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

Proteomic analysis of bovine nucleolus

Nucleolus is the most prominent subnuclear structure, which performs a wide variety of functions in the eukaryotic cellular processes. In order to understand the structural and functional role of the nucleoli in bovine cells, we analyzed the proteomic composition of the bovine nucleoli. The nucleoli were isolated from Madin Darby bovine kidney cells and subjected to proteomic analysis by LC-MS/MS after fractionation by SDS-PAGE and strong cation exchange chromatography. Analysis of the data using the Mascot database search and the GPM database search identified 311 proteins in the bovine nucleoli, which contained 22 proteins previously not identified in the proteomic analysis of human nucleoli. Analysis of the identified proteins using the GoMiner software suggested that the bovine nucleoli contained proteins involved in ribosomal biogenesis, cell cycle control, transcriptional, translational and post-translational regulation, transport, and structural organization.

Proteome analysis of mouse model systems: A tool to model human disease and for the investigation of tissue-specific biology

The molecular dissections of the mechanistic pathways involved in human disease have always relied on the use of model organisms. Among the higher mammalian organisms, the laboratory mouse (Mus musculus) is the most widely used model. A large number of commercially-available, inbred strains are available to the community, including an ever growing collection of transgenic, knock-out, and disease models. Coupled to availability is the fact that animal colonies can be kept under standardized housing condition at most major universities and research institutes, with relative ease and cost efficiency (compared to larger vertebrates). As such, mouse models to study human biology and disease remains extremely attractive. In the current review we will provide an historic overview of the use of mouse models in proteome research with a focus on general tissue and organelle biology, comparative proteomics of human and mouse and the use of mouse models to study cardiac disease.

A gel-free approach in vascular smooth muscle cell proteome: perspectives for a better insight into activation

Background

The use of chromatography coupled with mass spectrometry (MS) analysis is a powerful approach to identify proteins, owing to its capacity to fractionate molecules according to different chemical features. The first protein expression map of vascular smooth muscle cells (VSMC) was published in 2001 and since then other papers have been produced. The most detailed two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) map was presented by Mayr et al who identified 235 proteins, corresponding to the 154 most abundant unique proteins in mouse aortic VSMC. A chromatographic approach aimed at fractionating the VSMC proteome has never been used before.

Results

This paper describes a strategy for the study of the VSMC proteome. Our approach was based on pre-fractionation with ion exchange chromatography coupled with matrix assisted laser desorption-time of flight mass spectrometry analysis assisted by a liquid chromatography (LC-MALDI-TOF/TOF). Ion exchange chromatography resulted in a good strategy designed to simplify the complexity of the cellular extract and to identify a large number of proteins. Selectivity based on the ion-exchange chemical features was adequate if evaluated on the basis of protein pI. The LC-MALDI approach proved to be highly reproducible and sensitive since we were able to identify up to 815 proteins with a concentration dynamic range of 7 orders of magnitude.

Conclusions

In our opinion, the large number of identified proteins and the promising quantitative reproducibility made this approach a powerful method to analyze complex protein mixtures in a high throughput way and to obtain statistical data for the discovery of key factors involved in VSMC activation and to analyze a label-free differential protein expression.

An overview of label-free quantitation methods in proteomics by mass spectrometry

Protein quantification represents an important extension to identification proteomics, enabling the comparison of protein expression across different samples or treatments. Comparative protein quantification by mass spectrometry typically employs stable isotope incorporation, but recently, comparative quantification of label-free LC(n)-MS proteomics data has emerged as an alternative approach. In this chapter, we provide an overview of the different approaches for extracting quantitative data from label-free LC(n)-MS experiments. The computational procedure for recovering the quantitative information is outlined. Examples of statistical tests used to evaluate the relevance of results are also provided.

Proteomic study of human glioblastoma multiforme tissue employing complementary two-dimensional liquid chromatography- and mass spectrometry-based approaches

An extensive data set comprising 2660 unique protein identifications was obtained for the proteome of a human brain tumor (glioblastoma multiforme) by combining the results of two complementary analytical strategies based on two-dimensional chromatography and mass spectrometry. A bottom-up method, performing peptide separation in both chromatographic dimensions was employed as well as a semi-top-down method, in which intact proteins were separated in the first and tryptic peptides in the second dimension. The identified proteins were assigned to their molecular functions and compared to previously identified proteins of glioblastoma multiforme (= astrocytoma WHO grade IV), lower WHO grade astrocytomas (grade II and III), and nontumor brain tissue. With the use of a subset of 104 identified membrane proteins, the properties of intact protein fractionation in the first dimension of the semi-top-down approach were elucidated in detail. The benefit of the semi-top-down approach was further demonstrated by the identification of a set of endogenous glioblastoma multiforme expressed proteins. These proteins correspond to recombinant antigens which were recently found to be reactive against autoantibodies in glioblastoma multiforme patients. The results indicate the usefulness of the semi-top-down approach for the investigation of immunogenic antigens in human tumor tissue samples.

DtaRefinery, a software tool for elimination of systematic errors from parent ion mass measurements in tandem mass spectra data sets

Hybrid two-stage mass spectrometers capable of both highly accurate mass measurement and high throughput MS/MS fragmentation have become widely available in recent years, allowing for significantly better discrimination between true and false MS/MS peptide identifications by the application of a relatively narrow window for maximum allowable deviations of measured parent ion masses. To fully gain the advantage of highly accurate parent ion mass measurements, it is important to limit systematic mass measurement errors. Based on our previous studies of systematic biases in mass measurement errors, here, we have designed an algorithm and software tool that eliminates the systematic errors from the peptide ion masses in MS/MS data. We demonstrate that the elimination of the systematic mass measurement errors allows for the use of tighter criteria on the deviation of measured mass from theoretical monoisotopic peptide mass, resulting in a reduction of both false discovery and false negative rates of peptide identification. A software implementation of this algorithm called DtaRefinery reads a set of fragmentation spectra, searches for MS/MS peptide identifications using a FASTA file containing expected protein sequences, fits a regression model that can estimate systematic errors, and then corrects the parent ion mass entries by removing the estimated systematic error components. The output is a new file with fragmentation spectra with updated parent ion masses. The software is freely available.

Highly efficient and selective enrichment of peptide subsets combining fluorous chemistry with reversed-phase chromatography

The selective capture of target peptides poses a great challenge to modern chemists and biologists, especially when enriching them from proteome samples possessing extremes in concentration dynamic range and sequence diversity. While approaches based on traditional techniques such as biotin-avidin pairing offer versatile tools to design strategies for selective enrichment, problems are still encountered due to sample loss or poor selectivity of enrichment. Here we show that the recently introduced fluorous chemistry approach has attractive properties as an alternative method for selective enrichment. Through appending a perfluorine group to the target peptide, it is possible to dramatically increase the peptide's hydrophobicity and thus enable facile separation of labeled from non-labeled peptides. Use of reversed-phase chromatography allowed for improved peptide recovery in comparison with results obtained using the formerly reported fluorous bonded phase methods. Furthermore, this approach also allowed for on-line separation and identification of both labeled and unlabeled peptides in a single experiment. The net result is an increase in the confidence of protein identification by tandem mass spectrometry (MS2) as all peptides and subsequent information are retained. Successful off-line and on-line enrichment of cysteine-containing peptides was obtained, and high quality MS2 spectra were obtained by tandem mass spectrometry due to the stability of the tag, allowing for facile identification via standard database searching. We believe that this strategy holds great promise for selective enrichment and identification of low abundance target proteins or peptides.

Identification and expression profiling of blood-brain barrier membrane proteins

Blood-brain barrier (BBB) membrane proteins play crucial roles in the proper functioning of the BBB as well as in disease progression. Previously, we developed a novel approach for identifying membrane proteins expressed at the BBB, which we referred to as multiplex expression cloning. In this study, the proteome coverage of the multiplex expression cloning approach was expanded to allow the identification of a total of 30 BBB membrane proteins that are diverse in function and abundance. To unveil those membrane proteins that are enriched at the BBB and hence partially responsible for some of its unique characteristics, the transcript abundance levels for all 30 BBB membrane proteins were compared with those found in microvessels derived from lung, liver, heart, and kidney. Such quantitative PCR profiling of RNA samples from laser capture microdissected microvessels revealed that the transcripts for five membrane proteins, namely Lutheran glycoprotein, carbonic anhydrase IV, uncoupling protein 2, podocalyxin, and solute carrier family 38, member 5, were BBB selective, in that expression was elevated in brain microvessels when compared with all of the vascular beds tested. Many other membrane protein transcripts, whereas not as BBB-restricted, showed selective expression within subsets of tissues indicating other potential parallels and contrasts between vascular beds in the body. The identification of BBB membrane proteins could help better understand the molecular mechanisms responsible for BBB function and those with selective expression may have utility for BBB-targeted therapies.

Multiplex expression cloning of blood-brain barrier membrane proteins

The blood-brain barrier (BBB) is a vascular endothelial interface that separates the brain interior from the bloodstream. Membrane proteins resident at the BBB play important functional and regulatory roles. The current study describes the development and successful implementation of a multiplex expression cloning (MEC) method to allow facile identification of BBB membrane proteins. The overriding goal of the MEC approach was to mine a BBB cDNA library and selectively isolate membrane protein-encoding cDNAs. This selection process was achieved via fluorescence-activated cell sorting (FACS) of cDNA-expressing mammalian host cells for those cells that were immunolabeled with a BBB membrane protein-specific polyclonal antiserum (BMSPA). After optimization of the host cell expression system, four selection rounds allowed the isolation of a panel of 15 unique cDNAs that encoded BBB membrane proteins. The identified proteins display significant diversity in structure, function and in vivo expression levels. The MEC approach thus proved effective for conducting moderate throughput membrane proteome analyses of the BBB while limiting any biases caused by membrane protein insolubility or low in vivo expression levels that can complicate other proteomic approaches.

Proteomic-based identification of maternal proteins in mature mouse oocytes

BACKGROUND

The mature mouse oocyte contains the full complement of maternal proteins required for fertilization, reprogramming, zygotic gene activation (ZGA), and the early stages of embryogenesis. However, due to limitations of traditional proteomics strategies, only a few abundantly expressed proteins have yet been identified. Our laboratory applied a more effective strategy: one-dimensional sodium dodecyl sulfate polyacrylamide gel electrophoresis (1D SDS-PAGE) and reverse-phase liquid chromatography tandem mass spectrometry (RP-LC-MS/MS) were employed to analyze the mature oocyte proteome in depth.

RESULTS

Using this high-performance proteomic approach, we successfully identified 625 different proteins from 2700 mature mouse oocytes lacking zona pellucidae. This is the largest catalog of mature mouse oocyte proteins compiled to date. According to their pattern of expression, we screened 76 maternal proteins with high levels of mRNA expression both in oocytes and fertilized eggs. Many well-known maternal effect proteins were included in this subset, including MATER and NPM2. In addition, our mouse oocyte proteome was compared with a recently published mouse embryonic stem cell (ESC) proteome and 371 overlapping proteins were identified.

CONCLUSION

This proteomics analysis will be a valuable resource to aid in the characterization of important maternal proteins involved in oogenesis, fertilization, early embryonic development and in revealing their mechanisms of action.

Evaluation of a high-intensity focused ultrasound-immobilized trypsin digestion and 18O-labeling method for quantitative proteomics

A new method that uses immobilized trypsin concomitant with ultrasonic irradiation results in ultrarapid digestion and more thorough (18)O labeling for quantitative protein comparisons. The method was reproducible and provided effective digestions within <1 min with lower amounts of enzyme, compared to traditional methods. This method was demonstrated for digestion of both simple and complex protein mixtures, including bovine serum albumin, a global proteome extract from the bacteria Shewanella oneidensis, and mouse plasma, as well as (18)O labeling of complex protein mixtures, validating this method for differential proteomic measurements. This approach is simple, reproducible, cost-effective, rapid, and well suited for automation.

Repeatability of peptide identifications in shotgun proteome analysis employing off-line two-dimensional chromatographic separations and ion-trap MS

The repeatability of peptide identifications in shotgun proteome analyses employing strong cation-exchange-xion-pair RP HPLC hyphenated to ESI MS/MS was compared to an alternative scheme, comprising high-pH RP chromatography combined with low-pH ion-pair RP chromatography. Equivalent results were obtained with both methods in proteome analysis of Corynebacterium glutamicum. From a total number of 1350 to 1850 peptides identified in triplicate analyses of five consecutive fractions chosen from the first-dimension separation, 41-45% of the peptides were identified three times, whereas 16-22 and 37-39% of the peptides were identified only twice or once, respectively. A comparison of the repeatability of peptide identifications from complex samples upon 1- or 2-D chromatographic separation revealed that an additional separation dimension decreases the repeatability by approximately 25%.

Comparative proteomic profiling of membrane proteins in rat cerebellum, spinal cord, and sciatic nerve

Proteomics is an increasingly powerful technology that can provide in-depth insights into entire proteomes and their variation upon disease. Large-scale proteomics today enables identification and measurement of changes of thousands of proteins from minute amount of tissues. Here, we provide a proteomic profile of three distinct parts of the murine nerve system: cerebellum, spinal cord, and sciatic nerve. We focus on membrane proteins as the key regulators of neural transmission and memory. Rat tissues were homogenized and extracted to remove nonmembrane proteins and the resulting membranes were solubilized with detergents. Proteins were fractionated by size exclusion chromatography, depleted for detergents, digested and analyzed by LC-MS/MS using the LTQ-Orbitrap instrument. With the application of stringent identification criteria, in total, 4124 proteins were identified. Of these proteins, 3528, 3290, and 1649 were mapped to cerebellum, spinal cord, and sciatic nerve, respectively, allowing in-depth mapping of neurotransmitter receptors, ion channels, and transporter proteins. This work is the most in-depth proteomic analysis of nerve tissues to date and provides the first unbiased insights into the proteomes of anatomically and functionally distinct parts of the membrane proteome of the central and peripheral nerve systems. The methods applied here can be directly applied to studying nerve systems and their disorders.

Evaluation of strong cation exchange versus isoelectric focusing of peptides for multidimensional liquid chromatography-tandem mass spectrometry

Shotgun proteome analysis platforms based on multidimensional liquid chromatography-tandem mass spectrometry (LC-MS/MS) provide a powerful means to discover biomarker candidates in tissue specimens. Analysis platforms must balance sensitivity for peptide detection, reproducibility of detected peptide inventories and analytical throughput for protein amounts commonly present in tissue biospecimens (< 100 microg), such that platform stability is sufficient to detect modest changes in complex proteomes. We compared shotgun proteomics platforms by analyzing tryptic digests of whole cell and tissue proteomes using strong cation exchange (SCX) and isoelectric focusing (IEF) separations of peptides prior to LC-MS/MS analysis on a LTQ-Orbitrap hybrid instrument. IEF separations provided superior reproducibility and resolution for peptide fractionation from samples corresponding to both large (100 microg) and small (10 microg) protein inputs. SCX generated more peptide and protein identifications than did IEF with small (10 microg) samples, whereas the two platforms yielded similar numbers of identifications with large (100 microg) samples. In nine replicate analyses of tryptic peptides from 50 microg colon adenocarcinoma protein, overlap in protein detection by the two platforms was 77% of all proteins detected by both methods combined. IEF more quickly approached maximal detection, with 90% of IEF-detectable medium abundance proteins (those detected with a total of 3-4 peptides) detected within three replicate analyses. In contrast, the SCX platform required six replicates to detect 90% of SCX-detectable medium abundance proteins. High reproducibility and efficient resolution of IEF peptide separations make the IEF platform superior to the SCX platform for biomarker discovery via shotgun proteomic analyses of tissue specimens.

From complementarity to comprehensiveness--targeting the membrane proteome of growing Bacillus subtilis by divergent approaches

The analysis of integral membrane proteins (IMPs) with mass spectrometry-centered technologies has undergone great progress during the past few years, allowing for the analysis of several hundreds of IMPs. In this study, we investigated three promising shotgun approaches for the identification of IMPs of the model organism Bacillus subtilis. One comprises a classical membrane preparation procedure with carbonate and high-ionic-strength buffers, followed by SDS-PAGE and LC-MS/MS analysis. The two others are based on enzymatic trimming of the crude membrane fraction either with trypsin or proteinase K and subsequent gel-free analysis. As a result, we observed the highest degree of complementarity between the gel-based and the proteinase K approach, since the first exclusively addresses soluble loops and domains of IMPs and gave rise to 8709 unique peptides, whereas the latter contributed 1180 unique peptide identifications from otherwise inaccessible transmembrane helices (TMHs). All three methods contribute significant numbers (381, 284, and 276, respectively) to the total of 527 IMP identifications from the membrane fraction of exponentially growing B. subtilis cells, thus representing approximately 69% of all transcribed IMPs.

Identification of N-linked glycoproteins in human milk by hydrophilic interaction liquid chromatography and mass spectrometry

Breastfeeding is now generally recognized as a critical factor in protecting newborns against infections. An important mechanism responsible for the antibacterial and antiviral effects of breast milk is the prevention of pathogen adhesion to host cell membranes mediated by a number of glycoconjugates, also including glycoproteins. A number of approaches to describe the complexity of human milk proteome have provided only a partial characterization of restricted classes of N-linked glycoproteins. To achieve this objective, profiling N-linked glycoproteins of human milk was performed by Hydrophilic Interaction LC (HILIC) and MS analysis. Glycopeptides were selectively enriched from the protein tryptic digest of human milk samples. Oligosaccharide-free peptides obtained by peptide N-glycosidase F (PNGase F) treatment were characterized by a shotgun MS-based approach, allowing the identification of N-glycosylated sites localized on proteins. Using this strategy, 32 different glycoproteins were identified and 63 N-glycosylated sites encrypted in them were located. The glycoproteins include immunocompetent factors, membrane fat globule-associated proteins, enzymes involved in lipid degradation and cell differentiation, specific receptors, and other gene products with still unknown functions.

Comparisons of mass spectrometry compatible surfactants for global analysis of the mammalian brain proteome

Methods for the global analysis of protein expression offer an approach to study the molecular basis of disease. Studies of protein expression in tissue, such as brain, are complicated by the need for efficient and unbiased digestion of proteins that permit identification of peptides by shotgun proteomic methods. In particular, identification and characterization of less abundant membrane proteins has been of great interest for studies of brain physiology, but often proteins of interest are of low abundance or exist in multiple isoforms. Parsing protein isoforms as a function of disease will be essential. In this study, we develop a digestion scheme using detergents compatible with mass spectrometry that improves membrane protein identification from brain tissue. We show the modified procedure yields close to 5,000 protein identifications from 1.8 mg of rat brain homogenate with an average of 25% protein sequence coverage. This procedure achieves a remarkable reduction in the amount of starting material required to observe a broad spectrum of membrane proteins. Among the proteins identified from a mammalian brain homogenate, 1897 (35%) proteins are annotated by Gene Ontology as membrane proteins, and 1225 (22.6%) proteins are predicted to contain at least one transmembrane domain. Membrane proteins identified included neurotransmitter receptors and ion channels implicated in important physiological functions and disease.

Application of pressurized solvents for ultrafast trypsin hydrolysis in proteomics: proteomics on the fly

A new method for rapid proteolytic digestion of proteins under high pressure that uses pressure cycling technology in the range of 5-35 kpsi was demonstrated for proteomic analysis. Successful in-solution digestions of single proteins and complex protein mixtures were achieved in 60 s and then analyzed by reversed phase liquid chromatography-electrospray ionization ion trap-mass spectrometry. Method performance in terms of the number of Shewanella oneidensis peptides and proteins identified in a shotgun approach was evaluated relative to a traditional "overnight" sample preparation method. Advantages of the new method include greatly simplified sample processing, easy implementation, no cross contamination among samples, and cost effectiveness.

Characterization of the mouse pancreatic islet proteome and comparative analysis with other mouse tissues

The pancreatic islets of Langerhans, and especially the insulin-producing beta cells, play a central role in the maintenance of glucose homeostasis. Alterations in the expression of multiple proteins in the islets that contribute to the maintenance of islet function are likely to underlie the pathogenesis of types 1 and 2 diabetes. To identify proteins that constitute the islet proteome, we provide the first comprehensive proteomic characterization of pancreatic islets for mouse, the most commonly used animal model in diabetes research. Using strong cation exchange fractionation coupled with reversed phase LC-MS/MS we report the confident identification of 17,350 different tryptic peptides covering 2612 proteins having at least two unique peptides per protein. The data set also identified approximately 60 post-translationally modified peptides including oxidative modifications and phosphorylation. While many of the identified phosphorylation sites corroborate those previously known, the oxidative modifications observed on cysteinyl residues reveal potentially novel information suggesting a role for oxidative stress in islet function. Comparative analysis with 15 available proteomic data sets from other mouse tissues and cells revealed a set of 133 proteins predominantly expressed in pancreatic islets. This unique set of proteins, in addition to those with known functions such as peptide hormones secreted from the islets, contains several proteins with as yet unknown functions. The mouse islet protein and peptide database accessible at (http://ncrr.pnl.gov), provides an important reference resource for the research community to facilitate research in the diabetes and metabolism fields.

Mitochondrial dysfunction, oxidative stress, and apoptosis revealed by proteomic and transcriptomic analyses of the striata in two mouse models of Parkinson's disease

The molecular mechanisms underlying the changes in the nigrostriatal pathway in Parkinson's disease (PD) are not completely understood. Here, we use mass spectrometry and microarrays to study the proteomic and transcriptomic changes in the striatum of two mouse models of PD, induced by the distinct neurotoxins 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and methamphetamine (METH). Proteomic analyses resulted in the identification and relative quantification of 912 proteins with two or more unique peptides and 86 proteins with significant abundance changes following neurotoxin treatment. Similarly, microarray analyses revealed 181 genes with significant changes in mRNA, following neurotoxin treatment. The combined protein and gene list provides a clearer picture of the potential mechanisms underlying neurodegeneration observed in PD. Functional analysis of this combined list revealed a number of significant categories, including mitochondrial dysfunction, oxidative stress response, and apoptosis. These results constitute one of the largest descriptive data sets integrating protein and transcript changes for these neurotoxin models with many similar end point phenotypes but distinct mechanisms.

Proteomic analysis of mouse brain microsomes: identification and bioinformatic characterization of endoplasmic reticulum proteins in the mammalian central nervous system

The endoplasmic reticulum (ER) is the main source for the storage and release of intracellular calcium in neurons and, thus, contributes to the functionality of a diverse set of pathways that control critical aspects of central nervous system function including but not limited to gene expression, neurotransmission, learning, and memory. ER-derived proteins obtained after subcellular fractionation of mouse brain homogenate were digested with trypsin and the corresponding peptides fractionated by strong cation exchange chromatography followed by LC-MS/MS analysis on a hybrid linear ion trap--Fourier transform ion cyclotron resonance (FTICR) mass spectrometer. A comprehensive catalogue representing 1914 proteins was generated from this particular proteomic analysis using identification criteria that corresponded to a false positive identification rate of 0.4%. Various molecular functions and biological processes relevant to the ER were identified upon gene ontology (GO)-based analysis including pathways associated with molecular transport, protein trafficking and localization, and cell signaling. Comparison of the 2D-LC-MS/MS results with those obtained from shotgun LC-MS/MS analyses demonstrated that most molecular functions and biological processes were represented via GO analysis using either methodology. Results from this comparison as well as a focused investigation into components of calcium-mediated signaling in the mouse brain ER are also presented.

Elimination of systematic mass measurement errors in liquid chromatography-mass spectrometry based proteomics using regression models and a priori partial knowledge of the sample content

The high mass measurement accuracy and precision available with recently developed mass spectrometers is increasingly used in proteomics analyses to confidently identify tryptic peptides from complex mixtures of proteins, as well as post-translational modifications and peptides from nonannotated proteins. To take full advantage of high mass measurement accuracy instruments, it is necessary to limit systematic mass measurement errors. It is well known that errors in m/z measurements can be affected by experimental parameters that include, for example, outdated calibration coefficients, ion intensity, and temperature changes during the measurement. Traditionally, these variations have been corrected through the use of internal calibrants (well-characterized standards introduced with the sample being analyzed). In this paper, we describe an alternative approach where the calibration is provided through the use of a priori knowledge of the sample being analyzed. Such an approach has previously been demonstrated based on the dependence of systematic error on m/z alone. To incorporate additional explanatory variables, we employed multidimensional, nonparametric regression models, which were evaluated using several commercially available instruments. The applied approach is shown to remove any noticeable biases from the overall mass measurement errors and decreases the overall standard deviation of the mass measurement error distribution by 1.2-2-fold, depending on instrument type. Subsequent reduction of the random errors based on multiple measurements over consecutive spectra further improves accuracy and results in an overall decrease of the standard deviation by 1.8-3.7-fold. This new procedure will decrease the false discovery rates for peptide identifications using high-accuracy mass measurements.

High-throughput analysis of rat liver plasma membrane proteome by a nonelectrophoretic in-gel tryptic digestion coupled with mass spectrometry identification

In-gel digestion is commonly used after proteins are resolved by polyacrylamide gel electrophoresis (SDS-PAGE, 2-DE). It can also be used on its own in conjunction with tandem mass spectrometry (MS/MS) for the direct analysis of complex proteins. Here, we describe a strategy combining isolation of purified plasma membrane, efficient digestion of plasma membrane proteins in polyacrylamide gel, and high-sensitivity analysis by advanced mass spectrometry to create a new rapid and high-throughput method. The plasma membrane protein mixture is directly incorporated into a polyacrylamide gel matrix, After formation of the gel, proteins in the gel section are digested with trypsin, and the resulting peptides are subjected to reversed-phase, high-performance liquid chromatography followed by electrospray ion-trap tandem mass analysis. Using this optimized strategy, we have identified 883 rat liver membrane proteins, of which 490 had a gene ontology (GO) annotation indicating a cellular component, and 294 (60%) of the latter were known integral membrane proteins or membrane proteins. In total, 333 proteins are predicted by the TMHMM 2.0 algorithm to have transmembrane domains (TMDs) and 52% (175 of 333) proteins to contain 2-16 TMDs. The identified membrane proteins provide a broad representation of the rat plasma membrane proteome with little bias evident due to protein p I and molecular weight (MW). Also, membrane proteins with a high GRAVY score (grand average hydrophobicity score) were identified, and basic and acidic membrane proteins were evenly represented. This study not only offered an efficient and powerful method in shotgun proteomics for the identification of proteins of complex plasma membrane samples but also allowed in-depth study of liver membrane proteomes, such as of rat models of liver-related disease. This work represents one of the most comprehensive proteomic analyses of the membrane subproteome of rat liver plasma membrane in general.

Application of proteomics in the discovery of candidate protein biomarkers in a diabetes autoantibody standardization program sample subset

Novel biomarkers of type 1 diabetes must be identified and validated in initial, exploratory studies before they can be assessed in proficiency evaluations. Currently, untargeted "-omics" approaches are underutilized in profiling studies of clinical samples. This report describes the evaluation of capillary liquid chromatography (LC) coupled with mass spectrometry (MS) in a pilot proteomic analysis of human plasma and serum from a subset of control and type 1 diabetic individuals enrolled in the Diabetes Autoantibody Standardization Program, with the goal of identifying candidate biomarkers of type 1 diabetes. Initial high-resolution capillary LC-MS/MS experiments were performed to augment an existing plasma peptide database, while subsequent LC-FTICR studies identified quantitative differences in the abundance of plasma proteins. Analysis of LC-FTICR proteomic data identified five candidate protein biomarkers of type 1 diabetes. alpha-2-Glycoprotein 1 (zinc), corticosteroid-binding globulin, and lumican were 2-fold up-regulated in type 1 diabetic samples relative to control samples, whereas clusterin and serotransferrin were 2-fold up-regulated in control samples relative to type 1 diabetic samples. Observed perturbations in the levels of all five proteins are consistent with the metabolic aberrations found in type 1 diabetes. While the discovery of these candidate protein biomarkers of type 1 diabetes is encouraging, follow up studies are required for validation in a larger population of individuals and for determination of laboratory-defined sensitivity and specificity values using blinded samples.

A la carte proteomics with an emphasis on gel-free techniques

Since the introduction of the proteome term somewhat more than a decade ago the field of proteomics witnessed a rapid growth mainly fueled by instrumental analytical improvements. Of particular notice is the advent of a diverse set of gel-free proteomics techniques. In this review, we discuss several of these gel-free techniques both for monitoring protein concentration changes and protein modifications, in particular protein phosphorylation, glycosylation, and protein processing. Furthermore, different approaches for (multiplexed) gel-free proteome analysis are discussed.

Protein expression in the striatum and cortex regions of the brain for a mouse model of Huntington's disease

Liquid chromatography (LC) coupled with mass spectrometry (MS) and database assignment methods have been used to conduct a large-scale proteome survey of the R6/2 mouse model of Huntington's disease (HD). Although the neuropathological mechanisms of HD are not known, the mutant huntingtin gene that causes the disease is thought to alter gene transcription, leading to a cascade of neurotoxic events. In this report, we have focused on characterizing changes in the brain proteome associated with HD pathophysiology. Differences in the relative abundances of proteins (R6/2 compared to wild type) in brain tissue from the striatum and cortex, two primary loci of dysfunction in HD, were assessed by using a label-free approach based on calibrations to internal standards. In total, assignments were made for approximately 400 proteins. A set of criteria was used to establish 160 high confidence assignments, approximately 30% of which appear to show differences in expression relative to wild type (WT) animals. Many of the proteins that were differentially expressed are known to be associated with neurotransmission and likely play key roles in HD etiology. This study is the first to report that the majority of differentially expressed proteins in the striatum are up-regulated, while the majority of the expressed proteins in the cortex are down-regulated. The differentially expressed proteins identified in this proteomic screen may be potential biomarkers and drug targets for HD and may further our understanding of the disease pathology.

Nonergodicity in electron capture dissociation investigated using hydrated ion nanocalorimetry

Hydrated divalent magnesium and calcium clusters are used as nanocalorimeters to measure the internal energy deposited into size-selected clusters upon capture of a thermally generated electron. The infrared radiation emitted from the cell and vacuum chamber surfaces as well as from the heated cathode results in some activation of these clusters, but this activation is minimal. No measurable excitation due to inelastic collisions occurs with the low-energy electrons used under these conditions. Two different dissociation pathways are observed for the divalent clusters that capture an electron: loss of water molecules (Pathway I) and loss of an H atom and water molecules (Pathway II). For Ca(H(2)O)(n)(2+), Pathway I occurs exclusively for n >or= 30 whereas Pathway II occurs exclusively for n <or= 22 with a sharp transition in the branching ratio for these two processes that occurs for n approximately 24. The number of water molecules lost by both pathways increases with increasing cluster size reaching a broad maximum between n = 23 and 32, and then decreases for larger clusters. From the number of water molecules that are lost from the reduced cluster, the average and maximum possible internal energy is determined to be approximately 4.4 and 5.2 eV, respectively, for Ca(H(2)O)(30)(2+). This value is approximately the same as the calculated ionization energies of M(H(2)O)(n)(+), M = Mg and Ca, for large n indicating that the vast majority of the recombination energy is partitioned into internal modes of the ion and that the dissociation of these ions is statistical. For smaller clusters, estimates of the dissociation energies for the loss of H and of water molecules are obtained from theory. For Mg(H(2)O)(n)(2+), n = 4-6, the average internal energy deposition is estimated to be 4.2-4.6 eV. The maximum possible energy deposited into the n = 5 cluster is <7.1 eV, which is significantly less than the calculated recombination energy for this cluster. There does not appear to be a significant trend in the internal energy deposition with cluster size whereas the recombination energy is calculated to increase significantly for clusters with fewer than 10 water molecules. These, and other results, indicate that the dissociation of these smaller clusters is nonergodic.

Assessing a novel microfluidic interface for shotgun proteome analyses

Microfluidic interfaces coupled to ESI mass spectrometers hold great potential for proteomics as they have been shown to augment the overall sensitivity of measurements and require only a minimum of operator manipulations as compared to conventional nano-LC interfaces. Here, we evaluated a new type of HPLC-Chips holding larger enrichment columns (thus an increased sample loading capacity) for gel-free proteome studies. A tryptic digest of a human T-cell proteome was fractionated by strong cation exchange chromatography and selected fractions were analyzed by MS/MS on an IT mass spectrometer using both the new HPLC-Chip as well as a conventional nano-LC-MS/MS interface. Our results indicate that the HPLC-Chip is capable of handling very complex peptide mixtures and, in fact, leads to the identification of more peptides and proteins as compared to when a conventional interface was used. The HPLC-Chip preferentially produced doubly charged tryptic peptides. We further show that MS/MS spectra of doubly charged tryptic peptide ions are more readily identified by MASCOT as compared to those from triply charged precursors and thus argue that besides the improved chromatographic conditions provided by the HPLC-Chip, its peptide charging profile might be a secondary factor leading to an increased proteome coverage.

Analysis of human liver proteome using replicate shotgun strategy

In this study, a liquid-based shotgun strategy was used to comprehensively identify the expression of human liver proteome. Proteins were extracted from human liver tissue and digested in-solution. The tryptic digest mixture was desalted and separated by off-line strong cation exchange (SCX) chromatography with a 60-min elution. The MS/MS spectra were acquired in data-dependent mode after an RP chromatographic separation combined with linear IT MS analysis. To obtain the most comprehensive human liver proteome, each SCX fraction was run six times in RPLC MS/MS manner. Finally, more than 6,000,000 MS/MS spectra were collected. Using a relatively strict filter criteria, 24,311 proteins (48.42% of the predicted human proteome from human International Protein Index (IPI) protein database 3.07) corresponding to 13,150 nonredundant proteins were successfully identified, in which 7001 proteins (53.24%) were identified by two or more peptides, which could be considered as a high-confident dataset. Among the 6149 proteins (46.76%) identified by single peptide, 3812 proteins (61.99%) were detected more than twice in six repeated runs. Comparative analysis between different runs shows that the overlap of identified proteins between any two runs ranged from 25 to 44%. Of the nonredundant proteins identified, 8919 proteins (67.83%) were detected more than twice and 4231 proteins (32.17%) were detected only once in six RPLC MS/MS runs. The Gene Ontology annotation shows that the identified proteins come from various subcellular components. In addition, a large number of low abundant proteins were identified. The dynamic range of the approach reached at least nine orders of magnitude by estimating the concentration of proteins.

A Method for Selective Enrichment and Analysis of Nitrotyrosine-Containing Peptides in Complex Proteome Samples

Elevated levels of protein tyrosine nitration have been found in various neurodegenerative diseases and age-related pathologies. Until recently, however, the lack of an efficient enrichment method has prevented the analysis of this important low-level protein modification. We have developed a method that specifically enriches nitrotyrosine-containing peptides so that both nitrotyrosine peptides and specific nitration sites can be unambiguously identified with LC-MS/MS. The procedure consists of the derivatization of nitrotyrosine into free sulfhydryl groups followed by high efficiency enrichment of sulfhydryl-containing peptides with thiopropyl sepharose beads. The derivatization process includes: (1) acetylation with acetic anhydride to block all primary amines, (2) reduction of nitrotyrosine to aminotyrosine, (3) derivatization of aminotyrosine with N-Succinimidyl S-Acetylthioacetate (SATA), and (4) deprotection of S-acetyl on SATA to form free sulfhydryl groups. The high specificity of this method is demonstrated by the contrasting percentage of nitrotyrosine-derivatized peptides in the identified tandem mass spectra between enriched and unenriched samples. Global analysis of unenriched in vitro nitrated human histone H1.2, bovine serum albumin (BSA), and mouse brain homogenate samples had 9%, 9%, and 5.9% of identified nitrotyrosine-containing peptides, while the enriched samples had 91% , 62%, and 35%, respectively. Duplicate LC-MS/MS analyses of the enriched mouse brain homogenate identified 150 unique nitrated peptides covering 102 proteins with an estimated 3.3% false discovery rate.

Recent advances in neuroproteomics

The last few years have seen a rapid growth in the use of proteomic methods to study normal brain function. In addition, such methods have been used to analyze changes in protein expression associated with the onset and progression of neuronal disease. The field of neuroproteomics faces special challenges given the complex cellular and sub-cellular architecture of the central nervous system. This article presents a review of recent progress in studies of neuroproteomics, and highlights the strengths and limitations of current proteomic profiling technologies used in studies of neuronal protein expression.

A genome-scale map of expression for a mouse brain section obtained using voxelation

Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological diseases. We have reconstructed two-dimensional images of gene expression for 20,000 genes in a coronal slice of the mouse brain at the level of the striatum by using microarrays in combination with voxelation at a resolution of 1 mm3. Good reliability of the microarray results were confirmed using multiple replicates, subsequent quantitative RT-PCR voxelation, mass spectrometry voxelation, and publicly available in situ hybridization data. Known and novel genes were identified with expression patterns localized to defined substructures within the brain. In addition, genes with unexpected patterns were identified, and cluster analysis identified a set of genes with a gradient of dorsal/ventral expression not restricted to known anatomical boundaries. The genome-scale maps of gene expression obtained using voxelation will be a valuable tool for the neuroscience community.

Quantitative analysis of human immunodeficiency virus type 1-infected CD4+ cell proteome: dysregulated cell cycle progression and nuclear transport coincide with robust virus production

Relatively little is known at the functional genomic level about the global host response to human immunodeficiency virus type 1 (HIV-1) infection. Microarray analyses by several laboratories, including our own, have revealed that HIV-1 infection causes significant changes in host mRNA abundance and regulation of several cellular biological pathways. However, it remains unclear what consequences these changes bring about at the protein level. Here we report the expression levels of approximately 3,200 proteins in the CD4(+) CEMx174 cell line after infection with the LAI strain of human immunodeficiency virus type 1 (HIV-1); the proteins were assessed using liquid chromatography-mass spectrometry coupled with stable isotope labeling and the accurate mass and time tag approach. Furthermore, we found that 687 (21%) proteins changed in abundance at the peak of virus production at 36 h postinfection. Pathway analysis revealed that the differential expression of proteins was concentrated in select biological pathways, exemplified by ubiquitin-conjugating enzymes in ubiquitination, carrier proteins in nucleocytoplasmic transport, cyclin-dependent kinase in cell cycle progression, and pyruvate dehydrogenase of the citrate cycle pathways. Moreover, we observed changes in the abundance of proteins with known interactions with HIV-1 viral proteins. Our proteomic analysis captured changes in the host protein milieu at the time of robust virus production, depicting changes in cellular processes that may contribute to virus replication. Continuing analyses are expected to focus on blocking virus replication by targeting these pathways and their effector proteins.

The synaptic vesicle proteome

Synaptic vesicles are key organelles in neurotransmission. Vesicle integral or membrane-associated proteins mediate the various functions the organelle fulfills during its life cycle. These include organelle transport, interaction with the nerve terminal cytoskeleton, uptake and storage of low molecular weight constituents, and the regulated interaction with the pre-synaptic plasma membrane during exo- and endocytosis. Within the past two decades, converging work from several laboratories resulted in the molecular and functional characterization of the proteinaceous inventory of the synaptic vesicle compartment. However, up until recently and due to technical difficulties, it was impossible to screen the entire organelle thoroughly. Recent advances in membrane protein identification and mass spectrometry (MS) have dramatically promoted this field. A comparison of different techniques for elucidating the proteinaceous composition of synaptic vesicles revealed numerous overlaps but also remarkable differences in the protein constituents of the synaptic vesicle compartment, indicating that several protein separation techniques in combination with differing MS approaches are required to identify and characterize the synaptic vesicle proteome. This review highlights the power of various gel separation techniques and MS analyses for the characterization of the proteome of highly purified synaptic vesicles. Furthermore, the newly detected protein assignments to synaptic vesicles, especially those proteins which are new to the inventory of the synaptic vesicle proteome, are critically discussed.

Characterization of the human pancreatic islet proteome by two-dimensional LC/MS/MS

The pancreatic beta-cell plays a central role in the maintenance of glucose homeostasis and in the pathogenesis of both type 1 and type 2 diabetes mellitus. Elucidation of the insulin secretory defects observed in diabetes first requires a better understanding of the complex mechanisms regulating insulin secretion, which are only partly understood. While there have been reports detailing proteomic analyses of islet cell lines or isolated rodent islets, the information gained is not always applicable to humans. Therefore, definition of the human islet proteome could contribute to a better understanding of islet biology and lead to more effective treatment strategies. We have applied a two-dimensional LC-MS/MS-based analysis to the characterization of the human islet proteome, resulting in the confident identification of 29,021 different tryptic peptides covering 3365 proteins (> or =2 unique peptide identifications per protein). As expected, the three major islet hormones (insulin, glucagon, and somatostatin) were detected, as well as various beta-cell enriched secretory products, ion channels, and transcription factors. In addition, significant proteome coverage of metabolic enzymes and cellular pathways was observed, including the integrin signaling cascade and the MAP kinase, NF-kappa beta, and JAK/STAT pathways. The resulting peptide reference library provides a resource for future higher throughput and quantitative studies of islet biology.

Spatial mapping of protein abundances in the mouse brain by voxelation integrated with high-throughput liquid chromatography-mass spectrometry

Temporally and spatially resolved mapping of protein abundance patterns within the mammalian brain is of significant interest for understanding brain function and molecular etiologies of neurodegenerative diseases; however, such imaging efforts have been greatly challenged by complexity of the proteome, throughput and sensitivity of applied analytical methodologies, and accurate quantitation of protein abundances across the brain. Here, we describe a methodology for comprehensive spatial proteome mapping that addresses these challenges by employing voxelation integrated with automated microscale sample processing, high-throughput liquid chromatography (LC) system coupled with high-resolution Fourier transform ion cyclotron resonance (FTICR) mass spectrometer, and a "universal" stable isotope labeled reference sample approach for robust quantitation. We applied this methodology as a proof-of-concept trial for the analysis of protein distribution within a single coronal slice of a C57BL/6J mouse brain. For relative quantitation of the protein abundances across the slice, an 18O-isotopically labeled reference sample, derived from a whole control coronal slice from another mouse, was spiked into each voxel sample, and stable isotopic intensity ratios were used to obtain measures of relative protein abundances. In total, we generated maps of protein abundance patterns for 1028 proteins. The significant agreement of the protein distributions with previously reported data supports the validity of this methodology, which opens new opportunities for studying the spatial brain proteome and its dynamics during the course of disease progression and other important biological and associated health aspects in a discovery-driven fashion.