基于质谱的定量蛋白质组学策略和方法研究进展

定量蛋白质组学已经成为组学领域研究的热点之一.相关实验技术和计算方法的不断创新极大地促进了定量蛋白质组学的飞速发展.常用的定量蛋白质组学策略按照是否需要稳定同位素标记可以分为无标定量和有标定量两大类.每类策略又产生了众多定量方法和工具,它们一方面推动了定量蛋白质组学的深入发展;另一方面,也在实验策略与技术的发展过程中不断更新.因此对这些定量实验策略和方法进行系统总结和归纳将有助于定量蛋白质组学的研究.本文主要从方法学角度全面归纳了目前定量蛋白质组学研究的相关策略和算法,详述了无标定量和有标定量的具体算法流程并比较了各自特点,还对以研究蛋白质绝对丰度为目标的绝对定量算法进行了总结,列举了常用的定量软件和工具,最后概述了定量结果的质量控制方法,对定量蛋白质组学方法发展的前景进行了展望.     

蛋白质质谱分析的无标记定量算法研究进展

作为发现疾病相关生物标志物的重要途径,定量研究已成为蛋白质组学的热点问题.随着实验方法的发展和改进,定量数据处理算法也在不断更新和完善.将现有的无标记定量方法归纳为需要/不需要鉴定结果两类方法,分析比较了两类方法的异同及优缺点,详细讨论了所涉及的主要算法,总结了一些常用的无标记定量软件及对应的网络资源.展望了无标记定量数据分析的未来研究方向.     

18O标记法在定量蛋白质组学中的应用

基于质谱技术去识别和检测蛋白质表达差异是一个热点,有助于生物过程和体系的分子机制的研究。近年来各种基于质谱技术的定量蛋白质组学研究方法发展较快,相对其他方法而言,18O标记法是一种较为理想、相对容易实现并且在不断完善的体外标记方法,最近在定量蛋白质组学研究中应用较多。现对18O标记法原理、特点以及技术方法的优化和应用进展进行综述。     

高精度相对和绝对定量的等量异位标签在定量蛋白质组学研究中的新进展

蛋白质组学逐渐从定性研究转向定量研究。在定量蛋白质组学技术中,相对和绝对定量的等量异位标签(Isobaric tags for relative and absolute quantitation,iTRAQ)是应用最广泛的技术之一,具有通量高、稳定性强及不受样品来源制约等优点,几乎可以对任意样品进行标记,而且可以同时对多达8个样品进行定量分析,有效地提高了通量。iTRAQ技术不断改进,其定量准确性显著提高,适用的平台越来越多,为微生物、动物、植物、生物医学领域蛋白质及其翻译后修饰组研究创造了条件。文中综述了高精度iTRAQ技术在定量蛋白质组学研究中的最新发展及其应用。     

同位素标记相对和绝对定量技术研究进展

定量蛋白质组学是蛋白质研究的前沿学科。目前常用的定量蛋白质组学研究技术有荧光差异凝胶电泳（DIGE）、同位素亲和标记（ICAT）等。同位素标记相对和绝对定量（iTRAQ）技术是近年来最新开发的一种新的蛋白质组学定量研究技术。结合非凝胶串联质谱技术,该技术可对复杂样本、细胞器、细胞裂解液等样本进行相对和绝对定量研究,具有较好的定量效果、较高的重复性,并可对多达四种不同样本同时进行定量分析。本文对 iTRAQ 技术的原理、实验方法及应用进展进行了综述。     

同位素稀释法在绝对定量蛋白质组中的研究进展

绝对定量蛋白质组是指基于蛋白质组学方法对细胞、组织或体液中的蛋白质进行绝对量或浓度测定．目前,常用的绝对定量方法主要有基于同位素稀释法的蛋白质组学绝对定量方法和基于质谱数据统计分析的非标记方法．基于同位素稀释法的绝对定量方法是用已知量的同位素标记物对与其混合的样本蛋白质浓度进行测定．常见的同位素标记物包括：由AQUA法、QconCAT法产生的特异性水解肽段,由PSAQ法、Absolute SILAC法产生的标记蛋白和由PrESTs-SILAC法产生的蛋白抗原表位标签．由于同位素稀释法可以对蛋白质进行准确和精确定量,对于临床疾病的诊断和治疗具有明显的现实意义．本文对同位素稀释法在绝对定量蛋白质组中的研究进展及其优缺点和最新应用进行了评述．     

稳定同位素化学标记结合质谱技术在定量蛋白质组学中的应用

传统的蛋白质组定量策略主要是通过双向凝胶电泳来进行相对定量。由于该方法不能对相对分子质量极高或极低、等电点极酸或极碱和含量低的蛋白质以及膜蛋白质等进行有效分离和检测,所以已不能适应目前蛋白质组研究深入发展的需要。近年来,定量蛋白质组学的发展主要是以同位素亲和标签试剂为代表的、以质谱检测为核心的稳定同位素化学标记方法。稳定同位素化学标记结合质谱技术,使定量蛋白质组的分析更趋简单、准确和快速,具有良好的发展前景。本文对稳定同位素化学标记结合质谱技术在定量蛋白质组学中的研究进展进行了评述。     

基于电感耦合等离子体质谱的蛋白质定量技术研究进展

综述了ICP-MS法应用于蛋白质定量技术方面的研究进展.蛋白质定量研究已成为蛋白质组学研究领域的热点,它是解析生物体蛋白质功能的重要途径.基于同位素标记和生物质谱分析技术是蛋白质定量最常用的方法之一,近年来,随着质谱技术的发展,电感耦合等离子体质谱(ICP-MS)技术成为元素测量的重要手段,这使其在蛋白质定量中具一定的应用前景.     

磷酸化蛋白质组学分析和定量技术的研究进展

蛋白质的磷酸化是一种可逆性的蛋白质翻译后修饰,在生物体内起着极为重要的作用.近年来蛋白质翻译后修饰日益成为蛋白质组研究的热点之一.定量磷酸化蛋白质组学方法和技术的快速发展为研究蛋白质磷酸化时空动态变化,更好地了解生物学功能调节网络奠定了坚实的基础.作为蛋白质组学研究的一个重要组成部分,定量磷酸化蛋白质组学因其磷酸化蛋白质所具有的独特特征,在技术和方法研究方面将面临更为严峻的挑战.综述了磷酸化蛋白质组学定量的一些分析技术和方法的发展现状、优缺点以及未来的发展趋势.     

Orbitrap Exploris 480质谱在定量蛋白质组学应用中的优化和评测

基于数据依赖的扫描模式(data-dependent acquisition, DDA)和数据非依赖的扫描模式(data-independent acquisition,DIA)的非标记定量(label-free quantitative,LFQ)和同位素标记TMT (tandem mass tag)定量是蛋白质组学定量中较常见的技术.本文利用最新的Orbitrap Exploris 480质谱,优化了DDA、FAIMS DDA、FAIMS DIA的非标记定量方法以及TMT定量策略的关键质谱参数,并将其应用在人细胞蛋白质组、单细胞蛋白质组、血浆蛋白质组和酵母蛋白质组分析.结果表明,在DDA实验中,设置碰撞能量为27、二级谱图的分辨率为15 K、最大离子注入时间为22 ms是最佳的参数组合.针对极微量样品200 pg～5 ng,可以根据样品量相应设置最佳的质谱参数.使用200 pg和500 pg的HeLa细胞样品,分别鉴定到1 259和1 725个蛋白质,从而实现了单细胞蛋白质组学的深度覆盖.在FAIMS DDA实验中,60 min或90 min梯度时选择CV-45V的补偿电压,120 ...     

Mass Spectrometry-Based Approaches Toward Absolute Quantitative Proteomics

Mass spectrometry has served as a major tool for the discipline of proteomics to catalogue proteins in an unprecedented scale. With chemical and metabolic techniques for stable isotope labeling developed over the past decade, it is now routinely used as a method for relative quantification to provide valuable information on alteration of protein abundance in a proteome-wide scale. More recently, absolute or stoichiometric quantification of proteome is becoming feasible, in particular, with the development of strategies with isotope-labeled standards composed of concatenated peptides. On the other hand, remarkable progress has been also made in label-free quantification methods based on the number of identified peptides. Here we review these mass spectrometry-based approaches for absolute quantification of proteome and discuss their implications.Key Words: Quantitative proteomics, mass spectrometry, absolute quantification, stable isotope labeling, label-free.     

Biomedical applications of ion mobility-enhanced data-independent acquisition-based label-free quantitative proteomics

Mass spectrometry-based proteomics greatly benefited from recent improvements in instrument performance and the development of bioinformatics solutions facilitating the high-throughput quantification of proteins in complex biological samples. In addition to quantification approaches using stable isotope labeling, label-free quantification has emerged as the method of choice for many laboratories. Over the last years, data-independent acquisition approaches have gained increasing popularity. The integration of ion mobility separation into commercial instruments enabled researchers to achieve deep proteome coverage from limiting sample amounts. Additionally, ion mobility provides a new dimension of separation for the quantitative assessment of complex proteomes, facilitating precise label-free quantification even of highly complex samples. The present work provides a thorough overview of the combination of ion mobility and data-independent acquisition-based label-free quantification LC-MS and its applications in biomedical research.     

Current challenges in software solutions for mass spectrometry-based quantitative proteomics

Mass spectrometry-based proteomics has evolved as a high-throughput research field over the past decade. Significant advances in instrumentation, and the ability to produce huge volumes of data, have emphasized the need for adequate data analysis tools, which are nowadays often considered the main bottleneck for proteomics development. This review highlights important issues that directly impact the effectiveness of proteomic quantitation and educates software developers and end-users on available computational solutions to correct for the occurrence of these factors. Potential sources of errors specific for stable isotope-based methods or label-free approaches are explicitly outlined. The overall aim focuses on a generic proteomic workflow.     

Quantitative proteomic analyses of crop seedlings subjected to stress conditions; a commentary

Quantitative proteomics is one of the analytical approaches used to clarify crop responses to stress conditions. Recent remarkable advances in proteomics technologies allow for the identification of a wider range of proteins than was previously possible. Current proteomic methods fall into roughly two categories: gel-based quantification methods, including conventional two-dimensional gel electrophoresis and two-dimensional fluorescence difference gel electrophoresis, and MS-based quantification methods consists of label-based and label-free protein quantification approaches. Although MS-based quantification methods have become mainstream in recent years, gel-based quantification methods are still useful for proteomic analyses. Previous studies examining crop responses to stress conditions reveal that each method has both advantages and disadvantages in regard to protein quantification in comparative proteomic analyses. Furthermore, one proteomics approach cannot be fully substituted by another technique. In this review, we discuss and highlight the basis and applications of quantitative proteomic analysis approaches in crop seedlings in response to flooding and osmotic stress as two environmental stresses.     

Mass spectrometry-based plasma proteomics: state of the art and future outlook

Mass spectrometry-based plasma proteomics is a field where intense research has been performed during the last decade. Being closely linked to biomarker discovery, the field has received a fair amount of criticism, mostly due to the low number of novel biomarkers reaching the clinic. However, plasma proteomics is under gradual development with improvements on fractionation methods, mass spectrometry instrumentation and analytical approaches. These recent developments have contributed to the revival of plasma proteomics. The goal of this review is to summarize these advances, focusing in particular on fractionation methods, both for targeted and global mass spectrometry-based plasma analysis.     

Diffprot - software for non-parametric statistical analysis of differential proteomics data

Mass spectrometry-based global proteomics experiments generate large sets of data that can be converted into useful information only with an appropriate statistical approach. We present Diffprot - a software tool for statistical analysis of MS-derived quantitative data. With implemented resampling-based statistical test and local variance estimate, Diffprot allows to draw significant results from small scale experiments and effectively eliminates false positive results. To demonstrate the advantages of this software, we performed two spike-in tests with complex biological matrices, one label-free and one based on iTRAQ quantification; in addition, we performed an iTRAQ experiment on bacterial samples. In the spike-in tests, protein ratios were estimated and were in good agreement with theoretical values; statistical significance was assigned to spiked proteins and single or no false positive results were obtained with Diffprot. We compared the performance of Diffprot with other statistical tests - widely used t-test and non-parametric Wilcoxon test. In contrast to Diffprot, both generated many false positive hits in the spike-in experiment. This proved the superiority of the resampling-based method in terms of specificity, making Diffprot a rational choice for small scale high-throughput experiments, when the need to control the false positive rate is particularly pressing.     

RIBAR and xRIBAR: Methods for reproducible relative MS/MS-based label-free protein quantification

Mass spectrometry-driven proteomics is increasingly relying on quantitative analyses for biological discoveries. As a result, different methods and algorithms have been developed to perform relative or absolute quantification based on mass spectrometry data. One of the most popular quantification methods are the so-called label-free approaches, which require no special sample processing, and can even be applied retroactively to existing data sets. Of these label-free methods, the MS/MS-based approaches are most often applied, mainly because of their inherent simplicity as compared to MS-based methods. The main application of these approaches is the determination of relative protein amounts between different samples, expressed as protein ratios. However, as we demonstrate here, there are some issues with the reproducibility across replicates of these protein ratio sets obtained from the various MS/MS-based label-free methods, indicating that the existing methods are not optimally robust. We therefore present two new methods (called RIBAR and xRIBAR) that use the available MS/MS data more effectively, achieving increased robustness. Both the accuracy and the precision of our novel methods are analyzed and compared to the existing methods to illustrate the increased robustness of our new methods over existing ones.     

High throughput proteome screening for biomarker detection

Mass spectrometry-based quantitative proteomics has become an important component of biological and clinical research. Current methods, while highly developed and powerful, are falling short of their goal of routinely analyzing whole proteomes mainly because the wealth of proteomic information accumulated from prior studies is not used for the planning or interpretation of present experiments. The consequence of this situation is that in every proteomic experiment the proteome is rediscovered. In this report we describe an approach for quantitative proteomics that builds on the extensive prior knowledge of proteomes and a platform for the implementation of the method. The method is based on the selection and chemical synthesis of isotopically labeled reference peptides that uniquely identify a particular protein and the addition of a panel of such peptides to the sample mixture consisting of tryptic peptides from the proteome in question. The platform consists of a peptide separation module for the generation of ordered peptide arrays from the combined peptide sample on the sample plate of a MALDI mass spectrometer, a high throughput MALDI-TOF/TOF mass spectrometer, and a suite of software tools for the selective analysis of the targeted peptides and the interpretation of the results. Applying the method to the analysis of the human blood serum proteome we demonstrate the feasibility of using mass spectrometry-based proteomics as a high throughput screening technology for the detection and quantification of targeted proteins in a complex system.     

Site-specific degree of phosphorylation in proteins measured by liquid chromatography-electrospray mass spectrometry

This review focuses on quantitative protein phosphorylation analysis based on coverage of both the phosphorylated and nonphosphorylated forms. In this way, site-specific data on the degree of phosphorylation can be measured, generating the most detailed level of phosphorylation status analysis of proteins. To highlight the experimental challenges in this type of quantitative protein phosphorylation analysis, we discuss the typical workflows for mass spectrometry-based proteomics with a focus on the quantitative analysis of peptide/phosphopeptide ratios. We review workflows for measuring site-specific degrees of phosphorylation including the label-free approach, differential stable isotope labeling of analytes, and methods based on the addition of stable isotope labeled peptide/phosphopeptide pairs as internal standards. The discussion also includes the determination of phosphopeptide isoform abundance data for multiply phosphorylated motifs that contain information about the connectivity of phosphorylation events. The review closes with a prospective on the use of intact stable isotope labeled proteins as internal standards and a summarizing discussion of the typical accuracies of the individual methods.