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.     

A chemical proteomics approach to phosphatidylinositol 3-kinase signaling in macrophages

Prior work using lipid-based affinity matrices has been done to investigate distinct sets of lipid-binding proteins, and one series of experiments has proven successful in mammalian cells for the proteome-wide identification of lipid-binding proteins. However, most lipid-based proteomics screens require scaled up sample preparation, are often composed of multiple cell types, and are not adapted for simultaneous signal transduction studies. Herein we provide a chemical proteomics strategy that uses cleavable lipid "baits" with broad applicability to diverse biological samples. The novel baits were designed to avoid preparative steps to allow functional proteomics studies when the biological source is a limiting factor. Validation of the chemical baits was first confirmed by the selective isolation of several known endogenous phosphatidylinositol 3-kinase signaling proteins using primary bone marrow-derived macrophages. The use of this technique for cellular proteomics and MS/MS analysis was then demonstrated by the identification of known and potential novel lipid-binding proteins that was confirmed in vitro for several proteins by direct lipid-protein interactions. Further to the identification, the method is also compatible with subsequent signal transduction studies, notably for protein kinase profiling of the isolated lipid-bound protein complexes. Taken together, this integration of minimal scale proteomics, lipid chemistry, and activity-based readouts provides a significant advancement in the ability to identify and study the lipid proteome of single, relevant cell types.     

Tumor antigens and proteomics from the point of view of the major histocompatibility complex peptides

The major histocompatibility complex (MHC) peptide repertoire of cancer cells serves both as a source for new tumor antigens for development of cancer immunotherapy and as a rich information resource about the protein content of the cancer cells (their proteome). Thousands of different MHC peptides are normally displayed by each cell, where most of them are derived from different proteins and thus represent most of the cellular proteome. However, in contrast to standard proteomics, which surveys the cellular protein contents, analyses of the MHC peptide repertoire correspond more to the rapidly degrading proteins in the cells (i.e. the transient proteome). MHC peptides can be efficiently purified by affinity chromatography from membranal MHC molecules, or preferably following transfection of vectors for expression of recombinant soluble MHC molecules. The purified peptides are resolved and analyzed by capillary high-pressure liquid chromatography-electrospray ionization-tandem mass spectrometry, and the data are deciphered with new software tools enabling the creation of large databanks of MHC peptides displayed by different cell types and by different MHC haplotypes. These lists of identified MHC peptides can now be used for searching new tumor antigens, and for identification of proteins whose rapid degradation is significant to cancer progression and metastasis. These lists can also be used for identification of new proteins of yet unknown function that are not detected by standard proteomics approaches. This review focuses on the presentation, identification and analysis of MHC peptides significant for cancer immunotherapy. It is also concerned with the aspects of human proteomics observed through large-scale analyses of MHC peptides.     

Quantitative proteome analysis using isotope-coded affinity tags and mass spectrometry

A main objective of proteomics research is to systematically identify and quantify proteins in a given proteome (cells, subcellular fractions, protein complexes, tissues or body fluids). Protein labeling with isotope-coded affinity tags (ICAT) followed by tandem mass spectrometry allows sequence identification and accurate quantification of proteins in complex mixtures, and has been applied to the analysis of global protein expression changes, protein changes in subcellular fractions, components of protein complexes, protein secretion and body fluids. This protocol describes protein-sample labeling with ICAT reagents, chromatographic fractionation of the ICAT-labeled tryptic peptides, and protein identification and quantification using tandem mass spectrometry. The method is suitable for both large-scale analysis of complex samples including whole proteomes and small-scale analysis of subproteomes, and allows quantitative analysis of proteins, including those that are difficult to analyze by gel-based proteomics technology.     

Synergistic computational and experimental proteomics approaches for more accurate detection of active serine hydrolases in yeast

An analysis of the structurally and catalytically diverse serine hydrolase protein family in the Saccharomyces cerevisiae proteome was undertaken using two independent but complementary, large-scale approaches. The first approach is based on computational analysis of serine hydrolase active site structures; the second utilizes the chemical reactivity of the serine hydrolase active site in complex mixtures. These proteomics approaches share the ability to fractionate the complex proteome into functional subsets. Each method identified a significant number of sequences, but 15 proteins were identified by both methods. Eight of these were unannotated in the Saccharomyces Genome Database at the time of this study and are thus novel serine hydrolase identifications. Three of the previously uncharacterized proteins are members of a eukaryotic serine hydrolase family, designated as Fsh (family of serine hydrolase), identified here for the first time. OVCA2, a potential human tumor suppressor, and DYR-SCHPO, a dihydrofolate reductase from Schizosaccharomyces pombe, are members of this family. Comparing the combined results to results of other proteomic methods showed that only four of the 15 proteins were identified in a recent large-scale, "shotgun" proteomic analysis and eight were identified using a related, but similar, approach (neither identifies function). Only 10 of the 15 were annotated using alternate motif-based computational tools. The results demonstrate the precision derived from combining complementary, function-based approaches to extract biological information from complex proteomes. The chemical proteomics technology indicates that a functional protein is being expressed in the cell, while the computational proteomics technology adds details about the specific type of function and residue that is likely being labeled. The combination of synergistic methods facilitates analysis, enriches true positive results, and increases confidence in novel identifications. This work also highlights the risks inherent in annotation transfer and the use of scoring functions for determination of correct annotations.     

Application of Mass Spectrometry in Proteomics

Mass spectrometry has arguably become the core technology in proteomics. The application of mass spectrometry based techniques for the qualitative and quantitative analysis of global proteome samples derived from complex mixtures has had a big impact in the understanding of cellular function. Here, we give a brief introduction to principles of mass spectrometry and instrumentation currently used in proteomics experiments. In addition, recent developments in the application of mass spectrometry in proteomics are summarised. Strategies allowing high-throughput identification of proteins from highly complex mixtures include accurate mass measurement of peptides derived from total proteome digests and multidimensional peptide separations coupled with mass spectrometry. Mass spectrometric analysis of intact proteins permits the characterisation of protein isoforms. Recent developments in stable isotope labelling techniques and chemical tagging allow the mass spectrometry based differential display and quantitation of proteins, and newly established affinity procedures enable the targeted characterisation of post-translationally modified proteins. Finally, advances in mass spectrometric imaging allow the gathering of specific information on the local molecular composition, relative abundance and spatial distribution of peptides and proteins in thin tissue sections.     

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。     

A wiring of the human nucleolus

Recent proteomic efforts have created an extensive inventory of the human nucleolar proteome. However, approximately 30% of the identified proteins lack functional annotation. We present an approach of assigning function to uncharacterized nucleolar proteins by data integration coupled to a machine-learning method. By assembling protein complexes, we present a first draft of the human ribosome biogenesis pathway encompassing 74 proteins and hereby assign function to 49 previously uncharacterized proteins. Moreover, the functional diversity of the nucleolus is underlined by the identification of a number of protein complexes with functions beyond ribosome biogenesis. Finally, we were able to obtain experimental evidence of nucleolar localization of 11 proteins, which were predicted by our platform to be associates of nucleolar complexes. We believe other biological organelles or systems could be "wired" in a similar fashion, integrating different types of data with high-throughput proteomics, followed by a detailed biological analysis and experimental validation.     

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.     

Exploring the membrane proteome—Challenges and analytical strategies

The analysis of proteins in biological membranes forms a major challenge in proteomics. Despite continuous improvements and the development of more sensitive analytical methods, the analysis of membrane proteins has always been hampered by their hydrophobic properties and relatively low abundance. In this review, we describe recent successful strategies that have led to in-depth analyses of the membrane proteome. To facilitate membrane proteome analysis, it is essential that biochemical enrichment procedures are combined with special analytical workflows that are all optimized to cope with hydrophobic polypeptides. These include techniques for protein solubilization, and also well-matched developments in protein separation and protein digestion procedures. Finally, we discuss approaches to target membrane–protein complexes and lipid–protein interactions, as such approaches offer unique insights into function and architecture of cellular membranes.     

Proteomics approaches to study genetic and metabolic disorders

Several proteomics approaches to study different aspects of genetic and metabolic diseases are presented. The choice of technique is strongly dependent on the biological question to be addressed and the availability and amount of sample. In general, there are three approaches that may be used to study genetic and metabolic diseases: protein profiling of complex biological samples, identification of affected proteins, or a functional proteomics approach to study protein interactions and function.     

In-depth analysis of the adipocyte proteome by mass spectrometry and bioinformatics

Adipocytes are central players in energy metabolism and the obesity epidemic, yet their protein composition remains largely unexplored. We investigated the adipocyte proteome by combining high accuracy, high sensitivity protein identification technology with subcellular fractionation of nuclei, mitochondria, membrane, and cytosol of 3T3-L1 adipocytes. We identified 3,287 proteins while essentially eliminating false positives, making this one of the largest high confidence proteomes reported to date. Comprehensive bioinformatics analysis revealed that the adipocyte proteome, despite its specialized role, is very complex. Comparison with microarray data showed that the mRNA abundance of detected versus non-detected proteins differed by less than 2-fold and that proteomics covered as large a proportion of the insulin signaling pathway. We used the Endeavour gene prioritization algorithm to associate a number of factors with vesicle transport in response to insulin stimulation, a key function of adipocytes. Our data and analysis can serve as a model for cellular proteomics. The adipocyte proteome is available as supplemental material and from the Max-Planck Unified Proteome database.     

Mass spectrometry for the study of protein-protein interactions

The identification of subpicomolar amounts of protein by mass spectrometry (MS) coupled with two-dimensional methods to separate complex protein mixtures is fueling the field of proteomics, and making feasible the notion of cataloging and comparing all of the expressed proteins in a biological sample. Functional proteomics is a complementary effort aimed at the characterization of functional features of proteins, such as their interactions with other proteins. Proteins comprise modular domains, many of which are noncatalytic modules that direct protein-protein interactions. Capturing proteins of interest and their interacting proteins by using high-affinity antibodies presents a simple method to prepare relatively simple protein mixtures easily resolved in one-dimensional formats. Individual or mixtures of proteins identified as stained bands in polyacrylamide gels are subjected to in situ digestion with the protease trypsin, and the extracted peptide fragments are analyzed by MS. The quality, quantity, and complexity of the tryptic digest, the species origin of the proteins, and the quality of the corresponding databases of genomic and protein information greatly influence the subsequent MS analysis in terms of degree of difficulty and methodological approach required to make an unambiguous protein identification. In this article we report the isolation of associated proteins from a complex cell-derived lysate by using an epitope-directed antibody. The protein pICLn engineered to carry an epitope tag was purified from cultured human embryonic kidney cells, and found to associate with a variety of proteins including the spliceosomal proteins smE and smG. By application of this general approach, the systematic identification of protein complexes and assignment of protein function are possible.     

Functional genomics by mass spectrometry

Systematic analysis of the function of genes can take place at the oligonucleotide or protein level. The latter has the advantage of being closest to function, since it is proteins that perform most of the reactions necessary for the cell. For most protein based ('proteomic') approaches to gene function, mass spectrometry is the method of choice. Mass spectrometry can now identify proteins with very high sensitivity and medium to high throughput. New instrumentation for the analysis of the proteome has been developed including a MALDI hybrid quadrupole time of flight instrument which combines advantages of the mass finger printing and peptide sequencing methods for protein identification. New approaches include the isotopic labeling of proteins to obtain accurate quantitative data by mass spectrometry, methods to analyze peptides derived from crude protein mixtures and approaches to analyze large numbers of intact proteins by mass spectrometry directly. Examples from this laboratory illustrate biological problem solving by modern mass spectrometric techniques. These include the analysis of the structure and function of the nucleolus and the analysis of signaling complexes.     

Organellar proteomics reveals Golgi arginine dimethylation

The Golgi complex functions to posttranslationally modify newly synthesized proteins and lipids and to sort them to their sites of function. In this study, a stacked Golgi fraction was isolated by classical cell fractionation, and the protein complement (the Golgi proteome) was characterized using multidimensional protein identification technology. Many of the proteins identified are known residents of the Golgi, and 64% of these are predicted transmembrane proteins. Proteins localized to other organelles also were identified, strengthening reports of functional interfacing between the Golgi and the endoplasmic reticulum and cytoskeleton. Importantly, 41 proteins of unknown function were identified. Two were selected for further analysis, and Golgi localization was confirmed. One of these, a putative methyltransferase, was shown to be arginine dimethylated, and upon further proteomic analysis, arginine dimethylation was identified on 18 total proteins in the Golgi proteome. This survey illustrates the utility of proteomics in the discovery of novel organellar functions and resulted in 1) a protein profile of an enriched Golgi fraction; 2) identification of 41 previously uncharacterized proteins, two with confirmed Golgi localization; 3) the identification of arginine dimethylated residues in Golgi proteins; and 4) a confirmation of methyltransferase activity within the Golgi fraction.     

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.     

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.     

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.