Surface plasmon resonance mass spectrometry: recent progress and outlooks

The combination of surface plasmon resonance (SPR) and mass spectrometry (MS) has created a unique approach to protein investigations. Surface plasmon resonance is used to quantify interactions between proteins and surface-immobilized ligands, and MS is used to determine the structural features of the bound proteins. Recent progress in SPR-MS includes improved methods and operations, increased limits of detection, multi-protein analysis and protein-complex delineation. With the subsequent design of SPR protein arrays, SPR-MS is expected to enter into the field of high-throughput protein interaction discovery and miniaturized diagnostics.     

Protein-protein interaction networks: from interactions to networks

The goal of interaction proteomics that studies the protein-protein interactions of all expressed proteins is to understand biological processes that are strictly regulated by these interactions. The availability of entire genome sequences of many organisms and high-throughput analysis tools has led scientists to study the entire proteome (Pandey and Mann, 2000). There are various high-throughput methods for detecting protein interactions such as yeast two-hybrid approach and mass spectrometry to produce vast amounts of data that can be utilized to decipher protein functions in complicated biological networks. In this review, we discuss recent developments in analytical methods for large-scale protein interactions and the future direction of interaction proteomics.     

蛋白质相互作用实验技术的最新进展

蛋白质相互作用的研究, 是揭示生物体正常生长发育及其应对各种生物或(和)非生物胁迫的分子机制及其调控网络的重要途径。文章综述了近年来发展起来的研究蛋白质相互作用的常用实验性方法, 如酵母双杂交系统、串联亲和纯化、免疫共沉淀、GST Pull-down、双分子荧光互补、荧光共振能量转移、表面等离子共振分析, 介绍了其原理、发展进程, 并分析了其优缺点。     

RNA as a drug target: methods for biophysical characterization and screening

RNA folds into complex structures that can interact specifically with effector proteins. These interactions are essential for various biological functions. In order to discover small molecules that can affect important RNA-protein complexes, a thorough analysis of the thermodynamics and kinetics of RNA-protein binding is required. This can facilitate the formulation of high-throughput screening strategies and the development of structure-activity relationships for compound leads. In addition to traditional methods, such as filter binding, gel mobility shift assay and various fluorescence techniques, newer methods such as surface plasmon resonance and mass spectrometry are being used for the study of RNA-protein interactions.     

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.     

Integration of surface plasmon resonance with mass spectrometry: automated ligand fishing and sample preparation for MALDI MS using a Biacore 3000 biosensor.

Integrating surface plasmon resonance analysis with mass spectrometry allows detection and characterization of molecular interactions to be complemented with identification of interaction partners. We have developed a procedure for Biacore 3000 that automatically performs all steps from ligand fishing and recovery to sample preparation for matrix-assisted laser desorption/ionization (MALDI) mass spectrometry including on-target digestion. In the model system used in this study a signal transduction protein, calmodulin, was selectively captured from brain extract by one of its interaction partners immobilized on a sensor chip. The bound material was eluted, deposited directly onto a MALDI target, and analyzed by mass spectrometry both as an intact protein and after on-target tryptic digestion. The procedure with direct deposition of recovered material on the MALDI target reduces sample losses and, in combination with automatic sample processing, increases the throughput of surface plasmon resonance mass spectrometry analysis.     

Methods for the detection and analysis of protein-protein interactions

A large number of methods have been developed over the years to study protein-protein interactions. Many of these techniques are now available to the nonspecialist researcher thanks to new affordable instruments and/or resource centres. A typical protein-protein interaction study usually starts with an initial screen for novel binding partners. We start this review by describing three techniques that can be used for this purpose: (i) affinity-tagged proteins (ii) the two-hybrid system and (iii) some quantitative proteomic techniques that can be used in combination with, e.g., affinity chromatography and coimmunoprecipitation for screening of protein-protein interactions. We then describe some public protein-protein interaction databases that can be searched to identify previously reported interactions for a given bait protein. Four strategies for validation of protein-protein interactions are presented: confocal microscopy for intracellular colocalization of proteins, coimmunoprecipitation, surface plasmon resonance (SPR) and spectroscopic studies. Throughout the review we focus particularly on the advantages and limitations of each method.     

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.     

Proteomic approaches for generating comprehensive protein interaction maps

The availability of complete genome sequences of numerous model organisms has initiated the development of new approaches in biological research to complement conventional biochemistry and genetics. In this context, high-throughput methods for detecting protein interactions, such as mass spectrometry and yeast two-hybrid assays, have produced vast amounts of data that can be exploited to infer protein function and regulation. In this review, we explore different genome-wide protein interaction studies and comment on their extrapolation towards understanding protein functions. It is likely that improvements of these approaches, together with more sophisticated databases and the invention of novel technologies, will help to decipher the complex interactions among proteins and to integrate interacting proteins into existing and novel cellular pathways.     

Analysis of protein tyrosine phosphatase interactions with microarrayed phosphopeptide substrates using imaging mass spectrometry

Microarrays of peptide and recombinant protein libraries are routinely used for high-throughput studies of protein–protein interactions and enzymatic activities. Imaging mass spectrometry (IMS) is currently applied as a method to localize analytes on thin tissue sections and other surfaces. Here, we have applied IMS as a label-free means to analyze protein–peptide interactions in a microarray-based phosphatase assay. This IMS strategy visualizes the entire microarray in one composite image by collecting a predefined raster of matrix-assisted laser desorption/ionization time-of-flight (MALDI–TOF) mass spectrometry spectra over the surface of the chip. Examining the bacterial tyrosine phosphatase YopH, we used IMS as a label-free means to visualize enzyme binding and activity with a microarrayed phosphopeptide library printed on chips coated with either gold or indium–tin oxide. Furthermore, we demonstrate that microarray-based IMS can be coupled with surface plasmon resonance imaging to add kinetic analyses to measured binding interactions. The method described here is within the capabilities of many modern MALDI–TOF instruments and has general utility for the label-free analysis of microarray assays.     

大规模高通量方法在蛋白质相互作用研究中的应用

随着后基因组时代的到来,阐明蛋白质间相互作用关系成为蛋白质研究的又一热点,促进了相关技术的不断产生、发展和完善.其中涉及到诸多大规模高通量的方法,如双杂交系统、噬菌体展示、质谱、蛋白质芯片以及生物信息学等,这为系统分析蛋白质相互作用提供视点,有望在蛋白质组学研究中发挥重要作用.每种方法各有其优缺点且适用范围不同,在一定程度上各方法的实验结果互为补充.现拟就这些大规模高通量方法的研究进展及其在蛋白质相互作用研究中的应用作一综述.     

Computational detection of protein complexes in AP-MS experiments

Protein complex identification is an important goal of protein-protein interaction analysis. To date, development of computational methods for detecting protein complexes has been largely motivated by genome-scale interaction data sets from high-throughput assays such as yeast two-hybrid or tandem affinity purification coupled with mass spectrometry (TAP-MS). However, due to the popularity of small to intermediate-scale affinity purification-mass spectrometry (AP-MS) experiments, protein complex detection is increasingly discussed in local network analysis. In such data sets, protein complexes cannot be detected using binary interaction data alone because the data contain interactions with tagged proteins only and, as a result, interactions between all other proteins remain unobserved, limiting the scope of existing algorithms. In this article, we provide a pragmatic review of network graph-based computational algorithms for protein complex analysis in global interactome data, without requiring any computational background. We discuss the practical gap in applying these algorithms to recently surging small to intermediate-scale AP-MS data sets, and review alternative clustering algorithms using quantitative proteomics data and their limitations.     

BIA–MS–MS: biomolecular interaction analysis for functional proteomics

One of the experimental processes of functional proteomics is the analysis of protein interaction. Here, we review a new analytical platform, BIA–MS, for protein interaction analysis. BIA–MS is an integration of a surface plasmon resonance biosensor for real-time interaction analysis and mass spectrometry for the subsequent identification of interacting molecules.     

BIA–MS–MS: biomolecular interaction analysis for functional proteomics

One of the experimental processes of functional proteomics is the analysis of protein interaction. Here, we review a new analytical platform, BIA–MS, for protein interaction analysis. BIA–MS is an integration of a surface plasmon resonance biosensor for real-time interaction analysis and mass spectrometry for the subsequent identification of interacting molecules.     

双杂交和质谱技术在蛋白质-蛋白质相互作用研究中的应用

基因的功能是由蛋白质来执行的,而蛋白质要通过与其他生物分子相互作用来完成其各种生物功能。因此,如果能够快速做出蛋白质在不同时间、空间和不同环境中的相互作用图谱,就会帮助我们了解这些蛋白质的功能,进而了解许多生命活动的机制。目前,用于大规模研究蛋白质间相互作用的方法主要有酵母双杂交系统及其衍生系统、亲和纯化与质谱分析联用技术,前者用于研究蛋白分子间的两两相互作用,后者用于研究蛋白质复合物间的相互作用。本文主要阐述了酵母双杂交、细菌双杂交、哺乳动物细胞双杂交、亲和纯化与质谱联用技术在大规模蛋白质相互作用研究中的应用。     

Analyzing yeast protein-protein interaction data obtained from different sources

High-throughput methods for detecting protein interactions, such as mass spectrometry and yeast two-hybrid assays, continue to produce vast amounts of data that may be exploited to infer protein function and regulation. As this article went to press, the pool of all published interaction information on Saccharomyces cerevisiae was 15,143 interactions among 4,825 proteins, and power-law scaling supports an estimate of 20,000 specific protein interactions. To investigate the biases, overlaps, and complementarities among these data, we have carried out an analysis of two high-throughput mass spectrometry (HMS)-based protein interaction data sets from budding yeast, comparing them to each other and to other interaction data sets. Our analysis reveals 198 interactions among 222 proteins common to both data sets, many of which reflect large multiprotein complexes. It also indicates that a "spoke" model that directly pairs bait proteins with associated proteins is roughly threefold more accurate than a "matrix" model that connects all proteins. In addition, we identify a large, previously unsuspected nucleolar complex of 148 proteins, including 39 proteins of unknown function. Our results indicate that existing large-scale protein interaction data sets are nonsaturating and that integrating many different experimental data sets yields a clearer biological view than any single method alone.     

Mass spectrometry-based immunoassays for the next phase of clinical applications

Recent applications of affinity mass spectrometry into clinical laboratories brought a renewed interest in immunoaffinity mass spectrometry as a more specific affinity method capable of selectively targeting and studying protein biomarkers. In mass spectrometry-based immunoassays, proteins are affinity retrieved from biological samples via surface-immobilized antibodies, and are then detected via mass spectrometric analysis. The assays benefit from dual specificity, which is brought about by the affinity of the antibody and the protein mass readout. The mass spectrometry aspect of the assays enables single-step detection of protein isoforms and their individual quantification. This review offers a comprehensive review of mass spectrometry-based immunoassays, from historical perspectives in the development of the immunoaffinity mass spectrometry, to current applications of the assays in clinical and population proteomic endeavors. Described in more detail are two types of mass spectrometry-based immunoassays, one of which incorporates surface plasmon resonance detection for protein quantification. All mass spectrometry-based immunoassays offer high-throughput targeted protein investigation, with clear implications in clinical research, encompassing biomarker discovery and validation, and in diagnostic settings as the next-generation immunoassays.     

Mass spectrometry-based immunoassays for the next phase of clinical applications

Recent applications of affinity mass spectrometry into clinical laboratories brought a renewed interest in immunoaffinity mass spectrometry as a more specific affinity method capable of selectively targeting and studying protein biomarkers. In mass spectrometry-based immunoassays, proteins are affinity retrieved from biological samples via surface-immobilized antibodies, and are then detected via mass spectrometric analysis. The assays benefit from dual specificity, which is brought about by the affinity of the antibody and the protein mass readout. The mass spectrometry aspect of the assays enables single-step detection of protein isoforms and their individual quantification. This review offers a comprehensive review of mass spectrometry-based immunoassays, from historical perspectives in the development of the immunoaffinity mass spectrometry, to current applications of the assays in clinical and population proteomic endeavors. Described in more detail are two types of mass spectrometry-based immunoassays, one of which incorporates surface plasmon resonance detection for protein quantification. All mass spectrometry-based immunoassays offer high-throughput targeted protein investigation, with clear implications in clinical research, encompassing biomarker discovery and validation, and in diagnostic settings as the next-generation immunoassays.     

ABRF�CMIRG Benchmark Study: Molecular Interactions in a Three-Component System

Protein–protein interactions identified through high-throughput proteomics efforts continue to advance our understanding of the protein interactome. In addition to highly specific protein–protein interactions, it is becoming increasingly more common for yeast two-hybrid, pull-down assays, and other proteomics techniques to identify multiple protein ligands that bind to the same target protein. A resulting challenge is to accurately characterize the assembly of these multiprotein complexes and the competition among multiple protein ligands for a given target. The Association of Biomolecular Resource Facilities–Molecular Interactions Research Group recently conducted a benchmark study to assess participants'' ability to correctly describe the interactions between two protein ligands and their target protein using primarily biosensor technologies, such as surface plasmon resonance. Participants were provided with microgram quantities of three proteins (A, B, and C) and asked to determine if a ternary A-B-C complex can form or if protein-B and protein-C bind competitively to protein-A. This article will summarize the experimental approaches taken by participants to characterize the molecular interactions, the interpretation of the data, and the results obtained using different biosensor instruments.     

Predicting co-complexed protein pairs using genomic and proteomic data integration

Background  

Identifying all protein-protein interactions in an organism is a major objective of proteomics. A related goal is to know which protein pairs are present in the same protein complex. High-throughput methods such as yeast two-hybrid (Y2H) and affinity purification coupled with mass spectrometry (APMS) have been used to detect interacting proteins on a genomic scale. However, both Y2H and APMS methods have substantial false-positive rates. Aside from high-throughput interaction screens, other gene- or protein-pair characteristics may also be informative of physical interaction. Therefore it is desirable to integrate multiple datasets and utilize their different predictive value for more accurate prediction of co-complexed relationship.