Vectorial proteomics

Vectorial proteomics is a methodology for the differential identification and characterization of proteins and their domains exposed to the opposite sides of biological membranes. Proteomics of membrane vesicles from defined isolated membranes automatically determine cellular localization of the identified proteins and reduce complexity of protein characterizations. The enzymatic shaving of naturally-oriented, or specifically-inverted sealed membrane vesicles, release the surface-exposed peptides from membrane proteins. These soluble peptides are amenable to various chromatographic separations and to sequencing by mass spectrometry, which provides information on the topology of membrane proteins and on their posttranslational modifications. The membrane shaving techniques have made a breakthrough in the identification of in vivo protein phosphorylation sites in membrane proteins form plant photosynthetic and plasma membranes, and from caveolae membrane vesicles of human fat cells. This approach has also allowed investigation of dynamics for in vivo protein phosphorylation in membranes from cells exposed to different conditions. Vectorial proteomics of membrane vesicles with retained peripheral proteins identify extrinsic proteins associated with distinct membrane surfaces, as well as a variety of posttranslational modifications in these proteins. The rapid integration of versatile vectorial proteomics techniques in the functional characterization of biological membranes is anticipated to bring significant insights in cell biology.     

The effects of shared peptides on protein quantitation in label-free proteomics by LC/MS/MS

Assessment of differential protein abundance from the observed properties of detected peptides is an essential part of protein profiling based on shotgun proteomics. However, the abundance observed for shared peptides may be due to contributions from multiple proteins that are affected differently by a given treatment. Excluding shared peptides eliminates this ambiguity but may significantly decrease the number of proteins for which abundance estimates can be obtained. Peptide sharing within a family of biologically related proteins does not cause ambiguity if family members have a common response to treatment. On the basis of this concept, we have developed an approach for including shared peptides in the analysis of differential protein abundance in protein profiling. Data from a recent proteomics study of lung tissue from mice exposed to lipopolysaccharide, cigarette smoke, and a combination of these agents are used to illustrate our method. Starting from data where about half of the implicated database protein involved shared peptides, 82% of the affected proteins were grouped into families, based on FASTA annotation, with closure on peptide sharing. In many cases, a common abundance relative to control was sufficient to explain ion-current peak areas for peptides, both unique and shared, that identified biologically related proteins in a peptide-sharing closure group. On the basis of these results, we propose that peptide-sharing closure groups provide a way to include abundance data for shared peptides in quantitative protein profiling by high-throughput mass spectrometry.     

胰蛋白酶镜像酶LysargiNase的开发及其在蛋白质组学研究中的应用

蛋白质组学是系统鉴定、定量蛋白质及其翻译后修饰形式,并研究这些蛋白质生物学功能的学科。目前,基于质谱的鸟枪法蛋白质组学技术是蛋白质组学研究的主要手段之一,其技术流程是先将蛋白质组样品经位点特异性蛋白酶消化形成肽组,再进行高效液相色谱分离和质谱检测。而位点特异性蛋白酶对蛋白质样品的消化是质谱检测的前提和基础。随着蛋白质组学研究的深入,多种位点特异性蛋白酶被先后开发利用;而切割发生在相应氨基酸的N端,与传统的C端蛋白酶互为镜像的蛋白酶的鉴定、开发、特性研究和广泛使用更是为蛋白质组学研究提供了新的工具。文中对最近发现的胰蛋白酶的镜像酶——赖氨酸精氨酸N端蛋白酶(LysargiNase)的特点及其应用进行综述,为国内外学者更加广泛的使用创造条件。     

Perfluorooctanoic acid for shotgun proteomics

Here, we describe the novel use of a volatile surfactant, perfluorooctanoic acid (PFOA), for shotgun proteomics. PFOA was found to solubilize membrane proteins as effectively as sodium dodecyl sulfate (SDS). PFOA concentrations up to 0.5% (w/v) did not significantly inhibit trypsin activity. The unique features of PFOA allowed us to develop a single-tube shotgun proteomics method that used all volatile chemicals that could easily be removed by evaporation prior to mass spectrometry analysis. The experimental procedures involved: 1) extraction of proteins in 2% PFOA; 2) reduction of cystine residues with triethyl phosphine and their S-alkylation with iodoethanol; 3) trypsin digestion of proteins in 0.5% PFOA; 4) removal of PFOA by evaporation; and 5) LC-MS/MS analysis of the resulting peptides. The general applicability of the method was demonstrated with the membrane preparation of photoreceptor outer segments. We identified 75 proteins from 1 μg of the tryptic peptides in a single, 1-hour, LC-MS/MS run. About 67% of the proteins identified were classified as membrane proteins. We also demonstrate that a proteolytic (18)O labeling procedure can be incorporated after the PFOA removal step for quantitative proteomic experiments. The present method does not require sample clean-up devices such as solid-phase extractions and membrane filters, so no proteins/peptides are lost in any experimental steps. Thus, this single-tube shotgun proteomics method overcomes the major drawbacks of surfactant use in proteomic experiments.     

Mass spectrometry-based quantitative proteomics

A major aim of present-day proteomics is to study changes in protein expression levels at a global level, ideally monitoring all proteins present in cells or tissue. Mass spectrometry is a well-respected technology in proteomics that is widely used for the identification of proteins. More recently, methodologies have been introduced showing that mass spectrometry can also be used for protein quantification. This article reviews various mass spectrometry-based technologies in quantitative proteomics, highlighting several interesting applications in areas ranging from cell biology to clinical applications.     

Mass spectrometry-based quantitative proteomics

A major aim of present-day proteomics is to study changes in protein expression levels at a global level, ideally monitoring all proteins present in cells or tissue. Mass spectrometry is a well-respected technology in proteomics that is widely used for the identification of proteins. More recently, methodologies have been introduced showing that mass spectrometry can also be used for protein quantification. This article reviews various mass spectrometry-based technologies in quantitative proteomics, highlighting several interesting applications in areas ranging from cell biology to clinical applications.     

Applications of affinity chromatography in proteomics

Affinity chromatography is a powerful protein separation method that is based on the specific interaction between immobilized ligands and target proteins. Peptides can also be separated effectively by affinity chromatography through the use of peptide-specific ligands. Both two-dimensional electrophoresis (2-DE)- and non-2-DE-based proteomic approaches benefit from the application of affinity chromatography. Before protein separation by 2-DE, affinity separation is used primarily for preconcentration and pretreatment of samples. Those applications entail the removal of one protein or a class of proteins that might interfere with 2-DE resolution, the concentration of low-abundance proteins to enable them to be visualized in the gel, and the classification of total protein into two or more groups for further separation by gel electrophoresis. Non-2-DE-based approaches have extensively employed affinity chromatography to reduce the complexity of protein and peptide mixtures. Prior to mass spectrometry (MS), preconcentration and capture of specific proteins or peptides to enhance sensitivity can be accomplished by using affinity adsorption. Affinity purification of protein complexes followed by identification of proteins by MS serves as a powerful tool for generating a map of protein-protein interactions and cellular locations of complexes. Affinity chromatography of peptide mixtures, coupled with mass spectrometry, provides a tool for the study of protein posttranslational modification (PTM) sites and quantitative proteomics. Quantitation of proteomes is possible via the use of isotope-coded affinity tags and isolation of proteolytic peptides by affinity chromatography. An emerging area of proteomics technology development is miniaturization. Affinity chromatography is becoming more widely used for exploring PTM and protein-protein interactions, especially with a view toward developing new general tag systems and strategies of chemical derivatization on peptides for affinity selection. More applications of affinity-based purification can be expected, including increasing the resolution in 2-DE, improving the sensitivity of MS quantification, and incorporating purification as part of multidimensional liquid chromatography experiments.     

From protein catalogues towards targeted proteomics approaches in cereal grains

Due to their importance for human nutrition, the protein content of cereal grains has been a subject of intense study for over a century and cereal grains were not surprisingly one of the earliest subjects for 2D-gel-based proteome analysis. Over the last two decades, countless cereal grain proteomes, mostly derived using 2D-gel based technologies, have been described and hundreds of proteins identified. However, very little is still known about post-translational modifications, subcellular proteomes, and protein-protein interactions in cereal grains. Development of techniques for improved extraction, separation and identification of proteins and peptides is facilitating functional proteomics and analysis of sub-proteomes from small amounts of starting material, such as seed tissues. The combination of proteomics with structural and functional analysis is increasingly applied to target subsets of proteins. These “next-generation” proteomics studies will vastly increase our depth of knowledge about the processes controlling cereal grain development, nutritional and processing characteristics.     

Halobacterium salinarum NRC-1 PeptideAtlas: toward strategies for targeted proteomics and improved proteome coverage

The relatively small numbers of proteins and fewer possible post-translational modifications in microbes provide a unique opportunity to comprehensively characterize their dynamic proteomes. We have constructed a PeptideAtlas (PA) covering 62.7% of the predicted proteome of the extremely halophilic archaeon Halobacterium salinarum NRC-1 by compiling approximately 636 000 tandem mass spectra from 497 mass spectrometry runs in 88 experiments. Analysis of the PA with respect to biophysical properties of constituent peptides, functional properties of parent proteins of detected peptides, and performance of different mass spectrometry approaches has highlighted plausible strategies for improving proteome coverage and selecting signature peptides for targeted proteomics. Notably, discovery of a significant correlation between absolute abundances of mRNAs and proteins has helped identify low abundance of proteins as the major limitation in peptide detection. Furthermore, we have discovered that iTRAQ labeling for quantitative proteomic analysis introduces a significant bias in peptide detection by mass spectrometry. Therefore, despite identifying at least one proteotypic peptide for almost all proteins in the PA, a context-dependent selection of proteotypic peptides appears to be the most effective approach for targeted proteomics.     

A protease for 'middle-down' proteomics

We developed a method for restricted enzymatic proteolysis using the outer membrane protease T (OmpT) to produce large peptides (>6.3 kDa on average) for mass spectrometry-based proteomics. Using this approach to analyze prefractionated high-mass HeLa proteins, we identified 3,697 unique peptides from 1,038 proteins. We demonstrated the ability of large OmpT peptides to differentiate closely related protein isoforms and to enable the detection of many post-translational modifications.     

Quantitative proteomics targeting classes of motif-containing peptides using immunoaffinity-based mass spectrometry

The development of high-performance technology platforms for generating detailed protein expression profiles, or protein atlases, is essential. Recently, we presented a novel platform that we termed global proteome survey, where we combined the best features of affinity proteomics and mass spectrometry, to probe any proteome in a species independent manner while still using a limited set of antibodies. We used so called context-independent-motif-specific antibodies, directed against short amino acid motifs. This enabled enrichment of motif-containing peptides from a digested proteome, which then were detected and identified by mass spectrometry. In this study, we have demonstrated the quantitative capability, reproducibility, sensitivity, and coverage of the global proteome survey technology by targeting stable isotope labeling with amino acids in cell culture-labeled yeast cultures cultivated in glucose or ethanol. The data showed that a wide range of motif-containing peptides (proteins) could be detected, identified, and quantified in a highly reproducible manner. On average, each of six different motif-specific antibodies was found to target about 75 different motif-containing proteins. Furthermore, peptides originating from proteins spanning in abundance from over a million down to less than 50 copies per cell, could be targeted. It is worth noting that a significant set of peptides previously not reported in the PeptideAtlas database was among the profiled targets. The quantitative data corroborated well with the corresponding data generated after conventional strong cation exchange fractionation of the same samples. Finally, several differentially expressed proteins, with both known and unknown functions, many relevant for the central carbon metabolism, could be detected in the glucose- versus ethanol-cultivated yeast. Taken together, the study demonstrated the potential of our immunoaffinity-based mass spectrometry platform for reproducible quantitative proteomics targeting classes of motif-containing peptides.     

Quantitative proteomics and protein network analysis of hippocampal synapses of CaMKIIalpha mutant mice

Quantitative analysis of synaptic proteomes from specific brain regions is important for our understanding of the molecular basis of neuroplasticity and brain disorders. In the present study we have optimized comparative synaptic proteome analysis to quantitate proteins of the synaptic membrane fraction isolated from the hippocampus of wild type mice and 3'UTR-calcium/calmodulin-dependent kinase II alpha mutant mice. Synaptic proteins were solubilized in 0.85% RapiGest and digested with trypsin without prior dilution of the detergent, and the peptides from two groups of wild type mice and two groups of CaMKIIalpha 3'UTR mutants were tagged with iTRAQ reagents 114, 115, 116, and 117, respectively. The experiment was repeated once with independent biological replicates. Peptides were fractionated with tandem liquid chromatography and collected off-line onto MALDI metal plates. The first iTRAQ experiment was analyzed on an ABI 4700 proteomics analyzer, and the second experiment was analyzed on an ABI 4800 proteomics analyzer. Using the criteria that the proteins should be matched with at least three peptides with the highest CI% of a peptide at least 95%, 623 and 259 proteins were quantified by a 4800 proteomics analyzer and a 4700 proteomics analyzer, respectively, from which 249 proteins overlapped in the two experiments. There was a 3 fold decrease of calcium/calmodulin-dependent kinase II alpha in the synaptic membrane fraction of the 3'UTR mutant mice. No other major changes were observed, suggesting that the synapse protein constituents of the mutant mice were not substantially altered. A first draft of a synaptic protein interaction network has been constructed using commercial available software, and the synaptic proteins were organized into 10 (interconnecting) functional groups belonging to the pre- and postsynaptic compartments, e.g., receptors and ion channels, scaffolding proteins, cytoskeletal proteins, signaling proteins, adhesion molecules, and proteins of synaptic vesicles and those involved in membrane recycling.     

Positional proteomics: selective recovery and analysis of N-terminal proteolytic peptides

Bottom-up proteomics is the analysis of peptides derived from single proteins or protein mixtures, and because each protein generates tens of peptides, there is scope for controlled reduction in complexity. We report here a new strategy for selective isolation of the N-terminal peptides of a protein mixture, yielding positionally defined peptides. The method is tolerant of several fragmentation methods, and the databases that must be searched are substantially less complex.     

Multiplexed absolute quantification for proteomics using concatenated signature peptides encoded by QconCAT genes

An important area of proteomics involves the need for quantification, whether relative or absolute. Many methods now exist for relative quantification, but to support biomarker proteomics and systems biology, absolute quantification rather than relative quantification is required. Absolute quantification usually involves the concomitant mass spectrometric determination of signature proteotypic peptides and stable isotope-labeled analogs. However, the availability of standard labeled signature peptides in accurately known amounts is a limitation to the widespread adoption of this approach. We describe the design and synthesis of artificial QconCAT proteins that are concatamers of tryptic peptides for several proteins. This protocol details the methods for the design, expression, labeling, purification, characterization and use of the QconCATs in the absolute quantification of complex protein mixtures. The total time required to complete this protocol (from the receipt of the QconCAT expression plasmid to the absolute quantification of the set of proteins encoded by the QconCAT protein in an analyte sample) is approximately 29 d.     

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.     

Plant membrane proteomics

Plant membrane proteins are involved in many different functions according to their location in the cell. For instance, the chloroplast has two membrane systems, thylakoids and envelope, with specialized membrane proteins for photosynthesis and metabolite and ion transporters, respectively. Although recent advances in sample preparation and analytical techniques have been achieved for the study of membrane proteins, the characterization of these proteins, especially the hydrophobic ones, is still challenging. The present review highlights recent advances in methodologies for identification of plant membrane proteins from purified subcellular structures. The interest of combining several complementary extraction procedures to take into account specific features of membrane proteins is discussed in the light of recent proteomics data, notably for chloroplast envelope, mitochondrial membranes and plasma membrane from Arabidopsis. These examples also illustrate how, on one hand, proteomics can feed bioinformatics for a better definition of prediction tools and, on the other hand, although prediction tools are not 100% reliable, they can give valuable information for biological investigations. In particular, membrane proteomics brings new insights over plant membrane systems, on both the membrane compartment where proteins are working and their putative cellular function.     

A combination of immobilised pH gradients improves membrane proteomics

Membrane protein analyses have been notoriously difficult due to hydrophobicity and the general low abundance of these proteins compared to their soluble cytosolic counterparts. Shotgun proteomics has become the preferred method for analyses of membrane proteins, in particular the recent development of peptide immobilized pH gradient isoelectric focusing (IPG-IEF) as the first dimension of two-dimensional shotgun proteomics. Recently, peptide IPG-IEF has been shown to be a valuable shotgun proteomics technique through the use of acidic narrow range IPG strips, which demonstrated that small acidic p I increments are rich in peptides. In this study, we assess the utility of both broad range (BR) (p I 3-10) and narrow range (NR) (p I 3.4-4.9) IPG strips for rat liver membrane protein analyses. Furthermore, the use of these IPG strips was evaluated using label-free quantitation to demonstrate that the identification of a subset of proteins can be improved using NR IPG strips. NR IPG strips provided 2603 protein assignments on average (with 826 integral membrane proteins (IMPs)) compared to BR IPG strips, which provided 2021 protein assignments on average (with 712 IMPs). Nonredundant protein analysis demonstrated that in total from all experiments, 4195 proteins (with 1301 IMPs) could be identified with 1428 of these proteins unique to NR IPG strips with only 636 from BR IPG strips. With the use of label-free quantitation methods, 1659 proteins were used for quantitative comparison of which 319 demonstrated statistically significant increases in normalized spectral abundance factors (NSAF) in NR IPG strips compared to 364 in BR IPG strips. In particular, a selection of six highly hydrophobic transmembrane proteins was observed to increase in NSAF using NR IPG strips. These results provide evidence for the use of alternative pH gradients in combination to improve the shotgun proteomic analysis of the membrane proteome.