毛细管区带电泳／串联质谱联用法鉴定多肽和蛋白质

建立了毛细管区带电泳－串联质谱联用（ＣＺＥ／ＭＳ／ＭＳ）对多肽和蛋白质高灵敏度鉴定方法,对Ｍｅｔ－脑啡肽和Ｌｅｕ－脑啡肽的混合物进行了分析,用ＣＺＥ／ＭＳ／ＭＳ方法验证了各自的序列,同样对细胞色素ｃ的胰蛋白酶酶解产物用ＣＺＥ／ＭＳ／ＭＳ方法进行了肽质谱分析,几科所有肽段的序列及其与在分子中的位置都得到了确定,通过ＳＥＱＵＥＳＴ软件进行蛋白质序列数据库搜索得到准确的鉴定结果,所消耗的样品量均在低皮可     

Mass Spectral Analysis of Synthetic Peptides: Implications in Proteomics

Sequence determination of peptides is a crucial step in mass spectrometry–based proteomics. Peptide sequences are determined either by database search or by de novo sequencing using tandem mass spectrometry. Determination of all the theoretical expected peptide fragments and eliminating false discoveries remains a challenge in proteomics. Developing standards for evaluating the performance of mass spectrometers and algorithms used for identification of proteins is important for proteomics studies. The current study is focused on these aspects by using synthetic peptides. A total of 599 peptides were designed from in silico tryptic digest with 1 or 2 missed cleavages from 199 human proteins, and synthetic peptides corresponding to these sequences were obtained. The peptides were mixed together, and analysis was carried out using liquid chromatography–electrospray ionization tandem mass spectrometry on a Q-Exactive HF mass spectrometer. The peptides and proteins were identified with SEQUEST program. The analysis was carried out using the proteomics workflows. A total of 573 peptides representing 196 proteins could be identified, and a spectral library was created for these peptides. Analysis parameters such as “no enzyme selection” gave the maximum number of detected peptides as compared with trypsin in the selection. False discoveries could be identified. This study highlights the limitations of peptide detection and the need for developing powerful algorithms along with tools to evaluate mass spectrometers and algorithms. It also shows the limitations of peptide detection even with high-end mass spectrometers. The mass spectral data are available in ProteomeXchange with accession no. PXD017992.     

A new algorithm for the evaluation of shotgun peptide sequencing in proteomics: support vector machine classification of peptide MS/MS spectra and SEQUEST scores

Shotgun tandem mass spectrometry-based peptide sequencing using programs such as SEQUEST allows high-throughput identification of peptides, which in turn allows the identification of corresponding proteins. We have applied a machine learning algorithm, called the support vector machine, to discriminate between correctly and incorrectly identified peptides using SEQUEST output. Each peptide was characterized by SEQUEST-calculated features such as delta Cn and Xcorr, measurements such as precursor ion current and mass, and additional calculated parameters such as the fraction of matched MS/MS peaks. The trained SVM classifier performed significantly better than previous cutoff-based methods at separating positive from negative peptides. Positive and negative peptides were more readily distinguished in training set data acquired on a QTOF, compared to an ion trap mass spectrometer. The use of 13 features, including four new parameters, significantly improved the separation between positive and negative peptides. Use of the support vector machine and these additional parameters resulted in a more accurate interpretation of peptide MS/MS spectra and is an important step toward automated interpretation of peptide tandem mass spectrometry data in proteomics.     

Whole-Cell Protein Identification Using the Concept of Unique Peptides

A concept of unique peptides(CUP)was proposed and implemented to identify whole-cell proteins from tandem mass spectrometry(MS/MS)ion spectra.A unique peptide is defined as a peptide,irrespective of its length,that exists only in one protein of a proteome of interest,despite the fact that this peptide may appear more than once in the same protein.Integrating CUP,a two-step whole-cell protein identification strategy was developed to further increase the confidence of identified proteins.A dataset containing 40,243 MS/MS ion spectra of Saccharomyces cerevisiae and protein identification tools including Mascot and SEQUEST were used to illustrate the proposed concept and strategy.Without implementing CUP,the proteins identified by SEQUEST are 2.26 fold of those identified by Mascot.When CUP was applied,the proteins bearing unique peptides identified by SEQUEST are3.89 fold of those identified by Mascot.By cross-comparing two sets of identified proteins,only 89 common proteins derived from CUP were found.The key discrepancy between identified proteins was resulted from the filtering criteria employed by each protein identification tool.According to the origin of peptides classified by CUP and the commonality of proteins recognized by protein identification tools,all identified proteins were cross-compared,resulting in four groups of proteins possessing different levels of assigned confidence.     

Peptide end sequencing by orthogonal MALDI tandem mass spectrometry

Highly sensitive peptide fragmentation and identification in sequence databases is a cornerstone of proteomics. Previously, a two-layered strategy consisting of MALDI peptide mass fingerprinting followed by electrospray tandem mass spectrometry of the unidentified proteins has been successfully employed. Here, we describe a high-sensitivity/high-throughput system based on orthogonal MALDI tandem mass spectrometry (o-MALDI) and the automated recognition of fragments corresponding to the N- and C-terminal amino acid residues. Robotic deposition of samples onto hydrophobic anchor substrates is employed, and peptide spectra are acquired automatically. The pulsing feature of the QSTAR o-MALDI mass spectrometer enhances the low mass region of the spectra by approximately 1 order of magnitude. Software has been developed to automatically recognize characteristic features in the low mass region (such as the y1 ion of tryptic peptides), maintaining high mass accuracy even with very low count events. Typically, the sum of the N-terminal two ions (b2 ion), the third N-terminal ion (b3 ion), and the two C-terminal fragments of the peptide (y1 and y2) can be determined. Given mass accuracy in the low ppm range, peptide end sequencing on one or two tryptic peptides is sufficient to uniquely identify a protein from gel samples in the low silver-stained range.     

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.     

Large-scale identification of Caenorhabditis elegans proteins by multidimensional liquid chromatography-tandem mass spectrometry

A proteome of a model organism, Caenorhabditis elegans, was analyzed by an integrated liquid chromatography (LC)-based protein identification system, which was constructed by microscale two-dimensional liquid chromatography (2DLC) coupled with electrospray ionization (ESI) tandem mass spectrometry (MS/MS) on a high-resolution hybrid mass spectrometer with an automated data analysis system. Soluble and insoluble protein fractions were prepared from a mixed growth phase culture of the worm C. elegans, digested with trypsin, and fractionated separately on the 2DLC system. The separated peptides were directly analyzed by on-line ESI-MS/MS in a data-dependent mode, and the resultant spectral data were automatically processed to search a genome sequence database, wormpep 66, for protein identification. The total number of proteins of the composite proteome identified in this method was 1,616, including 110 secreted/targeted proteins and 242 transmembrane proteins. The codon adaptation indices of the identified proteins suggested that the system could identify proteins of relatively low abundance, which are difficult to identify by conventional 2D-gel electrophoresis (GE) followed by an offline mass spectrometric analysis such as peptide mass fingerprinting. Among the approximately 5,400 peptides assigned in this study, many peptides with post-translational modifications, such as N-terminal acetylation and phosphorylation, were detected. This expression profile of C. elegans, containing 571 hypothetical gene products, will serve as the basic data of a major proteome set expressed in the worm.     

Protein identification by syringe pump-driven reversed-phase LC-MS/MS

In typical mass spectrometry-based protein identification using peptide fragmentation fingerprinting, front-end separation plays a critical role in successful peptide sequencing. This separation step demands a great deal of time and usually is the rate-limiting step for the whole process. Here we provide an alternative separation method, based on a simple nanoflow delivery system, that is able to shorten the separation time considerably. This system consists of a 25-mul syringe connected to a manually packed reversed-phase mini-capillary column that can be directly coupled to an electrospray ionization tandem mass spectrometer. A syringe pump is then used to deliver the peptide mixtures at a nanoscale flow rate. We examined the efficiency and efficacy of this method by analyzing the tryptic peptides of bovine serum albumin and of 10 Escherichia coli proteins separated by two-dimensional gel electrophoresis (2DE). The results showed that identification of each protein could be achieved successfully within 25 min by using the disposable mini-capillary column. Moreover, all 2DE-separated E. coli proteins were identified at high confidence levels. Together, our data suggest that this method is a suitable option for mass spectrometry-based protein identification.     

The application of new software tools to quantitative protein profiling via isotope-coded affinity tag (ICAT) and tandem mass spectrometry: I. Statistically annotated datasets for peptide sequences and proteins identified via the application of ICAT and tandem mass spectrometry to proteins copurifying with T cell lipid rafts

Lipid rafts were prepared according to standard protocols from Jurkat T cells stimulated via T cell receptor/CD28 cross-linking and from control (unstimulated) cells. Co-isolating proteins from the control and stimulated cell preparations were labeled with isotopically normal (d0) and heavy (d8) versions of the same isotope-coded affinity tag (ICAT) reagent, respectively. Samples were combined, proteolyzed, and resultant peptides fractionated via cation exchange chromatography. Cysteine-containing (ICAT-labeled) peptides were recovered via the biotin tag component of the ICAT reagents by avidin-affinity chromatography. On-line micro-capillary liquid chromatography tandem mass spectrometry was performed on both avidin-affinity (ICAT-labeled) and flow-through (unlabeled) fractions. Initial peptide sequence identification was by searching recorded tandem mass spectrometry spectra against a human sequence data base using SEQUEST software. New statistical data modeling algorithms were then applied to the SEQUEST search results. These allowed for discrimination between likely "correct" and "incorrect" peptide assignments, and from these the inferred proteins that they collectively represented, by calculating estimated probabilities that each peptide assignment and subsequent protein identification was a member of the "correct" population. For convenience, the resultant lists of peptide sequences assigned and the proteins to which they corresponded were filtered at an arbitrarily set cut-off of 0.5 (i.e. 50% likely to be "correct") and above and compiled into two separate datasets. In total, these data sets contained 7667 individual peptide identifications, which represented 2669 unique peptide sequences, corresponding to 685 proteins and related protein groups.     

A comparison of immobilized pH gradient isoelectric focusing and strong-cation-exchange chromatography as a first dimension in shotgun proteomics

Recently, we have developed a high-resolution two-dimensional separation strategy for the analysis of complex peptide mixtures. This methodology employs isoelectric focusing of peptides on immobilized pH gradient (IPG) gels in the first dimension, followed by reversed-phase chromatography in the second dimension, and subsequent tandem mass spectrometry analysis. The traditional approach to this mixture problem employs strong-cation-exchange (SCX) chromatography in the first dimension. Here, we present a direct comparison of these two first-dimensional techniques using complex protein samples derived from the testis of Rattus norvegicus. It was found that the use of immobilized pH gradients (narrow range pH 3.5-4.5) for peptide separation in the first dimension yielded 13% more protein identifications than the optimized off-line SCX approach (employing the entire pI range of the sample). In addition, the IPG technique allows for a much more efficient use on mass spectrometer analysis time. Separation of a tryptic digest derived from a rat testis sample on a narrow range pH gradient (over the 3.5-4.5 pH range) yielded 7626 and 2750 peptides and proteins, respectively. Peptide and protein identification was performed with high confidence using SEQUEST in combination with a data filtering program employing pI and statistical based functions to remove false-positives from the data.     

Comparison of protein and peptide prefractionation methods for the shotgun proteomic analysis of Synechocystis sp. PCC 6803

Proteome analysis by gel-free "shotgun" proteomics relies on the simplification of a peptide mixture before it is analyzed in a mass spectrometer. While separation on a reverse-phase (RP) liquid chromatographic column is widely employed, a variety of other methods have been used to fractionate both proteins and peptides before this step. We compared six different protein and peptide fractionation workflows, using Synechocystis sp. PCC 6803, a useful model cyanobacterium for potential exploitation to improve its production of hydrogen and other secondary metabolites. Pre-digestion protein separation was performed by strip-based isoelectric focusing, one-dimensional polyacrylamide gel electrophoresis, or weak anion exchange chromatography, while pre-RP peptide separation was accomplished by isoelectric focusing (IEF) or strong cation exchange chromatography. Peptides were identified using electrospray ionization quadrupole time of flight-tandem mass spectrometry. Mass spectrometry (MS) and tandem mass spectra were analyzed using ProID software employing both a single organism database and the entire NCBI non-redundant database, and a total of 776 proteins were identified using a stringent set of selection criteria. Method comparisons were made on the basis of the results obtained (number and types of proteins identified), as well as ease of use and other practical aspects. IEF-IEF protein and peptide fractionation prior to RP gave the best overall performance.     

Systematic comparison of a two-dimensional ion trap and a three-dimensional ion trap mass spectrometer in proteomics

The utility and advantages of the recently introduced two-dimensional quadrupole ion trap mass spectrometer in proteomics over the traditional three-dimensional ion trap mass spectrometer have not been systematically characterized. Here we rigorously compared the performance of these two platforms by using over 100,000 tandem mass spectra acquired with identical complex peptide mixtures and acquisition parameters. Specifically we compared four factors that are critical for a successful proteomic study: 1) the number of proteins identified, 2) sequence coverage or the number of peptides identified for every protein, 3) the data base matching SEQUEST X(corr) and S(p) score, and 4) the quality of the fragment ion series of peptides. We found a 4-6-fold increase in the number of peptides and proteins identified on the two-dimensional ion trap mass spectrometer as a direct result of improvement in all the other parameters examined. Interestingly more than 70% of the doubly and triply charged peptides, but not the singly charged peptides, showed better quality of fragmentation spectra on the two-dimensional ion trap. These results highlight specific advantages of the two-dimensional ion trap over the conventional three-dimensional ion traps for protein identification in proteomic experiments.     

Analytical and micropreparative peptide mapping by high performance liquid chromatography/electrospray mass spectrometry of proteins purified by gel electrophoresis.

We report the use of microbore reverse-phase high performance liquid chromatography connected on-line to an electrospray mass spectrometer for the separation/detection of peptides derived by proteolytic digestion of proteins separated by polyacrylamide gel electrophoresis. A small fraction (typically 10% of the total) of the peptides eluting from the column was diverted through a flow-splitting device into the ion source of the mass spectrometer, whereas the majority of the peptide samples was collected for further analyses. We demonstrate the feasibility of obtaining reproducible peptide maps from submicrogram amounts of protein applied to the gel and good correlation of the signal detected by the mass spectrometer with peptide detection by UV absorbance. Furthermore, independently verifiable peptide masses were determined from subpicomole amounts of peptides directed into the mass spectrometer. The method was used to analyze the 265-kDa and the 280-kDa isoforms of the enzyme acetyl-CoA carboxylase isolated from rat liver. The results provide compelling evidence that the two enzyme isoforms are translation products of different genes and suggest that these approaches may be of general utility in the definitive comparison of protein isoforms. We furthermore illustrate that knowledge of peptide masses as determined by this technique provides a major advantage for error-free data interpretation in chemical high-sensitivity peptide sequence analysis.     

Faster SEQUEST searching for peptide identification from tandem mass spectra

Computational analysis of mass spectra remains the bottleneck in many proteomics experiments. SEQUEST was one of the earliest software packages to identify peptides from mass spectra by searching a database of known peptides. Though still popular, SEQUEST performs slowly. Crux and TurboSEQUEST have successfully sped up SEQUEST by adding a precomputed index to the search, but the demand for ever-faster peptide identification software continues to grow. Tide, introduced here, is a software program that implements the SEQUEST algorithm for peptide identification and that achieves a dramatic speedup over Crux and SEQUEST. The optimization strategies detailed here employ a combination of algorithmic and software engineering techniques to achieve speeds up to 170 times faster than a recent version of SEQUEST that uses indexing. For example, on a single Xeon CPU, Tide searches 10,000 spectra against a tryptic database of 27,499 Caenorhabditis elegans proteins at a rate of 1550 spectra per second, which compares favorably with a rate of 8.8 spectra per second for a recent version of SEQUEST with index running on the same hardware.     

Application of peptide LC retention time information in a discriminant function for peptide identification by tandem mass spectrometry

We describe the application of a peptide retention time reversed phase liquid chromatography (RPLC) prediction model previously reported (Petritis et al. Anal. Chem. 2003, 75, 1039) for improved peptide identification. The model uses peptide sequence information to generate a theoretical (predicted) elution time that can be compared with the observed elution time. Using data from a set of known proteins, the retention time parameter was incorporated into a discriminant function for use with tandem mass spectrometry (MS/MS) data analyzed with the peptide/protein identification program SEQUEST. For singly charged ions, the number of confident identifications increased by 12% when the elution time metric is included compared to when mass spectral data is the sole source of information in the context of a Drosophila melanogaster database. A 3-4% improvement was obtained for doubly and triply charged ions for the same biological system. Application to the larger Rattus norvegicus (rat) and human proteome databases resulted in an 8-9% overall increase in the number of confident identifications, when both the discriminant function and elution time are used. The effect of adding "runner-up" hits (peptide matches that are not the highest scoring for a spectra) from SEQUEST is also explored, and we find that the number of confident identifications is further increased by 1% when these hits are also considered. Finally, application of the discriminant functions derived in this work with approximately 2.2 million spectra from over three hundred LC-MS/MS analyses of peptides from human plasma protein resulted in a 16% increase in confident peptide identifications (9022 vs 7779) using elution time information. Further improvements from the use of elution time information can be expected as both the experimental control of elution time reproducibility and the predictive capability are improved.     

Matrix-assisted laser desorption/ionization-tandem mass spectrometry with high resolution and sensitivity for identification and characterization of proteins

Although peptide mass fingerprinting is currently the method of choice to identify proteins, the number of proteins available in databases is increasing constantly, and hence, the advantage of having sequence data on a selected peptide, in order to increase the effectiveness of database searching, is more crucial. Until recently, the ability to identify proteins based on the peptide sequence was essentially limited to the use of electrospray ionization tandem mass spectrometry (MS) methods. The recent development of new instruments with matrix-assisted laser desorption/ionization (MALDI) sources and true tandem mass spectrometry (MS/MS) capabilities creates the capacity to obtain high quality tandem mass spectra of peptides. In this work, using the new high resolution tandem time of flight MALDI-(TOF/TOF) mass spectrometer from Applied Biosystems, examples of successful identification and characterization of bovine heart proteins (SWISS-PROT entries: P02192, Q9XSC6, P13620) separated by two-dimensional electrophoresis and blotted onto polyvinylidene difluoride membrane are described. Tryptic protein digests were analyzed by MALDI-TOF to identify peptide masses afterward used for MS/MS. Subsequent high energy MALDI-TOF/TOF collision-induced dissociation spectra were recorded on selected ions. All data, both MS and MS/MS, were recorded on the same instrument. Tandem mass spectra were submitted to database searching using MS-Tag or were manually de novo sequenced. An interesting modification of a tryptophan residue, a "double oxidation", came to light during these analyses.     

The identification of protein-protein interactions of the nuclear pore complex of Saccharomyces cerevisiae using high throughput matrix-assisted laser desorption ionization time-of-flight tandem mass spectrometry

Mass spectrometry has become the technology of choice for detailed identification of proteins in complex mixtures. Although electrophoretic separation, proteolytic digestion, mass spectrometric analysis of unseparated digests, and database searching have become standard methods in widespread use, peptide sequence information obtained by collision-induced dissociation and tandem mass spectrometry is required to establish the most comprehensive and reliable results. Most tandem mass spectrometers in current use employ electrospray ionization. In this work a novel tandem mass spectrometer employing matrix-assisted laser desorption ionization-time-of-flight/time-of-flight operating at 200 Hz has been used to identify proteins interacting with known nucleoporins in the nuclear pore complex of Saccharomyces cerevisiae. Proteins interacting with recombinant proteins as bait were purified from yeast extracts and then separated by one-dimensional SDS-PAGE. Although peptide mass fingerprinting is sometimes sufficient to identify proteins, this study shows the importance of employing tandem mass spectrometry for identifying proteins in mixtures or as covalently modified forms. The rules for incorporating these features into MS-Tag are presented. In addition to providing an evaluation of the sensitivity and overall quality of collision-induced dissociation spectra obtained, standard conditions for ionization and fragmentation have been selected that would allow automatic data collection and analysis, without the need to adjust parameters in a sample-specific fashion. Other considerations essential for successful high throughput protein analysis are discussed.     

Molecular constituents of the postsynaptic density fraction revealed by proteomic analysis using multidimensional liquid chromatography-tandem mass spectrometry

Protein constituents of the postsynaptic density (PSD) fraction were analysed using an integrated liquid chromatography (LC)-based protein identification system, which was constructed by coupling microscale two-dimensional liquid chromatography (2DLC) with electrospray ionization (ESI) tandem mass spectrometry (MS/MS) and an automated data analysis system. The PSD fraction prepared from rat forebrain was solubilized in 6 m guanidium hydrochloride, and the proteins were digested with trypsin after S-carbamoylmethylation under reducing conditions. The tryptic peptide mixture was then analysed with the 2DLC-MS/MS system in a data-dependent mode, and the resultant spectral data were automatically processed to search a genome sequence database for protein identification. In triplicate analyses, the system allowed assignments of 5264 peptides, which could finally be attributed to 492 proteins. The PSD contained various proteins involved in signalling transduction, including receptors, ion channel proteins, protein kinases and phosphatases, G-protein and related proteins, scaffold proteins, and adaptor proteins. Structural proteins, including membrane proteins involved in cell adhesion and cell-cell interaction, proteins involved in endocytosis, motor proteins, and cytoskeletal proteins were also abundant. These results provide basic data on a major protein set associated with the PSD and a basis for future functional studies of this important neural machinery.     

AMASS: software for automatically validating the quality of MS/MS spectrum from SEQUEST results

Time-consuming and experience-dependent manual validations of tandem mass spectra are usually applied to SEQUEST results. This inefficient method has become a significant bottleneck for MS/MS data processing. Here we introduce a program AMASS (advanced mass spectrum screener), which can filter the tandem mass spectra of SEQUEST results by measuring the match percentage of high-abundant ions and the continuity of matched fragment ions in b, y series. Compared with Xcorr and DeltaCn filter, AMASS can increase the number of positives and reduce the number of negatives in 22 datasets generated from 18 known protein mixtures. It effectively removed most noisy spectra, false interpretations, and about half of poor fragmentation spectra, and AMASS can work synergistically with Rscore filter. We believe the use of AMASS and Rscore can result in a more accurate identification of peptide MS/MS spectra and reduce the time and energy for manual validation.