邻近标记在蛋白质组学中的发展及应用

人体内各种复杂的生命活动离不开蛋白质之间的相互作用。这种相互作用具有瞬时性和结合力弱等特点,并受到多种动态调节,特别是蛋白质翻译后修饰（post-translation modifications, PTM）。传统的亲和质谱检测方法存在蛋白纯化的局限性,在高效检测到动态变化方面存在不足。邻近标记是一种能够给与靶蛋白质瞬时靠近,或者互作（邻近）的蛋白质加上生物素的技术,它与质谱检测技术的联合使用能检测细胞过程中弱的、瞬时的蛋白质相互作用,有效解决上述问题。本文综述了基于生物素的邻近标记方法的发展现状,从依赖于融合序列的生物素标记开始,依次介绍有关生物素连接酶、过氧化物酶及其进化后的2代标记方法等经典生物素标记的方法和原理,比较各个方法间的差异和优缺点;也列举了一些近年来新出现的标记方法,如将生物素连接酶进行拆分、鉴定蛋白质在不同复合物中功能的方法、抗体靶向的标记方法,以及其他来源的生物素连接酶突变体,例如枯草芽孢杆菌（Bacillus subtilis）的C端氨基酸突变的生物素连接酶,能够应用在苍蝇和蠕虫中的生物素连接酶突变体。本文对这些方法进行归纳总结,旨在为初步接触该领域的科研工作者提供参考,同时也希望能够提供一些新的思路,推动蛋白质相互作用组学的发展。     

邻近标记在蛋白质组学中的发展及应用

人体内各种复杂的生命活动离不开蛋白质之间的相互作用。这种相互作用具有瞬时性和结合力弱等特点,并受到多种动态调节,特别是蛋白质翻译后修饰（post-translation modifications, PTM）。传统的亲和质谱检测方法存在蛋白纯化的局限性,在高效检测到动态变化方面存在不足。邻近标记是一种能够给与靶蛋白质瞬时靠近,或者互作（邻近）的蛋白质加上生物素的技术,它与质谱检测技术的联合使用能检测细胞过程中弱的、瞬时的蛋白质相互作用,有效解决上述问题。本文综述了基于生物素的邻近标记方法的发展现状,从依赖于融合序列的生物素标记开始,依次介绍有关生物素连接酶、过氧化物酶及其进化后的2代标记方法等经典生物素标记的方法和原理,比较各个方法间的差异和优缺点;也列举了一些近年来新出现的标记方法,如将生物素连接酶进行拆分、鉴定蛋白质在不同复合物中功能的方法、抗体靶向的标记方法,以及其他来源的生物素连接酶突变体,例如枯草芽孢杆菌（Bacillus subtilis）的C端氨基酸突变的生物素连接酶,能够应用在苍蝇和蠕虫中的生物素连接酶突变体。本文对这些方法进行归纳总结,旨在为初步接触该领域的科研工作者提供参考,同时也希望能够提供一些新的思路,推动蛋白质相互作用组学的发展。     

Proximity Dependent Biotinylation: Key Enzymes and Adaptation to Proteomics Approaches

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Highlights

• •Proximity-dependent biotinylation (PDB) approaches involve fusion of a bait with an enzyme.
• •BioID (biotin protein ligase) and APEX (peroxidase) are distinct enzymes used in PDB.
• •Past, present and future development and applications of PDB are discussed.
• •We review labeling mechanisms and kinetics to provide guidance for experimental design.
• •We discuss controls and considerations for data interpretation.

     

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.     

Protein Detection Methods in Proteomics Research

In proteomics research chemical as well as physical methods are used to detect proteins subsequently to their separation. Physical methods are mostly applied after chromatography. They are either based on spectroscopy like light absorption at certain wavelengths or mass determination of peptides and their fragments with mass spectrometry. Chemical methods are used after two-dimensional electrophoresis and employ staining with organic dyes, metal chelates, fluorescent dyes, complexing with silver, or pre-labeling with fluorophores. In some cases autoradiography is still used. Since all of these techniques are very different in terms of sensitivity, their usefulness for quantitative determinations varies significantly. This review will describe the various protein detection methods applied to electrophoresis gels.     

Deciphering Spatial Protein–Protein Interactions in Brain Using Proximity Labeling

Cellular biomolecular complexes including protein–protein, protein–RNA, and protein–DNA interactions regulate and execute most biological functions. In particular in brain, protein–protein interactions (PPIs) mediate or regulate virtually all nerve cell functions, such as neurotransmission, cell–cell communication, neurogenesis, synaptogenesis, and synaptic plasticity. Perturbations of PPIs in specific subsets of neurons and glia are thought to underly a majority of neurobiological disorders. Therefore, understanding biological functions at a cellular level requires a reasonably complete catalog of all physical interactions between proteins. An enzyme-catalyzed method to biotinylate proximal interacting proteins within 10 to 300 nm of each other is being increasingly used to characterize the spatiotemporal features of complex PPIs in brain. Thus, proximity labeling has emerged recently as a powerful tool to identify proteomes in distinct cell types in brain as well as proteomes and PPIs in structures difficult to isolate, such as the synaptic cleft, axonal projections, or astrocyte–neuron junctions. In this review, we summarize recent advances in proximity labeling methods and their application to neurobiology.     

蛋白质组学研究中的无标记定量方法

蛋白质定量是探索疾病发生发展状况和寻找新药靶标的重要手段.该领域最常用的技术是比较染色后的二维凝胶上蛋白点的光密度值或综合同位素标记后的质谱峰强度方法.但此二者的样品处理方法都比较麻烦,不利于进行大规模蛋白质组的定量研究.最近几年出现了利用质谱数据进行无标记定量的方法, 根据数据类型这些方法可以分为2类：基于鉴定蛋白的肽段数的方法和基于质谱峰强度的方法,在高通量大规模蛋白组定量研究中有很大优势.本综述主要介绍了这2类无标记定量方法的模型及优缺点,并比较了2类方法的灵敏度和准确度.肽段计数方法在检测蛋白丰度变化时更灵敏,而峰面积强度在评估蛋白比率时更准确.     

Proteomics for Protein Expression Profiling in Neuroscience

As the technology of proteomics moves from a theoretical approach to a practical reality, neuroscientists will have to determine the most appropriate applications for this technology. Neuroscientists will have to surmount difficulties particular to their research, such as limited sample amounts, heterogeneous cellular compositions in samples, and the fact that many proteins of interest are rare, hydrophobic proteins. This review examines protein isolation and protein fractionation and separation using two-dimensional electrophoresis (2-DE) and mass spectrometry proteomic methods. Methods for quantifying relative protein expression between samples (e.g., 2-DIGE, and ICAT) are also described. The coverage of the proteome, ability to detect membrane proteins, resource requirements, and quantitative reliability of different approaches is also discussed. Although there are many challenges in proteomic neuroscience, this field promises many rewards in the future.     

Proteomics of Protein Secretion by Aggregatibacter actinomycetemcomitans

The extracellular proteome (secretome) of periodontitis-associated bacteria may constitute a major link between periodontitis and systemic diseases. To obtain an overview of the virulence potential of Aggregatibacter actinomycetemcomitans, an oral and systemic human pathogen implicated in aggressive periodontitis, we used a combined LC-MS/MS and bioinformatics approach to characterize the secretome and protein secretion pathways of the rough-colony serotype a strain D7S. LC-MS/MS revealed 179 proteins secreted during biofilm growth. Further to confirming the release of established virulence factors (e.g. cytolethal distending toxin [CDT], and leukotoxin [LtxA]), we identified additional putative virulence determinants in the secretome. These included DegQ, fHbp, LppC, Macrophage infectivity protein (MIP), NlpB, Pcp, PotD, TolB, and TolC. This finding indicates that the number of extracellular virulence-related proteins is much larger than previously demonstrated, which was also supported by in silico analysis of the strain D7S genome. Moreover, our LC-MS/MS and in silico data revealed that at least Type I, II, and V secretion are actively used to excrete proteins directly into the extracellular space, or via two-step pathways involving the Sec/Tat systems for transport across the inner membrane, and outer membrane factors, secretins and auto-transporters, respectively for delivery across the outer membrane. Taken together, our results provide a molecular basis for further elucidating the role of A. actinomycetemcomitans in periodontal and systemic diseases.     

SELDI蛋白质芯片技术及其应用

随着人类基因组测序计划的完成,鉴定细胞内蛋白质表达、结构、功能及相互作用方式等成为后基因组时代的主要目标之一。为此,需要高通量的蛋白质组学研究的技术和方法。近年来出现的表面增强激光解吸／电离(surface—enhanced laser desorption／ionization,SELDI)蛋白质芯片技术是一种操作简单,方便快捷,样本需要量少,敏感性高,特异性强的高通量的研究蛋白组学的方法,在蛋白质功能分析、肿瘤标志物筛选、药物研发等方面具有广泛的应用前景。     

Characterization of Native Protein Complexes and Protein Isoform Variation Using Size-fractionation-based Quantitative Proteomics

Proteins form a diverse array of complexes that mediate cellular function and regulation. A largely unexplored feature of such protein complexes is the selective participation of specific protein isoforms and/or post-translationally modified forms. In this study, we combined native size-exclusion chromatography (SEC) with high-throughput proteomic analysis to characterize soluble protein complexes isolated from human osteosarcoma (U2OS) cells. Using this approach, we have identified over 71,500 peptides and 1,600 phosphosites, corresponding to over 8,000 proteins, distributed across 40 SEC fractions. This represents >50% of the predicted U2OS cell proteome, identified with a mean peptide sequence coverage of 27% per protein. Three biological replicates were performed, allowing statistical evaluation of the data and demonstrating a high degree of reproducibility in the SEC fractionation procedure. Specific proteins were detected interacting with multiple independent complexes, as typified by the separation of distinct complexes for the MRFAP1-MORF4L1-MRGBP interaction network. The data also revealed protein isoforms and post-translational modifications that selectively associated with distinct subsets of protein complexes. Surprisingly, there was clear enrichment for specific Gene Ontology terms associated with differential size classes of protein complexes. This study demonstrates that combined SEC/MS analysis can be used for the system-wide annotation of protein complexes and to predict potential isoform-specific interactions. All of these SEC data on the native separation of protein complexes have been integrated within the Encyclopedia of Proteome Dynamics, an online, multidimensional data-sharing resource available to the community.The majority of proteins function as part of multiprotein complexes and not as isolated polypeptides. These protein complexes range from simple homodimers to large structures composed of many different polypeptides. Protein complexes vary in their size and shape from small globular dimers, such as 14-3-3 proteins, to large elongated filaments of variable length, such as microtubules. The wide variety of possible protein–protein interactions within multiprotein complexes contributes to the diversity of functions that are involved in cellular processes and regulatory mechanisms.Another important source of functional diversity and regulation is the large number of protein isoforms that may be generated from each gene. Functionally and structurally distinct isoforms can arise via multiple mechanisms, including alternative splicing, post-translational modification (PTM),¹ and proteolytic cleavage. Distinct isoforms can exhibit radically different properties. For example, including or excluding individual exons can either create or remove protein–protein interaction interfaces for binding specific interaction partners. Similarly, phosphorylation, and other PTMs, can either create or remove binding sites for interacting proteins, substrates, or ligands. PTMs can also promote structural changes in proteins and affect catalytic activity.The association of protein isoforms and post-translationally modified factors in multiprotein complexes can influence their subcellular location, activity, and substrate specificity. This can be dynamically regulated to modulate protein complex composition, and hence localization and function, to allow cells to respond to spatial and temporal stimuli. It is therefore important to characterize protein complexes at the level of the protein isoforms and post-translationally modified forms they contain in order to fully decipher the network of signaling and regulatory pathways within cells.Although many types of protein complexes have been studied in detail, in-depth analysis of the composition, dynamics, and isoform association of protein complexes formed in either human cells or model organisms is still not well documented at a system-wide level. The CORUM database, compiled using a variety of information from the literature describing protein interactions and assemblies, currently provides the largest public dataset of protein complexes (1). CORUM contains information relating to ∼1,970 protein complexes identified in human cells. However, these complexes are formed from proteins encoded by only ∼16% of the known human protein-coding genes, indicating that many forms of protein complexes still remain to be identified and characterized (1). Furthermore, the CORUM database does not describe how the protein compositions of the complexes may vary, either dynamically or in different subcellular locations, or how this relates to protein isoforms and PTMs. This illustrates that there is still a major deficit in our knowledge of the structure and functions of cellular protein complexes and how they contribute to biological regulatory mechanisms.The technique that is now most widely used to identify the components of protein complexes is affinity purification of an individual “bait” protein and subsequent analysis of the co-isolated proteins, usually via mass spectrometry (2). Affinity purification can use antibodies specific for an endogenous target protein (3, 4), if available, or, alternatively, can utilize a genetically constructed, epitope-tagged bait protein. The latter procedure is now widely used and is advantageous in that many different complexes can be compared using an identical antibody, or other affinity-purification method, targeted to the tag on the bait (for examples, see Refs. 5–7; for reviews, see Refs. 8 and 9). In contrast, it is harder to directly compare the results from immunoprecipitation of different endogenous protein complexes because each specific antibody that is used has different affinities and properties. Nonetheless, although epitope-tag “pull-down” techniques are now commonly used, they also have limitations. Not least, the addition of epitope tags to the bait can affect protein function and interactions (10, 11).To help determine whether co-purifying proteins detected using pull-down strategies represent specific partner proteins in bona fide complexes or are nonspecific contaminants, we and others have developed quantitative approaches, for example, based on variations of the stable isotope labeling of amino acids in cell culture (12–16). Additional data analysis procedures, including the use of a “super experiment” database that predicts the likelihood of nonspecific protein interactions based on the frequency with which any given protein is co-purified across many separate experiments, can also help to define the composition of protein complexes (17). Nonetheless, affinity purification strategies have a limited ability to distinguish multiple related complexes that may differ with respect to isoforms and PTMs. They are also costly and difficult to implement for large-scale studies to survey cellular complexes, and thus not well suited to study variations in complexes under different cellular growth conditions and responses.For system-wide studies of the composition and dynamics of protein complexes, alternative methods, in addition to immune-affinity purification, are required for convenient separation, characterization, and comparison of cellular protein complexes. To address this, a number of studies have utilized various forms of either column chromatography or native gel electrophoresis in combination with mass-spectrometry-based proteomics. For example, protein complexes have been separated using techniques including blue native polyacrylamide gel electrophoresis (18, 19), ion-exchange chromatography (20), and size-exclusion chromatography (21, 22) prior to MS analysis of proteins in the fractionated complexes. Size-exclusion chromatography (SEC) is a well-established technique used to separate proteins and protein complexes in solution on the basis of their shape/size (rotational cross-section) (23). SEC has been extensively used as an intermediate step in conventional multistep biochemical protein purification strategies. In contrast, SEC has been less commonly combined with mass-spectrometry-based proteomics for the high-throughput characterization of protein complexes. However, this has been demonstrated in previous studies that analyzed native protein complexes in plant chloroplasts (22) or large cytosolic complexes in mammalian cells (21).In this study, we combined native SEC with high-throughput mass-spectrometry-based proteomic analysis to characterize soluble protein complexes isolated from human osteosarcoma cells. Herein we demonstrate the utility and reproducibility of this approach for the system-wide characterization of endogenous, untagged protein complexes and show how it can be used to identify specific protein isoforms and PTMs associated with distinct protein complexes. The resulting data are available to the community in a convenient format in the Encyclopedia of Proteome Dynamics (EPD) (www.peptracker.com/encyclopediaInformation/), a user-friendly, searchable online database.     

蛋白质组学技术在精子蛋白研究中的应用

从蛋白质组学研究的技术手段、蛋白质组学在人类不育及精卵相互识别并结合的机理研究、免疫法开展男性避孕方法的研究及蛋白质组学研究方法在家畜繁殖环节中的应用等几个方面阐述了蛋白质组学在人类生殖及动物繁殖环节相关研究中的重要作用。说明蛋白质组学已经成为生命科学未来发展的主要分支之一,为揭示生命个体的蛋白质动态变化提供了技术手段和理论基础,并将在药物开发,生命活动机理研究等方面发挥巨大作用,也必将会在家畜繁殖学领域发挥其应有的作用。     

邻位连接技术：一种新的高灵敏度蛋白质检测技术

蛋白质组学(proteomics)诞生以来,高效准确的蛋白质检测技术受到越来越多的关注.最近 ,一种高灵敏度的蛋白质检测技术,邻位连接技术(proximity ligation assay, PLA)被建 立.该技术采用核酸适体(aptamer)或单/多克隆抗体 核酸复合物作为邻位连接探针(proximity probes).当一对邻位探针同时识别同一个目标蛋白分子时,它们将在空间位置上相互临近,通过连接反应形成一段可扩增的DNA标签序列,该标签序列能够反映待测蛋白的种类及浓度.该技术将对蛋白质的检测转变为对DNA核酸序列的检测,实现了特殊蛋白质的检测,定量及定位.文章从该方法的产生背景,发展过程,原理以及探针制备等方面对该方法进行了系统的介绍,列举了该方法的几种重要应用,并对该方法在蛋白质组学研究领域的应用前景进行了展望.     

Global Subcellular Characterization of Protein Degradation Using Quantitative Proteomics

Protein degradation provides an important regulatory mechanism used to control cell cycle progression and many other cellular pathways. To comprehensively analyze the spatial control of protein degradation in U2OS osteosarcoma cells, we have combined drug treatment and SILAC-based quantitative mass spectrometry with subcellular and protein fractionation. The resulting data set analyzed more than 74,000 peptides, corresponding to ∼5000 proteins, from nuclear, cytosolic, membrane, and cytoskeletal compartments. These data identified rapidly degraded proteasome targets, such as PRR11 and highlighted a feedback mechanism resulting in translation inhibition, induced by blocking the proteasome. We show this is mediated by activation of the unfolded protein response. We observed compartment-specific differences in protein degradation, including proteins that would not have been characterized as rapidly degraded through analysis of whole cell lysates. Bioinformatic analysis of the entire data set is presented in the Encyclopedia of Proteome Dynamics, a web-based resource, with proteins annotated for stability and subcellular distribution.Targeted protein degradation is an important regulatory mechanism that allows co-ordination of cellular pathways in response to environmental and temporal stimuli (1). The control of diverse biochemical pathways, including cell cycle progression and the response to DNA damage, is mediated, at least in part, by dynamic alterations in protein degradation (2). Previous large scale proteomics studies in mammalian cells have shown that the rate of protein degradation can vary from the timescale of minutes, to essentially infinite stability for metastable proteins (3–8).Most intracellular proteins have similar degradation rates, with a half-life approximating the cell doubling rate. Under 5% of proteins display degradation rates more than threefold faster than the proteome average (3–5, 7). However, degradation rates for individual proteins can change, for example depending on either the cell cycle stage, or signaling events, and can also vary depending on subcellular localization. Disruption of such regulated protein stability underlies the disease mechanisms responsible for forms of cancer, e.g. p53 (9, 10) and the proto-oncogene c-Myc (11).Detection of rapidly degraded proteins can be difficult because of their low abundance. However, advances in mass spectrometry based proteomics have enabled in-depth quantitative analysis of cellular proteomes (12–14). Stable isotope labeling by amino acids in cell culture (SILAC)¹ (15), has been widely used to measure protein properties such as abundance, interactions, modifications, turnover, and subcellular localization under different conditions (16). Subcellular fractionation and protein size separation are also powerful techniques that enhance in-depth analysis of cellular proteomes. Not only do these fractionation techniques increase total proteome coverage, they also provide biological insight regarding how protein behavior differs between subcellular compartments. For example, subcellular fractionation has highlighted differences in the rate of ribosomal protein degradation between the nucleus and cytoplasm, (7, 17). Other studies have also demonstrated the benefit of in-depth subcellular fractionation and created methods for the characterization of how proteomes are localized in organelles (18–20).In this study we have used SILAC-based quantitative mass spectrometry combined with extensive subcellular and protein-level fractionation to identify rapidly degraded proteins in human U2OS cells. We provide a proteome level characterization of a major feedback mechanism involving inhibition of protein translation when the proteasome is inhibited. We also present the Encyclopedia of Proteome Dynamics, a user-friendly online resource providing access to the entire data set.     

Temporal Quantitative Proteomics of mGluR-induced Protein Translation and Phosphorylation in Neurons

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Highlights

• •Integrated phosphoproteomics and analyses of newly synthesized proteins in neurons.
• •Resource of temporal mGluR-induced signaling pathways upon DHPG stimulation.
• •Validation of PKC, MAPK1, CAMKIIa, and CDK2 in mGluR-activation and signaling.
• •Validation of Intersectin-1 in DHPG-induced AMPAR internalization.

     

蛋白质检测新技术——邻位连接技术及初步应用

邻位连接技术（proximity ligation assay,PLA）,是新研发的一项高灵敏度的蛋白质体外分析技术。该方法利用一对邻位探针（proximity probes）对靶分子进行双识别,通过连接反应产生可扩增的检测信号,以实时 PCR进行放大和检测,将对蛋白质的检测转变成为对DNA的检测,实现痕量蛋白的分析,具有极高的检测灵敏度和特异性。综述了邻位连接技术的原理、研究进展以及该技术在蛋白质分析及疾病诊断领域的初步应用。     

家蝇幼虫血淋巴蛋白组及血淋巴中热稳定蛋白研究

目的 初步研究家蝇幼虫血淋巴蛋白组学特征及其中的热稳定蛋白.方法 使用破壁法提取三龄幼虫血淋巴原液,设置全血淋巴组、沸水浴处理组,采用不同pH范围双向电泳胶条,分析血淋巴中蛋白的pH、分子量分布特点,采用二级质谱对蛋白点进行分子鉴定.结果 家蝇幼虫血淋巴中蛋白的分子量主要分布在10 kDa～66kDa之间,采用pH3～10的IPG胶,检测到286个蛋白点,采用pH4～7的IPG胶,测到601个蛋白点;血淋巴经沸水浴处理后,检测到41个蛋白点,分子量低于30 kDa,比未处理组减少了93.1％,对其中11个蛋白点进行质谱分析,鉴定出4个功能蛋白,包括存储蛋白、气味结合蛋白、铁蛋白重链样蛋白和铁蛋白2轻链蛋白同系物.结论 双向电泳能很好地分析家蝇幼虫血淋巴中的蛋白,血淋巴中的蛋白等电点主要分布在pH4～7之间;血淋巴经沸水浴处理后可去掉大量变性蛋白,其上清中可能包含耐热性较好的功能蛋白.