Mass spectrometry‐based protein–protein interaction networks for the study of human diseases

A better understanding of the molecular mechanisms underlying disease is key for expediting the development of novel therapeutic interventions. Disease mechanisms are often mediated by interactions between proteins. Insights into the physical rewiring of protein–protein interactions in response to mutations, pathological conditions, or pathogen infection can advance our understanding of disease etiology, progression, and pathogenesis and can lead to the identification of potential druggable targets. Advances in quantitative mass spectrometry (MS)‐based approaches have allowed unbiased mapping of these disease‐mediated changes in protein–protein interactions on a global scale. Here, we review MS techniques that have been instrumental for the identification of protein–protein interactions at a system‐level, and we discuss the challenges associated with these methodologies as well as novel MS advancements that aim to address these challenges. An overview of examples from diverse disease contexts illustrates the potential of MS‐based protein–protein interaction mapping approaches for revealing disease mechanisms, pinpointing new therapeutic targets, and eventually moving toward personalized applications.     

UPA, a universal protein array system for quantitative detection of protein–protein, protein–DNA, protein–RNA and protein–ligand interactions

Protein–protein interactions have been widely used to study gene expression pathways and may be considered as a new approach to drug discovery. Here I report the development of a universal protein array (UPA) system that provides a sensitive, quantitative, multi-purpose, effective and easy technology to determine not only specific protein–protein interactions, but also specific interactions of proteins with DNA, RNA, ligands and other small chemicals. (i) Since purified proteins are used, the results can be easily interpreted. (ii) UPA can be used multiple times for different targets, making it economically affordable for most laboratories, hospitals and biotechnology companies. (iii) Unlike DNA chips or DNA microarrays, no additional instrumentation is required. (iv) Since the UPA uses active proteins (without denaturation and renaturation), it is more sensitive compared with most existing methods. (v) Because the UPA can analyze hundreds (even thousands on a protein microarray) of proteins in a single experiment, it is a very effective method to screen proteins as drug targets in cancer and other human diseases.     

Detection of protein–DNA interaction with a DNA probe: distinction between single-strand and double-strand DNA–protein interaction

A simple, direct method for the detection of DNA–protein interaction was developed with electrochemical methods. Single-stranded DNA (ss-DNA) probes were prepared through the chemical bonding of an oligonucleotide to a polymer film bearing carboxylic acid groups, and double-stranded DNA (ds-DNA) probes were prepared through hybridization of the complementary sequence DNA on the ss-DNA probe. Impedance spectroscopy and differential pulse voltammetry (DPV) distinguished the interaction between the DNA probes with mouse Purβ (mPurβ), an ss-DNA binding protein, and with Escherichia coli MutH, a ds-DNA binding protein. Impedance spectra obtained before and after the interaction of DNA probes with these proteins clearly showed the sequence-specific ss-DNA preference of mPurβ and the sequence-specific ds-DNA preference of MutH. The concentration dependence of proteins on the response of the DNA probes was also investigated, and the detection limits of MutH and mPurβ were 25 and 3 μg/ml, respectively. To confirm the impedance results, the variation of the current oxidation peak of adenine of the DNA probe was monitored with DPV. The formation constants of the complexes formed between the probe DNA and the proteins were estimated based on the DPV results.     

VisANT: an online visualization and analysis tool for biological interaction data

Background  

New techniques for determining relationships between biomolecules of all types – genes, proteins, noncoding DNA, metabolites and small molecules – are now making a substantial contribution to the widely discussed explosion of facts about the cell. The data generated by these techniques promote a picture of the cell as an interconnected information network, with molecular components linked with one another in topologies that can encode and represent many features of cellular function. This networked view of biology brings the potential for systematic understanding of living molecular systems.     

The protein information and property explorer: an easy-to-use, rich-client web application for the management and functional analysis of proteomic data

MOTIVATION: Mass spectrometry experiments in the field of proteomics produce lists containing tens to thousands of identified proteins. With the protein information and property explorer (PIPE), the biologist can acquire functional annotations for these proteins and explore the enrichment of the list, or fraction thereof, with respect to functional classes. These protein lists may be saved for access at a later time or different location. The PIPE is interoperable with the Firegoose and the Gaggle, permitting wide-ranging data exploration and analysis. The PIPE is a rich-client web application which uses AJAX capabilities provided by the Google Web Toolkit, and server-side data storage using Hibernate. AVAILABILITY: http://pipe.systemsbiology.net.     

A novel approach for the identification of protein–protein interaction with integral membrane proteins

Protein–protein interaction plays a major role in all biological processes. The currently available genetic methods such as the two-hybrid system and the protein recruitment system are relatively limited in their ability to identify interactions with integral membrane proteins. Here we describe the development of a reverse Ras recruitment system (reverse RRS), in which the bait used encodes a membrane protein. The bait is expressed in its natural environment, the membrane, whereas the protein partner (the prey) is fused to a cytoplasmic Ras mutant. Protein–protein interaction between the proteins encoded by the prey and the bait results in Ras membrane translocation and activation of a viability pathway in yeast. We devised the expression of the bait and prey proteins under the control of dual distinct inducible promoters, thus enabling a rapid selection of transformants in which growth is attributed solely to specific protein–protein interaction. The reverse RRS approach greatly extends the usefulness of the protein recruitment systems and the use of integral membrane proteins as baits. The system serves as an attractive approach to explore novel protein–protein interactions with high specificity and selectivity, where other methods fail.     

Searching for the Holy Grail; protein–protein interaction analysis and modulation

The first EMBO workshop on ‘Protein–Protein Interaction Analysis & Modulation’ took place in June 2012 in Roscoff, France. It brought together researchers to discuss the growing field of protein network analysis and the modulation of protein–protein interactions, as well as outstanding related issues including the daunting challenge of integrating interactomes in systems biology and in the modelling of signalling networks.     

GeneXplorer: an interactive web application for microarray data visualization and analysis

Background

When publishing large-scale microarray datasets, it is of great value to create supplemental websites where either the full data, or selected subsets corresponding to figures within the paper, can be browsed. We set out to create a CGI application containing many of the features of some of the existing standalone software for the visualization of clustered microarray data.

Results

We present GeneXplorer, a web application for interactive microarray data visualization and analysis in a web environment. GeneXplorer allows users to browse a microarray dataset in an intuitive fashion. It provides simple access to microarray data over the Internet and uses only HTML and JavaScript to display graphic and annotation information. It provides radar and zoom views of the data, allows display of the nearest neighbors to a gene expression vector based on their Pearson correlations and provides the ability to search gene annotation fields.

Conclusions

The software is released under the permissive MIT Open Source license, and the complete documentation and the entire source code are freely available for download from CPAN http://search.cpan.org/dist/Microarray-GeneXplorer/.

     

Match_Motif: A rapid computational tool to assist in protein–protein interaction design

In order to generate protein assemblies with a desired function, the rational design of protein–protein binding interfaces is of significant interest. Approaches based on random mutagenesis or directed evolution may involve complex experimental selection procedures. Also, molecular modeling approaches to design entirely new proteins and interactions with partner molecules can involve large computational efforts and screening steps. In order to simplify at least the initial effort for designing a putative binding interface between two proteins the Match_Motif approach has been developed. It employs the large collection of known protein–protein complex structures to suggest interface modifications that may lead to improved binding for a desired input interaction geometry. The approach extracts interaction motifs based on the backbone structure of short (four residues) segments and the relative arrangement with respect to short segments on the partner protein. The interaction geometry is used to search through a database of such motifs in known stable bound complexes. All matches are rapidly identified (within a few seconds) and collected and can be used to guide changes in the interface that may lead to improved binding. In the output, an alternative interface structure is also proposed based on the frequency of occurrence of side chains at a given interface position in all matches and based on sterical considerations. Applications of the procedure to known complex structures and alternative arrangements are presented and discussed. The program, data files, and example applications can be downloaded from https://www.groups.ph.tum.de/t38/downloads/.     

Amino acid–base interactions: a three-dimensional analysis of protein–DNA interactions at an atomic level

To assess whether there are universal rules that govern amino acid–base recognition, we investigate hydrogen bonds, van der Waals contacts and water-mediated bonds in 129 protein–DNA complex structures. DNA–backbone interactions are the most numerous, providing stability rather than specificity. For base interactions, there are significant base–amino acid type correlations, which can be rationalised by considering the stereochemistry of protein side chains and the base edges exposed in the DNA structure. Nearly two-thirds of the direct read-out of DNA sequences involves complex networks of hydrogen bonds, which enhance specificity. Two-thirds of all protein–DNA interactions comprise van der Waals contacts, compared to about one-sixth each of hydrogen and water-mediated bonds. This highlights the central importance of these contacts for complex formation, which have previously been relegated to a secondary role. Although common, water-mediated bonds are usually non-specific, acting as space-fillers at the protein–DNA interface. In conclusion, the majority of amino acid–base interactions observed follow general principles that apply across all protein–DNA complexes, although there are individual exceptions. Therefore, we distinguish between interactions whose specificities are ‘universal’ and ‘context-dependent’. An interactive Web-based atlas of side chain–base contacts provides access to the collected data, including analyses and visualisation of the three-dimensional geometry of the interactions.     

Sulfotyrosine residues: Interaction specificity determinants for extracellular protein–protein interactions

Tyrosine sulfation, a post-translational modification, can determine and often enhance protein–protein interaction specificity. Sulfotyrosyl residues (sTyrs) are formed by the enzyme tyrosyl-protein sulfotransferase during protein maturation in the Golgi apparatus and most often occur singly or as a cluster within a six-residue span. With both negative charge and aromatic character, sTyr facilitates numerous atomic contacts as visualized in binding interface structural models, thus there is no discernible binding site consensus. Found exclusively in secreted proteins, in this review, we discuss the four broad sequence contexts in which sTyr has been observed: first, a solitary sTyr has been shown to be critical for diverse high-affinity interactions, such as between peptide hormones and their receptors, in both plants and animals. Second, sTyr clusters within structurally flexible anionic segments are essential for a variety of cellular processes, including coreceptor binding to the HIV-1 envelope spike protein during virus entry, chemokine interactions with receptors, and leukocyte rolling cell adhesion. Third, a subcategory of sTyr clusters is found in conserved acidic sequences termed hirudin-like motifs that enable proteins to interact with thrombin; consequently, many proven and potential therapeutic proteins derived from blood-consuming invertebrates depend on sTyrs for their activity. Finally, several proteins that interact with collagen or similar proteins contain one or more sTyrs within an acidic residue array. Refined methods to direct sTyr incorporation in peptides synthesized both in vitro and in vivo, together with continued advances in mass spectrometry and affinity detection, promise to accelerate discoveries of sTyr occurrence and function.     

ArrayCyGHt: a web application for analysis and visualization of array-CGH data

ArrayCyGHt is a web-based application tool for analysis and visualization of microarray-comparative genomic hybridization (array-CGH) data. Full process of array-CGH data analysis, from normalization of raw data to the final visualization of copy number gain or loss, can be straightforwardly achieved on this arrayCyGHt system without the use of any further software. ArrayCyGHt, therefore, provides an easy and fast tool for the analysis of copy number aberrations in any kinds of data format. AVAILABILITY: ArrayCyGHt can be accessed at http://genomics.catholic.ac.kr/arrayCGH/     

A protein–protein interaction map reveals that the Coxiella burnetii effector CirB inhibits host proteasome activity

Coxiella burnetii is the etiological agent of the zoonotic disease Q fever, which is featured by its ability to replicate in acid vacuoles resembling the lysosomal network. One key virulence determinant of C. burnetii is the Dot/Icm system that transfers more than 150 effector proteins into host cells. These effectors function to construct the lysosome-like compartment permissive for bacterial replication, but the functions of most of these effectors remain elusive. In this study, we used an affinity tag purification mass spectrometry (AP-MS) approach to generate a C. burnetii-human protein-protein interaction (PPI) map involving 53 C. burnetii effectors and 3480 host proteins. This PPI map revealed that the C. burnetii effector CBU0425 (designated CirB) interacts with most subunits of the 20S core proteasome. We found that ectopically expressed CirB inhibits hydrolytic activity of the proteasome. In addition, overexpression of CirB in C. burnetii caused dramatic inhibition of proteasome activity in host cells, while knocking down CirB expression alleviated such inhibitory effects. Moreover, we showed that a region of CirB that spans residues 91–120 binds to the proteasome subunit PSMB5 (beta 5). Finally, PSMB5 knockdown promotes C. burnetii virulence, highlighting the importance of proteasome activity modulation during the course of C. burnetii infection.     

PPI spider: A tool for the interpretation of proteomics data in the context of protein–protein interaction networks

Recent advances in experimental technologies allow for the detection of a complete cell proteome. Proteins that are expressed at a particular cell state or in a particular compartment as well as proteins with differential expression between various cells states are commonly delivered by many proteomics studies. Once a list of proteins is derived, a major challenge is to interpret the identified set of proteins in the biological context. Protein–protein interaction (PPI) data represents abundant information that can be employed for this purpose. However, these data have not yet been fully exploited due to the absence of a methodological framework that can integrate this type of information. Here, we propose to infer a network model from an experimentally identified protein list based on the available information about the topology of the global PPI network. We propose to use a Monte Carlo simulation procedure to compute the statistical significance of the inferred models. The method has been implemented as a freely available web‐based tool, PPI spider ( http://mips.helmholtz‐muenchen.de/proj/ppispider ). To support the practical significance of PPI spider, we collected several hundreds of recently published experimental proteomics studies that reported lists of proteins in various biological contexts. We reanalyzed them using PPI spider and demonstrated that in most cases PPI spider could provide statistically significant hypotheses that are helpful for understanding of the protein list.     

A novel strategy for the identification of protein–DNA contacts by photocrosslinking and mass spectrometry

Photochemical crosslinking is a method for studying the molecular details of protein–nucleic acid interactions. In this study, we describe a novel strategy to localize crosslinked amino acid residues that combines laser-induced photocrosslinking, proteolytic digestion, Fe³⁺-IMAC (immobilized metal affinity chromatography) purification of peptide–oligodeoxynucleotide heteroconjugates and hydrolysis of oligodeoxynucleotides by hydrogen fluoride (HF), with efficient matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS). The new method is illustrated by the identification of the DNA-binding site of the restriction endonuclease MboI. Photoactivatable 5-iododeoxyuridine was incorporated into a single site within the DNA recognition sequence (GATC) of MboI. Ultraviolet irradiation of the protein–DNA complex with a helium/cadmium laser at 325 nm resulted in 15% crosslinking yield. Proteolytic digestion with different proteases produced various peptide–oligodeoxynucleotide adducts that were purified together with free oligodeoxynucleotide by Fe³⁺-IMAC. A combination of MS analysis of the peptide–nucleosides obtained after hydrolysis by HF and their fragmentation by MS/MS revealed that Lys²⁰⁹ of MboI was crosslinked to the MboI recognition site at the position of the adenine, demonstrating that the region around Lys²⁰⁹ is involved in specific binding of MboI to its DNA substrate. This method is suitable for the fast identification of the site of contact between proteins and nucleic acids starting from picomole quantities of crosslinked complexes.     

MZmine: toolbox for processing and visualization of mass spectrometry based molecular profile data

SUMMARY: New additional methods are presented for processing and visualizing mass spectrometry based molecular profile data, implemented as part of the recently introduced MZmine software. They include new features and extensions such as support for mzXML data format, capability to perform batch processing for large number of files, support for parallel processing, new methods for calculating peak areas using post-alignment peak picking algorithm and implementation of Sammon's mapping and curvilinear distance analysis for data visualization and exploratory analysis. AVAILABILITY: MZmine is available under GNU Public license from http://mzmine.sourceforge.net/.     

Using the clustered circular layout as an informative method for visualizing protein–protein interaction networks

The force‐directed layout is commonly used in computer‐generated visualizations of protein–protein interaction networks. While it is good for providing a visual outline of the protein complexes and their interactions, it has two limitations when used as a visual analysis method. The first is poor reproducibility. Repeated running of the algorithm does not necessarily generate the same layout, therefore, demanding cognitive readaptation on the investigator's part. The second limitation is that it does not explicitly display complementary biological information, e.g. Gene Ontology, other than the protein names or gene symbols. Here, we present an alternative layout called the clustered circular layout. Using the human DNA replication protein–protein interaction network as a case study, we compared the two network layouts for their merits and limitations in supporting visual analysis.     

Quantitative analysis of cell signaling and drug action via mass spectrometry‐based systems level phosphoproteomics

Protein phosphorylation is a primary form of information transfer in cell signaling pathways and plays a crucial role in regulating biological responses. Aberrant phosphorylation has been implicated in a number of diseases, and kinases and phosphatases, the cellular enzymes that control dynamic phosphorylation events, present attractive therapeutic targets. However, the innate complexity of signaling networks has presented many challenges to therapeutic target selection and successful drug development. Approaches in phosphoproteomics can contribute functional, systems‐level datasets across signaling networks that can provide insight into suitable drug targets, more broadly profile compound activities, and identify key biomarkers to assess clinical outcomes. Advances in MS‐based phosphoproteomics efforts now provide the ability to quantitate phosphorylation with throughput and sensitivity to sample a significant portion of the phosphoproteome in clinically relevant systems. This review will discuss recent work and examples of application data that demonstrate the utility of MS, with a particular focus on the use of quantitative phosphoproteomics and phosphotyrosine‐directed signaling analyses to provide robust measurement for functional biological interpretation of drug action on signaling and phenotypic outcomes.     

Detection of membrane protein–protein interaction in planta based on dual‐intein‐coupled tripartite split‐GFP association

Despite the great interest in identifying protein–protein interactions (PPIs) in biological systems, only a few attempts have been made at large‐scale PPI screening in planta. Unlike biochemical assays, bimolecular fluorescence complementation allows visualization of transient and weak PPIs in vivo at subcellular resolution. However, when the non‐fluorescent fragments are highly expressed, spontaneous and irreversible self‐assembly of the split halves can easily generate false positives. The recently developed tripartite split‐GFP system was shown to be a reliable PPI reporter in mammalian and yeast cells. In this study, we adapted this methodology, in combination with the β‐estradiol‐inducible expression cassette, for the detection of membrane PPIs in planta. Using a transient expression assay by agroinfiltration of Nicotiana benthamiana leaves, we demonstrate the utility of the tripartite split‐GFP association in plant cells and affirm that the tripartite split‐GFP system yields no spurious background signal even with abundant fusion proteins readily accessible to the compartments of interaction. By validating a few of the Arabidopsis PPIs, including the membrane PPIs implicated in phosphate homeostasis, we proved the fidelity of this assay for detection of PPIs in various cellular compartments in planta. Moreover, the technique combining the tripartite split‐GFP association and dual‐intein‐mediated cleavage of polyprotein precursor is feasible in stably transformed Arabidopsis plants. Our results provide a proof‐of‐concept implementation of the tripartite split‐GFP system as a potential tool for membrane PPI screens in planta.