Advances in shotgun proteomics and the analysis of membrane proteomes

The emergence of shotgun proteomics has facilitated the numerous biological discoveries made by proteomic studies. However, comprehensive proteomic analysis remains challenging and shotgun proteomics is a continually changing field. This review details the recent developments in shotgun proteomics and describes emerging technologies that will influence shotgun proteomics going forward. In addition, proteomic studies of integral membrane proteins remain challenging due to the hydrophobic nature in integral membrane proteins and their general low abundance levels. However, there have been many strategies developed for enriching, isolating and separating membrane proteins for proteomic analysis that have moved this field forward. In summary, while shotgun proteomics is a widely used and mature technology, the continued pace of improvements in mass spectrometry and proteomic technology and methods indicate that future studies will have an even greater impact on biological discovery.     

Recent advances in the field of single-cell proteomics

The field of single-cell omics is rapidly progressing. Although DNA and RNA sequencing-based methods have dominated the field to date, global proteome profiling has also entered the main stage. Single-cell proteomics was facilitated by advancements in different aspects of mass spectrometry (MS)-based proteomics, such as instrument design, sample preparation, chromatography and ion mobility. Single-cell proteomics by mass spectrometry (scp-MS) has moved beyond being a mere technical development, and is now able to deliver actual biological application and has been successfully applied to characterize different cell states. Here, we review some key developments of scp-MS, provide a background to the field, discuss the various available methods and foresee possible future directions.     

The use of accurate mass tags for high-throughput microbial proteomics

We describe and review progress towards a global strategy that aims to extend the sensitivity, dynamic range, comprehensiveness, and throughput of proteomic measurements for microbial systems based upon the use of polypeptide accurate mass tags (AMTs) produced by global protein enzymatic digestions. The two-stage strategy exploits high accuracy mass measurements using Fourier transform ion cyclotron resonance mass spectrometry (FTICR) to validate polypeptide AMTs for a specific organism, from potential mass tags tentatively identified using tandem mass spectrometry (MS/MS), providing the basis for subsequent measurements without the need for routine MS/MS. A high-resolution capillary liquid chromatography separation combined with high sensitivity, and high-resolution accurate FTICR measurements is shown to be capable of characterizing polypeptide mixtures of more than 10(5) components, sufficient for broad protein identification using AMTs. Advantages of the approach include the high confidence of protein identification, its broad proteome coverage, and the capability for stable-isotope labeling methods for precise relative protein abundance measurements. The strategy has been initially evaluated using the microorganisms Saccharomyces cerevisiae and Deinococcus radiodurans. Additional developments, including the use of multiplexed-MS/MS capabilities and methods for dynamic range expansion of proteome measurements that promise to further extend the quality of proteomics measurements, are also described.     

Large improvements in MS/MS-based peptide identification rates using a hybrid analysis

We report a hybrid search method combining database and spectral library searches that allows for a straightforward approach to characterizing the error rates from the combined data. Using these methods, we demonstrate significantly increased sensitivity and specificity in matching peptides to tandem mass spectra. The hybrid search method increased the number of spectra that can be assigned to a peptide in a global proteomics study by 57-147% at an estimated false discovery rate of 5%, with clear room for even greater improvements. The approach combines the general utility of using consensus model spectra typical of database search methods with the accuracy of the intensity information contained in spectral libraries. A common scoring metric based on recent developments linking data analysis and statistical thermodynamics is used, which allows the use of a conservative estimate of error rates for the combined data. We applied this approach to proteomics analysis of Synechococcus sp. PCC 7002, a cyanobacterium that is a model organism for studies of photosynthetic carbon fixation and biofuels development. The increased specificity and sensitivity of this approach allowed us to identify many more peptides involved in the processes important for photoautotrophic growth.     

Translating clinical proteomics: the importance of study design

Mass spectrometry-based clinical proteomics approaches were introduced into the biomedical field more than two decades ago. Despite recent developments both in the field of mass spectrometry and bioinformatics, the gap between proteomics results and their translation into clinical practice still needs to be closed, as implementation of proteomics results in the clinic appears to be scarce. An extra focus on the importance of the experimental design is therefore of crucial importance.     

Modification-specific proteomics: characterization of post-translational modifications by mass spectrometry

Post-translational modifications generate tremendous diversity, complexity and heterogeneity of gene products, and their determination is one of the main challenges in proteomics research. Recent developments in mass spectrometry based approaches for systematic, qualitative and quantitative determination of modified proteins promise to bring new insights on the dynamics and spatio-temporal control of protein activities by post-translational modifications, and reveal their roles in biological processes and pathogenic conditions. Combinations of affinity-based enrichment and extraction methods, multidimensional separation technologies and mass spectrometry are particularly attractive for systematic investigation of post-translationally modified proteins in proteomics.     

Peptide identification by tandem mass spectrometry with alternate fragmentation modes

The high-throughput nature of proteomics mass spectrometry is enabled by a productive combination of data acquisition protocols and the computational tools used to interpret the resulting spectra. One of the key components in mainstream protocols is the generation of tandem mass (MS/MS) spectra by peptide fragmentation using collision induced dissociation, the approach currently used in the large majority of proteomics experiments to routinely identify hundreds to thousands of proteins from single mass spectrometry runs. Complementary to these, alternative peptide fragmentation methods such as electron capture/transfer dissociation and higher-energy collision dissociation have consistently achieved significant improvements in the identification of certain classes of peptides, proteins, and post-translational modifications. Recognizing these advantages, mass spectrometry instruments now conveniently support fine-tuned methods that automatically alternate between peptide fragmentation modes for either different types of peptides or for acquisition of multiple MS/MS spectra from each peptide. But although these developments have the potential to substantially improve peptide identification, their routine application requires corresponding adjustments to the software tools and procedures used for automated downstream processing. This review discusses the computational implications of alternative and alternate modes of MS/MS peptide fragmentation and addresses some practical aspects of using such protocols for identification of peptides and post-translational modifications.     

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.     

定量蛋白质组学无标记定量方法的研究进展

依靠质谱技术的蛋白质组学快速发展,寻求速度快、重复性好以及准确度高的定量方法是该领域的一项艰巨任务,定量蛋白质组学分支领域应运而生．其中,无标记定量方法以其样品制备简单、耗材费用低廉以及结果数据分析便捷等优点渐露锋芒．无标记定量方法通常分为信号强度法和谱图计数法两大类．本文在这两种无标记定量方法计算原理的基础上,针对各种常用的无标记定量方法及最新进展做一个较为全面的介绍,并将详细讨论两类方法的异同点,以及目前蛋白质组学中无标记定量方法所面临的主要挑战,希望能为这一领域的研究人员在选择无标记定量方法时提供一个合理的参考．     

Quantitation of target proteins and post-translational modifications in affinity-based proteomics approaches

As proteomics attempts to enter clinical and diagnostic application, key issues surrounding the viability of various proteomics approaches must be evaluated. A major issue at the forefront of discussion is the ability to quantitate protein targets, including the discrimination of endogenous variants that are the result of genetic and post-translational modifications. Mass spectrometry is the logical solution to this problem because of its ability to capitalize on the intrinsic property of molecular mass. However, the ability to successfully compete with classical immunoassays, the dominant technologies in the clinical and diagnostic world for quantitative protein assessment, is not a trivial task. This review offers a comprehensive discussion regarding some of the major developments in quantitative approaches towards both top-down and bottom-up proteomics. Described in more detail is the mass spectrometric immunoassay, including examples of how immunoaffinity capture is enhanced with mass spectrometry detection, and the use of this approach in protein quantification may be viewed as an improvement of the currently accepted clinical and diagnostic methodologies.     

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.     

Bioinformatics in proteomics

Several genome sequencing projects have recently been completed and the majority of human coding regions have been sequenced. In the next step many of the further studies will concentrate on proteins. Proteomics methods are essential for studying protein expression, activity, regulation and modifications. Bioinformatics is an integral part of proteomics research. The recent developments and applications in proteomics are discussed including mass spectrometry data analysis and interpretation, analysis and storage of the gel images to databases, gel comparison, and advanced methods to study e.g. protein co-expression, protein-protein interactions, as well as metabolic and cellular pathways. The significance of informatics in proteomics will gradually increase because of the advent of high-throughput methods relying on powerful data analysis.     

Recent advances in peptide separation by multidimensional liquid chromatography for proteome analysis

Shotgun proteomics dominates the field of proteomics. The foundations of the strategy consist of multiple rounds of peptide separation where chromatography provides the bedrock. Initially, the scene was relatively simple with the majority of strategies based on some types of ion exchange and reversed phase chromatography. The thirst to achieve comprehensivity, when it comes to proteome coverage and the global characterization of post translational modifications, has led to the introduction of several new separations. In this review, we attempt to provide a historical perspective to separations in proteomics as well as indicate the principles of their operation and rationales for their implementation. Furthermore, we provide a guide on what are the possibilities for combining different separations in order to increase peak capacity and proteome coverage. We aim to show how separations enrich the world of proteomics and how further developments may impact the field.     

Multiple hypothesis testing in proteomics: a strategy for experimental work

In quantitative proteomics work, the differences in expression of many separate proteins are routinely examined to test for significant differences between treatments. This leads to the multiple hypothesis testing problem: when many separate tests are performed many will be significant by chance and be false positive results. Statistical methods such as the false discovery rate method that deal with this problem have been disseminated for more than one decade. However a survey of proteomics journals shows that such tests are not widely implemented in one commonly used technique, quantitative proteomics using two-dimensional electrophoresis. We outline a selection of multiple hypothesis testing methods, including some that are well known and some lesser known, and present a simple strategy for their use by the experimental scientist in quantitative proteomics work generally. The strategy focuses on the desirability of simultaneous use of several different methods, the choice and emphasis dependent on research priorities and the results in hand. This approach is demonstrated using case scenarios with experimental and simulated model data.     

Design and analysis of experiments with high throughput biological assay data

The design and analysis of experiments using gene expression microarrays is a topic of considerable current research, and work is beginning to appear on the analysis of proteomics and metabolomics data by mass spectrometry and NMR spectroscopy. The literature in this area is evolving rapidly, and commercial software for analysis of array or proteomics data is rarely up to date, and is essentially nonexistent for metabolomics data. In this paper, I review some of the issues that should concern any biologists planning to use such high-throughput biological assay data in an experimental investigation. Technical details are kept to a minimum, and may be found in the referenced literature, as well as in the many excellent papers which space limitations prevent my describing. There are usually a number of viable options for design and analysis of such experiments, but unfortunately, there are even more non-viable ones that have been used even in the published literature. This is an area in which up-to-date knowledge of the literature is indispensable for efficient and effective design and analysis of these experiments. In general, we concentrate on relatively simple analyses, often focusing on identifying differentially expressed genes and the comparable issues in mass spectrometry and NMR spectroscopy (consistent differences in peak heights or areas for example). Complex multivariate and pattern recognition methods also need much attention, but the issues we describe in this paper must be dealt with first. The literature on analysis of proteomics and metabolomics data is as yet sparse, so the main focus of this paper will be on methods devised for analysis of gene expression data that generalize to proteomics and metabolomics, with some specific comments near the end on analysis of metabolomics data by mass spectrometry and NMR spectroscopy.     

Protein-protein interaction networks: from interactions to networks

The goal of interaction proteomics that studies the protein-protein interactions of all expressed proteins is to understand biological processes that are strictly regulated by these interactions. The availability of entire genome sequences of many organisms and high-throughput analysis tools has led scientists to study the entire proteome (Pandey and Mann, 2000). There are various high-throughput methods for detecting protein interactions such as yeast two-hybrid approach and mass spectrometry to produce vast amounts of data that can be utilized to decipher protein functions in complicated biological networks. In this review, we discuss recent developments in analytical methods for large-scale protein interactions and the future direction of interaction proteomics.     

Proteomics for routine identification of microorganisms

The invention of MALDI-TOF-MS enormously contributed to the understanding of protein chemistry and cell biology. Without this technique proteomics would most likely not be the important discipline it is today. Besides 'true' proteomics, MALDI-TOF-MS was applied for the analysis of microorganisms for their taxonomic characterization from its beginning. This approach has since been developed as a diagnostic tool readily available for routine, high-throughput analysis of microbial isolates from clinical specimens by intact-cell mass spectrometry (ICMS), the direct analysis of whole bacterial cell without a preceding fractionation or separation by chromatography or electrophoresis. ICMS exploits the reproducibility of mass fingerprints for individual bacterial and fungal strains as well as the high similarity of mass fingerprints within a species. Comparison of mass spectral data to genomic sequences emphasized the validity of peak patterns as taxonomic markers. Supported by comprehensive databases, MALDI-TOF-MS-based identification has been widely accepted in clinical laboratories within only a few years.     

基于质谱技术筛选差异表达蛋白的统计学策略研究进展

随着质谱技术的快速发展,蛋白质组学已成为继基因组学、转录组学之后的又一研究热点,寻找可靠的差异表达蛋白对于生物标记物的发现至关重要.因此,如何准确、灵敏地筛选出差异蛋白已成为基于质谱的定量蛋白质组学的主要研究内容之一.目前,针对该问题的研究方法众多,但这些方法策略的适用范围不尽相同.总体来说,基于质谱技术筛选差异蛋白的统计学策略可以分为3类:基于经典统计学派的策略、基于贝叶斯学派的统计检验策略和其他策略,这3类方法有各自的应用范围、特点及不足.此外,筛选过程还将产生部分假阳性结果,可以采用其他方法对差异表达蛋白的质量进行控制,以提高统计检验结果的可靠性.