蛋白质组研究新前沿：定量蛋白质组学

在过去几年里,蛋白质组研究取得了令人鼓舞的进展,2DE-MS途径的自动化,多维色谱整合串联质谱的使用,弥补了一些用双向凝胶电泳分离蛋白质的技术缺陷;从稳定同位素标记到ICAT战略的提出,为准确定量在细胞或组织中发挥重要调节功能的低丰度蛋白质提供了一个较为理想的方法。同时,蛋白质芯片技术的不断发展,也极大的丰富了定量蛋白质组学的研究。就定量蛋白质组学及其相关技术研究进展作一简要综述。     

干细胞的蛋白质组研究

干细胞研究和蛋白质组研究同属于21世纪生命科学的热点领域。将蛋白质组学技术应用于干细胞的研究,能够为了解干细胞提供蛋白质水平的信息,揭示干细胞的增殖、定向分化和迁移的机制,为人们更好地将干细胞技术应用于组织工程、基因治疗及药物开发等领域奠定基础。     

蛋白质组与蛋白质组学

１９９４年澳大利有针对后基因组时代研究趋势,提出了蛋白质组和蛋白质组学的新概念。即把基因组所编码的所有蛋白为研究对象,直接探讨基因、蛋白的功能。其核心技术包括双向电泳、质谱分析、生物信息学等。该技术在探索疾病发生,寻找新药等方面取得越来越广泛的应用。     

微生物蛋白质组研究进展

本文概括性地叙述蛋白质组相关的基本概念,主要蛋白质组技术,微生物学蛋白质、比较蛋白质组、功能蛋白质组研究进展和蛋白质组技术在细胞微生物学研究中的应用。     

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。     

蛋白质修饰组学在肉品质研究中的应用

蛋白质翻译后修饰(Post-translational modifications, PTMs)在生命体中具有十分重要的作用。生命有机体中常见的PTMs有磷酸化、酰化、糖基化、泛素化、乙酰化、氧化和甲基化等。文章主要介绍了蛋白质组学在肉制品科学方面的应用、PTMs的主要内容以及分析蛋白修饰特性常见技术的发展,总结了PTMs对肌肉生理特性的影响和蛋白质组学方法在肉质蛋白质修饰研究中的重要性及前景,讨论了利用蛋白质修饰组学技术研究肌肉熟化过程中品质特性变化的特点。     

定量蛋白质组同位素标记技术及应用

定量蛋白质组学是对蛋白质组进行精确的定量和鉴定的学科,突破了传统蛋白质组研究集中于对蛋白质的分离和鉴定,着重于定性定量解析细胞蛋白质的动态变化信息,更真实地反映了细胞功能、过程机制等综合信息。以同位素为内标的质谱分析新技术的提出,显示出可同时自动鉴定和精确定量的能力,代表了目前定量蛋白质组研究的主要发展方向。对近年来定量蛋白质组学同位素标记技术和应用研究所取得的重要进展以及最新的发展动态进行了综述。     

基于质谱的蛋白质N末端乙酰化程度定量方法的研究

随着质谱技术及各种定量方法的不断完善和发展,定量蛋白质组学的方法不断地被应用到各类生物学研究中。蛋白质组学定性定量数据的处理主要通过一些多功能的商业化或者开源软件来进行,如常用的数据分析软件Proteome Discoverer和Maxquant。但是在通过化学标记对蛋白质N末端乙酰化程度进行定量这一方面,Proteome Discoverer和Maxquant在一定程度上存在准确性不高和完整度不够的问题。于是本研究针对自己的实验特点,通过Java算法编写了相应的定量程序Acequant来完成N末端乙酰化程度的相对定量。本研究将该程序在已有相关报道的He La cell上进行了验证,Acequant共定量到1 587个蛋白质N末端,而Proteome Discoverer和Maxquant分别只定量到42个和306个N末端。同时,手动验证原始图谱也证实了Acequant定量的准确性更好。于是,本研究将此方法进一步应用到秀丽隐杆线虫N末端乙酰化的研究中,并初步发现了线虫整体的N末端乙酰化状态,为进一步的N末端研究提供了支持。     

定量蛋白质组学中的同位素标记技术

定量蛋白质组学的目的是对复杂的混合体系中所有的蛋白质进行鉴定,并对蛋白质的量及量的变化进行准确的测定,是当前系统生物科学研究的重要内容。近年来,由于质谱技术和生物信息学的进步,定量蛋白质组学在分析蛋白质组或亚蛋白质组方面已取得了令人瞩目的成就,但其最显著的成就应该归功于稳定同位素标记技术的应用。该技术使用针对某一类蛋白具有特异性的化学探针来标记目的蛋白质或肽段,同时化学探针要求含有用以精确定量的稳定同位素信号。在此基础上,实现了对表达的蛋白质差异和翻译后修饰的蛋白质差异进行精确定量分析。综述了在定量蛋白质组学中使用的各种同位素标记技术及其应用。     

The methods of quantitative proteomics

In modern science proteomic analysis is inseparable from other fields of systemic biology. Possessing huge resources quantitative proteomics operates colossal information on molecular mechanisms of life. Advances in proteomics help researchers to solve complex problems of cell signaling, posttranslational modification, structure and funciotnal homology of proteins, molecular diagnostics etc. More than 40 various methods have been developed in proteomics for quantitative analysis of proteins. Although each method is unique and has certain advantages and disadvantages all these use various isotope labels (tags). In this review we will consider the most popular and effective methods employing both chemical modifications of proteins and also metabolic and enzymatic methods of isotope labeling.     

Chemical proteomics and its impact on the drug discovery process

Despite the rapid growth of postgenomic data and fast-paced technology advancement, drug discovery is still a lengthy and difficult process. More effective drug design requires a better understanding of the interaction between drug candidates and their targets/off-targets in various situations. The ability of chemical proteomics to integrate a multiplicity of disciplines enables the direct analysis of protein activities on a proteome-wide scale, which has enormous potential to facilitate drug target elucidation and lead drug verification. Over recent years, chemical proteomics has experienced rapid growth and provided a valuable method for drug target identification and inhibitor discovery. This review introduces basic concepts and technologies of different popular chemical proteomic approaches. It also covers the essential features and recent advances of each approach while underscoring their potentials in drug discovery and development.     

Amino acid-coded tagging approaches in quantitative proteomics

To improve the efficiency, accuracy, reproducibility, throughput and proteome coverage of mass spectrometry-based quantitative approaches, both in vitro and in vivo tagging of particular amino acid residues of cellular proteins have been introduced to assist mass spectrometry for global-scale comparative studies of differentially expressed proteins/modifications between different biologically relevant cell states or cells at different pathological states. The basic features of these methods introduce pair-wise isotope signals of each individual peptide containing a particular type of tagged amino acid (amino acid-coded mass tagging) that originated from different cell states. In this review, the applications of major amino acid-coded mass tagging-based quantitative proteomics approaches, including isotope-coded affinity tag, isobaric tags for relative and absolute quantification (iTRAQ?) and stable isotope labeling by amino acids in cell culture are summarized in the context of their respective strengths/weakness in identifying those differentially expressed or post-translational modified proteins regulated by particular cellular stress on a genomic scale in a high-throughput manner. Importantly, these gel-free, in-spectra quantitative mechanisms have been further explored to identify/characterize large-scale protein–protein interactions involving various functional pathways. Taken together, the information about quantitative proteome changes, including multiple regulated proteins and their interconnected relationships, will provide an important insight into the molecular mechanisms, where novel targets for diagnosis and therapeutic intervention will be identified.     

Recent advances in quantitative and chemical proteomics for autophagy studies

Macroautophagy/autophagy is an evolutionarily well-conserved cellular degradative process with important biological functions that is closely implicated in health and disease. In recent years, quantitative mass spectrometry-based proteomics and chemical proteomics have emerged as important tools for the study of autophagy, through large-scale unbiased analysis of the proteome or through highly specific and accurate analysis of individual proteins of interest. At present, a variety of approaches have been successfully applied, including (i) expression and interaction proteomics for the study of protein post-translational modifications, (ii) investigating spatio-temporal dynamics of protein synthesis and degradation, and (iii) direct determination of protein activity and profiling molecular targets in the autophagic process. In this review, we attempted to provide an overview of principles and techniques relevant to the application of quantitative and chemical proteomics methods to autophagy, and outline the current landscape as well as future outlook of these methods in autophagy research.     

Use of proteomics for the identification of novel drug targets in brain diseases

In spite of the rapid advances in the development of the new proteomic technologies, there are, to date, relatively fewer studies aiming to explore the neuronal proteome. One of the reasons is the complexity of the brain, which presents high cellular heterogeneity and a unique subcellular compartmentalization. Therefore, tissue fractionation of the brain to enrich proteins of interest will reduce the complexity of the proteomics approach leading to the production of manageable and meaningful results. In this review, general considerations and strategies of proteomics, the advantages and challenges to exploring the neuronal proteome are described and summarized. In addition, this article presents an overview of recent advances of proteomic technologies and shows that proteomics can serve as a valuable tool to globally explore the changes in brain proteome during various disease states. Understanding the molecular basis of brain function will be extremely useful in identifying novel targets for the treatment of brain diseases.     

定量蛋白质组学分析ClpS在分枝杆菌耐药中的功能

ClpS是原核生物蛋白质降解复合物ClpAPS的重要组成成分,它可以识别某些特定的氨基酸序列并将其呈递给ClpAP以促进其降解。同时,ClpS也抑制了其他蛋白质底物的降解。本研究通过在耻垢分枝杆菌中过度表达ClpS,发现所构建的重组菌株提高了利福平的抗药性。应用定量蛋白质组学技术,我们系统地分析了过度表达ClpS对于细菌蛋白质组的影响,并推测出细菌抗利福平的分子机制:ClpS促进稳态的调整、促进药物沉降以及加速药物代谢。本研究首次通过改变细菌降解复合物的相关蛋白的表达增加细菌的抗药性,并证明蛋白质组学技术是细菌的抗药性研究以及耐药株筛选的重要工具。     

Understanding signal transduction through functional proteomics

The study of signal transduction provides fundamental information regarding the regulation of all biologic processes that support the normal function of life. Functional proteomics, a rapidly emerging discipline that aims to understand the expression, function and regulation of the entire set of proteins in a given cell type, tissue or organism, offers unprecedented opportunity for signal transduction research in terms of understanding cellular behavior and regulation at the systems level. Indeed, swift progress in the area of proteomics has demonstrated the major impact of proteomic approaches on signal transduction and biomedical research. In this review, recent and innovative applications of functional proteomics in determining changes in protein contents, modifications, activities and interactions underpinning signaling transduction pathways are discussed.     

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.     

Advances in fungal proteomics

Proteomics, the global analysis of proteins, will contribute greatly to our understanding of gene function in the post-genomic era. This review summarizes recent developments in fungal proteomics and also generalizes protocols for sample preparation from plant pathogenic fungi. Challenges and future perspectives of proteomics are discussed as well.