生物质谱技术在蛋白质组学研究中的应用

随着技术的进步,蛋白质组学的研究重心由最初旨在鉴定细胞或组织内基因组所表达的全部蛋白质转移到从整个蛋白质组水平上阐述包括蛋白翻译后修饰、生物大分子相互作用等反映蛋白质功能的层次。多种质谱离子化技术的突破使质谱技术成为蛋白质组学研究必不可少的手段。质谱技术联合蛋白质组学多角度、深层次探索生命系统分子本质成为现阶段生命科学研究领域的主旋律之一。本文简要综述了肽和蛋白质等生物大分子质谱分析的原理、方式和应用,并对其发展前景做出展望。     

生物质谱及其在蛋白质组学研究中的应用

生物质谱是蛋白质组学研究必不可少的关键技术。近年来,生物质谱在鉴定通量、分辨率和灵敏度等方面均有质的飞跃,从而促进了蛋白质组研究各个领域的飞速发展。本文就生物质谱技术的原理、技术和仪器发展现状,及其在蛋白质组学研究中的应用进展作一简要的综述。     

蛋白质组中蛋白质鉴定技术的研究近况

蛋白质组学的核心内容之一就是蛋白质的鉴定,基于双向凝胶电泳的图象分析技术可以对组织细胞蛋白质表达的量、表观分子量和等电点等特性进行初步的鉴定,但是对于蛋白质的结构和功能必须借助其它技术手段。目前逐渐形成了以生物质谱为核心的鉴定技术,蛋白质微测和氨基酸组成分析在表达模型分析中也有应用。关于蛋白质组功能模式研究目前可用的方法有酵母双杂交、噬菌体展示、生物传感芯片质谱、蛋白质工程中的定点突变技术等。这些技术对推动蛋白质组学的发展起了一定作用,但是单一技术通常不能确切的鉴定某一蛋白质,常需联合应用几种技术才能准确的鉴定蛋白质。     

乳腺癌蛋白质组学研究

乳腺癌是妇女中最常见的一种癌症,鉴定出与乳腺癌癌变相关的蛋白质以及病情发展过程中蛋白质的变化对揭示乳腺癌变机理及早期诊断是非常重要的。早在蛋白质组学这一概念提出以前,人们已应用2－维凝胶电泳技术（2DE）研究乳腺癌的癌变机理,且随着人类基因序列测序的完成,质谱的应用,以及生物信息学的引入,蛋白质组的研究获得了飞速发展,高通量的蛋白质组研究以及新的技术如激光捕获显微切割（LCM）,表面加强激光解吸／电离飞行时间质谱（SELDI－TOF）,蛋白质阵列,组织阵列等蛋白质组学技术已被用于乳腺癌研究并获得了很快速的发展。乳腺癌蛋白质组学研究已经鉴定了一些具有诊断潜能的生物分子靶标和信号传导因子。介绍了乳腺癌蛋白质组学研究中所使用的最新研究方法和研究进展。     

植物蛋白质组学研究若干重要进展

植物蛋白质组学近年来正从定性向精确定量蛋白质组学的方向发展。国际上近两年发表的约160篇研究论文报道了利用不断改进的双向电泳结合生物质谱技术、多维蛋白质鉴定技术,以及包括双向荧光差异凝胶电泳、幅N体内代谢标记、同位素标记的亲和标签、同位素标记相对和绝对定量等在内的第2代蛋白质组学技术,对植物组织（器官）与细胞器、植物发育过程和植物响应环境胁迫的蛋白质组特征,以及植物蛋白质翻译后修饰和蛋白质相互作用等方面的研究成果。该文对上述报道进行总结,综述了2007年以来植物蛋白质组学若干重要问题研究的新进展。     

蛋白质组学研究技术及其在植物抗渗透胁迫研究中的应用

蛋白质组学是功能基因组学研究的热点领域之一。该文介绍了蛋白质组学的基本的和新兴的研究技术方法如蛋白质组样品的制备、双向凝胶电泳、生物质谱技术、蛋白质芯片技术、酵母双杂交系统和生物信息学等,以及蛋白质组学技术在植物抗干旱、盐渍等渗透胁迫研究中的应用。     

植物蛋白质组学研究若干重要进展

植物蛋白质组学近年来正从定性向精确定量蛋白质组学的方向发展。国际上近两年发表的约160篇研究论文报道了利用不断改进的双向电泳结合生物质谱技术、多维蛋白质鉴定技术, 以及包括双向荧光差异凝胶电泳、15N体内代谢标记、同位素标记的亲和标签、同位素标记相对和绝对定量等在内的第2代蛋白质组学技术, 对植物组织(器官)与细胞器、植物发育过程和植物响应环境胁迫的蛋白质组特征, 以及植物蛋白质翻译后修饰和蛋白质相互作用等方面的研究成果。该文对上述报道进行总结, 综述了2007年以来植物蛋白质组学若干重要问题研究的新进展。     

现代质谱技术在蛋白质组学中的应用及其最新进展

简述了蛋白质组学的概念、内容和意义,重点综述了现代质谱技术在蛋白质组学中的应用,主要包括蛋白质和肽段的鉴定和定量、蛋白质翻译后修饰的鉴定和蛋白质间相互作用的检测等。随着新的高质量精确度、分辨率、灵敏度和通量质谱仪的出现,现代质谱技术在蛋白质组学中的应用将越来越广泛,并给蛋白质组学研究带来新的机遇。     

“自顶向下(top-down)”的蛋白质组学——蛋白质变体的规模化鉴定

高分辨率质谱技术的快速发展使得"自顶向下"的蛋白质组学(top-down proteomics)研究逐渐成熟起来.在完整蛋白质水平上研究蛋白质组可以提供更精准、更丰富的生物学信息,特别是对于蛋白质上发生了多种关联性的翻译后修饰的情况.另外,由于基因突变、RNA可变剪接和大量蛋白质翻译后修饰的存在,同一个基因往往最终会产生多个"蛋白质变体"(proteoform),而要准确地鉴定这些蛋白质变体,也离不开"自顶向下"的蛋白质组学.在蛋白质水平上的分离技术、质谱技术与生物信息学技术是完整蛋白质鉴定最关键的三项技术.高效的分离技术是实现规模化蛋白质变体鉴定的前提,有效的质谱碎裂是提供可靠鉴定的核心,而快速准确的质谱鉴定算法则是数据分析效率的保障.本文对这三项技术进行了详细总结,重点集中在生物信息学相关技术上,包括对完整蛋白质的质谱数据预处理、数据库搜索鉴定以及翻译后修饰定位等几个计算问题的讨论.     

林木蛋白质组学研究进展

近年来,应用新的基因组学技术来研究林木生长发育以及林木对生物与非生物胁迫的反应已使得人们对林木生物学有了相当大的了解。蛋白质组学是林木生物学的重要内容。本文综述了林木蛋白质组学在群体遗传、遗传作图、逆境生理、组织器官以及木材形成等方面的研究进展,并简要介绍了林木蛋白质组数据库。最后展望了林木蛋白质组学的发展前景。     

Protein profiling in respiratory disease: techniques and impact

Multifactorial diseases such as respiratory disease call for a global analysis of such disorders. Recent advances in protein profiling techniques may allow for early diagnosis of respiratory disease, which is crucial for intervention and treatment. In order to reduce false-positive rates, clinical diagnosis requires a high degree of sensitivity and specificity to be an effective screening tool. Protein profiles identified by ProteinChip^® (Ciphergen Biosystems) technology coupled with mass spectrometry affords a global analysis of clinical samples and is beginning to reach acceptable levels of sensitivity and specificity. Combining the profile with another diagnostic tool enhances the effectiveness of protein profiles to classify disease. Although current efforts have centered on serum protein profiling, the local environment of the lung may be better reflected in proteins of bronchoalveolar lavage or sputum. Identification of biomarkers of disease by protein profiling anaylses may lead to an understanding of the mechanisms of this disease and contribute to the discovery of new therapeutics for the prevention and treatment of disease. Advancing these analyses are techniques such as ProteinChip mass spectrometry, laser capture microdissection, tissue microarrays and fluorescently labeled antibody bead arrays, which enable the direct global analysis of complex mixtures. Effective high-throughput and ease of use of clinical testing will arrive with improvements in bioinformatics and decreases in instrumentation costs.     

Protein profiling in respiratory disease: techniques and impact

Multifactorial diseases such as respiratory disease call for a global analysis of such disorders. Recent advances in protein profiling techniques may allow for early diagnosis of respiratory disease, which is crucial for intervention and treatment. In order to reduce false-positive rates, clinical diagnosis requires a high degree of sensitivity and specificity to be an effective screening tool. Protein profiles identified by ProteinChip (Ciphergen Biosystems) technology coupled with mass spectrometry affords a global analysis of clinical samples and is beginning to reach acceptable levels of sensitivity and specificity. Combining the profile with another diagnostic tool enhances the effectiveness of protein profiles to classify disease. Although current efforts have centered on serum protein profiling, the local environment of the lung may be better reflected in proteins of bronchoalveolar lavage or sputum. Identification of biomarkers of disease by protein profiling analyses may lead to an understanding of the mechanisms of this disease and contribute to the discovery of new therapeutics for the prevention and treatment of disease. Advancing these analyses are techniques such as ProteinChip mass spectrometry, laser capture microdissection, tissue microarrays and fluorescently labeled antibody bead arrays, which enable the direct global analysis of complex mixtures. Effective high-throughput and ease of use of clinical testing will arrive with improvements in bioinformatics and decreases in instrumentation costs.     

Mass spectrometry imaging and profiling of single cells

Mass spectrometry imaging and profiling of individual cells and subcellular structures provide unique analytical capabilities for biological and biomedical research, including determination of the biochemical heterogeneity of cellular populations and intracellular localization of pharmaceuticals. Two mass spectrometry technologies-secondary ion mass spectrometry (SIMS) and matrix assisted laser desorption/ionization mass spectrometry (MALDI MS)-are most often used in micro-bioanalytical investigations. Recent advances in ion probe technologies have increased the dynamic range and sensitivity of analyte detection by SIMS, allowing two- and three-dimensional localization of analytes in a variety of cells. SIMS operating in the mass spectrometry imaging (MSI) mode can routinely reach spatial resolutions at the submicron level; therefore, it is frequently used in studies of the chemical composition of subcellular structures. MALDI MS offers a large mass range and high sensitivity of analyte detection. It has been successfully applied in a variety of single-cell and organelle profiling studies. Innovative instrumentation such as scanning microprobe MALDI and mass microscope spectrometers enables new subcellular MSI measurements. Other approaches for MS-based chemical imaging and profiling include those based on near-field laser ablation and inductively-coupled plasma MS analysis, which offer complementary capabilities for subcellular chemical imaging and profiling.     

Small-molecule probes elucidate global enzyme activity in a proteomic context

The recent dramatic improvements in high-resolution mass spectrometry (MS) have revolutionized the speed and scope of proteomic studies. Conventional MS-based proteomics methodologies allow global protein profiling based on expression levels. Although these techniques are promising, there are numerous biological activities yet to be unveiled, such as the dynamic regulation of enzyme activity. Chemical proteomics is an emerging field that extends these types proteomic profiling. In particular, activity-based protein profiling (ABPP) utilizes small-molecule probes to monitor enzyme activity directly in living intact subjects. In this mini-review, we summarize the unique roles of smallmolecule probes in proteomics studies and highlight some recent examples in which this principle has been applied. [BMB Reports 2014; 47(3): 149-157]     

Lipid imaging with time-of-flight secondary ion mass spectrometry (ToF-SIMS)

Fundamental advances in secondary ion mass spectrometry (SIMS) now allow for the examination and characterization of lipids directly from biological materials. The successful application of SIMS-based imaging in the investigation of lipids directly from tissue and cells are demonstrated. Common complications and technical pitfalls are discussed. In this review, we examine the use of cluster ion sources and cryogenically compatible sample handling for improved ion yields and to expand the application potential of SIMS. Methodological improvements, including pre-treating the sample to improve ion yields and protocol development for 3-dimensional analyses (i.e. molecular depth profiling), are also included in this discussion. New high performance SIMS instruments showcasing the most advanced instrumental developments, including tandem MS capabilities and continuous ion beam compatibility, are described and the future direction for SIMS in lipid imaging is evaluated.     

Combined experimental and statistical strategy for mass spectrometry based serum protein profiling for diagnosis of breast cancer: a case-control study

Serum protein profiling by mass spectrometry is a promising method for early detection of cancer. We have implemented a combined strategy based on matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) and statistical data analysis for serum protein profiling and applied it in a well-described breast cancer case-control study. A rigorous sample collection protocol ensured high quality specimen and reduced bias from preanalytical factors. Preoperative serum samples obtained from 48 breast cancer patients and 28 controls were used to generate MALDI MS protein profiles. A total of nine mass spectrometric protein profiles were obtained for each serum sample. A total of 533 common peaks were defined and represented a 'reference protein profile'. Among these 533 common peaks, we identified 72 peaks exhibiting statistically significant intensity differences ( p < 0.01) between cases and controls. A diagnostic rule based on these 72 mass values was constructed and exhibited a cross-validated sensitivity and specificity of approximately 85% for the detection of breast cancer. With this method, it was possible to distinguish early stage cancers from controls without major loss of sensitivity and specificity. We conclude that optimized serum sample handling and mass spectrometry data acquisition strategies in combination with statistical analysis provide a viable platform for serum protein profiling in cancer diagnosis.     

Dissecting the ubiquitin pathway by mass spectrometry

Protein modification by ubiquitin is a central regulatory mechanism in eukaryotic cells. Recent proteomics developments in mass spectrometry enable systematic analysis of cellular components in the ubiquitin pathway. Here, we review the advances in analyzing ubiquitinated substrates, determining modified lysine residues, quantifying polyubiquitin chain topologies, as well as profiling deubiquitinating enzymes based on the activity. Moreover, proteomic approaches have been developed for probing the interactome of proteasome and for identifying proteins with ubiquitin-binding domains. Similar strategies have been applied on the studies of the modification by ubiquitin-like proteins as well. These strategies are discussed with respect to their advantages, limitations and potential improvements. While the utilization of current methodologies has rapidly expanded the scope of protein modification by the ubiquitin family, a more active role is anticipated in the functional studies with the emergence of quantitative mass spectrometry.     

Technical aspects of functional proteomics in plants

Since the completion of genome sequences of several organisms, attention has been focused to determine the function and functional network of proteins by proteome analysis. This analysis is achieved by separation and identification of proteins, determination of their function and functional network, and construction of an appropriate database. Many improvements in separation and identification of proteins, such as two-dimensional electrophoresis, nano-liquid chromatography and mass spectrometry, have rapidly been achieved. Some new techniques which include top-down mass spectrometry and tandem affinity purification have emerged. These techniques have provided the possibility of high-throughput analysis of function and functional network of proteins in plants. However, to cope with the huge information emerging from proteome analyses, more sophisticated techniques and software are essential. The development and adaptation of such techniques will ease analyses of protein profiling, identification of post-translational modifications and protein-protein interaction, which are vital for elucidation of the protein functions.     

Aligning extracted LC-MS peak lists via density maximization

Rapid improvements in mass spectrometry sensitivity and mass accuracy combined with improved liquid chromatography separation technologies allow acquisition of high throughput metabolomics data, providing an excellent opportunity to understand biological processes. While spectral deconvolution software can identify discrete masses and their associated isotopes and adducts, the utility of metabolomic approaches for many statistical analyses such as identifying differentially abundant ions depends heavily on data quality and robustness, especially, the accuracy of aligning features across multiple biological replicates. We have developed a novel algorithm for feature alignment using density maximization. Instead of a greedy iterative, hence local, merging strategy, which has been widely used in the literature and in commercial applications, we apply a global merging strategy to improve alignment quality. Using both simulated and real data, we demonstrate that our new algorithm provides high map (e.g. chromatogram) coverage, which is critically important for non-targeted comparative metabolite profiling of highly replicated biological datasets.     

Aligning extracted LC-MS peak lists via density maximization

Rapid improvements in mass spectrometry sensitivity and mass accuracy combined with improved liquid chromatography separation technologies allow acquisition of high throughput metabolomics data, providing an excellent opportunity to understand biological processes. While spectral deconvolution software can identify discrete masses and their associated isotopes and adducts, the utility of metabolomic approaches for many statistical analyses such as identifying differentially abundant ions depends heavily on data quality and robustness, especially, the accuracy of aligning features across multiple biological replicates. We have developed a novel algorithm for feature alignment using density maximization. Instead of a greedy iterative, hence local, merging strategy, which has been widely used in the literature and in commercial applications, we apply a global merging strategy to improve alignment quality. Using both simulated and real data, we demonstrate that our new algorithm provides high map (e.g. chromatogram) coverage, which is critically important for non-targeted comparative metabolite profiling of highly replicated biological datasets.