Two-dimensional mass spectra generated from the analysis of 15N-labeled and unlabeled peptides for efficient protein identification and de novo peptide sequencing

Protein identification has been greatly facilitated by database searches against protein sequences derived from product ion spectra of peptides. This approach is primarily based on the use of fragment ion mass information contained in a MS/MS spectrum. Unambiguous protein identification from a spectrum with low sequence coverage or poor spectral quality can be a major challenge. We present a two-dimensional (2D) mass spectrometric method in which the numbers of nitrogen atoms in the molecular ion and the fragment ions are used to provide additional discriminating power for much improved protein identification and de novo peptide sequencing. The nitrogen number is determined by analyzing the mass difference of corresponding peak pairs in overlaid spectra of (15)N-labeled and unlabeled peptides. These peptides are produced by enzymatic or chemical cleavage of proteins from cells grown in (15)N-enriched and normal media, respectively. It is demonstrated that, using 2D information, i.e., m/z and its associated nitrogen number, this method can, not only confirm protein identification results generated by MS/MS database searching, but also identify peptides that are not possible to identify by database searching alone. Examples are presented of analyzing Escherichia coli K12 extracts that yielded relatively poor MS/MS spectra, presumably from the digests of low abundance proteins, which can still give positive protein identification using this method. Additionally, this 2D MS method can facilitate spectral interpretation for de novo peptide sequencing and identification of posttranslational or other chemical modifications. We envision that this method should be particularly useful for proteome expression profiling of organelles or cells that can be grown in (15)N-enriched media.     

Automated methods for improved protein identification by peptide mass fingerprinting

In order to maximize protein identification by peptide mass fingerprinting noise peaks must be removed from spectra and recalibration is often required. The preprocessing of the spectra before database searching is essential but is time-consuming. Nevertheless, the optimal database search parameters often vary over a batch of samples. For high-throughput protein identification, these factors should be set automatically, with no or little human intervention. In the present work automated batch filtering and recalibration using a statistical filter is described. The filter is combined with multiple data searches that are performed automatically. We show that, using several hundred protein digests, protein identification rates could be more than doubled, compared to standard database searching. Furthermore, automated large-scale in-gel digestion of proteins with endoproteinase LysC, and matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) analysis, followed by subsequent trypsin digestion and MALDI-TOF analysis were performed. Several proteins could be identified only after digestion with one of the enzymes, and some less significant protein identifications were confirmed after digestion with the other enzyme. The results indicate that identification of especially small and low-abundance proteins could be significantly improved after sequential digestions with two enzymes.     

Prediction of missed cleavage sites in tryptic peptides aids protein identification in proteomics

Protein identification via peptide mass fingerprinting (PMF) remains a key component of high-throughput proteomics experiments in post-genomic science. Candidate protein identifications are made using bioinformatic tools from peptide peak lists obtained via mass spectrometry (MS). These algorithms rely on several search parameters, including the number of potential uncut peptide bonds matching the primary specificity of the hydrolytic enzyme used in the experiment. Typically, up to one of these "missed cleavages" are considered by the bioinformatics search tools, usually after digestion of the in silico proteome by trypsin. Using two distinct, nonredundant datasets of peptides identified via PMF and tandem MS, a simple predictive method based on information theory is presented which is able to identify experimentally defined missed cleavages with up to 90% accuracy from amino acid sequence alone. Using this simple protocol, we are able to "mask" candidate protein databases so that confident missed cleavage sites need not be considered for in silico digestion. We show that that this leads to an improvement in database searching, with two different search engines, using the PMF dataset as a test set. In addition, the improved approach is also demonstrated on an independent PMF data set of known proteins that also has corresponding high-quality tandem MS data, validating the protein identifications. This approach has wider applicability for proteomics database searching, and the program for predicting missed cleavages and masking Fasta-formatted protein sequence databases has been made available via http:// ispider.smith.man.ac uk/MissedCleave.     

A Heuristic method for assigning a false-discovery rate for protein identifications from Mascot database search results

MS/MS and database searching has emerged as a valuable technology for rapidly analyzing protein expression, localization, and post-translational modifications. The probability-based search engine Mascot has found widespread use as a tool to correlate tandem mass spectra with peptides in a sequence database. Although the Mascot scoring algorithm provides a probability-based model for peptide identification, the independent peptide scores do not correlate with the significance of the proteins to which they match. Herein, we describe a heuristic method for organizing proteins identified at a specified false-discovery rate using Mascot-matched peptides. We call this method PROVALT, and it uses peptide matches from a random database to calculate false-discovery rates for protein identifications and reduces a complex list of peptide matches to a nonredundant list of homologous protein groups. This method was evaluated using Mascot-identified peptides from a Trypanosoma cruzi epimastigote whole-cell lysate, which was separated by multidimensional LC and analyzed by MS/MS. PROVALT was then compared with the two traditional methods of protein identification when using Mascot, the single peptide score and cumulative protein score methods, and was shown to be superior to both in regards to the number of proteins identified and the inclusion of lower scoring nonrandom peptide matches.     

Comparison of SDS- and methanol-assisted protein solubilization and digestion methods for Escherichia coli membrane proteome analysis by 2-D LC-MS/MS

Both organic solvent and surfactant have been used for dissolving membrane proteins for shotgun proteomics. In this work, two methods of protein solubilization, namely using 60% methanol or 1% SDS, to dissolve and analyze the inner membrane fraction of an Escherichia coli K12 cell lysate were compared. A total of 358 proteins (1417 unique peptides) from the methanol-solubilized protein mixture and 299 proteins (892 peptides) from the SDS-solubilized sample-were identified by using trypsin digestion and 2-D LC-ESI MS/MS. It was found that the methanol method detected more hydrophobic peptides, resulting in a greater number of proteins identified, than the SDS method. We found that 159 out of 358 proteins (44%) and 120 out of 299 proteins (40%) detected from the methanol- and SDS-solubilized samples, respectively, are integral membrane proteins. Among the 190 integral membrane proteins 70 were identified exclusively in the methanol-solubilized sample, 89 were identified by both methods, and only 31 proteins were exclusively identified by the SDS method. It is shown that the integral membrane proteins reflected the theoretical proteome for number of transmembrane helices, length, functional class, and topology, indicating there was no bias in the proteins identified.     

The synaptic vesicle proteome: a comparative study in membrane protein identification

A proteomic analysis of the synaptic vesicle was undertaken to obtain a better understanding of vesicle regulation. Synaptic vesicles primarily consist of integral membrane proteins that are not well resolved on traditional isoelectric focusing/two-dimensional gel electrophoresis (IEF/2-DE) gels and are resistant to in-gel digestion with trypsin thereby reducing the number of peptides available for mass spectrometric analysis. To address these limitations, two complementary 2-DE methods were investigated in the proteome analysis: (a) IEF/sodium dodecyl sulfate-polyacrylamide gel electrophoresis (IEF/SDS-PAGE) for resolution of soluble proteins and, (b) Benzyl hexadecyl ammonium chloride/SDS-PAGE (16-BAC/SDS-PAGE) for resolution of integral membrane proteins. The IEF/SDS-PAGE method provided superior resolution of soluble proteins, but could only resolve membrane proteins with a single transmembrane domain. The 16-BAC/SDS-PAGE method improved separation, resolution and identification of integral membrane proteins with up to 12 transmembrane domains. Trypsin digestion of the integral membrane proteins was poor and fewer peptides were identified from these proteins. Analysis of both the peptide mass fingerprint and the tandem mass spectra using electrospray ionization quadrupole-time of flight mass spectrometry led to the positive identification of integral membrane proteins. Using both 2-DE separation methods, a total of 36 proteins were identified including seven integral membrane proteins, 17 vesicle regulatory proteins and four proteins whose function in vesicles is not yet known.     

Profiling human brain proteome by multi-dimensional separations coupled with MS

In our initial attempt to analyze the human brain proteome, we applied multi-dimensional protein separation and identification techniques using a combination of sample fractionation, 1-D SDS-PAGE, and MS analysis. The complexity of human brain proteome requires multiple fractionation strategies to extend the range and total number of proteins identified. According to the method of Klose (Methods Mol. Biol. 1999, 112, 67), proteins of the temporal lobe of human brain were fractionated into (i) cytoplasmic and nucleoplasmic, (ii) membrane and other structural, and (iii) DNA-binding proteins. Each fraction was then separated by SDS-PAGE, and the resulting gel line was cut into approximately 50 bands. After trypsin digestion, the resulting peptides from each band were analyzed by RP-LC/ESI-MS/MS using an LTQ spectrometer. The SEQUEST search program, which searched against the IPI database, was used for peptide sequence identification, and peptide sequences were validated by reversed sequence database search and filtered by the Protein Hit Score. Ultimately, 1533 proteins could be detected from the human brain. We classified the identified proteins according to their distribution on cellular components. Among these proteins, 24% were membrane proteins. Our results show that the multiple separation strategy is effective for high-throughput characterization of proteins from complex proteomic mixtures.     

Randomized sequence databases for tandem mass spectrometry peptide and protein identification

Tandem mass spectrometry (MS/MS) combined with database searching is currently the most widely used method for high-throughput peptide and protein identification. Many different algorithms, scoring criteria, and statistical models have been used to identify peptides and proteins in complex biological samples, and many studies, including our own, describe the accuracy of these identifications, using at best generic terms such as "high confidence." False positive identification rates for these criteria can vary substantially with changing organisms under study, growth conditions, sequence databases, experimental protocols, and instrumentation; therefore, study-specific methods are needed to estimate the accuracy (false positive rates) of these peptide and protein identifications. We present and evaluate methods for estimating false positive identification rates based on searches of randomized databases (reversed and reshuffled). We examine the use of separate searches of a forward then a randomized database and combined searches of a randomized database appended to a forward sequence database. Estimated error rates from randomized database searches are first compared against actual error rates from MS/MS runs of known protein standards. These methods are then applied to biological samples of the model microorganism Shewanella oneidensis strain MR-1. Based on the results obtained in this study, we recommend the use of use of combined searches of a reshuffled database appended to a forward sequence database as a means providing quantitative estimates of false positive identification rates of peptides and proteins. This will allow researchers to set criteria and thresholds to achieve a desired error rate and provide the scientific community with direct and quantifiable measures of peptide and protein identification accuracy as opposed to vague assessments such as "high confidence."     

Protein identification by in-gel digestion and mass spectrometric analysis

This protocol details a method for the identification of proteins that have been separated by gel electrophoresis. In-gel digestion of the protein bands with trypsin followed by quadrupole ion-trap or other triple quadrupole mass spectrometry techniques is described. The proteins can be identified by database searching of the mass fingerprint of the intact peptides and of the characteristic fragment masses produced by tandem mass spectrometry.     

Phase transfer surfactant-aided trypsin digestion for membrane proteome analysis

We have developed a new protocol for digesting hydrophobic proteins using trypsin with the aid of phase-transfer surfactants (PTS), such as sodium deoxycholate (SDC). SDC increases the solubility of hydrophobic proteins, enhances the activity of trypsin, and improves the accessibility to trypsin of proteins denatured during the extraction process. After digestion, SDC was successfully removed from the acidified solution containing tryptic peptides by adding a water-immiscible organic solvent, into which SDC was predominantly transferred, while the digested peptides remained in the aqueous phase. Compared with a protocol using an acid-labile surfactant, this PTS protocol increased the number of identified proteins and the recovery of hydrophobic peptides in the analysis of 400 ng of a membrane-enriched fraction of Escherichia coli. Application of the PTS protocol to 9.0 microg of a membrane-enriched pellet from human cervical cancer HeLa cells resulted in identification of a total of 1450 proteins, of which 764 (53%) were membrane proteins, by two-dimensional strong cation exchange (SCX)-C18 LC-MSMS with 5 SCX fractions. The distribution of the number of transmembrane domains in proteins identified in this study was in agreement with that in the IPI human database, suggesting that the PTS protocol can provide unbiased digestion of the membrane proteome.     

Enhanced identification of peptides lacking basic residues by LC-ESI-MS/MS analysis of singly charged peptides

Peptide sequences lacking basic residues (arginine, lysine, or histidine, referred to as "base-less") are of particular importance in proteomic experiments targeting protein C-termini or employing nontryptic proteases such as GluC or chymotrypsin. We demonstrate enhanced identification of base-less peptides by focused analysis of singly charged precursors in liquid chromatography (LC) electrospray ionization (ESI) tandem mass spectrometry (MS/MS). Singly charged precursors are often excluded from fragmentation and sequence analysis in LC-MS/MS. We generated different pools of base-less and base-containing peptides by tryptic and nontryptic digestion of bacterial proteomes. Focused LC-MS/MS analysis of singly charged precursor ions yielded predominantly base-less peptide identifications. Similar numbers of base-less peptides were identified by LC-MS/M Sanalysis targeting multiply charged precursors. There was little redundancy between the base-less sequences derived by both MS/MS schemes. In the present experimental outcome, additional LC-MS/MS analysis of singly charged precursors substantially increased the identification rate of base-less sequences derived from multiply charged precursors. In conclusion, LC-MS/MS based identification of base-less peptides is substantially enhanced by additional focused analysis of singly charged precursors.     

Comparison of protein expression lists from mass spectrometry of human blood fluids using exact peptide sequences versus BLAST

The proteins in blood were all first expressed as mRNAs from genes within cells. There are databases of human proteins that are known to be expressed as mRNA in human cells and tissues. Proteins identified from human blood by the correlation of mass spectra that fail to match human mRNA expression products may not be correct. We compared the proteins identified in human blood by mass spectrometry by 10 different groups by correlation to human and nonhuman nucleic acid sequences. We determined whether the peptides or proteins identified by the different groups mapped to the human known proteins of the Reference Sequence (RefSeq) database. We used Structured Query Language data base searches of the peptide sequences correlated to tandem mass spectrometry spectra and basic local alignment search tool analysis of the identified full length proteins to control for correlation to the wrong peptide sequence or the existence of the same or very similar peptide sequence shared by more than one protein. Mass spectra were correlated against large protein data bases that contain many sequences that may not be expressed in human beings yet the search returned a very high percentage of peptides or proteins that are known to be found in humans. Only about 5% of proteins mapped to hypothetical sequences, which is in agreement with the reported false-positive rate of searching algorithms conditions. The results were highly enriched in secreted and soluble proteins and diminished in insoluble or membrane proteins. Most of the proteins identified were relatively short and showed a similar size distribution compared to the RefSeq database. At least three groups agree on a nonredundant set of 1671 types of proteins and a nonredundant set of 3151 proteins were identified by at least three peptides.     

Analysis of electroblotted proteins by mass spectrometry: protein identification after Western blotting

We describe a new approach for the identification and characterization by mass spectrometry of proteins that have been electroblotted onto nitrocellulose. Using this method (Blotting and Removal of Nitrocellulose (BARN)), proteins can be analyzed either as intact proteins for molecular weight determination or as peptides generated by on-membrane proteolysis. Acetone is used to dissolve the nitrocellulose and to precipitate the adsorbed proteins/peptides, thus removing the nitrocellulose which can interfere with MS analysis. This method offers improved protein coverage, especially for membrane proteins, such as uroplakins, because the extraction step after in-gel digestion is avoided. Moreover, removal of nitrocellulose from the sample solution allows sample analysis by both MALDI- and (LC) ESI-based mass spectrometers. Finally, we demonstrate the utility of BARN for the direct identification of soluble and membrane proteins after Western blotting, obtaining comparable or better results than with in-gel digestion.     

质谱图聚类网络法在鉴定多肽翻译后修饰中的应用及研究进展

蛋白质组学多肽鉴定方法一直以基于质谱分析和数据库搜索的方法为主,随着质谱仪技术的发展,海量的质谱数据被获取,这为大规模蛋白质的鉴定提供了一个强大的数据仓库,使得以质谱数据为基础的蛋白质组学研究成为主流。传统的串联质谱图搜库方法鉴定多肽翻译后修饰时具有诸多局限,质谱网络方法可以在一定程度上弥补局限。文中系统综述了基于质谱聚类的质谱网络和质谱图库搜索方法的发展历程、理论研究和应用研究,讨论了质谱网络库方法在鉴定多肽翻译后修饰的优势,并进行了分析和展望。     

Genetic screen for signal peptides in Hydra reveals novel secreted proteins and evidence for non-classical protein secretion

We have screened a Hydra cDNA library for sequences encoding N-terminal signal peptides using the yeast invertase secretion vector pSUC [Jacobs et al., 1997. A genetic selection for isolating cDNAs encoding secreted proteins. Gene 198, 289-296]. We isolated and sequenced 907 positive clones; 88% encoded signal peptides; 12% lacked signal peptides. By searching the Hydra EST database we identified full-length sequences for the selected clones. These encoded 37 known proteins with signal peptides and 40 novel Hydra-specific proteins with signal peptides. Localization of two signal peptide-containing sequences, VEGF and ferritin, to the secretory pathway was confirmed with GFP fusion proteins. In addition, we isolated 105 clones which lacked signal peptides but which supported invertase secretion from yeast. Isolation of plasmids from these clones and retransformation in invertase-negative yeast cells confirmed the phenotype. A GFP fusion protein of one such clone encoding the foot morphogen pedibin was localized to the cytoplasm in transfected Hydra cells and did not enter the ER/Golgi secretory pathway. Secretion of pedibin and other proteins lacking signal peptides appears to occur by a non-classical protein secretion route.     

A combination method of chemical with enzyme reactions for identification of membrane proteins

A simple method for effective analysis of various proteins has been developed, including membrane proteins, with LC-MS/MS, using CNBr and acetic acid cleavage in one reaction for the digestion of both the M/ and /D/ positions within the target proteins. This dual chemical reaction has been compared with traditional CNBr or an acid cleavage method using a rat kidney membrane fraction and it showed an advantage of the dual reaction with respect to a high number of peptides detected and a high protein recovery. Furthermore, when this dual chemical reaction was combined with trypsin digestion, the number of proteins surprisingly increased approximately 3.0 times more than in the cases with the trypsin digestion only. It was also 1.9 times more than in cases dealing with Tube-Gel trypsin digestion, which is one of the most efficient digestion methods. In addition, it was shown that this dual chemical reaction could be applied to an in-gel digestion. Using the combination of the chemical and enzyme reaction, 172 proteins including 95 membrane proteins were identified. This indicated that this method is one of the efficient systems in single MS/MS analysis. In particular, many membrane proteins identified in this study were detected by a new combination, but not by a traditional trypsin digestion method.     

Trypsin-based monolithic bioreactor coupled on-line with LC/MS/MS system for protein digestion and variant identification in standard solutions and serum samples

The applicability of a trypsin-based monolithic bioreactor coupled on-line with LC/MS/MS for rapid proteolytic digestion and protein identification is here described. Dilute samples are passed through the bioreactor for generation of proteolytic fragments in less than 10 min. After digestion and peptide separation, electrospray ionization tandem mass spectrometry is used to generate a peptide map and to identify proteolytic peptides by correlating their fragmentation spectra with amino acid sequences from a protein database. By digesting picomoles of proteins sufficient data from ESI and MS/MS were obtained to unambiguously identify proteins alone and in serum samples. This approach was also extended to locate mutation sites in beta-lactoglobulin A and B variants.     

Characterization of the rat liver membrane proteome using peptide immobilized pH gradient isoelectric focusing

Membrane proteins are of particular interest in proteomics because of their potential therapeutic utility. Past proteomic approaches used to investigate membrane proteins have only been partially successful at providing a comprehensive analysis due to the inherently hydrophobic nature and low abundance for some of these proteins. Recently, these difficulties have been improved by analyzing membrane protein enriched samples using shotgun proteomics. In addition, the recent application of methanol-assisted trypsin digestion of membrane proteins has been shown to be a method to improve membrane protein identifications. In this study, a comparison of different concentrations of methanol was assessed for assisting membrane protein digestion with trypsin prior to analysis using a gel-based shotgun proteomics approach called peptide immobilized pH gradient isoelectric focusing (IPG-IEF). We demonstrate the use of peptide IEF on pH 3-10 IPG strips as the first dimension of two-dimensional shotgun proteomics for protein identifications from the membrane fraction of rat liver. Tryptic digestion of proteins was carried out in varying concentrations of methanol in 10 mM ammonium bicarbonate: 0% (v/v), 40% (v/v), and 60% (v/v). A total of 800 proteins were identified from 60% (v/v) methanol, which increased the protein identifications by 17% and 14% compared to 0% (v/v) methanol and 40% (v/v) methanol assisted digestion, respectively. In total, 1549 nonredundant proteins were identified from all three concentrations of methanol including 690 (42%) integral membrane proteins of which 626 of these proteins contained at least one transmembrane domain. Peptide IPG-IEF separation of peptides was successful as the peptides were separated into discrete pI regions with high resolution. The results from this study prove utility of 60% (v/v) methanol assisted digestion in conjunction with peptide IPG-IEF as an optimal shotgun proteomics technique for the separation and identification of previously unreported membrane proteins.