. Various high-throughput experimental and computation methods have been developed to predict PPIs. Here, we provide a straightforward guide of using the program "SPRINT" to predict the PPIs on an interactome level in an organism. First, some installation guides and input file formats are described. Then, the commands and options to run SPRINT are discussed with examples. In addition, some notes on possible extended installation and usage of SPRINT are given.

Towards deorphanizing G protein-coupled receptors of Schistosoma mansoni using the MALAR yeast two-hybrid system

Schistosomiasis is an acute and chronic disease caused by parasitic worms of the genus Schistosoma. Treatment is solely dependent on praziquantel. In the face of the worldwide dimension, projects have been initiated to develop new chemotherapies. Due to their proven druggability, G protein-coupled receptors (GPCRs) are promising targets for anthelmintics. However, to identify candidate receptors, a deeper understanding of GPCR signalling in schistosome biology is essential. Comparative transcriptomics of paired and unpaired worms and their gonads revealed 59 differentially regulated GPCR-coding genes putatively involved in neuronal processes. In general, the diversity among GPCRs and their integral membrane topology make it difficult to characterize and deorphanize these receptors. To overcome existing limitations, we performed a pilot approach and utilized the innovative Membrane-Anchored Ligand And Receptor yeast two-hybrid system (MALAR-Y2H) to associate potential neuropeptide ligands with their cognate receptors. Here, we demonstrated the ability to express full-length GPCRs of Schistosoma mansoni in a heterologous yeast-based system. Additionally, we localized GPCRs and chimeras of neuropeptides fused to the WBP1 transmembrane domain of yeast to the plasma membrane of yeast cells. Reporter gene assays indicated ligand-receptor binding, which allowed us to identify certain neuropeptides as potential ligands for two GPCRs, which had been found before to be differentially expressed in schistosomes in a pairing-dependent manner. Thus, the MALAR-Y2H system appears suitable to unravel schistosome GPCR–ligand interactions. Besides its relevance for understanding schistosome biology, identifying and characterizing GPCR–ligand interaction will also contribute to applied research aspects.

Applications of in Silico Methods for Design and Development of Drugs Targeting Protein-Protein Interactions

BACKGROUND

Identification of Protein-Protein Interactions (PPIs) is a major challenge in modern molecular biology and biochemistry research, due to the unquestionable role of proteins in cells, biological process and pathological states. Over the past decade, the PPIs have evolved from being considered a highly challenging field of research to being investigated and examined as targets for pharmacological intervention.

OBJECTIVE

Comprehension of protein interactions is crucial to known how proteins come together to build signalling pathways, to carry out their functions, or to cause diseases, when deregulated. Multiplicity and great amount of PPIs structures offer a huge number of new and potential targets for the treatment of different diseases.

METHODS

Computational techniques are becoming predominant in PPIs studies for their effectiveness, flexibility, accuracy and cost. As a matter of fact, there are effective in silico approaches which are able to identify PPIs and PPI site. Such methods for computational target prediction have been developed through molecular descriptors and data-mining procedures.

RESULTS

In this review, we present different types of interactions between protein-protein and the application of in silico methods for design and development of drugs targeting PPIs. We described computational approaches for the identification of possible targets on protein surface and to detect of stimulator/ inhibitor molecules.

CONCLUSION

A deeper study of the most recent bioinformatics methodologies for PPIs studies is vital for a better understanding of protein complexes and for discover new potential PPI modulators in therapeutic intervention.

Protein-Protein Interactions of Phosphodiesterases

BACKGROUND

Phosphodiesterases (PDEs) are enzymes that play a key role in terminating cyclic nucleotides signalling by catalysing the hydrolysis of 3', 5'- cyclic adenosine monophosphate (cAMP) and/or 3', 5' cyclic guanosine monophosphate (cGMP), the second messengers within the cell that transport the signals produced by extracellular signalling molecules which are unable to get into the cells. However, PDEs are proteins which do not operate alone but in complexes that made up of a many proteins.

OBJECTIVE

This review highlights some of the general characteristics of PDEs and focuses mainly on the Protein-Protein Interactions (PPIs) of selected PDE enzymes. The objective is to review the role of PPIs in the specific mechanism for activation and thereby regulation of certain biological functions of PDEs.

METHODS

The article discusses some of the PPIs of selected PDEs as reported in recent scientific literature. These interactions are critical for understanding the biological role of the target PDE.

RESULTS

The PPIs have shown that each PDE has a specific mechanism for activation and thereby regulation a certain biological function.

CONCLUSION

Targeting of PDEs to specific regions of the cell is based on the interaction with other proteins where each PDE enzyme binds with specific protein(s) via PPIs.

Four novel interaction partners demonstrate diverse modulatory effects on voltage-gated CaV2.2 Ca2+ channels

Voltage-gated Ca²⁺ channels are embedded in a network of protein interactions that are fundamental for channel function and modulation. Different strategies such as high-resolution quantitative MS analyses and yeast-two hybrid screens have been used to uncover these Ca²⁺ channel nanodomains. We applied the yeast split-ubiquitin system with its specific advantages to search for interaction partners of the Ca_V2.2 Ca²⁺ channel and identified four proteins: reticulon 1 (RTN1), member 1 of solute carrier family 38 (SLC38), prostaglandin D2 synthase (PTGDS) and transmembrane protein 223 (TMEM223). Interactions were verified using the yeast split-ubiquitin system and narrowed down to Ca_V2.2 domain IV. Colocalization studies using fluorescent constructs demonstrated defined regions of subcellular localization. Detailed electrophysiological studies revealed that coexpression of RTN1 modulated Ca_V2.2 channels only to a minor extent. SLC38 accelerated the cumulative current inactivation during a high-frequency train of brief depolarizing pulses. As neurons expressing Ca_V2.2 channels were exposed to high-frequency bursts under physiological conditions, observed regulation may have a negative modulatory effect on transmitter release. Coexpression of PTGDS significantly lowered the average current density and slowed the kinetics of cumulative current inactivation. Since the latter effect was not significant, it may only partly compensate the first one under physiological conditions. Expression of TMEM223 lowered the average current density, accelerated the kinetics of cumulative current inactivation and slowed the kinetics of recovery from inactivation. Therefore, TMEM223 and, to a lesser extent, PTGDS, may negatively modulate Ca²⁺ entry required for transmitter release and/or for dendritic plasticity under physiological conditions.

High-Throughput Protein-Protein Interaction Assays Using Tripartite Split-GFP Complementation

Most cellular processes are driven by complex protein-protein interaction networks. Identifying key players and characterizing their interactions at the cellular and molecular level is of key importance to understand biochemical mechanisms that control cellular responses. Here, we detail a protocol for monitoring protein-protein interactions in E. coli cells or in cell extracts using a tripartite split-GFP system comprised of a protein interaction detector fragment (GFP ß-strands 1 through 9 or GFP1-9) and small tagging fragments of GFP ß-strands 10 (GFP10) and 11 (GFP11). Interaction of bait and prey proteins fused to GFP10 and GFP11 tether the small GFP fragments, allowing self-association with GFP1-9. In this scenario, fluorescence intensity of the reconstituted GFP is correlated with the strength of interaction.

Interactome-Seq: A Protocol for Domainome Library Construction, Validation and Selection by Phage Display and Next Generation Sequencing

Folding reporters are proteins with easily identifiable phenotypes, such as antibiotic resistance, whose folding and function is compromised when fused to poorly folding proteins or random open reading frames. We have developed a strategy where, by using TEM-1 β-lactamase (the enzyme conferring ampicillin resistance) on a genomic scale, we can select collections of correctly folded protein domains from the coding portion of the DNA of any intronless genome. The protein fragments obtained by this approach, the so called "domainome", will be well expressed and soluble, making them suitable for structural/functional studies. By cloning and displaying the "domainome" directly in a phage display system, we have showed that it is possible to select specific protein domains with the desired binding properties (e.g., to other proteins or to antibodies), thus providing essential experimental information for gene annotation or antigen identification. The identification of the most enriched clones in a selected polyclonal population can be achieved by using novel next-generation sequencing technologies (NGS). For these reasons, we introduce deep sequencing analysis of the library itself and the selection outputs to provide complete information on diversity, abundance and precise mapping of each of the selected fragment. The protocols presented here show the key steps for library construction, characterization, and validation.

Multiple functionalities of molecular chaperones revealed through systematic mapping of their interaction networks

Chaperones are a highly interactive group of proteins that function globally in many cellular processes involved in maintaining protein homeostasis. Traditional biochemical assays typically do not provide a complete view of the intricate networks through which chaperones collaborate to promote proteostasis. Recent advances in high-throughput systematic analyses of chaperone interactions have uncovered that chaperones display a remarkable cooperativity in their interactions with numerous client proteins. This cooperativity has been found to be a fundamental aspect of a properly functioning cell. Aberrant formation or improper regulation of these interactions can easily lead to disease states. Herein, we provide an overview of the use of large-scale interaction assays, whether physical (protein-protein) or genetic (epistatic), to study chaperone interaction networks. Importantly, we discuss the ongoing need for such studies to determine the mechanisms by which protein homeostasis is controlled in the cell.

Protein-protein interactions: detection, reliability assessment and applications

Protein-protein interactions (PPIs) participate in all important biological processes in living organisms, such as catalyzing metabolic reactions, DNA replication, DNA transcription, responding to stimuli and transporting molecules from one location to another. To reveal the function mechanisms in cells, it is important to identify PPIs that take place in the living organism. A large number of PPIs have been discovered by high-throughput experiments and computational methods. However, false-positive PPIs have been introduced too. Therefore, to obtain reliable PPIs, many computational methods have been proposed. Generally, these methods can be classified into two categories. One category includes the methods that are designed to determine new reliable PPIs. The other one is designed to assess the reliability of existing PPIs and filter out the unreliable ones. In this article, we review the two kinds of methods for detecting reliable PPIs, and then focus on evaluating the performance of some of these typical methods. Later on, we also enumerate several PPI network-based applications with taking a reliability assessment of the PPI data into consideration. Finally, we will discuss the challenges for obtaining reliable PPIs and future directions of the construction of reliable PPI networks. Our research will provide readers some guidance for choosing appropriate methods and features for obtaining reliable PPIs.

The computational prediction of protein assemblies

The function of proteins in the cell is almost always mediated by their interaction with different partners, including other proteins, nucleic acids or small organic molecules. The ability of identifying all of them is an essential step in our quest for understanding life at the molecular level. The inference of the protein complex composition and of its molecular details can also provide relevant clues for the development and the design of drugs. In this short review, I will discuss the computational aspects of the analysis and prediction of protein-protein assemblies and discuss some of the most recent developments as seen in the last Critical Assessment of Techniques for Protein Structure Prediction (CASP) experiment.

Protein complex analysis: From raw protein lists to protein interaction networks

The elucidation of molecular interaction networks is one of the pivotal challenges in the study of biology. Affinity purification-mass spectrometry and other co-complex methods have become widely employed experimental techniques to identify protein complexes. These techniques typically suffer from a high number of false negatives and false positive contaminants due to technical shortcomings and purification biases. To support a diverse range of experimental designs and approaches, a large number of computational methods have been proposed to filter, infer and validate protein interaction networks from experimental pull-down MS data. Nevertheless, this expansion of available methods complicates the selection of the most optimal ones to support systems biology-driven knowledge extraction. In this review, we give an overview of the most commonly used computational methods to process and interpret co-complex results, and we discuss the issues and unsolved problems that still exist within the field. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 36:600-614, 2017.

Yeast-based assays for detecting protein-protein/drug interactions and their inhibitors

Understanding cellular processes at molecular levels in health and disease requires the knowledge of protein-protein interactions (PPIs). In line with this, identification of PPIs at genome-wide scale is highly valuable to understand how different cellular pathways are interconnected, and it eventually facilitates designing effective drugs against certain PPIs. Furthermore, investigating PPIs at a small laboratory scale for deciphering certain biochemical pathways has been demanded for years. In this regard, yeast two hybrid system (Y2HS) has proven an extremely useful tool to discover novel PPIs, while Y2HS derivatives and novel yeast-based assays are contributing significantly to identification of protein-drug/inhibitor interaction at both large- and small-scale set-ups. These methods have been evolving over time to provide more accurate, reproducible and quantitative results. Here we briefly describe different yeast-based assays for identification of various protein-protein/drug/inhibitor interactions and their specific applications, advantages, shortcomings, and improvements. The broad range of yeast-based assays facilitates application of the most suitable method(s) for each specific need.

Detecting Membrane Protein-protein Interactions Using the Mammalian Membrane Two-hybrid (MaMTH) Assay

Protein-protein interactions (PPIs) play an integral role in numerous cellular processes. Membrane protein interactions, in particular, are critical in cellular responses to stresses and stimuli, with dysfunction of these PPIs (e.g., due to aberrant expression and/or mutation of interaction partners) leading to a diverse array of pathological states. Exploration of the interaction space and dynamics of membrane proteins is difficult due to the limitations of current techniques used to study proteins in the biochemically complex environment of biological membranes. In the protocols below, we describe a newly developed membrane protein interaction assay called the Mammalian-Membrane Two-Hybrid (MaMTH), designed specifically for the detection of integral membrane PPIs in the context of living mammalian cells. Prior to using MaMTH, cell lines of interest are genetically modified to encode a reporter of choice. MaMTH "bait" and "prey" constructs of interest are also generated using Gateway cloning technology. The assay is then performed by co-transfection of baits and preys, with bait-prey interaction quantifiably assessed by way of a reporter signal (e.g., light (luciferase), fluorescence (GFP). © 2017 by John Wiley & Sons, Inc.

Development of a membrane-anchored ligand and receptor yeast two-hybrid system for ligand-receptor interaction identification

Identifying interactions between ligands and transmembrane receptors is crucial for understanding the endocrine system. However, the present approaches for this purpose are still not capable of high-throughput screening. In this report, a membrane-anchored ligand and receptor yeast two-hybrid (MALAR-Y2H) system was established. In the method, an extracellular ligand is linked with an intracellular split-ubiquitin reporter system via a chimeric transmembrane structure. Meanwhile, the prey proteins of transmembrane receptors are fused to the other half of the split-ubiquitin reporter system. The extracellular interaction of ligands and receptors can lead to the functional recovery of the ubiquitin reporter system in yeast, and eventually lead to the expression of report genes. Consequently, the system can be used to detect the interactions between extracellular ligands and their transmembrane receptors. To test the efficiency and universality of the method, interactions between several pairs of ligands and receptors of mouse were analyzed. The detecting results were shown to be thoroughly consistent with the present knowledge, indicating MALAR-Y2H can be utilized for such purpose with high precision, high efficiency and strong universality. The characteristics of the simple procedure and high-throughput potential make MALAR-Y2H a powerful platform to study protein-protein interaction networks between secreted proteins and transmembrane proteins.

Identification and function analysis of the host cell protein that interacted with Orf virus Bcl-2-like protein ORFV125

Orf virus (ORFV) causes contagious ecthyma, a non-systemic skin disease in sheep and goat. Bioinformatics analysis showed that ORFV125 has Bcl-2-like homologous domain and 3D structurally, it is generally known that Bcl-2 protein is known to be a key protein to control cell apoptosis. Maybe ORFV125 act as a Bcl-2-like manner to control cell apoptosis, but its exact function isn't very clear. So in this study, we use yeast two-hybrid system to identity the putative host cell protein interacting partners of ORFV125, and meanwhile using the data obtained from the Gene Ontology, Uniprot, and Kyoto Encyclopedia of Genes and Genomes databases to analysis the functions and pathways associated with them. Finally, five host proteins were shown to be interacted with ORFV125, including cytochrome b (cytb) gene, GUCY2C, BIRC5, GTF3C6 and SERBP1, we also found that BIRC5 has complex biological functions, can inhibit apoptosis, promote cell transformation and are involved in mitosis, and the interaction network of BIRC5 and ORFV125 were constructed. These findings provide a foundation to better understand the biology of the interactions between ORFV125 and the host proteins with which it directly interacts with and resultant downstream events.

Recombinant expression of backbone-cyclized polypeptides

Here we review the different biochemical approaches available for the expression of backbone-cyclized polypeptides, including peptides and proteins. These methods allow for the production of circular polypeptides either in vitro or in vivo using standard recombinant DNA expression techniques. Polypeptide circularization provides a valuable tool to study the effects of topology on protein stability and folding kinetics. Furthermore, having biosynthetic access to backbone-cyclized polypeptides makes the production of genetically encoded libraries of cyclic polypeptides possible. The production of such libraries, which was previously restricted to the domain of synthetic chemistry, now offers biologists access to highly diverse and stable molecular libraries that can be screened using high-throughput methods for the rapid selection of novel cyclic polypeptide sequences with new biological activities.

Live cell micropatterning reveals the dynamics of signaling complexes at the plasma membrane

The use of micropatterned surfaces that bind HaloTag fusion proteins allows spatial organization of plasma membrane proteins for efficient visualization and quantification of protein–protein interactions in live cells.

Interactions of proteins in the plasma membrane are notoriously challenging to study under physiological conditions. We report in this paper a generic approach for spatial organization of plasma membrane proteins into micropatterns as a tool for visualizing and quantifying interactions with extracellular, intracellular, and transmembrane proteins in live cells. Based on a protein-repellent poly(ethylene glycol) polymer brush, micropatterned surface functionalization with the HaloTag ligand for capturing HaloTag fusion proteins and RGD peptides promoting cell adhesion was devised. Efficient micropatterning of the type I interferon (IFN) receptor subunit IFNAR2 fused to the HaloTag was achieved, and highly specific IFN binding to the receptor was detected. The dynamics of this interaction could be quantified on the single molecule level, and IFN-induced receptor dimerization in micropatterns could be monitored. Assembly of active signaling complexes was confirmed by immunostaining of phosphorylated Janus family kinases, and the interaction dynamics of cytosolic effector proteins recruited to the receptor complex were unambiguously quantified by fluorescence recovery after photobleaching.

LlHSFA1, a novel heat stress transcription factor in lily (Lilium longiflorum), can interact with LlHSFA2 and enhance the thermotolerance of transgenic Arabidopsis thaliana

A heat stress transcription factor LlHSFA1 in lily and its relationship with LlHSFA2 was investigated, and its function in enhancing thermotolerance was confirmed by analyzing transgenic Arabidopsis thaliana overexpressed LlHSFA1. A large family of heat stress transcription factors that are involved in the heat stress response in plants can induce the expression of multiple genes related to thermotolerance including heat-shock proteins. In this study, a novel class A1 HSF named LlHSFA1 was isolated from leaves of lily (Lilium longiflorum cv. 'White Heaven') using the rapid amplification of cDNA ends technique. Analysis of the deduced amino acid sequence and construction of a phylogenetic tree showed that LlHSFA1 contained five critical domains and motifs and belonged to the A1 family of HSFs. Following the heat treatment of lily leaves, transcription of LlHSFA1 was induced to a varying extent, related to the time of measurement. The induced expression peak of LlHSFA1 occurred prior to that of LlHSFA2, during the early phase of heat stress. Following transient expression of LlHSFA1 in Nicotiana benthamiana, LlHSFA1 was found to be localized in both the nucleus and the cytoplasm. Analysis using bimolecular fluorescence complementation and a yeast two-hybrid assay demonstrated that LlHSFA1 could interact with LlHSFA2. Use of a yeast one-hybrid assay confirmed that LlHSFA1 had transcriptional activation activity. In transgenic Arabidopsis lines overexpressing LlHSFA1 under unstressed conditions, the expression of some putative target genes was up-regulated, in comparison with expression in wild-type plants, and furthermore, the thermotolerance of the transgenic lines was enhanced. Overall, LlHSFA1 was demonstrated to play an important role in the heat stress response of lily and to be a novel candidate gene for application in lily breeding, using genetic modification approaches.

Investigating protein-protein interactions in live cells using bioluminescence resonance energy transfer

Assays based on Bioluminescence Resonance Energy Transfer (BRET) provide a sensitive and reliable means to monitor protein-protein interactions in live cells. BRET is the non-radiative transfer of energy from a 'donor' luciferase enzyme to an 'acceptor' fluorescent protein. In the most common configuration of this assay, the donor is Renilla reniformis luciferase and the acceptor is Yellow Fluorescent Protein (YFP). Because the efficiency of energy transfer is strongly distance-dependent, observation of the BRET phenomenon requires that the donor and acceptor be in close proximity. To test for an interaction between two proteins of interest in cultured mammalian cells, one protein is expressed as a fusion with luciferase and the second as a fusion with YFP. An interaction between the two proteins of interest may bring the donor and acceptor sufficiently close for energy transfer to occur. Compared to other techniques for investigating protein-protein interactions, the BRET assay is sensitive, requires little hands-on time and few reagents, and is able to detect interactions which are weak, transient, or dependent on the biochemical environment found within a live cell. It is therefore an ideal approach for confirming putative interactions suggested by yeast two-hybrid or mass spectrometry proteomics studies, and in addition it is well-suited for mapping interacting regions, assessing the effect of post-translational modifications on protein-protein interactions, and evaluating the impact of mutations identified in patient DNA.

In silico prediction of protein-protein interactions in human macrophages

Background

Protein-protein interaction (PPI) network analyses are highly valuable in deciphering and understanding the intricate organisation of cellular functions. Nevertheless, the majority of available protein-protein interaction networks are context-less, i.e. without any reference to the spatial, temporal or physiological conditions in which the interactions may occur. In this work, we are proposing a protocol to infer the most likely protein-protein interaction (PPI) network in human macrophages.

Results

We integrated the PPI dataset from the Agile Protein Interaction DataAnalyzer (APID) with different meta-data to infer a contextualized macrophage-specific interactome using a combination of statistical methods. The obtained interactome is enriched in experimentally verified interactions and in proteins involved in macrophage-related biological processes (i.e. immune response activation, regulation of apoptosis). As a case study, we used the contextualized interactome to highlight the cellular processes induced upon Mycobacterium tuberculosis infection.

Conclusion

Our work confirms that contextualizing interactomes improves the biological significance of bioinformatic analyses. More specifically, studying such inferred network rather than focusing at the gene expression level only, is informative on the processes involved in the host response. Indeed, important immune features such as apoptosis are solely highlighted when the spotlight is on the protein interaction level.

Tetraspanin-13 modulates voltage-gated CaV2.2 Ca2+ channels

Integration of voltage-gated Ca(2+) channels in a network of protein-interactions is a crucial requirement for proper regulation of channel activity. In this study, we took advantage of the specific properties of the yeast split-ubiquitin system to search for and characterize so far unknown interaction partners of CaV2 Ca(2+) channels. We identified tetraspanin-13 (TSPAN-13) as an interaction partner of the α1 subunit of N-type CaV2.2, but not of P/Q-type CaV2.1 or L- and T-type Ca(2+) channels. Interaction could be located between domain IV of CaV2.2 and transmembrane segments S1 and S2 of TSPAN-13. Electrophysiological analysis revealed that TSPAN-13 specifically modulates the efficiency of coupling between voltage sensor activation and pore opening of the channel and accelerates the voltage-dependent activation and inactivation of the Ba(2+) current through CaV2.2. These data indicate that TSPAN-13 might regulate CaV2.2 Ca(2+) channel activity in defined synaptic membrane compartments and thereby influences transmitter release.

The Rab-interacting lysosomal protein (RILP) regulates vacuolar ATPase acting on the V1G1 subunit

RILP is a downstream effector of the Rab7 GTPase. GTP-bound Rab7 recruits RILP on endosomal membranes and, together, they control late endocytic traffic, phagosome and autophagosome maturation and are responsible for signaling receptor degradation. We have identified, using different approaches, the V1G1 subunit of the vacuolar ATPase (V-ATPase) as a RILP interacting protein. V1G1 is a component of the peripheral stalk and it is fundamental for correct V-ATPase assembly. We established that RILP regulates the recruitment of V1G1 subunit to late endosomal/lysosomal membranes but also controls V1G1 stability. Indeed, we demonstrated that V1G1 is ubiquitinated and that RILP is responsible for proteasomal degradation of V1G1. Furthermore, we demonstrated that alterations of V1G1 expression levels impair V-ATPase activity. Thus, our data demonstrate for the first time that RILP regulates the activity of the V-ATPase through the interaction with V1G1. Given the importance of V-ATPase in several cellular processes and human diseases, these data suggest that modulation of RILP activity could be used to control V-ATPase function.

Mass spectrometry for proteomics-based investigation

Within the past years, we have witnessed a great improvement in mass spectrometry (MS) and proteomics approaches in terms of instrumentation, protein fractionation, and bioinformatics. With the current technology, protein identification alone is no longer sufficient. Both scientists and clinicians want not only to identify proteins but also to identify the protein's posttranslational modifications (PTMs), protein isoforms, protein truncation, protein-protein interaction (PPI), and protein quantitation. Here, we describe the principle of MS and proteomics and strategies to identify proteins, protein's PTMs, protein isoforms, protein truncation, PPIs, and protein quantitation. We also discuss the strengths and weaknesses within this field. Finally, in our concluding remarks we assess the role of mass spectrometry and proteomics in scientific and clinical settings in the near future. This chapter provides an introduction and overview for subsequent chapters that will discuss specific MS proteomic methodologies and their application to specific medical conditions. Other chapters will also touch upon areas that expand beyond proteomics, such as lipidomics and metabolomics.

Replication of Plant Viruses

Viruses replicate using both their own genetic information and host cell components and machinery. The different genome types have different replication pathways which contain controls on linking the process with translation and movement around the cell as well as not compromising the infected cell. This chapter discusses the replication mechanisms, faults in replication and replication of viruses co-infecting cells.

Viruses replicate using both their own genetic information and host cell components and machinery. The different genome types have different replication pathways which contain controls on linking the process with translation and movement around the cell as well as not compromising the infected cell. This chapter discusses the replication mechanisms, faults in replication and replication of viruses coinfecting cells.

Application of genomics, proteomics and metabolomics in drug discovery, development and clinic

Genomics, proteomics and metabolomics are three areas that are routinely applied throughout the drug-development process as well as after a product enters the market. This review discusses all three 'omics, reporting on the key applications, techniques, recent advances and expectations of each. Genomics, mainly through the use of novel and next-generation sequencing techniques, has advanced areas of drug discovery and development through the comparative assessment of normal and diseased-state tissues, transcription and/or expression profiling, side-effect profiling, pharmacogenomics and the identification of biomarkers. Proteomics, through techniques including isotope coded affinity tags, stable isotopic labeling by amino acids in cell culture, isobaric tags for relative and absolute quantification, multidirectional protein identification technology, activity-based probes, protein/peptide arrays, phage displays and two-hybrid systems is utilized in multiple areas through the drug development pipeline including target and lead identification, compound optimization, throughout the clinical trials process and after market analysis. Metabolomics, although the most recent and least developed of the three 'omics considered in this review, provides a significant contribution to drug development through systems biology approaches. Already implemented to some degree in the drug-discovery industry and used in applications spanning target identification through to toxicological analysis, metabolic network understanding is essential in generating future discoveries.

The role of protein interactions in mediating essentiality and synthetic lethality

Genes are characterized as essential if their knockout is associated with a lethal phenotype, and these "essential genes" play a central role in biological function. In addition, some genes are only essential when deleted in pairs, a phenomenon known as synthetic lethality. Here we consider genes displaying synthetic lethality as "essential pairs" of genes, and analyze the properties of yeast essential genes and synthetic lethal pairs together. As gene duplication initially produces an identical pair or sets of genes, it is often invoked as an explanation for synthetic lethality. However, we find that duplication explains only a minority of cases of synthetic lethality. Similarly, disruption of metabolic pathways leads to relatively few examples of synthetic lethality. By contrast, the vast majority of synthetic lethal gene pairs code for proteins with related functions that share interaction partners. We also find that essential genes and synthetic lethal pairs cluster in the protein-protein interaction network. These results suggest that synthetic lethality is strongly dependent on the formation of protein-protein interactions. Compensation by duplicates does not usually occur mainly because the genes involved are recent duplicates, but is more commonly due to functional similarity that permits preservation of essential protein complexes. This unified view, combining genes that are individually essential with those that form essential pairs, suggests that essentiality is a feature of physical interactions between proteins protein-protein interactions, rather than being inherent in gene and protein products themselves.

The evolutionary dynamics of protein-protein interaction networks inferred from the reconstruction of ancient networks

Cellular functions are based on the complex interplay of proteins, therefore the structure and dynamics of these protein-protein interaction (PPI) networks are the key to the functional understanding of cells. In the last years, large-scale PPI networks of several model organisms were investigated. A number of theoretical models have been developed to explain both the network formation and the current structure. Favored are models based on duplication and divergence of genes, as they most closely represent the biological foundation of network evolution. However, studies are often based on simulated instead of empirical data or they cover only single organisms. Methodological improvements now allow the analysis of PPI networks of multiple organisms simultaneously as well as the direct modeling of ancestral networks. This provides the opportunity to challenge existing assumptions on network evolution. We utilized present-day PPI networks from integrated datasets of seven model organisms and developed a theoretical and bioinformatic framework for studying the evolutionary dynamics of PPI networks. A novel filtering approach using percolation analysis was developed to remove low confidence interactions based on topological constraints. We then reconstructed the ancient PPI networks of different ancestors, for which the ancestral proteomes, as well as the ancestral interactions, were inferred. Ancestral proteins were reconstructed using orthologous groups on different evolutionary levels. A stochastic approach, using the duplication-divergence model, was developed for estimating the probabilities of ancient interactions from today's PPI networks. The growth rates for nodes, edges, sizes and modularities of the networks indicate multiplicative growth and are consistent with the results from independent static analysis. Our results support the duplication-divergence model of evolution and indicate fractality and multiplicative growth as general properties of the PPI network structure and dynamics.

Identification of protein interactions involved in cellular signaling

Protein-protein interactions drive biological processes. They are critical for all intra- and extracellular functions, and the technologies to analyze them are widely applied throughout the various fields of biological sciences. This study takes an in-depth view of some common principles of cellular regulation and provides a detailed account of approaches required to comprehensively map signaling protein-protein interactions in any particular cellular system or condition. We provide a critical review of the benefits and disadvantages of the yeast two-hybrid method and affinity purification coupled with mass spectrometric procedures for identification of signaling protein-protein interactions. In particular, we emphasize the quantitative and qualitative differences between tandem affinity and one-step purification (such as FLAG and Strep tag) methods. Although applicable to all types of interaction studies, a special section is devoted in this review to aspects that should be considered when attempting to identify signaling protein interactions that often are transient and weak by nature. Finally, we discuss shotgun and quantitative information that can be gleaned by MS-coupled methods for analysis of multiprotein complexes.

Applications of Mass Spectrometry in Proteomics

Characterisation of proteins and whole proteomes can provide a foundation to our understanding of physiological and pathological states and biological diseases or disorders. Constant development of more reliable and accurate mass spectrometry (MS) instruments and techniques has allowed for better identification and quantification of the thousands of proteins involved in basic physiological processes. Therefore, MS-based proteomics has been widely applied to the analysis of biological samples and has greatly contributed to our understanding of protein functions, interactions, and dynamics, advancing our knowledge of cellular processes as well as the physiology and pathology of the human body. This review will discuss current proteomic approaches for protein identification and characterisation, including post-translational modification (PTM) analysis and quantitative proteomics as well as investigation of protein–protein interactions (PPIs).

Infectomics Screening for Novel Antiviral Drug Targets

Preclinical Research

Copyright 2012 Wiley-Liss, Inc., A Wiley Company

Infectomics, a novel way to globally and comprehensively understand the interactions between microbial pathogens and their hosts, has significantly expanded understanding of the microbial infections. The infectomics view of viral–host interactions on the viral perspective principally focuses on gene acquisition, deletion, and point mutation, while traditional antiviral drug discovery concentrates on viral encoding proteins. Recently, high‐throughput technologies, such as mass spectrometry‐based proteomics, activity‐based protein profiling, microarray analysis, yeast two‐hybrid assay, small interfering RNA screening, and micro RNA profiling, have been gradually employed in the research of virus–host interactions. Besides, signaling pathways and cellular processes involved in viral–host interactions provide new insights of infectomics in antiviral drug discovery. In this review, we summarize related infectomics approaches in the studies of virus–host interactions, which shed light on the development of novel antiviral drug targets screening.

Mass spectrometry-based proteomics and network biology

In the life sciences, a new paradigm is emerging that places networks of interacting molecules between genotype and phenotype. These networks are dynamically modulated by a multitude of factors, and the properties emerging from the network as a whole determine observable phenotypes. This paradigm is usually referred to as systems biology, network biology, or integrative biology. Mass spectrometry (MS)-based proteomics is a central life science technology that has realized great progress toward the identification, quantification, and characterization of the proteins that constitute a proteome. Here, we review how MS-based proteomics has been applied to network biology to identify the nodes and edges of biological networks, to detect and quantify perturbation-induced network changes, and to correlate dynamic network rewiring with the cellular phenotype. We discuss future directions for MS-based proteomics within the network biology paradigm.

Protein-protein interaction networks: unraveling the wiring of molecular machines within the cell

Mapping and understanding of the protein interaction networks with their key modules and hubs can provide deeper insights into the molecular machinery underlying complex phenotypes. In this article, we present the basic characteristics and definitions of protein networks, starting with a distinction of the different types of associations between proteins. We focus the review on protein-protein interactions (PPIs), a subset of associations defined as physical contacts between proteins that occur by selective molecular docking in a particular biological context. We present such definition as opposed to other types of protein associations derived from regulatory, genetic, structural or functional relations. To determine PPIs, a variety of binary and co-complex methods exist; however, not all the technologies provide the same information and data quality. A way of increasing confidence in a given protein interaction is to integrate orthogonal experimental evidences. The use of several complementary methods testing each single interaction assesses the accuracy of PPI data and tries to minimize the occurrence of false interactions. Following this approach there have been important efforts to unify primary databases of experimentally proven PPIs into integrated databases. These meta-databases provide a measure of the confidence of interactions based on the number of experimental proofs that report them. As a conclusion, we can state that integrated information allows the building of more reliable interaction networks. Identification of communities, cliques, modules and hubs by analysing the topological parameters and graph properties of the protein networks allows the discovery of central/critical nodes, which are candidates to regulate cellular flux and dynamics.

Virtual interactomics of proteins from biochemical standpoint

Virtual interactomics represents a rapidly developing scientific area on the boundary line of bioinformatics and interactomics. Protein-related virtual interactomics then comprises instrumental tools for prediction, simulation, and networking of the majority of interactions important for structural and individual reproduction, differentiation, recognition, signaling, regulation, and metabolic pathways of cells and organisms. Here, we describe the main areas of virtual protein interactomics, that is, structurally based comparative analysis and prediction of functionally important interacting sites, mimotope-assisted and combined epitope prediction, molecular (protein) docking studies, and investigation of protein interaction networks. Detailed information about some interesting methodological approaches and online accessible programs or databases is displayed in our tables. Considerable part of the text deals with the searches for common conserved or functionally convergent protein regions and subgraphs of conserved interaction networks, new outstanding trends and clinically interesting results. In agreement with the presented data and relationships, virtual interactomic tools improve our scientific knowledge, help us to formulate working hypotheses, and they frequently also mediate variously important in silico simulations.

The Cross-and-Capture system: a versatile tool in yeast proteomics

High-throughput technologies such as affinity purification and yeast two-hybrid (Y2H) screening have been applied to explore protein-protein interactions (PPIs) in the model organism Saccharomyces cerevisiae. The "Cross-and-Capture" system is an alternative approach for an assessment of PPIs using two arrayed collections of differentially tagged yeast strains. In its current implementation, Cross-and-Capture encompasses ∼500 endogenously tagged yeast proteins, predominantly with roles in DNA metabolism and maintenance. The tagged arrays can also serve other purposes in yeast proteomics, such as monitoring of protein expression and the detection of posttranslational protein modifications. In this article, I summarize the development of this tool and describe its application to detect protein complexes and to screen for novel PPIs.

ORF phage display to identify cellular proteins with different functions

Open reading frame (ORF) phage display is a new branch of phage display aimed at improving its efficiency to identify cellular proteins with specific binding or functional activities. Despite the success of phage display with antibody libraries and random peptide libraries, phage display with cDNA libraries of cellular proteins identifies a high percentage of non-ORF clones encoding unnatural short peptides with minimal biological implications. This is mainly because of the uncontrollable reading frames of cellular proteins in conventional cDNA libraries. ORF phage display solves this problem by eliminating non-ORF clones to generate ORF cDNA libraries. Here I summarize the procedures of ORF phage display, discuss the factors influencing its efficiency, present examples of its versatile applications, and highlight evidence of its capability of identifying biologically relevant cellular proteins. ORF phage display coupled with different selection strategies is capable of delineating diverse functions of cellular proteins with unique advantages.