Inferring physical protein contacts from large-scale purification data of protein complexes

Recent large-scale data sets of protein complex purifications have provided unprecedented insights into the organization of cellular protein complexes. Several computational methods have been developed to detect co-complexed proteins in these data sets. Their common aim is the identification of biologically relevant protein complexes. However, much less is known about the network of direct physical protein contacts within the detected protein complexes. Therefore, our work investigates whether direct physical contacts can be computationally derived by combining raw data of large-scale protein complex purifications. We assess four established scoring schemes and introduce a new scoring approach that is specifically devised to infer direct physical protein contacts from protein complex purifications. The physical contacts identified by the five methods are comprehensively benchmarked against different reference sets that provide evidence for true physical contacts. Our results show that raw purification data can indeed be exploited to determine high-confidence physical protein contacts within protein complexes. In particular, our new method outperforms competing approaches at discovering physical contacts involving proteins that have been screened multiple times in purification experiments. It also excels in the analysis of recent protein purification screens of molecular chaperones and protein kinases. In contrast to previous findings, we observe that physical contacts inferred from purification experiments of protein complexes can be qualitatively comparable to binary protein interactions measured by experimental high-throughput assays such as yeast two-hybrid. This suggests that computationally derived physical contacts might complement binary protein interaction assays and guide large-scale interactome mapping projects by prioritizing putative physical contacts for further experimental screens.     

Identification of protein-protein interactions and topologies in living cells with chemical cross-linking and mass spectrometry

We present results from a novel strategy that enables concurrent identification of protein-protein interactions and topologies in living cells without specific antibodies or genetic manipulations for immuno-/affinity purifications. The strategy consists of (i) a chemical cross-linking reaction: intact cell labeling with a novel class of chemical cross-linkers, protein interaction reporters (PIRs); (ii) two-stage mass spectrometric analysis: stage 1 identification of PIR-labeled proteins and construction of a restricted database by two-dimensional LC/MSMS and stage 2 analysis of PIR-labeled peptides by multiplexed LC/FTICR-MS; and (iii) data analysis: identification of cross-linked peptides and proteins of origin using accurate mass and other constraints. The primary advantage of the PIR approach and distinction from current technology is that protein interactions together with topologies are detected in native biological systems by stabilizing protein complexes with new covalent bonds while the proteins are present in the original cellular environment. Thus, weak or transient interactions or interactions that require properly folded, localized, or membrane-bound proteins can be labeled and identified through the PIR approach. This strategy was applied to Shewanella oneidensis bacterial cells, and initial studies resulted in identification of a set of protein-protein interactions and their contact/binding regions. Furthermore most identified interactions involved membrane proteins, suggesting that the PIR approach is particularly suited for studies of membrane protein-protein interactions, an area under-represented with current widely used approaches.     

SAINT-MS1: protein-protein interaction scoring using label-free intensity data in affinity purification-mass spectrometry experiments

We present a statistical method SAINT-MS1 for scoring protein-protein interactions based on the label-free MS1 intensity data from affinity purification-mass spectrometry (AP-MS) experiments. The method is an extension of Significance Analysis of INTeractome (SAINT), a model-based method previously developed for spectral count data. We reformulated the statistical model for log-transformed intensity data, including adequate treatment of missing observations, that is, interactions identified in some but not all replicate purifications. We demonstrate the performance of SAINT-MS1 using two recently published data sets: a small LTQ-Orbitrap data set with three replicate purifications of single human bait protein and control purifications and a larger drosophila data set targeting insulin receptor/target of rapamycin signaling pathway generated using an LTQ-FT instrument. Using the drosophila data set, we also compare and discuss the performance of SAINT analysis based on spectral count and MS1 intensity data in terms of the recovery of orthologous and literature-curated interactions. Given rapid advances in high mass accuracy instrumentation and intensity-based label-free quantification software, we expect that SAINT-MS1 will become a useful tool allowing improved detection of protein interactions in label-free AP-MS data, especially in the low abundance range.     

Determining Protein Complex Connectivity Using a Probabilistic Deletion Network Derived from Quantitative Proteomics

Protein complexes are key molecular machines executing a variety of essential cellular processes. Despite the availability of genome-wide protein-protein interaction studies, determining the connectivity between proteins within a complex remains a major challenge. Here we demonstrate a method that is able to predict the relationship of proteins within a stable protein complex. We employed a combination of computational approaches and a systematic collection of quantitative proteomics data from wild-type and deletion strain purifications to build a quantitative deletion-interaction network map and subsequently convert the resulting data into an interdependency-interaction model of a complex. We applied this approach to a data set generated from components of the Saccharomyces cerevisiae Rpd3 histone deacetylase complexes, which consists of two distinct small and large complexes that are held together by a module consisting of Rpd3, Sin3 and Ume1. The resulting representation reveals new protein-protein interactions and new submodule relationships, providing novel information for mapping the functional organization of a complex.     

Different Mi-2 complexes for various developmental functions in Caenorhabditis elegans

Biochemical purifications from mammalian cells and Xenopus oocytes revealed that vertebrate Mi-2 proteins reside in multisubunit NuRD (Nucleosome Remodeling and Deacetylase) complexes. Since all NuRD subunits are highly conserved in the genomes of C. elegans and Drosophila, it was suggested that NuRD complexes also exist in invertebrates. Recently, a novel dMec complex, composed of dMi-2 and dMEP-1 was identified in Drosophila. The genome of C. elegans encodes two highly homologous Mi-2 orthologues, LET-418 and CHD-3. Here we demonstrate that these proteins define at least three different protein complexes, two distinct NuRD complexes and one MEC complex. The two canonical NuRD complexes share the same core subunits HDA-1/HDAC, LIN-53/RbAp and LIN-40/MTA, but differ in their Mi-2 orthologues LET-418 or CHD-3. LET-418 but not CHD-3, interacts with the Krüppel-like protein MEP-1 in a distinct complex, the MEC complex. Based on microarrays analyses, we propose that MEC constitutes an important LET-418 containing regulatory complex during C. elegans embryonic and early larval development. It is required for the repression of germline potential in somatic cells and acts when blastomeres are still dividing and differentiating. The two NuRD complexes may not be important for the early development, but may act later during postembryonic development. Altogether, our data suggest a considerable complexity in the composition, the developmental function and the tissue-specificity of the different C. elegans Mi-2 complexes.     

High throughput protein-protein interaction data: clues for the architecture of protein complexes

Background

High-throughput techniques are becoming widely used to study protein-protein interactions and protein complexes on a proteome-wide scale. Here we have explored the potential of these techniques to accurately determine the constituent proteins of complexes and their architecture within the complex.

Results

Two-dimensional representations of the 19S and 20S proteasome, mediator, and SAGA complexes were generated and overlaid with high quality pairwise interaction data, core-module-attachment classifications from affinity purifications of complexes and predicted domain-domain interactions. Pairwise interaction data could accurately determine the members of each complex, but was unexpectedly poor at deciphering the topology of proteins in complexes. Core and module data from affinity purification studies were less useful for accurately defining the member proteins of these complexes. However, these data gave strong information on the spatial proximity of many proteins. Predicted domain-domain interactions provided some insight into the topology of proteins within complexes, but was affected by a lack of available structural data for the co-activator complexes and the presence of shared domains in paralogous proteins.

Conclusion

The constituent proteins of complexes are likely to be determined with accuracy by combining data from high-throughput techniques. The topology of some proteins in the complexes will be able to be clearly inferred. We finally suggest strategies that can be employed to use high throughput interaction data to define the membership and understand the architecture of proteins in novel complexes.     

Targeted Identification of Protein Interactions in Eukaryotic mRNA Translation

To identify protein–protein interactions and phosphorylated amino acid sites in eukaryotic mRNA translation, replicate TAP‐MudPIT and control experiments are performed targeting Saccharomyces cerevisiae genes previously implicated in eukaryotic mRNA translation by their genetic and/or functional roles in translation initiation, elongation, termination, or interactions with ribosomal complexes. Replicate tandem affinity purifications of each targeted yeast TAP‐tagged mRNA translation protein coupled with multidimensional liquid chromatography and tandem mass spectrometry analysis are used to identify and quantify copurifying proteins. To improve sensitivity and minimize spurious, nonspecific interactions, a novel cross‐validation approach is employed to identify the most statistically significant protein–protein interactions. Using experimental and computational strategies discussed herein, the previously described protein composition of the canonical eukaryotic mRNA translation initiation, elongation, and termination complexes is calculated. In addition, statistically significant unpublished protein interactions and phosphorylation sites for S. cerevisiae’s mRNA translation proteins and complexes are identified.     

In vivo analysis of proteomes and interactomes using Parallel Affinity Capture (iPAC) coupled to mass spectrometry

Affinity purification coupled to mass spectrometry provides a reliable method for identifying proteins and their binding partners. In this study we have used Drosophila melanogaster proteins triple tagged with Flag, Strep II, and Yellow fluorescent protein in vivo within affinity pull-down experiments and isolated these proteins in their native complexes from embryos. We describe a pipeline for determining interactomes by Parallel Affinity Capture (iPAC) and show its use by identifying partners of several protein baits with a range of sizes and subcellular locations. This purification protocol employs the different tags in parallel and involves detailed comparison of resulting mass spectrometry data sets, ensuring the interaction lists achieved are of high confidence. We show that this approach identifies known interactors of bait proteins as well as novel interaction partners by comparing data achieved with published interaction data sets. The high confidence in vivo protein data sets presented here add new data to the currently incomplete D. melanogaster interactome. Additionally we report contaminant proteins that are persistent with affinity purifications irrespective of the tagged bait.     

Highly reproducible label free quantitative proteomic analysis of RNA polymerase complexes

The use of quantitative proteomics methods to study protein complexes has the potential to provide in-depth information on the abundance of different protein components as well as their modification state in various cellular conditions. To interrogate protein complex quantitation using shotgun proteomic methods, we have focused on the analysis of protein complexes using label-free multidimensional protein identification technology and studied the reproducibility of biological replicates. For these studies, we focused on three highly related and essential multi-protein enzymes, RNA polymerase I, II, and III from Saccharomyces cerevisiae. We found that label-free quantitation using spectral counting is highly reproducible at the protein and peptide level when analyzing RNA polymerase I, II, and III. In addition, we show that peptide sampling does not follow a random sampling model, and we show the need for advanced computational models to predict peptide detection probabilities. In order to address these issues, we used the APEX protocol to model the expected peptide detectability based on whole cell lysate acquired using the same multidimensional protein identification technology analysis used for the protein complexes. Neither method was able to predict the peptide sampling levels that we observed using replicate multidimensional protein identification technology analyses. In addition to the analysis of the RNA polymerase complexes, our analysis provides quantitative information about several RNAP associated proteins including the RNAPII elongation factor complexes DSIF and TFIIF. Our data shows that DSIF and TFIIF are the most highly enriched RNAP accessory factors in Rpb3-TAP purifications and demonstrate our ability to measure low level associated protein abundance across biological replicates. In addition, our quantitative data supports a model in which DSIF and TFIIF interact with RNAPII in a dynamic fashion in agreement with previously published reports.     

Analytical biochemistry of DNA–protein assemblies from crude cell extracts

Purification of specific DNA–protein complexes is a challenging task, as the involved interactions can be both electrostatic/H-bond and hydrophobic. The chromatographic stringency needed to obtain reasonable purifications uses salts and detergents. However, these components elicit the removal of proteins unspecifically bound to the chromatographic support itself, thus contaminating the purification products. In this work, a photocleavable linker connected the target oligonucleotidic sequence to the chromatographic beads so as to allow the irradiation-based release of the purified DNA–protein complexes off the beads. Our bioanalytical conditions were validated by purifying the tetracycline repressor protein onto a specific oligonucleotide. The purification factor was unprecedented, with a single contaminant. The robustness of our method was challenged by applying it to the purification of multiprotein assemblies forming onto DNA damage-mimicking oligonucleotides. The purified components were identified as well-known DNA repair proteins, and were shown to retain their enzymatic activities, as seen by monitoring DNA ligation products. Remarkably, kinase activities, also monitored, were found to be distinct on the beads and on the purified DNA–protein complexes, showing the benefits to uncouple the DNA–protein assemblies from the beads for a proper understanding of biochemical regulatory mechanisms involved in the DNA–protein assemblies.     

Tandem affinity purification in Drosophila: the advantages of the GS-TAP system

Tandem affinity purification (TAP) has been widely used for the analysis of protein complexes. We investigated the parameters of the recently developed TAP method (GS-TAP) and its application in Drosophila. This new tag combination includes two Protein G modules and a streptavidin binding peptide (SBP), separated by one or two TEV protease cleavage sites. We made pMK33-based GS-TAP vectors to allow for generation of stable cell lines using hygromycin selection and inducible expression from a metallothionein promoter, as well as pUAST-based vectors that can be used for inducible expression in flies. Rescue experiments in flies demonstrated that the GS-TAP tag preserves the function of the tagged protein. We have done parallel purifications of proteins tagged with the new GS-TAP tag or with the conventional TAP tag (containing the Protein A and calmodulin binding peptide domains) at the amino terminus, using both cultured cells and embryos. A major difference between the two tags was in the levels of contaminating proteins, which were significantly lower in the GS-TAP purifications. The GS-TAP procedure also resulted in higher yield of the bait protein. Overall, GS-TAP is an improved method of protein complex purification because it provides a superior signal-to-noise ratio of the bait protein relative to contaminants in purified material.     

Immobilized metal ion affinity chromatography.

The introduction of immobilized metal ion affinity chromatography, directed toward specific protein side chains, has opened a new dimension in protein purification. This review covers the principles and practice of IMAC that can be performed under very mild, nondenaturing conditions. IMAC is particularly suitable for preparative group fractionation of complex extracts and biofluids, but can also be used in high-performance mode: "HP-IMAC." Single-step purifications of 1000-fold or more may allow isolation of a particular protein from crude extracts on a milligram or gram scale. With respect to separation efficiency, IMAC compares well with biospecific affinity chromatography, and the immobilized metal ion ligand complexes are more likely to withstand wear and tear than are antibodies or enzymes. The enormous potential of IMAC and related metal affinity techniques is only in the initial stages of being explored and exploited. Synthesis of IMA adsorbents, and various modes of performing IMAC are discussed and exemplified with selected applications. Advantages and disadvantages are listed. Effective means of counteracting the few undesirable effects that can occur are suggested.     

Tumor-associated blocking factors: isolation from sera of tumor-bearing mice.

An isolation and partial purifications of tumor-associated blocking factors from the sera of tumor-bearing mice is described. Columns for affinity chromatography were prepared by coupling syngeneic tumor-immune antibodies to Sepharose 4B. Passage of serum through such immunoadsorbent columns removed all blocking activity from tumor-bearers' sera; subsequent elution of the absorbent with 3 M NaSCN recovered the activity. The blocking material was further purified on Sephadex G-200. The data provide evidence for the presence of antigen in tumor-associated blocking factors and are compatible with the hypothesis that blocking factors often consist of antigen and antibodies in the form of immune complexes.     

NetworkBLAST: comparative analysis of protein networks

The identification of protein complexes is a fundamental challenge in interpreting protein-protein interaction data. Cross-species analysis allows coping with the high levels of noise that are typical to these data. The NetworkBLAST web-server provides a platform for identifying protein complexes in protein-protein interaction networks. It can analyze a single network or two networks from different species. In the latter case, NetworkBLAST outputs a set of putative complexes that are evolutionarily conserved across the two networks. AVAILABILITY: NetworkBLAST is available as web-server at: www.cs.tau.ac.il/~roded/networkblast.htm.     

Analytical biochemistry of DNA--protein assemblies from crude cell extracts

Purification of specific DNA-protein complexes is a challenging task, as the involved interactions can be both electrostatic/H-bond and hydrophobic. The chromatographic stringency needed to obtain reasonable purifications uses salts and detergents. However, these components elicit the removal of proteins unspecifically bound to the chromatographic support itself, thus contaminating the purification products. In this work, a photocleavable linker connected the target oligonucleotidic sequence to the chromatographic beads so as to allow the irradiation-based release of the purified DNA-protein complexes off the beads. Our bioanalytical conditions were validated by purifying the tetracycline repressor protein onto a specific oligonucleotide. The purification factor was unprecedented, with a single contaminant. The robustness of our method was challenged by applying it to the purification of multiprotein assemblies forming onto DNA damage-mimicking oligonucleotides. The purified components were identified as well-known DNA repair proteins, and were shown to retain their enzymatic activities, as seen by monitoring DNA ligation products. Remarkably, kinase activities, also monitored, were found to be distinct on the beads and on the purified DNA-protein complexes, showing the benefits to uncouple the DNA-protein assemblies from the beads for a proper understanding of biochemical regulatory mechanisms involved in the DNA-protein assemblies.     

Mapping the protein interaction network of the human COP9 signalosome complex using a label-free QTAX strategy

The COP9 signalosome (CSN) is a multi-subunit protein complex that performs critical roles in controlling diverse cellular and developmental processes. Aberrant regulation of the CSN complex has been shown to lead to tumorigenesis. Despite its biological significance, our current knowledge of the function and regulation of the CSN complex is very limited. To explore CSN biology, we have developed and employed a new version of the tag team-based QTAX strategy (quantitative analysis of tandem affinity purified in vivo cross-linked (X) protein complexes) by incorporating a label-free MS method for quantitation. Coupled with protein interaction network analysis, this strategy produced a comprehensive and detailed assessment of the protein interaction network of the human CSN complex. In total, we quantitatively characterized 825 putative CSN-interacting proteins, with 270 classified as core interactors (captured by all three bait purifications). Biochemical validation further confirms the validity of selected identified interactors. This work presents the most complete analysis of the CSN interaction network to date, providing an inclusive set of physical interaction data consistent with physiological roles for the CSN. Moreover, the methodology described here is a general proteomic tool for the comprehensive study of protein interaction networks.