Proteome analysis of Epstein-Barr virus-transformed B-lymphoblasts and the proteome database

The proteome is the entire protein complement of the genome expressed in a particular cell, tissue, or organism at a given time under a specific set of environmental conditions. Proteomics is a combinatorial methodology to comprehensively analyze the proteome. The general protocol of the expression proteomics consists of advanced methods of high-resolution protein separation, high-quality image analysis and high-throughput protein identification. Although Epstein-Barr virus-transformed B-lymphoblastoid cell lines (LCLs) have long been believed to be immortalized, recent studies have provided ample evidence that a large proportion of LCLs have limited life spans due to shortening of telomeres, and that part of them are truly immortalized by developing strong telomerase activity to maintain telomeres. Differential proteome analysis of pre- and post-immortal LCLs would provide a powerful tool to analyze proteins participating in the process of immortalization. We focus in this review on cumulative data of proteomic information on pre- and post-immortal LCLs.     

酵母双杂交技术及其在蛋白质组研究中的应用

蛋白质组学是后基因组时代出现的一个新兴的研究领域,它的主要任务是识别鉴定细胞,组织或机体的全部蛋白质,并分析蛋白质的功能及其模式。因此,揭示蛋白质组中蛋白质间的相互作用关系也是蛋白质组学的重要内容之一。酵母双杂交技术是用来检测蛋白质间是否相互作用的一个非常有效的手段,该技术在酵母蛋白质组研究中的初步成功应用,表明它有望在人类蛋白质且研究中发挥重要作用。     

种子蛋白质组的研究进展

蛋白质组学是通过对全套蛋白质动态的研究,来阐明生物体、组织、细胞和亚细胞全部蛋白质的表达模式及功能模式。大量可用的核苷酸序列信息和灵敏高速的质谱鉴定技术,使得蛋白质组学方法为分析模式植物和农作物的复杂功能开辟了新的途径。目前,种子蛋白质组研究主要集中在两个方面：一方面是鉴定尽可能多的蛋白,以创建种子特定生命时期的蛋白质组参照图谱;另一方面主要集中在差异蛋白质组,通过比较分析不同蛋白质组,以探明关键功能蛋白。该文综述了近年来种子蛋白质组的研究进展,内容包括种子发育过程中蛋白质组的变化,与种子休眠/萌发相关的蛋白质组、翻译后修饰蛋白质组、细胞与亚细胞差异蛋白质组以及环境因子对种子蛋白质组的影响;并对种子蛋白质组研究的热点问题进行了展望。     

种子蛋白质组的研究进展

蛋白质组学是通过对全套蛋白质动态的研究, 来阐明生物体、组织、细胞和亚细胞全部蛋白质的表达模式及功能模式。大量可用的核苷酸序列信息和灵敏高速的质谱鉴定技术, 使得蛋白质组学方法为分析模式植物和农作物的复杂功能开辟了新的途径。目前, 种子蛋白质组研究主要集中在两个方面: 一方面是鉴定尽可能多的蛋白, 以创建种子特定生命时期的蛋白质组参照图谱; 另一方面主要集中在差异蛋白质组, 通过比较分析不同蛋白质组, 以探明关键功能蛋白。该文综述了近年来种子蛋白质组的研究进展, 内容包括种子发育过程中蛋白质组的变化, 与种子休眠/萌发相关的蛋白质组、翻译后修饰蛋白质组、细胞与亚细胞差异蛋白质组以及环境因子对种子蛋白质组的影响; 并对种子蛋白质组研究的热点问题进行了展望。     

Bioinformatics meets proteomics--bridging the gap between mass spectrometry data analysis and cell biology

Proteomics research programs typically comprise the identification of protein content of any given cell, their isoforms, splice variants, post-translational modifications, interacting partners and higher-order complexes under different conditions. These studies present significant analytical challenges owing to the high proteome complexity and the low abundance of the corresponding proteins, which often requires highly sensitive and resolving techniques. Mass spectrometry plays an important role in proteomics and has become an indispensable tool for molecular and cellular biology. However, the analysis of mass spectrometry data can be a daunting task in view of the complexity of the information to decipher, the accuracy and dynamic range of quantitative analysis, the availability of appropriate bioinformatics software and the overwhelming size of data files. The past ten years have witnessed significant technological advances in mass spectrometry-based proteomics and synergy with bioinformatics is vital to fulfill the expectations of biological discovery programs. We present here the technological capabilities of mass spectrometry and bioinformatics for mining the cellular proteome in the context of discovery programs aimed at trace-level protein identification and expression from microgram amounts of protein extracts from human tissues.     

Current trends in computational inference from mass spectrometry-based proteomics

Mass spectrometry offers a high-throughput approach to quantifying the proteome associated with a biological sample and hence has become the primary approach of proteomic analyses. Computation is tightly coupled to this advanced technological platform as a required component of not only peptide and protein identification, but quantification and functional inference, such as protein modifications and interactions. Proteomics faces several key computational challenges such as identification of proteins and peptides from tandem mass spectra as well as their quantitation. In addition, the application of proteomics to systems biology requires understanding the functional proteome, including how the dynamics of the cell change in response to protein modifications and complex interactions between biomolecules. This review presents an overview of recently developed methods and their impact on these core computational challenges currently facing proteomics.     

Proteome of a methicillin-resistant Staphylococcus aureus clinical strain of sequence type ST398

Proteomics is a powerful tool to analyze the differences in gene expression of bacterial strains. Staphylococcus aureus has long been recognized as an important pathogen in human disease. In order to investigate this pathogen, the proteome of a clinical methicillin-resistant S. aureus (MRSA) strain of the sequence type ST398 was determined using 2-DE. Using 2-DE we obtained a total of 105 spots the MRSA strain. Furthermore in correlation with bioinformatic databases, they allowed accurate identification and characterization of proteins, resulting in 227 identified proteins. There were found proteins related to basic function of the cell, but also proteins related to virulence like catalase, specific of S. aureus species, and proteins related to antibiotic resistance. Proteins associated with antibiotic resistance or virulence factors are related to genomic databases. The most abundant classes identified involved glycolysis, energy production, one-carbon metabolism, and oxidation-reduction process, all of which reflect an active metabolism. These results highlight the importance of proteomics to deepen in the knowledge of protein expression of MRSA strain of the lineage ST398, microorganism with diverse and important resistance mechanisms. With this proteome map we have an essential tool for a better understanding of this pathogen and providing new data for protein databases. This article is part of a Special Issue entitled: Proteomics: The clinical link.     

Two-dimensional gel electrophoresis in bacterial proteomics

Two-dimensional gel electrophoresis (2-DE) is a gel-based technique widely used for analyzing the protein composition of biological samples. It is capable of resolving complex mixtures containing more than a thousand protein components into individual protein spots through the coupling of two orthogonal biophysical separation techniques: isoelectric focusing (first dimension) and polyacrylamide gel electrophoresis (second dimension). 2-DE is ideally suited for analyzing the entire expressed protein complement of a bacterial cell: its proteome. Its relative simplicity and good reproducibility have led to 2-DE being widely used for exploring proteomics within a wide range of environmental and medically-relevant bacteria. Here we give a broad overview of the basic principles and historical development of gel-based proteomics, and how this powerful approach can be applied for studying bacterial biology and physiology. We highlight specific 2-DE applications that can be used to analyze when, where and how much proteins are expressed. The links between proteomics, genomics and mass spectrometry are discussed. We explore how proteomics involving tandem mass spectrometry can be used to analyze (post-translational) protein modifications or to identify proteins of unknown origin by de novo peptide sequencing. The use of proteome fractionation techniques and non-gel-based proteomic approaches are also discussed. We highlight how the analysis of proteins secreted by bacterial cells (secretomes or exoproteomes) can be used to study infection processes or the immune response. This review is aimed at non-specialists who wish to gain a concise, comprehensive and contemporary overview of the nature and applications of bacterial proteomics.     

Plant proteome analysis: a 2006 update

This 2006 'Plant Proteomics Update' is a continuation of the two previously published in 'Proteomics' by 2004 (Canovas et al., Proteomics 2004, 4, 285-298) and 2006 (Rossignol et al., Proteomics 2006, 6, 5529-5548) and it aims to bring up-to-date the contribution of proteomics to plant biology on the basis of the original research papers published throughout 2006, with references to those appearing last year. According to the published papers and topics addressed, we can conclude that, as observed for the three previous years, there has been a quantitative, but not qualitative leap in plant proteomics. The full potential of proteomics is far from being exploited in plant biology research, especially if compared to other organisms, mainly yeast and humans, and a number of challenges, mainly technological, remain to be tackled. The original papers published last year numbered nearly 100 and deal with the proteome of at least 26 plant species, with a high percentage for Arabidopsis thaliana (28) and rice (11). Scientific objectives ranged from proteomic analysis of organs/tissues/cell suspensions (57) or subcellular fractions (29), to the study of plant development (12), the effect of hormones and signalling molecules (8) and response to symbionts (4) and stresses (27). A small number of contributions have covered PTMs (8) and protein interactions (4). 2-DE (specifically IEF-SDS-PAGE) coupled to MS still constitutes the almost unique platform utilized in plant proteome analysis. The application of gel-free protein separation methods and 'second generation' proteomic techniques such as multidimensional protein identification technology (MudPIT), and those for quantitative proteomics including DIGE, isotope-coded affinity tags (ICAT), iTRAQ and stable isotope labelling by amino acids in cell culture (SILAC) still remains anecdotal. This review is divided into seven sections: Introduction, Methodology, Subcellular proteomes, Development, Responses to biotic and abiotic stresses, PTMs and Protein interactions. Section 8 summarizes the major pitfalls and challenges of plant proteomics.     

Plant proteome analysis: a 2004-2006 update

Since the appearance of the review entitled "Plant Proteome Analysis" in Proteomics in February 2004 (Cánovas, F. M., Dumas-Gaudot, E., Recorbert, G., Jorrín, J. et al., Proteomics 2004, 4, 285-298), about 200 original articles focusing on plant proteomics have been published. Although this represents less than 1% of the global proteomics output during this period, it nevertheless reflects an increase in activity over the period 1999-2004. These papers concern the proteome of at least 35 plant species but have concentrated mainly on thale cress (Arabidopsis thaliana) and rice (Oryza sativa). The scientific objectives have ranged from a proteomic analysis of organs, tissues, cell suspensions, or subcellular fractions to the study of plant development and response to various stresses. A number of contributions have covered PTMs and protein interactions. The dominant analytical platform has been 2-DE coupled to MS, but "second generation" techniques such as DIGE, multidimensional protein identification technology, isotope-coded affinity tags, and stable isotope labeling by amino acids in cell culture have begun to make an impact. This review aims to provide an update of the contribution of proteomics to plant biology during the period 2004-2006, and is divided into six sections: introduction, subcellular proteomes, plant development, responses to biotic and abiotic stresses, PTMs, and protein interactions. The conclusions summarize a view of the major pitfalls and challenges of plant proteomics.     

Update and challenges on proteomics in rice

Rice is not only an important agricultural resource but also a model plant for biological research. Our previous review highlighted different aspects of the construction of rice proteome database, cataloguing rice proteins of different tissues and organelle, differential proteomics using 2-DE and functional characterization of some of the proteins identified (Komatsu, S., Tanaka, N., Proteomics 2005, 5, 938-949). In this review, the powerfulness and weaknesses of proteomic technologies as a whole and limitations of the currently used techniques in rice proteomics are discussed. The information obtained from these techniques regarding proteins modification, protein-protein interaction and the development of new methods for differential proteomics will aid in deciphering more precisely the functions of known and/or unknown proteins in rice.     

Avian proteomics: advances, challenges and new technologies

Proteomics is defined as an analysis of the full complement of proteins of a cell or tissue under given conditions. Avian proteomics, or more specifically chicken proteomics, has focussed on the study of individual tissues and organs of interest to specific researchers. Researchers have looked at skeletal muscle and growth, and embryonic development and have performed initial studies in avian disease. Traditional proteomics involves identifying and cataloguing proteins in a cell and identifying relative changes in populations between two or more states, be that physiological or disease-induced states. Recent advances in proteomic technologies have included absolute quantification, proteome simplification and the ability to determine the turnover of individual proteins in a global context. This review discusses the current developments in this relatively new field, new technologies and how they may be applied to biological questions, and the challenges faced by researchers in this ever-expanding and exciting field.     

The current state of microbial proteomics: where we are and where we want to go

Proteomics allows the assessment of cellular processes in an unprecedented scale by providing a comprehensive quantitative and qualitative overview of the protein content of a cell. Consequently, proteomics has been employed to investigate a multitude of bacterial processes ranging from the analysis of environmental communities, identification of virulence factors to the proteome-guided optimization of production strains. Proteomics has, in short, become an indispensable tool for the global analysis of bacterial physiology. Nonetheless, challenges exist, especially in the accurate prediction of phenotypic consequences based on any given proteome composition. In this review, we will give an overview of current highlights in the area of microbial proteomics, discuss some current challenges and present new developments that may help in overcoming them.     

蛋白质组学研究相关技术及进展

蛋白质组学以蛋白质组为研究对象,应用相关研究技术,从整体水平上来认识蛋白的存在及活动方式。随着人类基因组计划的完成,蛋白质组学的研究也得到了快速发展,与蛋白质组学研究相关的一些技术也日益得到完善和提高。简要综述了近年来蛋白质组学研究中最为重要的样品制备、蛋白质分离、蛋白质鉴定等技术及研究进展。     

Mascot file parsing and quantification (MFPaQ), a new software to parse, validate, and quantify proteomics data generated by ICAT and SILAC mass spectrometric analyses: application to the proteomics study of membrane proteins from primary human endothelial cells

Proteomics strategies based on nanoflow (nano-) LC-MS/MS allow the identification of hundreds to thousands of proteins in complex mixtures. When combined with protein isotopic labeling, quantitative comparison of the proteome from different samples can be achieved using these approaches. However, bioinformatics analysis of the data remains a bottleneck in large scale quantitative proteomics studies. Here we present a new software named Mascot File Parsing and Quantification (MFPaQ) that easily processes the results of the Mascot search engine and performs protein quantification in the case of isotopic labeling experiments using either the ICAT or SILAC (stable isotope labeling with amino acids in cell culture) method. This new tool provides a convenient interface to retrieve Mascot protein lists; sort them according to Mascot scoring or to user-defined criteria based on the number, the score, and the rank of identified peptides; and to validate the results. Moreover the software extracts quantitative data from raw files obtained by nano-LC-MS/MS, calculates peptide ratios, and generates a non-redundant list of proteins identified in a multisearch experiment with their calculated averaged and normalized ratio. Here we apply this software to the proteomics analysis of membrane proteins from primary human endothelial cells (ECs), a cell type involved in many physiological and pathological processes including chronic inflammatory diseases such as rheumatoid arthritis. We analyzed the EC membrane proteome and set up methods for quantitative analysis of this proteome by ICAT labeling. EC microsomal proteins were fractionated and analyzed by nano-LC-MS/MS, and database searches were performed with Mascot. Data validation and clustering of proteins were performed with MFPaQ, which allowed identification of more than 600 unique proteins. The software was also successfully used in a quantitative differential proteomics analysis of the EC membrane proteome after stimulation with a combination of proinflammatory mediators (tumor necrosis factor-alpha, interferon-gamma, and lymphotoxin alpha/beta) that resulted in the identification of a full spectrum of EC membrane proteins regulated by inflammation.     

Expanding the proteome two-dimensional gel electrophoresis reference map of human renal cortex by peptide mass fingerprinting

Proteomics methodologies hold great promise in basic renal research and clinical nephrology. The classical approach for proteomic analysis couples two-dimensional gel electrophoresis (2-DE) with protein identification by mass spectrometry, to produce more global information regarding normal protein expression and alterations in different physiological and pathological states. In this report we have expanded the identification of proteins in the renal cortex, improving the previously published map to facilitate the study of different diseases affecting the human kidney. About 250 spots were analyzed by peptide mass fingerprinting, 89 proteins and 74 isoforms for some of them were identified and implemented in the normal human renal cortex 2-DE reference map. This more comprehensive view of the proteome of the human renal cortex could be of invaluable help to the differential proteomic display of urological diseases.     

Mapping of alkaline proteins in bovine skeletal muscle

In agricultural sciences, proteomics has become the new hope for analyzing the meat quality traits that are closely related to the skeletal muscle traits. 2-DE muscle maps of many species have been recently reported and used to find molecular markers of meat quality traits. However, one limitation of 2-DE based analyses is due to the limited alkaline protein separation. Considering this problem, there is a need to use recent advances that have markedly improved the 2-DE based analysis of alkaline proteins. Hence, the present study provides additional information concerning the alkaline proteome of bovine skeletal muscle by using an appropriate protocol to characterize proteins over the entire range of pH 7-11. A total of 32 distinct gene products corresponding to 60 protein spots were identified by PMF and grouped in seven categories according to their main function. This 2-D map will contribute to muscle proteome studies since a significant portion of proteins is in the alkaline pH range.     

Proteome signatures—how are they obtained and what do they teach us?

The dawn of a new Proteomics era, just over a decade ago, allowed for large-scale protein profiling studies that have been applied in the identification of distinctive molecular cell signatures. Proteomics provides a powerful approach for identifying and studying these multiple molecular markers in a vast array of biological systems, whether focusing on basic biological research, diagnosis, therapeutics, or systems biology. This is a continuously expanding field that relies on the combination of different methodologies and current advances, both technological and analytical, which have led to an explosion of protein signatures and biomarker candidates. But how are these biological markers obtained? And, most importantly, what can we learn from them? Herein, we briefly overview the currently available approaches for obtaining relevant information at the proteome level, while noting the current and future roles of both traditional and modern proteomics. Moreover, we provide some considerations on how the development of powerful and robust bioinformatics tools will greatly benefit high-throughput proteomics. Such strategies are of the utmost importance in the rapidly emerging field of immunoproteomics, which may play a key role in the identification of antigens with diagnostic and/or therapeutic potential and in the development of new vaccines. Finally, we consider the present limitations in the discovery of new signatures and biomarkers and speculate on how such hurdles may be overcome, while also offering a prospect for the next few years in what could be one of the most significant strategies in translational medicine research.