An evaluation of in vitro protein-protein interaction techniques: assessing contaminating background proteins

Determination of protein-protein interactions is an important component in assigning function and discerning the biological relevance of proteins within a broader cellular context. In vitro protein-protein interaction methodologies, including affinity chromatography, coimmunoprecipitation, and newer approaches such as protein chip arrays, hold much promise in the detection of protein interactions, particularly in well-characterized organisms with sequenced genomes. However, each of these approaches attracts certain background proteins that can thwart detection and identification of true interactors. In addition, recombinant proteins expressed in Escherichia coli are also extensively used to assess protein-protein interactions, and background proteins in these isolates can thus contaminate interaction studies. Rigorous validation of a true interaction thus requires not only that an interaction be found by alternate techniques, but more importantly that researchers be aware of and control for matrix/support dependence. Here, we evaluate these methods for proteins interacting with DmsD (an E. coli redox enzyme maturation protein chaperone), in vitro, using E. coli subcellular fractions as prey sources. We compare and contrast the various in vitro interaction methods to identify some of the background proteins and protein profiles that are inherent to each of the methods in an E. coli system.     

Identification of binary interactions between human cytomegalovirus virion proteins

Human cytomegalovirus (HCMV) virions are composed of a DNA-containing nucleocapsid surrounded by a tegument layer and host-derived lipid envelope studded with virally encoded glycoproteins. These complex virions are estimated to be composed of more than 50 viral proteins. Assembly of HCMV virions is poorly understood, especially with respect to acquisition of the tegument; however, it is thought to involve the stepwise addition of virion components through protein-protein interactions. We sought to identify interactions among HCMV virion proteins using yeast two-hybrid analysis. Using 33 known capsid and tegument proteins, we tested 1,089 pairwise combinations for binary interaction in the two-hybrid assay. We identified 24 interactions among HCMV virion proteins, including 13 novel interactions among tegument proteins and one novel interaction between capsid proteins. Several of these novel interactions were confirmed by coimmunoprecipitation of protein complexes from transfected cells. In addition, we demonstrate three of these interactions in the context of HCMV infection. This study reveals several new protein-protein interactions among HCMV tegument proteins, some of which are likely important for HCMV replication and pathogenesis.     

Construction of reliable protein-protein interaction networks with a new interaction generality measure

MOTIVATION: Recent screening techniques have made large amounts of protein-protein interaction data available, from which biologically important information such as the function of uncharacterized proteins, the existence of novel protein complexes, and novel signal-transduction pathways can be discovered. However, experimental data on protein interactions contain many false positives, making these discoveries difficult. Therefore computational methods of assessing the reliability of each candidate protein-protein interaction are urgently needed. RESULTS: We developed a new 'interaction generality' measure (IG2) to assess the reliability of protein-protein interactions using only the topological properties of their interaction-network structure. Using yeast protein-protein interaction data, we showed that reliable protein-protein interactions had significantly lower IG2 values than less-reliable interactions, suggesting that IG2 values can be used to evaluate and filter interaction data to enable the construction of reliable protein-protein interaction networks.     

Protein-protein interactions: methods for detection and analysis.

The function and activity of a protein are often modulated by other proteins with which it interacts. This review is intended as a practical guide to the analysis of such protein-protein interactions. We discuss biochemical methods such as protein affinity chromatography, affinity blotting, coimmunoprecipitation, and cross-linking; molecular biological methods such as protein probing, the two-hybrid system, and phage display: and genetic methods such as the isolation of extragenic suppressors, synthetic mutants, and unlinked noncomplementing mutants. We next describe how binding affinities can be evaluated by techniques including protein affinity chromatography, sedimentation, gel filtration, fluorescence methods, solid-phase sampling of equilibrium solutions, and surface plasmon resonance. Finally, three examples of well-characterized domains involved in multiple protein-protein interactions are examined. The emphasis of the discussion is on variations in the approaches, concerns in evaluating the results, and advantages and disadvantages of the techniques.     

Protein interaction screening by quantitative immunoprecipitation combined with knockdown (QUICK)

Present screening methods for protein-protein interactions (PPIs) rely on the overexpression of artificial fusion proteins, making it difficult to assess in vivo relevance. Here we combine stable isotope labeling with amino acids in cell culture (SILAC), RNA interference (RNAi), coimmunoprecipitation and quantitative mass-spectrometry analysis to detect cellular interaction partners of endogenous proteins in mammalian cells with very high confidence. We used this screen to identify interaction partners of beta-catenin and Cbl.     

Coevolution study of mitochondria respiratory chain proteins: toward the understanding of protein--protein interaction

Coevolution can be seen as the interdependency between evolutionary histories. In the context of protein evolution, functional correlation proteins are ever-present coordinated evolutionary characters without disruption of organismal integrity. As to complex system, there are two forms of protein-protein interactions in vivo, which refer to inter-complex interaction and intra-complex interaction. In this paper, we studied the difference of coevolution characters between inter-complex interaction and intra-complex interaction using "Mirror tree" method on the respiratory chain (RC) proteins. We divided the correlation coefficients of every pairwise RC proteins into two groups corresponding to the binary protein-protein interaction in intra-complex and the binary protein-protein interaction in inter-complex, respectively. A dramatical discrepancy is detected between the coevolution characters of the two sets of protein interactions (Wilcoxon test, p-value = 4.4 x 10-6). Our finding reveals some critical information on coevolutionary study and assists the mechanical investigation of protein-protein interaction.Furthermore, the results also provide some unique clue for supramolecular organization of protein complexes in the mitochondrial inner membrane. More detailed binding sites map and genome information of nuclear encoded RC proteins will be extraordinary valuable for the further mitochondria dynamics study.     

基于质谱技术的蛋白质互作研究进展

蛋白质作为生命活动的执行者,其功能往往体现在与其他蛋白质的相互作用中,研究蛋白-蛋白相互作用对于人们深入了解和预防传染病、靶向治疗多基因疾病、阐明蛋白质的分子作用机制及各种复杂的生命现象具有重要意义。目前,有多种技术被用来研究蛋白间的相互作用,研究难点在于实时捕获瞬时或弱蛋白质间的相互作用,质谱技术（mass spectrometry, MS）可在某种程度上解决该难点。由于质谱技术可研究简单的蛋白质复合物再到大规模的蛋白质组实验,基于质谱技术研究蛋白质间相互作用被越来越多地应用于科学研究中。综述了蛋白质间相互作用检测方法的研究进展,重点介绍了氢氘交换质谱法和化学交联质谱法研究蛋白质间相互作用的优缺点及其应用,最后对基于质谱技术研究蛋白质间相互作用进行了总结与展望,以期为深入开展相关研究提供借鉴。     

Protein microarrays, biosensors, and cell-based methods for secretome-wide extracellular protein-protein interaction mapping

Approximately one quarter of all human genes encode proteins that function in the extracellular space or serve to bridge the extracellular and intracellular environments. Physical associations between these secretome proteins serve to regulate a wide range of biological activities and consequently represent important therapeutic targets. Moreover, some extracellular proteins are targeted by pathogens to allow host access or immune evasion. Despite the importance of extracellular protein-protein interactions, our knowledge in this area has remained sparse. Weak affinities and low abundance have often hindered efforts to identify these interactions using traditional methods such as biochemical purification and cDNA library expression cloning. Moreover, current large-scale protein-protein interaction mapping techniques largely under represent extracellular protein-protein interactions. This review highlights emerging biosensor and protein microarray technology, along with more traditional cell-based techniques, that are compatible with secretome-wide screens for extracellular protein-protein interaction discovery. A combination of these approaches will serve to rapidly expand our knowledge of the extracellular protein-protein interactome.     

Systematic identification of SH3 domain-mediated human protein-protein interactions by peptide array target screening

Systematic identification of direct protein-protein interactions is often hampered by difficulties in expressing and purifying the corresponding full-length proteins. By taking advantage of the modular nature of many regulatory proteins, we attempted to simplify protein-protein interactions to the corresponding domain-ligand recognition and employed peptide arrays to identify such binding events. A group of 12 Src homology (SH) 3 domains from eight human proteins (Swiss-Prot ID: SRC, PLCG1, P85A, NCK1, GRB2, FYN, CRK) were used to screen a peptide target array composed of 1536 potential ligands, which led to the identification of 921 binary interactions between these proteins and 284 targets. To assess the efficiency of the peptide array target screening (PATS) method in identifying authentic protein-protein interactions, we examined a set of interactions mediated by the PLCgamma1 SH3 domain by coimmunoprecipitation and/or affinity pull-downs using full-length proteins and achieved a 75% success rate. Furthermore, we characterized a novel interaction between PLCgamma1 and hematopoietic progenitor kinase 1 (HPK1) identified by PATS and demonstrated that the PLCgamma1 SH3 domain negatively regulated HPK1 kinase activity. Compared to protein interactions listed in the online predicted human interaction protein database (OPHID), the majority of interactions identified by PATS are novel, suggesting that, when extended to the large number of peptide interaction domains encoded by the human genome, PATS should aid in the mapping of the human interactome.     

规模化蛋白质相互作用的研究技术

蛋白质相互作用既是蛋白质执行功能的主要方式,也是细胞功能调控网络的结构基础。蛋白质间异常的相互作用及其连锁网络的紊乱是引起许多病理改变的原因。作为功能基因组和蛋白质组研究的重要内容,规模化蛋白质相互作用研究已成为近年国际上研究的热点之一。文章综述了当前规模化蛋白质相互作用研究中的常用技术和常用蛋白质相互作用数据库,研究者可根据研究需要和技术特点利用这些资源。     

The importance of being proline: the interaction of proline-rich motifs in signaling proteins with their cognate domains.

Acommon focus among molecular and cellular biologists is the identification of proteins that interact with each other. Yeast two-hybrid, cDNA expression library screening, and coimmunoprecipitation experiments are powerful methods for identifying novel proteins that bind to one's favorite protein for the purpose of learning more regarding its cellular function. These same techniques, coupled with truncation and mutagenesis experiments, have been used to define the region of interaction between pairs of proteins. One conclusion from this work is that many interactions occur over short regions, often less than 10 amino acids in length within one protein. For example, mapping studies and 3-dimensional analyses of antigen-antibody interactions have revealed that epitopes are typically 4-7 residues long (1). Other examples include protein-interaction modules, such as Src homology (SH) 2 and 3 domains, phosphotyrosine binding domains (PTB), postsynaptic density/disc-large/ZO1 (PDZ) domains, WW domains, Eps15 homology (EH) domains, and 14-3-3 proteins that typically recognize linear regions of 3-9 amino acids. Each of these domains has been the subject of recent reviews published elsewhere (2 3 4 5 6 7). Among the primary structures of many ligands for protein-protein interactions, the amino acid proline is critical. In particular, SH3, WW, and several new protein-interaction domains prefer ligand sequences that are proline-rich. In addition, even though ligands for EH domains and 14-3-3 domains are not proline-rich, they do include a single proline residue. This review highlights the analysis of those protein-protein interactions that involve proline residues, the biochemistry of proline, and current drug discovery efforts based on proline peptidomimetics.-Kay, B. K., Williamson, M. P., Sudol, M. The importance of being proline: the interaction of proline-rich motifs in signaling proteins with their cognate domains.     

Virion-wide protein interactions of Kaposi's sarcoma-associated herpesvirus

Herpesvirus virions are highly organized structures built through specific protein-protein interactions. Thus, revelation of the protein interactions among virion proteins will shed light on the processes and the mechanisms of virion formation. Recently, we identified 24 virion proteins of Kaposi's sarcoma-associated herpesvirus (KSHV), using a proteomic approach (F. X. Zhu et al., J. Virol. 79:800-811, 2005). In the current study, a comprehensive analysis of protein-protein interaction between KSHV virion proteins was carried out using yeast two-hybrid (Y2H) and coimmunoprecipitation (co-IP) approaches. Every pairwise combination between KSHV tegument and capsid proteins, between tegument and envelope proteins, and among tegument proteins was tested for possible binary interaction. Thirty-seven protein-protein interactions were identified by both Y2H and co-IP analyses. The results revealed interactions between tegument and capsid proteins such as that of open reading frame 64 (ORF64) with ORF25 (major capsid protein [MCP]), ORF62 (triplex-1 [TRI-1]), and ORF26 (TRI-2). Many interactions were detected among the tegument proteins. ORF64 was found to interact with several tegument proteins including ORF11, ORF21, ORF33, ORF45, ORF63, ORF75, and ORF64 itself, suggesting that ORF64 may serve as a hub protein and play a role in recruiting tegument proteins during tegumentation and virion assembly. Our investigation also revealed redundant interactions between tegument proteins and envelope glycoproteins. These interactions are believed to contribute to final envelopment in virion assembly. Overall, this study allows us to establish a virion-wide protein interaction map, which provides insight into the architecture of the KSHV virion and sets up a foundation for exploring the functions of these proteins in viral particle assembly.     

Microarray image analysis: background estimation using quantile and morphological filters

Background

Identification of protein interaction networks has received considerable attention in the post-genomic era. The currently available biochemical approaches used to detect protein-protein interactions are all time and labour intensive. Consequently there is a growing need for the development of computational tools that are capable of effectively identifying such interactions.

Results

Here we explain the development and implementation of a novel Protein-Protein Interaction Prediction Engine termed PIPE. This tool is capable of predicting protein-protein interactions for any target pair of the yeast Saccharomyces cerevisiae proteins from their primary structure and without the need for any additional information or predictions about the proteins. PIPE showed a sensitivity of 61% for detecting any yeast protein interaction with 89% specificity and an overall accuracy of 75%. This rate of success is comparable to those associated with the most commonly used biochemical techniques. Using PIPE, we identified a novel interaction between YGL227W (vid30) and YMR135C (gid8) yeast proteins. This lead us to the identification of a novel yeast complex that here we term vid30 complex (vid30c). The observed interaction was confirmed by tandem affinity purification (TAP tag), verifying the ability of PIPE to predict novel protein-protein interactions. We then used PIPE analysis to investigate the internal architecture of vid30c. It appeared from PIPE analysis that vid30c may consist of a core and a secondary component. Generation of yeast gene deletion strains combined with TAP tagging analysis indicated that the deletion of a member of the core component interfered with the formation of vid30c, however, deletion of a member of the secondary component had little effect (if any) on the formation of vid30c. Also, PIPE can be used to analyse yeast proteins for which TAP tagging fails, thereby allowing us to predict protein interactions that are not included in genome-wide yeast TAP tagging projects.

Conclusion

PIPE analysis can predict yeast protein-protein interactions. Also, PIPE analysis can be used to study the internal architecture of yeast protein complexes. The data also suggests that a finite set of short polypeptide signals seem to be responsible for the majority of the yeast protein-protein interactions.     

Poxvirus Proteomics and Virus-Host Protein Interactions

Summary: Studies of the functional proteins encoded by the poxvirus genome provide information about the composition of the virus as well as individual virus-virus protein and virus-host protein interactions, which provides insight into viral pathogenesis and drug discovery. Widely used proteomic techniques to identify and characterize specific protein-protein interactions include yeast two-hybrid studies and coimmunoprecipitations. Recently, various mass spectrometry techniques have been employed to identify viral protein components of larger complexes. These methods, combined with structural studies, can provide new information about the putative functions of viral proteins as well as insights into virus-host interaction dynamics. For viral proteins of unknown function, identification of either viral or host binding partners provides clues about their putative function. In this review, we discuss poxvirus proteomics, including the use of proteomic methodologies to identify viral components and virus-host protein interactions. High-throughput global protein expression studies using protein chip technology as well as new methods for validating putative protein-protein interactions are also discussed.     

Calculation of weak protein-protein interactions: the pH dependence of the second virial coefficient

Interactions between proteins are often sufficiently weak that their study through the use of conventional structural techniques becomes problematic. Of the few techniques capable of providing experimental measures of weak protein-protein interactions, perhaps the most useful is the second virial coefficient, B(22), which quantifies a protein solution's deviations from ideal behavior. It has long been known that B(22) can in principle be computed, but only very recently has it been demonstrated that such calculations can be performed using protein models of true atomic detail (Biophys. J. 1998, 75:2469-2477). The work reported here extends these previous efforts in an attempt to develop a transferable energetic model capable of reproducing the experimental trends obtained for two different proteins over a range of pH and ionic strengths. We describe protein-protein interaction energies by a combination of three separate terms: (i) an electrostatic interaction term based on the use of effective charges, (ii) a term describing the electrostatic desolvation that occurs when charged groups are buried by an approaching protein partner, and (iii) a solvent-accessible surface area term that is used to describe contributions from van der Waals and hydrophobic interactions. The magnitude of the third term is governed by an adjustable, empirical parameter, gamma, that is altered to optimize agreement between calculated and experimental values of B(22). The model is applied separately to the proteins lysozyme and chymotrypsinogen, yielding optimal values of gamma that are almost identical. There are, however, clear difficulties in reproducing B(22) values at the extremes of pH. Explicit calculation of the protonation states of ionizable amino acids in the 200 most energetically favorable protein-protein structures suggest that these difficulties are due to a neglect of the protonation state changes that can accompany complexation. Proper reproduction of the pH dependence of B(22) will, therefore, almost certainly require that account be taken of these protonation state changes. Despite this problem, the fact that almost identical gamma values are obtained from two different proteins suggests that the basic energetic formulation used here, which can be evaluated very rapidly, might find use in dynamical simulations of weak protein-protein interactions at intermediate pH values.     

Detection and identification of plasma proteins that bind GlialCAM using ProteinChip arrays, SELDI-TOF MS, and nano-LC MS/MS

In order to fully understand biological processes it is essential to identify interactions in protein complexes. There are several techniques available to study this type of interactions, such as yeast two-hybrid screens, affinity chromatography, and coimmunoprecipitation. We propose a novel strategy to identify protein-protein interactions, comprised of first detecting the interactions using ProteinChips and SELDI-TOF MS, followed by the isolation of the interacting proteins through affinity beads and RP-HPLC and finally identifying the proteins using nano-LC MS/MS. The advantages of this new strategy are that the primary high-throughput screening of samples can be performed with small amounts of sample, no specific antibody is needed and the proteins represented on the SELDI-TOF MS spectra can be identified with high confidence. Furthermore, the method is faster and less labor-intensive than other current approaches. Using this novel method, we isolated and identified the interactions of two mouse plasma proteins, mannose binding lectin C and properdin, with GlialCAM, a type 1 transmembrane glycoprotein that belongs to the Ig superfamily.