Evaluating Peptide Mass Fingerprinting-based Protein Identification

Identification of proteins by mass spectrometry (MS) is an essential step in pro- teomic studies and is typically accomplished by either peptide mass fingerprinting (PMF) or amino acid sequencing of the peptide. Although sequence information from MS/MS analysis can be used to validate PMF-based protein identification, it may not be practical when analyzing a large number of proteins and when high- throughput MS/MS instrumentation is not readily available. At present, a vast majority of proteomic studies employ PMF. However, there are huge disparities in criteria used to identify proteins using PMF. Therefore, to reduce incorrect protein identification using PMF, and also to increase confidence in PMF-based protein identification without accompanying MS/MS analysis, definitive guiding principles are essential. To this end, we propose a value-based scoring system that provides guidance on evaluating when PMF-based protein identification can be deemed sufficient without accompanying amino acid sequence data from MS/MS analysis.     

Evaluating Peptide Mass Fingerprinting-based Protein Identification

Identification of proteins by mass spectrometry (MS) is an essential step in pro- teomic studies and is typically accomplished by either peptide mass fingerprinting (PMF) or amino acid sequencing of the peptide. Although sequence information from MS/MS analysis can be used to validate PMF-based protein identification, it may not be practical when analyzing a large number of proteins and when high- throughput MS/MS instrumentation is not readily available. At present, a vast majority of proteomic studies employ PMF. However, there are huge disparities in criteria used to identify proteins using PMF. Therefore, to reduce incorrect protein identification using PMF, and also to increase confidence in PMF-based protein identification without accompanying MS/MS analysis, definitive guiding principles are essential. To this end, we propose a value-based scoring system that provides guidance on evaluating when PMF-based protein identification can be deemed sufficient without accompanying amino acid sequence data from MS/MS analysis.     

Comparison of search engine contributions in protein mass fingerprinting for protein identification

Peptide mass fingerprinting (PMF) is a valuable method for rapid and high-throughput protein identification using the proteomics approach. Automated search engines, such as Ms-Fit, Mascot, ProFound, and Peptldent, have facilitated protein identification through PMF. The potential to obtain a true MS protein identification result depends on the choice of algorithm as well as experimental factors that influence the information content in MS data. When mass spectral data are incomplete and/or have low mass accuracy, the “number of matches” approach may be inadequate for a useful identification. Several studies have evaluated factors influencing the quality of mass spectrometry (MS) experiments. Missed cleavages, posttranslational modifications of peptides and contaminants (e.g., keratin) are important factors that can affect the results of MS analyses by influencing the identification process as well as the quality of the MS spectra. We compared search engines frequently used to identify proteins fromHomo sapiens andHalobacterium salinarum by evaluating factors, including data-based and mass tolerance to develop an improved search engine for PMF. This study may provide information to help develop a more effective algorithm for protein identification in each species through PMF.     

A systematical analysis of tryptic peptide identification with reverse phase liquid chromatography and electrospray ion trap mass spectrometry

In this study we systematically analyzed the elution condition of tryptic peptides and the characteristics of identified peptides in reverse phase liquid chromatography and electrospray tandem mass spectrometry (RPLC-MS/MS) analysis. Following protein digestion with trypsin, the peptide mixture was analyzed by on-line RPLC-MS/MS. Bovine serum albumin (BSA) was used to optimize acetonitrile (ACN) elution gradient for tryptic peptides, and Cytochrome C was used to retest the gradient and the sensitivity of LC-MS/MS. The characteristics of identified peptides were also analyzed. In our experiments, the suitable ACN gradient is 5% to 30% for tryptic peptide elution and the sensitivity of LC-MS/MS is 50 fmol.Analysis of the tryptic peptides demonstrated that longer (more than 10 amino acids) and multi-charge state ( 2, 3) peptides are likely to be identified, and the hydropathicity of the peptides might not be related to whether it is more likely to be identified or not. The number of identified peptides for a protein might be used to estimate its loading amount under the same sample background. Moreover, in this study the identified peptides present three types of redundancy, namely identification, charge, and sequence redundancy, which may repress low abundance protein identification.     

基于质谱和生物信息学分析的小菜蛾蛋白质鉴定

本研究以非模式昆虫小菜蛾Plutella xylostella为材料, 对比2, 3, 4龄幼虫的蛋白质组双向电泳图谱, 得到24个蛋白质差异点, 从中选取了编号为1111的差异表达蛋白质点进行质谱鉴定和生物信息学分析. 采用胶内酶解的多肽进行MALDI-TOF/TOF分析, 获得该点的肽质量指纹图谱（PMF）及串联质谱（MS/MS）图谱。将获得的PMF分别用MASCOT和ProFound等常用软件在NCBInr的Metazoa蛋白质数据库进行搜索, 匹配结果不理想. 进一步用PMF+MS/MS谱图搜索NCBInr的Metazoa蛋白质数据库, 以及小菜蛾EST数据库。 在NCBInr库中匹配结果为拟暗果蝇Drosophila pseudoobscura中的一种假定蛋白GA18218-PA, 而用EST库搜索的结果为家蚕Bombyx mori的ATP合酶的亚基。为验证搜索结果, 将该蛋白质点进行磺基异硫氰酸苯酯（SPITC）化学衍生后de novo测序, 最后确认该点可能为ATP合酶的一个亚基。最后着重讨论了蛋白质的质谱鉴定与生物信息学分析的联合使用, 希望据此选择出最适合于非模式昆虫蛋白质组学鉴定的方法。     

利用EST序列构建Mascot本地数据库

对蛋白质质谱数据进行数据库比对和鉴定是蛋白质组学研究技术中的一个重要步骤。由于公共数据库蛋白质数据信息不全,有些蛋白质质谱数据无法得到有效的鉴定。而利用相关物种的EST序列构建专门的质谱数据库则可以增加鉴定未知蛋白的几率。本文介绍了利用EST序列构建Mascot本地数据库的具体方法和步骤,扩展了Mascot检索引擎对蛋白质质谱数据的鉴定范围,从数据库层面提高了对未知蛋白的鉴别几率,为蛋白质组学研究提供了一种较为实用的生物信息学分析技术。     

Screening for transglutaminase-catalyzed modifications by peptide mass finger printing using multipoint recalibration on recognized peaks for high mass accuracy.

Detection of posttranslational modifications is expected to be one of the major future experimental challenges for proteomics. We describe herein a mass spectrometric procedure to screen for protein modifications by peptide mass fingerprinting that is based on post-data acquisition improvement of the mass accuracy by exporting the peptide mass values into analytical software for multipoint recalibration on recognized peaks. Subsequently, the calibrated peak mass data set is used in searching for modified peptides, i.e., peptides possessing specific mass deviations. In order to identify the location of Lys- and Gln-residues available for transglutaminase-catalyzed isopeptide bond formation, mammalian small heat shock proteins (sHsps) were screened for labeling with the two hexapeptide probes GQDPVR and GNDPVK in presence of transglutaminase. Peptide modification due to cross-linking of the GQDPVR hexa-peptide probe was detected for C-terminal Lys residues. Novel transglutaminase-susceptible Gln sites were identified in two sHsps (Q31/Q27 in Hsp20 and HspB2, respectively), by cross-linking of the GNDPVK hexapeptide probe. Deamidation of specific Gln residues was also detected, as well an isopeptide derived from intramolecular Gln-Lys isopeptide bond formation. We conclude that peptide mass fingerprinting can be an efficient way of screening for various posttranslational modifications. Basically any instrumentation for MALDI mass spectrometry can be used, provided that post-data acquisition recalibration is applied.     

正常精子和圆头精子差异表达蛋白的分离与鉴定

圆头精子症是一种表现为顶体缺失的男性不育症.为了研究正常精子和圆头精子的蛋白质组成差异,用固相pH梯度双向凝胶电泳和质谱分析等蛋白质组学方法,分离了30份正常和3份圆头精子标本的蛋白质.对其中16个在正常精子中有高丰度表达而在圆头精子中缺失,和1个在圆头精子中表达明显下调的蛋白质点,以及在圆头精子中存在而在正常精子中缺失的蛋白质簇W和点X,进行了肽质指纹分析和蛋白质鉴定,获得8个点的肽质量指纹图,经MS-Fit软件搜索SWISS-PROT数据库来鉴定其身分.发现其中3个点与高尔基体相关、2个点与蛋白酶体相关、2个点为锌指蛋白,对其功能和与圆头精子形成的可能关系进行了初步探讨.     

Problems Associated with the Identification of Proteins in Homologous Families: The Wool Keratin Family as a Case Study

The keratin proteins from wool can be divided into two classes: the intermediate filament proteins (IFPs) and the matrix proteins. Using peptide mass spectral fingerprinting it was possible to match spots to the known theoretical sequences of some IFPs in web-based databases, as enzyme digestion generated sufficient numbers of peptides from each spot to achieve this. In contrast, it was more difficult to obtain good matches for some of the lower molecular weight matrix proteins. Relatively few peaks were generated from tryptic digests of high-sulfur proteins because of their lower molecular weight and the absence of basic residues in the first two-thirds of the sequence. Their high sequence homology also means that generally only a few of these peptides could be considered to be unique identifiers for each protein. Nevertheless, it was still possible to uniquely identify some of these proteins, while the presence of two peptides in the matrix-assisted laser desorption/ionization time-of-flight mass spectrum allowed classification of other protein spots as being members of this family. Only one major peptide peak was generated by the high-glycine tyrosine proteins (HGTPs) and there were relatively few sequences available in web-based databases, limiting their identification to one HGTP family.     

一种适用于质谱分析的简化胶内酶解方法

在常规方法的基础上,设计了一种适于质谱分析的简化胶内酶解方法。改进的步骤包括:(1)通过加大洗涤所用超纯水量、延长涡混时间来强化凝胶洗涤的环节;(2)加入酸化处理来提高胰蛋白酶的活性;(3)在预酶解时不加CaCl_2,减少了酶的自切作用;(4)省略了蛋白质样品脱盐、脱SDS的步骤;(5)直接吸取酶解液进行质谱分析。系统比较该简化酶解法和最新报道的一种酶解方法的质谱鉴定效果,简化法能有效减少酶解后肽段的损失,增加质谱数据库搜索的信息量,得到更可靠的蛋白质鉴定结果。     

大鼠不同发育时期胰腺相关蛋白的差异表达

探讨大鼠胰腺不同发育时期相关蛋白的差异表达,应用显微技术分离了大鼠孕15.5天,孕18.5天胚胎胰腺和新生鼠及成年鼠的胰腺,提取其蛋白质后,用固相pH梯度双向聚丙烯酰胺凝胶电泳和质谱分析等蛋白质组学方法,得到了4个不同发育时期的蛋白质表达谱.对其中的6个在孕18.5天胚胎胰腺中有高丰度表达,而在成年鼠胰腺中缺失的蛋白质点,4个在成年胰腺中特异表达的蛋白质点, 8个在成年胰腺中表达明显下调的蛋白质点和1个在成年中表达上调的点,进行了肽质量指纹分析和蛋白质鉴定,共获得18个点的肽质量指纹图.经BIOWORK等软件搜索大鼠非冗余蛋白质数据库来鉴定其身份,发现其中7个点为大鼠甲胎蛋白（AFP）、5个点为胰脂酶相关蛋白1前体、1个点为微管蛋白β、2个点为蛋白二硫异构酶、1个为FLN29基因产物的类似物、1个为胰蛋白酶V-A前体、1个为过氧化物氧化还原酶4.其中AFP为特异表达于大鼠胚胎期及新生期胰腺的蛋白质,在孕18.5天的胰腺中表达量最高,在成年胰腺中极低表达.对它们的功能和与胚胎胰腺代谢调节功能完善过程的可能关系进行了初步探讨.     

Immunoaffinity techniques coupled to mass spectrometry for the analysis of human peptide hormones: advances and applications

Introduction: The accurate and comprehensive determination of peptide hormones from biological fluids has represented a considerable challenge to analytical chemists for decades. Besides long-established bioanalytical ligand binding assays (or ELISA, RIA, etc.), more and more mass spectrometry-based methods have been developed recently for purposes commonly referred to as targeted proteomics. Eventually the combination of both, analyte extraction by immunoaffinity and subsequent detection by mass spectrometry, has shown to synergistically enhance the test methods’ performance characteristics.

Areas covered: The review provides an overview about the actual state of existing methods and applications concerning the analysis of endogenous peptide hormones. Here, special focus is on recent developments considering the extraction procedures with immobilized antibodies, the subsequent separation of target analytes, and their detection by mass spectrometry.

Expert commentary: Key aspects of procedures aiming at the detection and/or quantification of peptidic analytes in biological matrices have experienced considerable improvements in the last decade, particularly in terms of the assays’ sensitivity, the option of multiplexing target compounds, automatization, and high throughput operation. Despite these advances and progress as expected to be seen in the near future, immunoaffinity purification coupled to mass spectrometry is not yet a standard procedure in routine analysis compared to ELISA/RIA.     

Mass processing--an improved technique for protein identification with mass spectrometry data.

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry analysis following tryptic digestion of polyacrylamide gel pieces is a common technique used to identify proteins. This approach is rapid, sensitive, and user friendly, and is becoming widely available to scientists in a variety of biological fields. Here we introduce a simple and effective strategy called "mass processing" where the list of masses generated from a mass spectrometer undergoes two stages of data reduction before identification. Mass processing improves the ability to identify in-gel tryptic-digested proteins by reducing the number of nonsample masses submitted to protein identification database search engines. Our results demonstrate that mass processing improves the statistical score and rank of putative protein identifications, especially with low-quantity samples, thus increasing the ability to confidently identify proteins with mass spectrometry data.     

Selection of the peptide mass tolerance value for protein identification with peptide mass fingerprinting

Peptide mass fingerprinting (PMF) is widely used for protein identification while studying proteome via time-of-flight mass spectrometer or via 1D or 2D electrophoresis. Peptide mass tolerance indicating the fit of theoretical peptide mass to an experimental one signifcantly influences protein identification. The role of peptide mass tolerance could be estimated by counting the number of correctly identified proteins for the reference set of mass spectra. The reference set of 400 Ultraflex (Bruker Daltonics, Germany) protein mass spectra was obtained for liver microsomes slices hydrolyzed via 1D gel electrophoresis. Using a Mascot server for protein identification, the peptide mass tolerance value varied within 0.02–0.40 Da with a step of 0.01 Da. The number of identified proteins changed up to 10 times depending on the tolerance. The maximal number of identified proteins was reported for the tolerance value of 0.15 Da (120 ppm) known to be 1.5–2-fold higher than the recommended values for such a type of mass spectrometer. The software program PMFScan was developed to obtain the dependence between the number of identified proteins and the tolerance values.     

Database search engines and target database features impinge upon the identification of post-translationally cis-spliced peptides in HLA class I immunopeptidomes

Unconventional epitopes presented by HLA class I complexes are emerging targets for T cell targeted immunotherapies. Their identification by mass spectrometry (MS) required development of novel methods to cope with the large number of theoretical candidates. Methods to identify post-translationally spliced peptides led to a broad range of outcomes. We here investigated the impact of three common database search engines – that is, Mascot, Mascot+Percolator, and PEAKS DB – as final identification step, as well as the features of target database on the ability to correctly identify non-spliced and cis-spliced peptides. We used ground truth datasets measured by MS to benchmark methods’ performance and extended the analysis to HLA class I immunopeptidomes. PEAKS DB showed better precision and recall of cis-spliced peptides and larger number of identified peptides in HLA class I immunopeptidomes than the other search engine strategies. The better performance of PEAKS DB appears to result from better discrimination between target and decoy hits and hence a more robust FDR estimation, and seems independent to peptide and spectrum features here investigated.     

Ga2O3 photocatalyzed on-line tagging of cysteine to facilitate peptide mass fingerprinting

β-Ga(2)O(3) is a wide-band-gap semiconductor having strong oxidation ability under light irradiation. Herein, the steel target plates modified with β-Ga(2)O(3) nanoparticles have been developed to carry out in-source photo-catalytic oxidative reactions for online peptide tagging during laser desorption/ionization mass spectrometry (LDI-MS) analysis. Under UV laser irradiation, β-Ga(2)O(3) can catalyze the photo-oxidation of 2-methoxyhydroquinone added to a sample mixture to 2-methoxy benzoquinone that can further react with the thiol groups of cysteine residues by Michael addition reaction. The tagging process leads to appearance of pairs of peaks with an m/z shift of 138.1Th. This online labelling strategy is demonstrated to be sensitive and efficient with a detection-limit at femtomole level. Using the strategy, the information on cysteine content in peptides can be obtained together with peptide mass, therefore constraining the database searching for an advanced identification of cysteine-containing proteins from protein mixtures. The current peptide online tagging method can be important for specific analysis of cysteine-containing proteins especially the low-abundant ones that cannot be completely isolated from other high-abundant non-cysteine-proteins.     

Current trends in computational inference from mass spectrometry-based proteomics

Mass spectrometry offers a high-throughput approach to quantifying the proteome associated with a biological sample and hence has become the primary approach of proteomic analyses. Computation is tightly coupled to this advanced technological platform as a required component of not only peptide and protein identification, but quantification and functional inference, such as protein modifications and interactions. Proteomics faces several key computational challenges such as identification of proteins and peptides from tandem mass spectra as well as their quantitation. In addition, the application of proteomics to systems biology requires understanding the functional proteome, including how the dynamics of the cell change in response to protein modifications and complex interactions between biomolecules. This review presents an overview of recently developed methods and their impact on these core computational challenges currently facing proteomics.     

Using annotated peptide mass spectrum libraries for protein identification

A system for creating a library of tandem mass spectra annotated with corresponding peptide sequences was described. This system was based on the annotated spectra currently available in the Global Proteome Machine Database (GPMDB). The library spectra were created by averaging together spectra that were annotated with the same peptide sequence, sequence modifications, and parent ion charge. The library was constructed so that experimental peptide tandem mass spectra could be compared with those in the library, resulting in a peptide sequence identification based on scoring the similarity of the experimental spectrum with the contents of the library. A software implementation that performs this type of library search was constructed and successfully used to obtain sequence identifications. The annotated tandem mass spectrum libraries for the Homo sapiens, Mus musculus, and Saccharomyces cerevisiae proteomes and search software were made available for download and use by other groups.     

Selection of the peptide mass tolerance value for the protein identification with peptide mass fingerprinting

Peptide mass-fingerprint is widely used for protein identification while studying proteome with the use of 1D or 2D electrophoresis. Peptide mass tolerance indicates the fit of theoretical peptide mass with the experimental measurements, and choice of this parameter sufficiently influences the protein identification. The role of peptide mass tolerance was estimated by counting the number of identified proteins for the reference set of mass-spectra. The reference set of 400 Ultraflex (Bruker Daltonics, Germany) mass-spectra was obtained for the slices of 1D gel of liver microsomes. Using Mascot server for protein identification, the peptide mass tolerance value was varied in the range from 0.02 to 0.40 Da with a step 0.01 Da. Depending on the tolerance the number of identified protein changes up to 10 times. Maximal number of identified proteins was reported for the tolerance value of 0.15 Da (120 ppm), which is 1.5 - 2 times higher than the recommended values for such type of mass-spectrometers. The software program PMFScan was developed to obtain the dependence of number of identified proteins of the tolerance values.