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.     

Global proteome discovery using an online three-dimensional LC-MS/MS

We have developed a proteomics technology featuring on-line three-dimensional liquid chromatography coupled to tandem mass spectrometry (3D LC-MS/MS). Using 3D LC-MS/MS, the yeast-soluble, urea-solubilized peripheral membrane and SDS-solubilized membrane protein samples collectively yielded 3019 unique yeast protein identifications with an average of 5.5 peptides per protein from the 6300-gene Saccharomyces Genome Database searched with SEQUEST. A single run of the urea-solubilized sample yielded 2255 unique protein identifications, suggesting high peak capacity and resolving power of 3D LC-MS/MS. After precipitation of SDS from the digested membrane protein sample, 3D LC-MS/MS allowed the analysis of membrane proteins. Among 1221 proteins containing two or more predicted transmembrane domains, 495 such proteins were identified. The improved yeast proteome data allowed the mapping of many metabolic pathways and functional categories. The 3D LC-MS/MS technology provides a suitable tool for global proteome discovery.     

Addressing trypsin bias in large scale (phospho)proteome analysis by size exclusion chromatography and secondary digestion of large post-trypsin peptides

In the vast majority of bottom-up proteomics studies, protein digestion is performed using only mammalian trypsin. Although it is clearly the best enzyme available, the sole use of trypsin rarely leads to complete sequence coverage, even for abundant proteins. It is commonly assumed that this is because many tryptic peptides are either too short or too long to be identified by RPLC-MS/MS. We show through in silico analysis that 20-30% of the total sequence of three proteomes (Schizosaccharomyces pombe, Saccharomyces cerevisiae, and Homo sapiens) is expected to be covered by Large post-Trypsin Peptides (LpTPs) with M(r) above 3000 Da. We then established size exclusion chromatography to fractionate complex yeast tryptic digests into pools of peptides based on size. We found that secondary digestion of LpTPs followed by LC-MS/MS analysis leads to a significant increase in identified proteins and a 32-50% relative increase in average sequence coverage compared to trypsin digestion alone. Application of the developed strategy to analyze the phosphoproteomes of S. pombe and of a human cell line identified a significant fraction of novel phosphosites. Overall our data indicate that specific targeting of LpTPs can complement standard bottom-up workflows to reveal a largely neglected portion of the proteome.     

Probability-based evaluation of peptide and protein identifications from tandem mass spectrometry and SEQUEST analysis: the human proteome

Large-scale protein identifications from highly complex protein mixtures have recently been achieved using multidimensional liquid chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) and subsequent database searching with algorithms such as SEQUEST. Here, we describe a probability-based evaluation of false positive rates associated with peptide identifications from three different human proteome samples. Peptides from human plasma, human mammary epithelial cell (HMEC) lysate, and human hepatocyte (Huh)-7.5 cell lysate were separated by strong cation exchange (SCX) chromatography coupled offline with reversed-phase capillary LC-MS/MS analyses. The MS/MS spectra were first analyzed by SEQUEST, searching independently against both normal and sequence-reversed human protein databases, and the false positive rates of peptide identifications for the three proteome samples were then analyzed and compared. The observed false positive rates of peptide identifications for human plasma were significantly higher than those for the human cell lines when identical filtering criteria were used, suggesting that the false positive rates are significantly dependent on sample characteristics, particularly the number of proteins found within the detectable dynamic range. Two new sets of filtering criteria are proposed for human plasma and human cell lines, respectively, to provide an overall confidence of >95% for peptide identifications. The new criteria were compared, using a normalized elution time (NET) criterion (Petritis et al. Anal. Chem. 2003, 75, 1039-1048), with previously published criteria (Washburn et al. Nat. Biotechnol. 2001, 19, 242-247). The results demonstrate that the present criteria provide significantly higher levels of confidence for peptide identifications from mammalian proteomes without greatly decreasing the number of identifications.     

Development of a two-dimensional protein-peptide separation protocol for comprehensive proteome measurements

We have developed an effective two-dimensional fractionation protocol of complex proteome mixtures that extends the ability to conduct more comprehensive proteome measurements. A sample containing intact proteins extracted from Saccharomyces cerevisiae was fractionated by liquid phase isoelectric focusing, followed by tryptic digestion and solid-phase extraction (SPE) clean-up and reversed-phase liquid chromatography-electrospray ionization tandem mass spectrometry (LC-MS-MS) of the resultant peptides. The clean-up step is designed to desalt the fractions and rid them of urea and ampholytes prior to analysis by LC-MS-MS. Fifty milligrams of protein were separated into 20 fractions by liquid-phase isoelectric focusing, spanning a pH range of 3-10. The effectiveness of the removal of ampholytes was monitored by capillary zone electrophoresis and LC-MS-MS. The ability to analyze all of the 20 fractions without any noticeable decrease in the separation efficiency demonstrates the overall effectiveness of the SPE clean-up step. The results show that the separation strategy is effective for high throughput characterization of proteins from complex proteomic mixtures.     

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.     

Comparison of 2-D LC and 3-D LC with post- and pre-tryptic-digestion SEC fractionation for proteome analysis of normal human liver tissue

The current "shotgun" proteomic analysis, strong cation exchange-RPLC-MS/MS system, is a widely used method for proteome research. Currently, it is not suitable for complicated protein sample analysis, like mammal tissues or cells. To increase the protein identification confidence and number, an additional separation dimension for sample fractionation is necessary to be coupled prior to current multi-dimensional protein identification technology (MudPIT). In this work, SEC was elaborately selected and applied for sample prefractionation in consideration of its non-bias against sample and variety of choice of mobile phases. The analysis of the global lysate of normal human liver tissue sample provided by the China Human Liver Proteome Project, were performed to compare the proteome coverage, sequence coverage (peptide per protein identification) and protein identification efficiency in MudPIT, 3-D LC-MS/MS identification strategy with preproteolytic and postproteolytic fractionation. It was demonstrated that 3-D LC-MS/MS utilizing protein level fractionation was the most effective method. A MASCOT search using the MS/MS results acquired by QSTAR(XL) identified 1622 proteins from 3-D LC-MS/MS identification approaches. A primary analysis on molecular weight, pI and grand average hydrophobicity value distribution of the identified proteins in different approaches was made to further evaluate the 3-D LC-MS/MS analysis strategy.     

mTRAQ-based quantitative analysis combined with peptide fractionation based on cysteinyl peptide enrichment

In the present study, the fractionation scheme for cysteinyl peptide enrichment (CPE) was combined with the mass differential tags for relative and absolute quantification (mTRAQ) method to reduce sample complexity and increase proteome coverage. Cysteine residues of the proteins were first alkylated using iodoacetyl PEG₂–biotin instead of other conventional alkylating agents such as iodoacetamide. After trypsin digestion, amine groups were labeled with mTRAQ, and these labeled peptides were fractionated according to the presence or absence of cysteine residues using avidin–biotin affinity chromatography. With these approaches, we were able to divide the peptides into the two fractions with more than 90% fractionation efficiency for standard protein and MCF7 cell lysate. When the fractionation strategy was applied to colorectal cancer tissue samples, we were able to obtain quantitative information that was consistent with the previous study based on mTRAQ quantification, implying that the cysteine-based fractionation method does not affect mTRAQ quantification. We expect that the mTRAQ-based quantitative analysis combined with peptide fractionation through the CPE strategy would allow for deep-down analysis of proteome samples and ultimately for increasing proteome coverage with simultaneous quantification for biomarker discovery.     

Enhanced analysis of the mouse plasma proteome using cysteine-containing tryptic glycopeptides

A comprehensive understanding of the mouse plasma proteome is important for studies using mouse models to identify protein markers of human disease. To enhance our analysis of the mouse plasma proteome, we have developed a method for isolating low-abundance proteins using a cysteine-containing glycopeptide strategy. This method involves two orthogonal affinity capture steps. First, glycoproteins are coupled to an azlactone copolymer gel using hydrazide chemistry and cysteine residues are then biotinylated. After trypsinization and extensive washing, tethered N-glycosylated tryptic peptides are released from the gel using PNGase F. Biotinylated cysteinyl-containing glycopeptides are then affinity selected using a monomeric avidin gel and analyzed by LC-MS/MS. We have applied the method to a proteome analysis of mouse plasma. In two independent analyses using 200 muL each of C57BL mouse plasma, 51 proteins were detected. Only 42 proteins were seen when the same plasma sample was analyzed by glycopeptides only. A total of 104 N-glycosylation sites were identified. Of these, 17 sites have hitherto not been annotated in the Swiss-Prot database whereas 48 were considered probable, potential, or by similarity - i.e., based on little or no experimental evidence. We show that analysis by cysteine-containing glycopeptides allows detection of low-abundance proteins such as the epidermal growth factor receptor, the Vitamin K-dependent protein Z, the hepatocyte growth factor activator, and the lymphatic endothelium-specific hyaluronan receptor as these proteins were not detected in the glycopeptide control analysis.     

Highly informative proteome analysis by combining improved N-terminal sulfonation for de novo peptide sequencing and online capillary reverse-phase liquid chromatography/tandem mass spectrometry

Recently, various chemical modifications of peptides have been incorporated into mass spectrometric analyses of proteome samples, predominantly in conjunction with matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS), to facilitate de novo sequencing of peptides. In this work, we investigate systematically the utility of N-terminal sulfonation of tryptic peptides by 4-sulfophenyl isothiocyanate (SPITC) for proteome analysis by capillary reverse-phase liquid chromatography/tandem mass spectrometry (cRPLC/MS/MS). The experimental conditions for the sulfonation were carefully adjusted so that SPITC reacts selectively with the N-terminal amino groups, even in the presence of the epsilon-amino groups of lysine residues. Mass spectrometric analyses of the modified peptides by cRPLC/MS/MS indicated that SPITC derivatization proceeded toward near completion under the experimental conditions employed here. The SPITC-derivatized peptides underwent facile fragmentation, predominantly resulting in y-series ions in the MS/MS spectra. Combining SPITC derivatization and cRPLC/MS/MS analyses facilitated the acquisition of sequence information for lysine-terminated tryptic peptides as well as arginine-terminated peptides without the need for additional peptide pretreatment, such as guanidination of lysine amino group. This process alleviated the biased detection of arginine-terminated peptides that is often observed in MALDI MS experiments. We will discuss the utility of the technique as a viable method for proteome analyses and present examples of its application in analyzing samples having different levels of complexity.     

Differential expression analysis of Escherichia coli proteins using a novel software for relative quantitation of LC-MS/MS data

The study of changes in protein levels between samples derived from cells representing different biological conditions is a key to the understanding of cellular function. There are two main methods available that allow both for global scanning for significantly varying proteins and targeted profiling of proteins of interest. One method is based on 2-D gel electrophoresis and image analysis of labelled proteins. The other method is based on LC-MS/MS analysis of either unlabelled peptides or peptides derived from isotopically labelled proteins or peptides. In this study, the non-labelling approach was used involving a new software, DeCyder MS Differential Analysis Software (DeCyder MS) intended for automated detection and relative quantitation of unlabelled peptides in LC-MS/MS data.Total protein extracts of E. coli strains expressing varying levels of dihydrofolate reductase and integron integrase were digested with trypsin and analyzed using a nanoscale liquid chromatography system, Ettan MDLC, online connected to an LTQTM linear ion-trap mass spectrometer fitted with a nanospray interface. Acquired MS data were subjected to DeCyder MS analysis where 2-D representations of the peptide patterns from individual LC-MS/MS analyses were matched and compared.This approach to unlabelled quantitative analysis of the E. coli proteome resulted in relative protein abundances that were in good agreement with results obtained from traditional methods for measuring protein levels.     

Expanding the zebrafish embryo proteome using multiple fractionation approaches and tandem mass spectrometry

The proteome of zebrafish, Danio rerio, embryos has not been studied in great detail mainly due to the presence of high abundance yolk proteins in embryos. Here we report the highest number of the zebrafish embryo proteins identified so far to our knowledge, through a combination of a protein-level fractionation approach (1D SDS-PAGE) and two different peptide-level fractionation approaches (IEF and strong anion exchange (SAX)) of deyolked zebrafish embryos followed by LC-MS/MS. We detected 5267 proteins in total of which 3464 proteins were identified with at least two peptides (less than 1% peptide false discovery rate). The analysis of proteome coverage from each method showed that 56% of detected proteins were common to all approaches and 95% of the detected proteome was obtained from 1D SDS-PAGE approach alone. Bioinformatics analysis of the detected proteome demonstrated that nucleocytoplasmic transport (biological process) and ribosomal proteins (cellular component) were the most over-represented proteins, whereas cell-cell signaling (biological process) and extracellular space proteins (cellular component) were the most under-represented proteins in the identified proteome.     

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.     

Large-scale identification of proteins in human salivary proteome by liquid chromatography/mass spectrometry and two-dimensional gel electrophoresis-mass spectrometry

Human saliva contains a large number of proteins and peptides (salivary proteome) that help maintain homeostasis in the oral cavity. Global analysis of human salivary proteome is important for understanding oral health and disease pathogenesis. In this study, large-scale identification of salivary proteins was demonstrated by using shotgun proteomics and two-dimensinal gel electrophoresis-mass spectrometry (2-DE-MS). For the shotgun approach, whole saliva proteins were prefractionated according to molecular weight. The smallest fraction, presumably containing salivary peptides, was directly separated by capillary liquid chromatography (LC). However, the large protein fractions were digested into peptides for subsequent LC separation. Separated peptides were analyzed by on-line electrospray tandem mass spectrometry (MS/MS) using a quadrupole-time of flight mass spectrometer, and the obtained spectra were automatically processed to search human protein sequence database for protein identification. Additionally, 2-DE was used to map out the proteins in whole saliva. Protein spots 105 in number were excised and in-gel digested; and the resulting peptide fragments were measured by matrix-assisted laser desorption/ionization-mass spectrometry and sequenced by LC-MS/MS for protein identification. In total, we cataloged 309 proteins from human whole saliva by using these two proteomic approaches.     

A high-confidence human plasma proteome reference set with estimated concentrations in PeptideAtlas

Human blood plasma can be obtained relatively noninvasively and contains proteins from most, if not all, tissues of the body. Therefore, an extensive, quantitative catalog of plasma proteins is an important starting point for the discovery of disease biomarkers. In 2005, we showed that different proteomics measurements using different sample preparation and analysis techniques identify significantly different sets of proteins, and that a comprehensive plasma proteome can be compiled only by combining data from many different experiments. Applying advanced computational methods developed for the analysis and integration of very large and diverse data sets generated by tandem MS measurements of tryptic peptides, we have now compiled a high-confidence human plasma proteome reference set with well over twice the identified proteins of previous high-confidence sets. It includes a hierarchy of protein identifications at different levels of redundancy following a clearly defined scheme, which we propose as a standard that can be applied to any proteomics data set to facilitate cross-proteome analyses. Further, to aid in development of blood-based diagnostics using techniques such as selected reaction monitoring, we provide a rough estimate of protein concentrations using spectral counting. We identified 20,433 distinct peptides, from which we inferred a highly nonredundant set of 1929 protein sequences at a false discovery rate of 1%. We have made this resource available via PeptideAtlas, a large, multiorganism, publicly accessible compendium of peptides identified in tandem MS experiments conducted by laboratories around the world.     

Bacterial proteome of streptococcus pneumoniae through multidimensional separations coupled with LC-MS/MS

Streptococcus pneumoniae is a major human respiratory pathogen causing considerable morbidity and mortality worldwide. In order to better understand the pathogenesis of S. pneumoniae, we employed SDS-PAGE combined with LC-MS/MS analysis and in-solution digestion coupled with 2D-LC-MS/MS to obtain the whole-cell proteome of the bacterium. Among the identified 1,210 proteins, 345 proteins were annotated for cellular components, 613 for biological processes, and 421 for molecular functions. Important virulence-associated surface proteins such as Eno, ZmpB, and PrtA were identified. Classification analysis and protein-protein interaction map revealed that these identified proteins are involved in many biological processes including protein biosynthesis, protein folding and proteolysis, cell cycle, or regulation and carbohydrate metabolism. These data represent a comprehensive reference map of S. pneumoniae proteome, providing a useful source for further analysis of the virulence factors and the regulatory network involved in the pathogenesis of the bacterium.     

Toward the complete yeast mitochondrial proteome: multidimensional separation techniques for mitochondrial proteomics

Proteomic analyses of different subcellular compartments, so-called organellar proteomics, facilitate the understanding of cellular functions on a molecular level. In this work, various orthogonal multidimensional separation techniques both on the protein and on the peptide level are compared with regard to the number of identified proteins as well as the classes of proteins accessible by the respective methodology. The most complete overview was achieved by a combination of such orthogonal techniques as shown by the analysis of the yeast mitochondrial proteome. A total of 851 different proteins (PROMITO dataset) were identified by use of multidimensional LC-MS/MS, 1D-SDS-PAGE combined with nano-LC-MS/MS and 2D-PAGE with subsequent MALDI-mass fingerprinting. Our PROMITO approach identified the 749 proteins, which were found in the largest previous study on the yeast mitochondrial proteome, and additionally 102 proteins including 42 open reading frames with unknown function, providing the basis for a more detailed elucidation of mitochondrial processes. Comparison of the different approaches emphasizes a bias of 2D-PAGE against proteins with very high isoelectric points as well as large and hydrophobic proteins, which can be accessed more appropriately by the other methods. While 2D-PAGE has advantages in the possible separation of protein isoforms and quantitative differential profiling, 1D-SDS-PAGE with nano-LC-MS/MS and multidimensional LC-MS/MS are better suited for efficient protein identification as they are less biased against distinct classes of proteins. Thus, comprehensive proteome analyses can only be realized by a combination of such orthogonal approaches, leading to the largest dataset available for the mitochondrial proteome of yeast.     

Plasma proteome dynamics: analysis of lipoproteins and acute phase response proteins with 2H2O metabolic labeling

Understanding the pathologies related to the regulation of protein metabolism requires methods for studying the kinetics of individual proteins. We developed a (2)H(2)O metabolic labeling technique and software for protein kinetic studies in free living organisms. This approach for proteome dynamic studies requires the measurement of total body water enrichments by GC-MS, isotopic distribution of the tryptic peptide by LC-MS/MS, and estimation of the asymptotical number of deuterium incorporated into a peptide by software. We applied this technique to measure the synthesis rates of several plasma lipoproteins and acute phase response proteins in rats. Samples were collected at different time points, and proteins were separated by a gradient gel electrophoresis. (2)H labeling of tryptic peptides was analyzed by ion trap tandem mass spectrometry (LTQ MS/MS) for measurement of the fractional synthesis rates of plasma proteins. The high sensitivity of LTQ MS in zoom scan mode in combination with (2)H label amplification in proteolytic peptides allows detection of the changes in plasma protein synthesis related to animal nutritional status. Our results demonstrate that fasting has divergent effects on the rate of synthesis of plasma proteins, increasing synthesis of ApoB 100 but decreasing formation of albumin and fibrinogen. We conclude that this technique can effectively measure the synthesis of plasma proteins and can be used to study the regulation of protein homeostasis under physiological and pathological conditions.