Integrating forward and reverse proteomics to unravel protein function

To date, proteomics approaches have aimed to either identify novel proteins or change in protein expression/modification in various organisms under normal or disease conditions. One major aspect of functional proteomics is to identify protein biological properties in a given context, however, forward proteomics approaches alone cannot complete this goal. Indeed, with the increasing successes of such proteomics-based research strategies and the subsequent increasing amounts of proteins identified with unknown molecular functions, approaches allowing for systematic analyses of protein functions are desired. In this review, we propose to depict the complementarities of forward and reverse proteomics approaches in the definite understanding of protein functions. This dual strategy requires a data integration loop which allows for systematic characterization of protein function(s). The details of the integrative process combining both in silico and experimental resources and tools are presented. Altogether, we believe that the integration of forward and reverse proteomics approaches supported by bioinformatics will provide an efficient path towards systems biology.     

Interaction Proteomics

The term proteome is traditionally associated with the identification of a large number of proteins within complex mixtures originating from a given organelle, cell or even organism. Current proteome investigations are basically focused on two major areas, expression proteomics and functional proteomics. Both approaches rely on the fractionation of protein mixtures essentially by two-dimensional polyacrylamide gel electrophoresis (2D-gel) and the identification of individual protein bands by mass spectrometric techniques (2D-MS). Functional proteomics approaches are basically addressing two main targets, the elucidation of the biological function of unknown proteins and the definition of cellular mechanisms at the molecular level. In the cell many processes are governed not only by the relative abundance of proteins but also by rapid and transient regulation of activity, association and localization of proteins and protein complexes. The association of an unknown protein with partners belonging to a specific protein complex involved in a particular process would then be strongly suggestive of its biological function. The identification of interacting proteins in stable complexes in a cellular system is essentially achieved by affinity-based procedures. Different strategies relying on this simple concept have been developed and a brief overview of the main approaches presently used in functional proteomics studies is described.     

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.     

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.     

High-throughput expression,purification, and characterization of recombinant Caenorhabditis elegans proteins

Modern proteomics approaches include techniques to examine the expression, localization, modifications, and complex formation of proteins in cells. In order to address issues of protein function in vitro using classical biochemical and biophysical approaches, high-throughput methods of cloning the appropriate reading frames, and expressing and purifying proteins efficiently are an important goal of modern proteomics approaches. This process becomes more difficult as functional proteomics efforts focus on the proteins from higher organisms, since issues of correctly identifying intron-exon boundaries and efficiently expressing and solubilizing the (often) multi-domain proteins from higher eukaryotes are challenging. Recently, 12,000 open-reading-frame (ORF) sequences from Caenorhabditis elegans have become available for functional proteomics studies [Nat. Gen. 34 (2003) 35]. We have implemented a high-throughput screening procedure to express, purify, and analyze by mass spectrometry hexa-histidine-tagged C. elegans ORFs in Escherichia coli using metal affinity ZipTips. We find that over 65% of the expressed proteins are of the correct mass as analyzed by matrix-assisted laser desorption MS. Many of the remaining proteins indicated to be "incorrect" can be explained by high-throughput cloning or genome database annotation errors. This provides a general understanding of the expected error rates in such high-throughput cloning projects. The ZipTip purified proteins can be further analyzed under both native and denaturing conditions for functional proteomics efforts.     

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。     

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.     

膜转运蛋白的功能性超表达和纯化

膜转运蛋白结构和功能的研究是功能膜蛋白质组研究中的一个重要内容,而大量蛋白质的分离纯化是进行蛋白质的结构和功能研究的基础.目前,结构和功能膜蛋白质组学相关研究的瓶颈,在于不能有效地超量表达和纯化具有生物活性的膜转运蛋白.影响膜转运蛋白超量表达和纯化的关键因素,包括目标蛋白的拓扑学结构分析和去垢剂的选择.进行膜转运蛋白拓扑学结构的分析,对于构建用于活体表达的重组膜转运蛋白具有指导意义.去垢剂能够稳定去膜状态的膜蛋白,在膜转运蛋白的离体表达和亲和纯化以及包涵体的处理过程中具有重要的作用.本文就目前功能膜蛋白质组学研究中所涉及的有关膜转运蛋白功能性超表达和分离纯化策略及关键技术作一简述.     

Cutting-edge technology. II. Proteomics: core technologies and applications in physiology

Technologies for proteomics, e.g., studies examining the protein complement of the genome, have been in development for over 20 years. More recently, proteomics has become formalized by combining techniques for large-scale protein separation with very precise, high-fidelity approaches that analyze, identify, and characterize the separated proteins. These methods bring to reality the powerful scope of proteomics, enabling researchers to investigate cellular function at the protein level and thus representing one of proteomics' most fitting applications. In this review, we take a brief and concise look at some of the current, physiologically relevant technologies that comprise proteomics and report specific applications in which proteomics has provided valuable biological insight.     

The German cDNA Network: cDNAs,functional genomics and proteomics

Among the greatest challenges facing biology today is the exploitation of huge amounts of genomic data, and their conversion into functional information about the proteins encoded. For example, the large-scale cDNA sequencing project of the German cDNA Consortium is providing vast numbers of open reading frames (ORFs) encoding novel proteins of completely unknown function. As a first step towards their characterization we have tagged over 500 of these with the green fluorescent protein (GFP), and examined the subcellular localizations of these fusion proteins in living cells. These data have allowed us to classify the proteins into subcellular groups which determines the next step towards a detailed functional characterization. To make further use of these GFP-tagged constructs, a series of functional assays have been designed and implemented to assess the effect of these novel proteins on processes such as cell growth, cell death, and protein transport.Functional assays with such a large set of molecules is only possible by automation. Therefore, we have developed, and adapted, functional assays for use by robotic liquid handling stations and reading stations. A transport assay allows to identify proteins which localize to distinct organelles of the secretory pathway and have the potential to be new regulators in protein transport, a proliferation assay helps identifying proteins that stimulate or repress mitosis. Further assays to monitor the effects of the proteins in apoptosis and signal transduction pathways are in progress. Integrating the functional information that is generated in the assays with data from expression profiling and further functional genomics and proteomics approaches, will ultimately allow us to identify functional networks of proteins in a morphological context, and will greatly contribute to our understanding of cell function.     

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.     

Mass spectrometry-based proteomics turns quantitative

The field of proteomics is built on technologies to analyze large numbers of proteins--ideally the entire proteome--in the same experiment. Mass spectrometry (MS) has been successfully used to characterize proteins in complex mixtures, but results so far have largely been qualitative. Two recently developed methodologies offer the opportunity to obtain quantitative proteomic information. Comparing the signals from the same peptide under different conditions yields a rough estimate of relative protein abundance between two proteomes. Alternatively, and more accurately, peptides are labeled with stable isotopes, introducing a predictable mass difference between peptides from two experimental conditions. Stable isotope labels can be incorporated 'post-harvest', by chemical approaches or in live cells through metabolic incorporation. This isotopic handle facilitates direct quantification from the mass spectra. Using these quantitative approaches, precise functional information as well as temporal changes in the proteome can be captured by MS.     

Application of proteomics to ecology and population biology

Proteomics is a relatively new scientific discipline that merges protein biochemistry, genome biology and bioinformatics to determine the spatial and temporal expression of proteins in cells, tissues and whole organisms. There has been very little application of proteomics to the fields of behavioral genetics, evolution, ecology and population dynamics, and has only recently been effectively applied to the closely allied fields of molecular evolution and genetics. However, there exists considerable potential for proteomics to impact in areas related to functional ecology; this review will introduce the general concepts and methodologies that define the field of proteomics and compare and contrast the advantages and disadvantages with other methods. Examples of how proteomics can aid, complement and indeed extend the study of functional ecology will be discussed including the main tool of ecological studies, population genetics with an emphasis on metapopulation structure analysis. Because proteomic analyses provide a direct measure of gene expression, it obviates some of the limitations associated with other genomic approaches, such as microarray and EST analyses. Likewise, in conjunction with associated bioinformatics and molecular evolutionary tools, proteomics can provide the foundation of a systems-level integration approach that can enhance ecological studies. It can be envisioned that proteomics will provide important new information on issues specific to metapopulation biology and adaptive processes in nature. A specific example of the application of proteomics to sperm ageing is provided to illustrate the potential utility of the approach.     

Structural proteomics: developments in structure-to-function predictions

The major challenge for post-genomic research is to functionally assign and validate a large number of novel target genes and their corresponding proteins. Functional genomics approaches have, therefore, gained considerable attention in the quest to convert this massive data set into useful information. One of the crucial components for the functional understanding of unassigned proteins is the analysis of their experimental or modeled 3D structures. Structural proteomics initiatives are generating protein structures at an unprecedented rate but our current knowledge of 3D-structural space is still limited. Estimates on the completeness of the 3D-structural coverage of proteins vary but it is generally accepted that only a minority of the structural proteome has a template structure from which reliable conclusions can be drawn. Thus, structural proteomics has set out to build a map of protein structures that will represent all protein folds included in the 'global proteome'.     

An overview of human protein databases and their application to functional proteomics in health and disease

Functional proteomics can be defined as a strategy to couple proteomic information with biochemical and physiological analyses with the aim of understanding better the functions of proteins in normal and diseased organs. In recent years, a variety of publicly available bioinformatics databases have been developed to support protein-related information management and biological knowledge discovery. In addition to being used to annotate the proteome, these resources also offer the opportunity to develop global approaches to the study of the functional role of proteins both in health and disease. Here, we present a comprehensive review of the major human protein bioinformatics databases. We conclude this review by discussing a few examples that illustrate the importance of these databases in functional proteomics research.     

Methodologies for characterizing phosphoproteins by mass spectrometry

Posttranslational regulation of proteins via protein phosphorylation is one of the major means of protein regulation. Phosphorylation is a very rapid and reversible method of changing the function of proteins. Detection of phosphorylated proteins and the identification of phosphorylation sites are necessary to molecularly link specific phosphorylated events with change in phosphoprotein function. Mass Spectrometry (MS) has become the methodology of choice for phosphosite identification. Here we review current approaches including sample separation and enrichment techniques (SDS-PAGE, immunoprecipitation, metal-assisted enrichment, strong cation exchange, dendrimer capture), quantitative MS analysis methods (SILAC, iTRAQ, AQUA), and the application of recently developed methods including electron transfer dissociation ionization and "top-down" proteomics to phosphoprotein analysis.