Analysis of the mouse liver proteome using advanced mass spectrometry

We report a large-scale analysis of mouse liver tissue comprising a novel fractionation approach and high-accuracy mass spectrometry techniques. Two fractions enriched for soluble and membrane proteins from 20 mg of frozen tissue were separated by one-dimensional electrophoresis followed by LC-MS/MS on the hybrid linear ion trap (LTQ)-Orbitrap mass spectrometer. Confident identification of 2210 proteins relied on at least two peptides. We combined this proteome with our previously reported organellar map (Foster et al. Cell 2006, 125, 187-199) to generate a very high confidence mouse liver proteome of 3244 proteins. The identified proteins represent the liver proteome with no discernible bias due to protein physicochemical properties, subcellular distribution, or biological function. Forty-seven percent of identified proteins were annotated as membrane-bound, and for 35.3%, transmembrane domains were predicted. For potential application in toxicology or clinical studies, we demonstrate that it is possible to consistently identify more than 1000 proteins in a single run.     

Advances in mass spectrometry for proteome analysis

The most demanding problems in proteomics continue to challenge modern mass spectrometry. Recent developments in instrument design have led to lower limits of detection, while new ion activation techniques and improved understanding of gas-phase ion chemistry have enhanced the capabilities of tandem mass spectrometry for peptide and protein structure elucidation. Future developments must address the., understanding of protein-protein interactions and the characterisation of the dynamic proteome.     

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.     

Advances in proteome analysis by mass spectrometry

Proteome characterization using mass spectrometry is essential for the systematic investigation of biological systems and for the study of gene function. Recent advances in this multifaceted field have occurred in four general areas: protein and peptide separation methodologies; selective labeling chemistries for quantitative measurement of peptide and protein abundances; characterization of post-translational protein modifications; and instrumentation.     

Strategy for surveying the proteome using affinity proteomics and mass spectrometry

Antibody‐based microarrays is a rapidly evolving technology that has gone from the first proof‐of‐concept studies to more demanding proteome profiling applications, during the last years. Miniaturized microarrays can be printed with large number of antibodies harbouring predetermined specificities, capable of targeting high‐ as well as low‐abundant analytes in complex, nonfractionated proteomes. Consequently, the resolution of such proteome profiling efforts correlate directly to the number of antibodies included, which today is a key limiting factor. To overcome this bottleneck and to be able to perform in‐depth global proteome surveys, we propose to interface affinity proteomics with MS‐based read‐out, as outlined in this technical perspective. Briefly, we have defined a range of peptide motifs, each motif being present in 5–100 different proteins. In this manner, 100 antibodies, binding 100 different motifs commonly distributed among different proteins, would potentially target a protein cluster of 10⁴ individual molecules, i.e. around 50% of the nonredundant human proteome. Notably, these motif‐specific antibodies would be directly applicable to any proteome in a specie independent manner and not biased towards abundant proteins or certain protein classes. The biological sample is digested, exposed to these immobilized antibodies, whereby motif‐containing peptides are specifically captured, enriched and subsequently detected and identified using MS.     

Generating and navigating proteome maps using mass spectrometry

Proteomes, the ensembles of all proteins expressed by cells or tissues, are typically analysed by mass spectrometry. Recent technical and computational advances have greatly increased the fraction of a proteome that can be identified and quantified in a single study. Current mass spectrometry-based proteomic strategies have the potential to reproducibly, accurately, quantitatively and comprehensively measure any protein or whole proteomes from cells and tissues at different states. Achieving these goals will require complete proteome maps and analytical strategies that use these maps as prior information and will greatly enhance the impact of proteomics on biological and clinical research.     

Current chemical tagging strategies for proteome analysis by mass spectrometry

Proteomics, the analysis of the protein complement of a cell or an organism, has grown rapidly as a subdiscipline of the life sciences. Mass spectrometry (MS) is one of the central detection techniques in proteome analysis, yet it has to rely on prior sample preparation steps that reduce the enormous complexity of the protein mixtures obtained from biological systems. For that reason, a number of so-called tagging (or labeling) strategies have been developed that target specific amino acid residues or post-translational modifications, enabling the enrichment of subfractions via affinity clean-up, resulting in the identification of an ever increasing number of proteins. In addition, the attachment of stable-isotope-labeled tags now allows the relative quantitation of protein levels of two samples, e.g. those representing different cell states, which is of great significance for drug discovery and molecular biology. Finally, tagging schemes also serve to facilitate interpretation of MS/MS spectra, therefore assisting in de novo elucidation of protein sequences and automated database searching. This review summarizes the different application fields for tagging strategies for today's MS-based proteome analysis. Advantages and drawbacks of the numerous strategies that have appeared in the literature in the last years are highlighted, and an outlook on emerging tagging techniques is given.     

Comparison of statistical methods for classification of ovarian cancer using mass spectrometry data

MOTIVATION: Novel methods, both molecular and statistical, are urgently needed to take advantage of recent advances in biotechnology and the human genome project for disease diagnosis and prognosis. Mass spectrometry (MS) holds great promise for biomarker identification and genome-wide protein profiling. It has been demonstrated in the literature that biomarkers can be identified to distinguish normal individuals from cancer patients using MS data. Such progress is especially exciting for the detection of early-stage ovarian cancer patients. Although various statistical methods have been utilized to identify biomarkers from MS data, there has been no systematic comparison among these approaches in their relative ability to analyze MS data. RESULTS: We compare the performance of several classes of statistical methods for the classification of cancer based on MS spectra. These methods include: linear discriminant analysis, quadratic discriminant analysis, k-nearest neighbor classifier, bagging and boosting classification trees, support vector machine, and random forest (RF). The methods are applied to ovarian cancer and control serum samples from the National Ovarian Cancer Early Detection Program clinic at Northwestern University Hospital. We found that RF outperforms other methods in the analysis of MS data.     

High resolution proteome analysis of cryoglobulins using Fourier transform-ion cyclotron resonance mass spectrometry

Cryoglobulins are cold-precipitable serum immunoglobulins associated with a number of infectious, autoimmune and neoplastic disorders such as hepatitis C, Waldenstr?m's macroglobulinemia, multiple myeloma, chronic lymphocytic leukemia, and rheumatoid arthritis. The mechanism(s) of cryoprecipitation has remained obscure hitherto, which has prompted recent intensive efforts on the identification of cryoglobulin components. In the present study, two-dimensional gel electrophoresis (2-DE) combined with high resolution Fourier transform-ion cyclotron resonance (FT-ICR) mass spectrometry has been applied as a powerful approach for the analysis of cryoglobulins. While FT-ICR mass spectrometry has been shown to enable the high resolution identification and structure analysis of biopolymers using both electrospray (ESI) and matrix-assisted laser desorption ionization (MALDI), the recently developed MALDI-FT-ICR source is shown here to provide high (sub-ppm) mass determination accuracy and isotopic fine structure as particular advantages in the identification of proteins. The main protein components in a serum cryoprecipitate from a patient with hepatitis C virus (HCV) infection and presenting type II cryogobulinemia are immunoglobulin (Ig)M and IgG which were identified by MALDI-FT-ICR MS analysis after separation by 2-DE as mu- and gamma-heavy chains, kappa- and lambda-light chains, and J-chains. Furthermore, complementarity determining regions CDR1 and CDR2 from monoclonal IgM-RF variable region (V)L were directly identified using accurate mass determinations by FT-ICR-MS. The presence of Spalpha was ascertained as an IgM-associated protein in the serum cryoprecipitate from a patient with HCV infection.     

Characterization of the mouse bronchoalveolar lavage proteome by micro-capillary LC-FTICR mass spectrometry

Bronchoalveolar lavage fluid (BALF) contains proteins derived from various pulmonary cell types, secretions and blood. As the characterization of the BALF proteome will be instrumental in establishing potential biomarkers of pathophysiology in the lungs, the objective of this study was to contribute to the comprehensive collection of Mus musculus BALF proteins using high resolution and highly sensitive micro-capillary liquid chromatography (microLC) combined with state-of-the-art high resolution mass spectrometry (MS). BALF was collected from ICR and C57BL/6 male mice exposed to nose-only inhalation to either air or cigarette smoke. The tandem mass spectra were analyzed by SEQUEST for peptide identifications with the subsequent application of accurate mass and time tags resulting in the identification of 1797 peptides with high confidence by high resolution MS. These peptides covered 959 individual proteins constituting the largest collection of BALF proteins to date. High throughput monitoring profiles of this extensive collection of BALF proteins will facilitate the discovery and validation of biomarkers that would elucidate pathogenic or adaptive responses of the lungs upon toxic insults.     

Gel absorption-based sample preparation for the analysis of membrane proteome by mass spectrometry

A gel absorption-based sample preparation method for shotgun analysis of membrane proteome has been developed. In this new method, membrane proteins solubilized in a starting buffer containing a high concentration of sodium dodecyl sulfate (SDS) were directly entrapped and immobilized into gel matrix when the membrane protein solution was absorbed by the vacuum-dried polyacrylamide gel. After the detergent and other salts were removed by washing, the proteins were subjected to in-gel digestion and the tryptic peptides were extracted and analyzed by capillary liquid chromatography coupled with tandem mass spectrometry (CapLC-MS/MS). The results showed that the newly developed method not only avoided the protein loss and the adverse protein modifications during gel embedment but also improved the subsequent in-gel digestion and the recovery of tryptic peptides, particularly the hydrophobic peptides, thereby facilitating the identification of membrane proteins, especially the integral membrane proteins. Compared with the conventional tube-gel digestion method, the newly developed method increased the numbers of identified membrane proteins and integral membrane proteins by 25.0% and 30.2%, respectively, demonstrating that the method is of broad practicability in gel-based shotgun analysis of membrane proteome.     

Characterization of the mouse brain proteome using global proteomic analysis complemented with cysteinyl-peptide enrichment

We report a global proteomic approach for analyzing brain tissue and for the first time a comprehensive characterization of the whole mouse brain proteome. Preparation of the whole brain sample incorporated a highly efficient cysteinyl-peptide enrichment (CPE) technique to complement a global enzymatic digestion method. Both the global and the cysteinyl-enriched peptide samples were analyzed by SCX fractionation coupled with reversed phase LC-MS/MS analysis. A total of 48,328 different peptides were confidently identified (>98% confidence level), covering 7792 nonredundant proteins ( approximately 34% of the predicted mouse proteome). A total of 1564 and 1859 proteins were identified exclusively from the cysteinyl-peptide and the global peptide samples, respectively, corresponding to 25% and 31% improvements in proteome coverage compared to analysis of only the global peptide or cysteinyl-peptide samples. The identified proteins provide a broad representation of the mouse proteome with little bias evident due to protein pI, molecular weight, and/or cellular localization. Approximately 26% of the identified proteins with gene ontology (GO) annotations were membrane proteins, with 1447 proteins predicted to have transmembrane domains, and many of the membrane proteins were found to be involved in transport and cell signaling. The MS/MS spectrum count information for the identified proteins was used to provide a measure of relative protein abundances. The mouse brain peptide/protein database generated from this study represents the most comprehensive proteome coverage for the mammalian brain to date, and the basis for future quantitative brain proteomic studies using mouse models. The proteomic approach presented here may have broad applications for rapid proteomic analyses of various mouse models of human brain diseases.     

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.     

Molecular imaging of amyloid beta peptides in mouse brain sections using mass spectrometry

In this paper, a reverse-phase high-performance liquid chromatographic method using a chemically modified electrode coupled with microdialysis was developed to study the effect of electromagnetic impulse (EMI) on monoamine neurotransmitter metabolism in nerve cells. To detect the monoamines and their metabolites, a poly (para-aminobenzoic acid) (P-pABA)-modified electrode was prepared. The modified electrode exhibited efficiently electrocatalytic oxidation for monoamines and their metabolites with relatively high sensitivity, stability, and long life. Nerve cells were primarily cultured. EMI was radiated to three experimental model nerve cells: (i) on mature nerve cells, (ii) on the culture medium, and (iii) on juvenile nerve cells for various periods of time. Then the levels of monoamines in the culture medium were detected by high-performance liquid chromatography-electrochemical detection. The data indicated that electromagnetic fields could influence neurotransmitter metabolism by direct effect on nerve cells or effect on the nutrient medium and that the effect was not only relevant with the length of radiation time, but also with the growing state of the nerve cells.     

Quantitative proteome analysis by solid-phase isotope tagging and mass spectrometry

The adaptation of sequences of chemical reactions to a solid-phase format has been essential to the automation, reproducibility, and efficiency of a number of biotechnological processes including peptide and oligonucleotide synthesis and sequencing. Here we describe a method for the site-specific, stable isotopic labeling of cysteinyl peptides in complex peptide mixtures through a solid-phase capture and release process, and the concomitant isolation of the labeled peptides. The recovered peptides were analyzed by microcapillary liquid chromatography and tandem mass spectrometry (microLC-MS/MS) to determine their sequences and relative quantities. The method was used to detect galactose-induced changes in protein abundance in the yeast Saccharomyces cerevisiae. A side-by-side comparison with the isotope-coded affinity tag (ICAT) method demonstrated that the solid-phase method for stable isotope tagging of peptides is comparatively simpler, more efficient, and more sensitive.     

Utility of mass spectrometry for proteome analysis: part II. Ion-activation methods,statistics, bioinformatics and annotation

This is the second article in a series, intended as a tutorial to provide the interested reader with an overview of the concepts not covered in part I, such as: the principles of ion-activation methods, the ability of mass-spectrometric methods to interface with various proteomic strategies, analysis techniques, bioinformatics and data interpretation and annotation. Although these are different topics, it is important that a reader has a basic and collective understanding of all of them for an overall appreciation of how to carry out and analyze a proteomic experiment. Different ion-activation methods for MS/MS, such as collision-induced dissociation (including postsource decay) and surface-induced dissociation, electron capture and electron-transfer dissociation, infrared multiphoton and blackbody infrared radiative dissociation have been discussed since they are used in proteomic research. The high dimensionality of data generated from proteomic studies requires an understanding of the underlying analytical procedures used to obtain these data, as well as the development of improved bioinformatics tools and data-mining approaches for efficient and accurate statistical analyses of biological samples from healthy and diseased individuals, in addition to determining the utility of the interpreted data. Currently available strategies for the analysis of the proteome by mass spectrometry, such as those employed for the analysis of substantially purified proteins and complex peptide mixtures, as well as hypothesis-driven strategies, have been elaborated upon. Processing steps prior to the analysis of mass spectrometry data, statistics and the several informatics steps currently used for the analysis of shotgun proteomic experiments, as well as proteomics ontology, are also discussed.     

Automation of nanoflow liquid chromatography-tandem mass spectrometry for proteome analysis by using a strong cation exchange trap column

An approach was developed to automate sample introduction for nanoflow LC-MS/MS (microLC-MS/MS) analysis using a strong cation exchange (SCX) trap column. The system consisted of a 100 microm id x 2 cm SCX trap column and a 75 microm id x 12 cm C18 RP analytical column. During the sample loading step, the flow passing through the SCX trap column was directed to waste for loading a large volume of sample at high flow rate. Then the peptides bound on the SCX trap column were eluted onto the RP analytical column by a high salt buffer followed by RP chromatographic separation of the peptides at nanoliter flow rate. It was observed that higher performance of separation could be achieved with the system using SCX trap column than with the system using C18 trap column. The high proteomic coverage using this approach was demonstrated in the analysis of tryptic digest of BSA and yeast cell lysate. In addition, this system was also applied to two-dimensional separation of tryptic digest of human hepatocellular carcinoma cell line SMMC-7721 for large scale proteome analysis. This system was fully automated and required minimum changes on current microLC-MS/MS system. This system represented a promising platform for routine proteome analysis.     

Global methods for protein glycosylation analysis by mass spectrometry

Mass spectrometry has been an analytical tool of choice for glycosylation analysis of individual proteins. Over the last 5 years several previously and newly developed mass spectrometry methods have been extended to global glycoprotein studies. In this review we discuss the importance of these global studies and the advances that have been made in enrichment analyses and fragmentation methods. We also briefly describe relevant sample preparation methods that have been used for the analysis of a single glycoprotein that could be extrapolated to global studies. Finally this review covers aspects of improvements and advances on the instrument front which are important to future global glycoproteomic studies.