血液蛋白质组学的研究技术及进展

人血液含有来源于几乎所有细胞、组织、器官的蛋白质,可以直接反映病理、生理状态,是各种疾病诊断、生物标志物发现的最有价值的标本。因此,长期以来,血浆蛋白质组一直是人们研究的热点,并被人类蛋白质组组织(HUPO)列为首批启动的重大国际合作研究项目。血浆蛋白质含量动态范围非常广、成分极其复杂,血浆蛋白质组的研究极富挑战性。近年来,血浆高丰度蛋白质去除、蛋白质/肽段分离、质谱鉴定、数据处理等多种相关技术都取得了很大的进展。本文简要综述了上述技术领域的研究和应用进展。     

Tissue proteomics using capillary isoelectric focusing-based multidimensional separations

The capabilities of capillary isoelectric focusing-based multidimensional separations for performing proteome analysis from minute samples create new opportunities in the pursuit of biomarker discovery using enriched and selected cell populations procured from tissue specimens. In this article, recent advances in online integration of capillary isoelectric focusing with nano-reversed phase liquid chromatography for achieving high-resolution peptide and protein separations prior to mass spectrometry analysis are reviewed, along with its potential application to tissue proteomics. These proteome technological advances combined with recently developed tissue microdissection techniques, provide powerful tools for those seeking to gain a greater understanding at the global level of the cellular machinery associated with human diseases such as cancer.     

Tissue proteomics using capillary isoelectric focusing-based multidimensional separations

The capabilities of capillary isoelectric focusing-based multidimensional separations for performing proteome analysis from minute samples create new opportunities in the pursuit of biomarker discovery using enriched and selected cell populations procured from tissue specimens. In this article, recent advances in online integration of capillary isoelectric focusing with nano-reversed phase liquid chromatography for achieving high-resolution peptide and protein separations prior to mass spectrometry analysis are reviewed, along with its potential application to tissue proteomics. These proteome technological advances combined with recently developed tissue microdissection techniques, provide powerful tools for those seeking to gain a greater understanding at the global level of the cellular machinery associated with human diseases such as cancer.     

Chemical probes and tandem mass spectrometry: a strategy for the quantitative analysis of proteomes and subproteomes

Quantitative proteome profiling using mass spectrometry and stable isotope dilution is being widely applied for the functional analysis of biological systems and for the detection of clinical, diagnostic or prognostic marker proteins. Because of the enormous complexity of proteomes, their comprehensive analysis is unlikely to be routinely achieved in the near future. However, in recent years, significant progress has been achieved focusing quantitative proteomic analyses on specific protein classes or subproteomes that are rich in biologically or clinically important information. Such projects typically combine the use of chemical probes that are specific for a targeted group of proteins and may contain stable isotope signatures for accurate quantification with automated tandem mass spectrometry and bioinformatics tools for data analysis. In this review, we summarize technical and conceptual advances in quantitative subproteome profiling based on tandem mass spectrometry and chemical probes.     

The molecular scanner: concept and developments

Approaches aimed at deciphering the proteome have illustrated the need for relatively complex and highly sensitive methodologies. The major elements of proteome analysis, such as powerful protein separation and enzymatic processing, mass spectrometry and dedicated bioinformatics have been assembled in the development of the molecular scanner. This highly flexible and data-rich approach has combined the power of electrophoretic protein separation, the simultaneous digestion and transfer of proteins through an enzymatic membrane, the immediate use of the MALDI mass spectrometer to scan a collecting membrane, and the development of dedicated bioinformatics tools to perform protein identification and molecular imaging of the proteome. Clinical applications of the molecular scanner have also started to be developed for disease diagnosis in biological material.     

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。     

Biomarker discovery: proteome fractionation and separation in biological samples.

Proteomics, analogous with genomics, is the analysis of the protein complement present in a cell, organ, or organism at any given time. While the genome provides information about the theoretical status of the cellular proteins, the proteome describes the actual content, which ultimately determines the phenotype. The broad application of proteomic technologies in basic science and clinical medicine has the potential to accelerate our understanding of the molecular mechanisms underlying disease and may facilitate the discovery of new drug targets and diagnostic disease markers. Proteomics is a rapidly developing and changing scientific discipline, and the last 5 yr have seen major advances in the underlying techniques as well as expansion into new applications. Core technologies for the separation of proteins and/or peptides are one- and two-dimensional gel electrophoresis and one- and two-dimensional liquid chromatography, and these are coupled almost exclusively with mass spectrometry. Proteomic studies have shown that the most effective analysis of even simple biological samples requires subfractionation and/or enrichment before protein identification by mass spectrometry. Selection of the appropriate technology or combination of technologies to match the biological questions is essential for maximum coverage of the selected subproteome and to ensure both the full interpretation and the downstream utility of the data. In this review, we describe the current technologies for proteome fractionation and separation of biological samples, based on our lab workflow for biomarker discovery and validation.     

Proteomic Analysis to Identify Tightly-Bound Cell Wall Protein in Rice Calli

Rice is a model plant widely used for basic and applied research programs. Plant cell wall proteins play key roles in a broad range of biological processes. However, presently, knowledge on the rice cell wall proteome is rudimentary in nature. In the present study, the tightly-bound cell wall proteome of rice callus cultured cells using sequential extraction protocols was developed using mass spectrometry and bioinformatics methods, leading to the identification of 1568 candidate proteins. Based on bioinformatics analyses, 389 classical rice cell wall proteins, possessing a signal peptide, and 334 putative non-classical cell wall proteins, lacking a signal peptide, were identified. By combining previously established rice cell wall protein databases with current data for the classical rice cell wall proteins, a comprehensive rice cell wall proteome, comprised of 496 proteins, was constructed. A comparative analysis of the rice and Arabidopsis cell wall proteomes revealed a high level of homology, suggesting a predominant conservation between monocot and eudicot cell wall proteins. This study importantly increased information on cell wall proteins, which serves for future functional analyses of these identified rice cell wall proteins.     

Mouse models for neurodegenerative diseases and a theory of proteomics

Proteome analysis is usually performed by separating complex cellular protein extracts by two‐dimensional‐electrophoresis followed by protein identification using mass spectrometry. In this way proteins are compared from normal and diseased tissue in order to detect disease related protein changes. In a strict sense, however, this procedure cannot be called proteome analysis: the tools of proteomics are used just to detect some interesting proteins which are then investigated by protein chemistry as usual. Real proteome research would be studying the cellular proteome as a whole, its composition, organization and its kind of action. At present however, we have no idea how a proteome works as a whole; we have not even a theory about that. If we would know how the proteome of a cell type is arranged, we probably would alter our strategy to detect and analyze disease‐related proteins. I will present a theory of proteomics and show some results from our laboratory which support this theory. The results come from investigations of the mouse brain proteome and include mouse models for neurodegenerative diseases.     

Gene therapy approaches for Parkinson's disease

Proteome analysis is usually performed by separating complex cellular protein extracts by two-dimensional-electrophoresis followed by protein identification using mass spectrometry. In this way proteins are compared from normal and diseased tissue in order to detect disease related protein changes. In a strict sense, however, this procedure cannot be called proteome analysis: the tools of proteomics are used just to detect some interesting proteins which are then investigated by protein chemistry as usual. Real proteome research would be studying the cellular proteome as a whole, its composition, organization and its kind of action. At present however, we have no idea how a proteome works as a whole; we have not even a theory about that. If we would know how the proteome of a cell type is arranged, we probably would alter our strategy to detect and analyze disease-related proteins. I will present a theory of proteomics and show some results from our laboratory which support this theory. The results come from investigations of the mouse brain proteome and include mouse models for neurodegenerative diseases.     

In-depth analysis of the human CSF proteome using protein prefractionation

The identification of disease markers in human body fluids requires an extensive and thorough analysis of its protein constituents. In the present study, we have extended our analysis of the human cerebrospinal fluid (CSF) proteome using protein prefractional followed by shotgun mass spectrometry. After the removal of abundant protein components from the mixture with the help of immunodepletion affinity chromatography, we used either anion exchange chromatography or sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) to further subfractionate the proteins present in CSFs. Each protein subfraction was enzyme digested and analyzed by tandem mass spectrometry and the resulting data evaluated using the Spectrum Mill software. Different subfractionation methods resulted in the identification of a grant total of 259 proteins in CSF from a patient with normal pressure hydrocephalus. The greatest number of protein, 240 in total, were identified after prefractionating the CSF proteins by immunodepletion and SDS-PAGE. Immuno-depletion combined with anion exchange fractionation resulted in 112 proteins and 74 proteins were found when only immunodepletion of the CSF samples was carried out. All methods used showed a significant increase in the number of identified proteins as compared with nondepleted and unfractionated CSF sample analysis, which yielded only 38 protein identifications. The present work establishes a platform for future studies aimed at a detailed comparative proteome analysis of CSFs from different groups of patients suffering from various psychiatric and neurological disorders.     

基于质谱的蛋白质生物标志物发现中的特征选择与机器学习方法研究进展

随着质谱技术的进步以及生物信息学与统计学算法的发展,以疾病研究为主要目的之一的人类蛋白质组计划正快速推进。蛋白质生物标志物在疾病早期诊断和临床治疗等方面有着非常重要的意义,其发现策略和方法的研究已成为一个重要的热点领域。特征选择与机器学习对于解决蛋白质组数据"高维度"及"稀疏性"问题有较好的效果,因而逐渐被广泛地应用于发现蛋白质生物标志物的研究中。文中主要阐述蛋白质生物标志物的发现策略以及其中特征选择与机器学习方法的原理、应用实例和适用范围,并讨论深度学习方法在本领域的应用前景及局限性,以期为相关研究提供参考。     

Proteome analysis at the level of subcellular structures.

The targeting of proteins to particular subcellular sites is an important principle of the functional organization of cells at the molecular level. In turn, knowledge about the subcellular localization of a protein is a characteristic that may provide a hint as to the function of the protein. The combination of classic biochemical fractionation techniques for the enrichment of particular subcellular structures with the large-scale identification of proteins by mass spectrometry and bioinformatics provides a powerful strategy that interfaces cell biology and proteomics, and thus is termed 'subcellular proteomics'. In addition to its exceptional power for the identification of previously unknown gene products, the analysis of proteins at the subcellular level is the basis for monitoring important aspects of dynamic changes in the proteome such as protein transloction. This review summarizes data from recent subcellular proteomics studies with an emphasis on the type of data that can retrieved from such studies depending on the design of the analytical strategy.     

Multidimensional fractionation of the bovine skeletal muscle proteome.

The ultimate goal of proteomics is to understand complex biological systems. The first step toward this end is the discovery of protein differences by profiling a given proteome. One approach to proteome profiling is to fractionate it into intact proteins, with subsequent identification and quantitation. In this work, lysates of bovine skeletal muscle were prepared. Reproducible proteome profiles were generated by an automatic two-dimensional protein fractionation system. Proteins were separated by isoelectric point and then by hydrophobicity. The data collected from both separations were used to generate proteome profiles. A high protein content fraction with pl above 8.5 was digested with trypsin, and its main protein component was identified as lysozyme C by matrix assisted laser desorption/ionization-time of flight mass spectrometry.     

Methods and approaches for the comprehensive characterization and quantification of cellular proteomes using mass spectrometry.

Proteomics has been proposed as one of the key technologies in the postgenomic era. So far, however, the comprehensive analysis of cellular proteomes has been a challenge because of the dynamic nature and complexity of the multitude of proteins in cells and tissues. Various approaches have been established for the analyses of proteins in a cell at a given state, and mass spectrometry (MS) has proven to be an efficient and versatile tool. MS-based proteomics approaches have significantly improved beyond the initial identification of proteins to comprehensive characterization and quantification of proteomes and their posttranslational modifications (PTMs). Despite these advances, there is still ongoing development of new technologies to profile and analyze cellular proteomes more completely and efficiently. In this review, we focus on MS-based techniques, describe basic approaches for MS-based profiling of cellular proteomes and analysis methods to identify proteins in complex mixtures, and discuss the different approaches for quantitative proteome analysis. Finally, we briefly discuss novel developments for the analysis of PTMs. Altered levels of PTM, sometimes in the absence of protein expression changes, are often linked to cellular responses and disease states, and the comprehensive analysis of cellular proteome would not be complete without the identification and quantification of the extent of PTMs of proteins.     

Functional assignment of the 20 S proteasome from Trypanosoma brucei using mass spectrometry and new bioinformatics approaches

As experimental technologies for characterization of proteomes emerge, bioinformatic analysis of the data becomes essential. Separation and identification technologies currently based on two-dimensional gels/mass spectrometry provide the inherent analytical power required. This strategy involves protein spot digestion and accurate mass mapping together with computational interrogation of available data bases for protein functional identification. When either no exact match is found or when the possible matches only partially account for molecular weights actually observed, peptide sequencing by tandem mass spectrometry has emerged as the methodology of choice to provide the basic additional information required. To evaluate the capabilities of bioinformatics methods employed for identifying homologs of a protein of interest, we attempted to identify the major proteins from the 20 S proteasome of Trypanosoma brucei using sequence information determined using mass spectrometry. The results suggest that neither the traditional query engines, BLAST and FASTA, nor specialized software developed for analysis of sequence information obtained by mass spectrometry are able to identify even closely related sequences at statistically significant scores. To address this deficit, new bioinformatics approaches were developed for concomitant use of the multiple fragments of short sequence typically available from methods of tandem mass spectrometry. These approaches rely on the occurrence of congruence across searches of multiple fragments from a single protein. This method resulted in sharply better statistical significance values for correct hits in the data base output relative to that achieved for independent searches using single sequence fragments.     

A comprehensive map of the human urinary proteome

The study of the human urinary proteome has the potential to offer significant insights into normal physiology as well as disease pathology. The information obtained from such studies could be applied to the diagnosis of various diseases. The high sensitivity, resolution, and mass accuracy of the latest generation of mass spectrometers provides an opportunity to accurately catalog the proteins present in human urine, including those present at low levels. To this end, we carried out a comprehensive analysis of human urinary proteome from healthy individuals using high-resolution Fourier transform mass spectrometry. Importantly, we used the Orbitrap for detecting ions in both MS (resolution 60 000) and MS/MS (resolution 15 000) modes. To increase the depth of our analysis, we characterized both unfractionated as well as lectin-enriched proteins in our experiments. In all, we identified 1,823 proteins with less than 1% false discovery rate, of which 671 proteins have not previously been reported as constituents of human urine. This data set should serve as a comprehensive reference list for future studies aimed at identification and characterization of urinary biomarkers for various diseases.     

Proteome profiling of breast tumors by gel electrophoresis and nanoscale electrospray ionization mass spectrometry

We have conducted proteome-wide analysis of fresh surgery specimens derived from breast cancer patients, using an approach that integrates size-based intact protein fractionation, nanoscale liquid separation of peptides, electrospray ion trap mass spectrometry, and bioinformatics. Through this approach, we have acquired a large amount of peptide fragmentation spectra from size-resolved fractions of the proteomes of several breast tumors, tissue peripheral to the tumor, and samples from patients undergoing noncancer surgery. Label-free quantitation was used to generate protein abundance maps for each proteome and perform comparative analyses. The mass spectrometry data revealed distinct qualitative and quantitative patterns distinguishing the tumors from healthy tissue as well as differences between metastatic and non-metastatic human breast cancers including many established and potential novel candidate protein biomarkers. Selected proteins were evaluated by Western blotting using tumors grouped according to histological grade, size, and receptor expression but differing in nodal status. Immunohistochemical analysis of a wide panel of breast tumors was conducted to assess expression in different types of breast cancers and the cellular distribution of the candidate proteins. These experiments provided further insights and an independent validation of the data obtained by mass spectrometry and revealed the potential of this approach for establishing multimodal markers for early metastasis, therapy outcomes, prognosis, and diagnosis in the future.     

Proteomic approaches in the search for disease biomarkers

Significant technological advances in protein chemistry, physics and computer sciences in the last two decades have greatly improved protein separation methodologies, such as electrophoresis and chromatography, and have established mass spectrometry (MS) as an indispensable tool for protein study. The goal of this review is to provide a brief overview of the recent improvements in these methodologies and present examples from their application in proteome analysis and search for disease biomarkers.