Identification of protein fragments as pattern features in MALDI-MS analyses of serum

The use of matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) to acquire spectral profiles has become a common approach to detect proteomic biomarkers of disease. MALDI-MS signals may represent both intact proteins as well as proteolysis products. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis can tentatively identify the corresponding proteins Here, we describe the application of a data analysis utility called FragMint, which combines MALDI-MS spectral data with LC-MS/MS based protein identifications to generate candidate protein fragments consistent with both types of data. This approach was used to identify protein fragments corresponding to spectral signals in MALDI-MS analyses of unfractionated human serum. The serum also was analyzed by one-dimensional SDS-PAGE and bands corresponding to the MALDI-MS signal masses were excised and subjected to in-gel digestion and LC-MS/MS analysis. Database searches mapped all of the identified peptides to abundant blood proteins larger than the observed MALDI-MS signals. FragMint identified fragments of these proteins that contained the MS/MS identified sequences and were consistent with the observed MALDI-MS signals. This approach should be generally applicable to identify protein species corresponding to MALDI-MS signals.     

Tandem mass spectrometry for the detection of plant pathogenic fungi and the effects of database composition on protein inferences

LC-MS/MS has demonstrated potential for detecting plant pathogens. Unlike PCR or ELISA, LC-MS/MS does not require pathogen-specific reagents for the detection of pathogen-specific proteins and peptides. However, the MS/MS approach we and others have explored does require a protein sequence reference database and database-search software to interpret tandem mass spectra. To evaluate the limitations of database composition on pathogen identification, we analyzed proteins from cultured Ustilago maydis, Phytophthora sojae, Fusarium graminearum, and Rhizoctonia solani by LC-MS/MS. When the search database did not contain sequences for a target pathogen, or contained sequences to related pathogens, target pathogen spectra were reliably matched to protein sequences from nontarget organisms, giving an illusion that proteins from nontarget organisms were identified. Our analysis demonstrates that when database-search software is used as part of the identification process, a paradox exists whereby additional sequences needed to detect a wide variety of possible organisms may lead to more cross-species protein matches and misidentification of pathogens.     

Comparison of strong cation exchange and SDS-PAGE fractionation for analysis of multiprotein complexes

Affinity purification of protein complexes followed by identification using liquid chromatography/mass spectrometry (LC-MS/MS) is a robust method to study the fundamental process of protein interaction. Although affinity isolation reduces the complexity of the sample, fractionation prior to LC-MS/MS analysis is still necessary to maximize protein coverage. In this study, we compared the protein coverage obtained via LC-MS/MS analysis of protein complexes prefractionated using two commonly employed methods, SDS-PAGE and strong cation exchange chromatography (SCX). The two complexes analyzed focused on the nuclear proteins Bmi-1 and GATA3 that were expressed within the cells at low and high levels, respectively. Prefractionation of the complexes at the peptide level using SCX consistently resulted in the identification of approximately 3-fold more proteins compared to separation at the protein level using SDS-PAGE. The increase in the number of identified proteins was especially pronounced for the Bmi-1 complex, where the target protein was expressed at a low level. The data show that prefractionation of affinity isolated protein complexes using SCX prior to LC-MS/MS analysis significantly increases the number of identified proteins and individual protein coverage, particularly for target proteins expressed at low levels.     

Proteomic analysis of eccrine sweat: implications for the discovery of schizophrenia biomarker proteins

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) and multiple reaction monitoring mass spectrometry (MRM-MS) proteomics analyses were performed on eccrine sweat of healthy controls, and the results were compared with those from individuals diagnosed with schizophrenia (SZ). This is the first large scale study of the sweat proteome. First, we performed LC-MS/MS on pooled SZ samples and pooled control samples for global proteomics analysis. Results revealed a high abundance of diverse proteins and peptides in eccrine sweat. Most of the proteins identified from sweat samples were found to be different than the most abundant proteins from serum, which indicates that eccrine sweat is not simply a plasma transudate and may thereby be a source of unique disease-associated biomolecules. A second independent set of patient and control sweat samples were analyzed by LC-MS/MS and spectral counting to determine qualitative protein differential abundances between the control and disease groups. Differential abundances of selected proteins, initially determined by spectral counting, were verified by MRM-MS analyses. Seventeen proteins showed a differential abundance of approximately 2-fold or greater between the SZ pooled sample and the control pooled sample. This study demonstrates the utility of LC-MS/MS and MRM-MS as a viable strategy for the discovery and verification of potential sweat protein disease biomarkers.     

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.     

Separation and identification of soybean leaf proteins by two-dimensional gel electrophoresis and mass spectrometry

To establish a proteomic reference map for soybean leaves, we separated and identified leaf proteins using two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) and mass spectrometry (MS). Tryptic digests of 260 spots were subjected to peptide mass fingerprinting (PMF) by matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) MS. Fifty-three of these protein spots were identified by searching NCBInr and SwissProt databases using the Mascot search engine. Sixty-seven spots that were not identified by MALDI-TOF-MS analysis were analyzed with liquid chromatography tandem mass spectrometry (LC-MS/MS), and 66 of these spots were identified by searching against the NCBInr, SwissProt and expressed sequence tag (EST) databases. We have identified a total of 71 unique proteins. The majority of the identified leaf proteins are involved in energy metabolism. The results indicate that 2D-PAGE, combined with MALDI-TOF-MS and LC-MS/MS, is a sensitive and powerful technique for separation and identification of soybean leaf proteins. A summary of the identified proteins and their putative functions is discussed.     

Ampicillin/penicillin-binding protein interactions as a model drug-target system to optimize affinity pull-down and mass spectrometric strategies for target and pathway identification

The identification and validation of the targets of active compounds identified in cell-based assays is an important step in preclinical drug development. New analytical approaches that combine drug affinity pull-down assays with mass spectrometry (MS) could lead to the identification of new targets and druggable pathways. In this work, we investigate a drug-target system consisting of ampicillin- and penicillin-binding proteins (PBPs) to evaluate and compare different amino-reactive resins for the immobilization of the affinity compound and mass spectrometric methods to identify proteins from drug affinity pull-down assays. First, ampicillin was immobilized onto various amino-reactive resins, which were compared in the ampicillin-PBP model with respect to their nonspecific binding of proteins from an Escherichia coli membrane extract. Dynal M-270 magnetic beads were chosen to further study the system as a model for capturing and identifying the targets of ampicillin, PBPs that were specifically and covalently bound to the immobilized ampicillin. The PBPs were identified, after in situ digestion of proteins bound to ampicillin directly on the beads, by using either one-dimensional (1-D) or two-dimensional (2-D) liquid chromatography (LC) separation techniques followed by tandem mass spectrometry (MS/MS) analysis. Alternatively, an elution with N-lauroylsarcosine (sarcosyl) from the ampicillin beads followed by in situ digestion and 2-D LC-MS/MS analysis identified proteins potentially interacting noncovalently with the PBPs or the ampicillin. The in situ approach required only little time, resources, and sample for the analysis. The combination of drug affinity pull-down assays with in situ digestion and 2-D LC-MS/MS analysis is a useful tool in obtaining complex information about a primary drug target as well as its protein interactors.     

Identification of phosphorylation sites on phosducin-like protein by QTOF mass spectrometry.

Post-translational modifications are used by cells to control the functions of proteins. Phosducin-like protein (PhLP) is a regulator of G-protein signaling that is post-translationally modified via phosphorylation. Phosphorylation of PhLP initiates its degradation by the 26S proteasome in serum-stimulated cells. In this report, we show that PhLP is phosphorylated in serum-stimulated Chinese hamster ovary (CHO) cells. Through the use of tandem mass spectrometry (MS/MS), the specific amino acids phosphorylated can be identified. A PhLP-myc-His construct was purified and phosphorylated by serum-stimulated CHO extract. The resulting protein was digested with trypsin and the peptides were identified by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Automated collison-induced dissociation data acquisition was compared with LC-MS/MS of manually chosen parents. In general, LC-MS/MS is superior for parent ions chosen manually, with the notable exception that automated fragmentation employs dynamic collision energy, which can result in higher quality collison-induced dissociation. Using the LC-MS/MS methods, four phosphorylation sites on PhLP were positively identified.     

Tube-gel digestion: a novel proteomic approach for high throughput analysis of membrane proteins

This study describes a new protein digestion protocol in which a variety of detergents can be used to solubilize membrane proteins and facilitate trypsin digestion with higher efficiency. In this protocol, proteins are dissolved in solutions containing various detergents and directly incorporated into a polyacrylamide gel matrix without electrophoresis. Detergents are subsequently eliminated from the gel matrix while proteins are still immobilized in the gel matrix. After in-gel digestion of proteins, LC-MS/MS is used to analyze the extracted peptides for protein identification. The uniqueness of the protocol is that it allows usage of a variety of detergents in the starting solution without interfering with LC-MS/MS analysis. We hereby demonstrate that different detergents, including ionic SDS, non-ionic Triton X-100 and n-octyl beta-d-glucopyranoside, and zwitterionic CHAPS, can be used to achieve maximum solubilization of membrane proteins with minimal interference with LC-MS/MS analysis. Enhanced digestions, i.e. improved number and intensity of detected peptides, are also demonstrated for digestion-resistant proteins such as myoglobin, ubiquitin, and bacteriorhodopsin. An additional advantage of the Tube-Gel digestion protocol is that, even without electrophoresis separation, it allows high throughput analysis of complex protein mixtures when coupled with LC-MS/MS. The protocol was used to analyze a complex membrane protein mixture prepared from prostate cancer cells. The protocol involves only a single digestion and 2.5 h of LC-MS/MS analysis and identified 178 membrane proteins. In comparison, the same membrane fraction was resolved by SDS-PAGE, and 20 gel slices were excised and individually digested and analyzed by LC-MS/MS. The more elaborate effort demanded more than 50 h of LC-MS/MS analysis and identified 268 proteins. The new Tube-Gel digestion protocol is an alternative method for high throughput analysis of membrane proteins.     

Deep and highly sensitive proteome coverage by LC-MS/MS without prefractionation

In-depth MS-based proteomics has necessitated fractionation of either proteins or peptides or both, often requiring considerable analysis time. Here we employ long liquid chromatography runs with high resolution coupled to an instrument with fast sequencing speed to investigate how much of the proteome is directly accessible to liquid chromatography-tandem MS characterization without any prefractionation steps. Triplicate single-run analyses identified 2990 yeast proteins, 68% of the total measured in a comprehensive yeast proteome. Among them, we covered the enzymes of the glycolysis and gluconeogenesis pathway targeted in a recent multiple reaction monitoring study. In a mammalian cell line, we identified 5376 proteins in a triplicate run, including representatives of 173 out of 200 KEGG metabolic and signaling pathways. Remarkably, the majority of proteins could be detected in the samples at sub-femtomole amounts and many in the low attomole range, in agreement with absolute abundance estimation done in previous works (Picotti et al. Cell, 138, 795-806, 2009). Our results imply an unexpectedly large dynamic range of the MS signal and sensitivity for liquid chromatography-tandem MS alone. With further development, single-run analysis has the potential to radically simplify many proteomic studies while maintaining a systems-wide view of the proteome.     

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.     

Detecting differential and correlated protein expression in label-free shotgun proteomics

Recent studies have revealed a relationship between protein abundance and sampling statistics, such as sequence coverage, peptide count, and spectral count, in label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) shotgun proteomics. The use of sampling statistics offers a promising method of measuring relative protein abundance and detecting differentially expressed or coexpressed proteins. We performed a systematic analysis of various approaches to quantifying differential protein expression in eukaryotic Saccharomyces cerevisiae and prokaryotic Rhodopseudomonas palustris label-free LC-MS/MS data. First, we showed that, among three sampling statistics, the spectral count has the highest technical reproducibility, followed by the less-reproducible peptide count and relatively nonreproducible sequence coverage. Second, we used spectral count statistics to measure differential protein expression in pairwise experiments using five statistical tests: Fisher's exact test, G-test, AC test, t-test, and LPE test. Given the S. cerevisiae data set with spiked proteins as a benchmark and the false positive rate as a metric, our evaluation suggested that the Fisher's exact test, G-test, and AC test can be used when the number of replications is limited (one or two), whereas the t-test is useful with three or more replicates available. Third, we generalized the G-test to increase the sensitivity of detecting differential protein expression under multiple experimental conditions. Out of 1622 identified R. palustris proteins in the LC-MS/MS experiment, the generalized G-test detected 1119 differentially expressed proteins under six growth conditions. Finally, we studied correlated expression of these 1119 proteins by analyzing pairwise expression correlations and by delineating protein clusters according to expression patterns. Through pairwise expression correlation analysis, we demonstrated that proteins co-located in the same operon were much more strongly coexpressed than those from different operons. Combining cluster analysis with existing protein functional annotations, we identified six protein clusters with known biological significance. In summary, the proposed generalized G-test using spectral count sampling statistics is a viable methodology for robust quantification of relative protein abundance and for sensitive detection of biologically significant differential protein expression under multiple experimental conditions in label-free shotgun proteomics.     

Characterisation of host defence proteins in milk using a proteomic approach

Besides providing nutrition to the newborn, milk also protects the neonate and the mammary gland against infection. As well as the six major proteins, bovine milk contains minor proteins, not all of which have been characterized. In this study, we have subjected bovine skim milk, whey, and milk fat globule membrane (MFGM) fractions to both direct liquid chromatography-tandem mass spectrometry (LC-MS/MS), and two-dimensional electrophoresis (2-DE) followed by matrix assisted laser desorption ionization-time-of-flight (MALDI-TOF) mass spectrometry (MS) of individual protein spots to better characterize the repertoire of minor milk proteins, particularly those involved with host defense. Milk from peak lactation as well as during the period of colostrum formation and during mastitis were analyzed to gain a more complete sampling of the milk proteome. In total, 2903 peptides were detected by LC-MS and 2770 protein spots by 2-DE. From these, 95 distinct gene products were identified, comprising 53 identified through direct LC-MS/MS and 57 through 2-DE-MS. The latter were derived from a total of 363 spots analyzed with 181 being successfully identified. At least 15 proteins were identified that are involved in host defense. These results demonstrate that the proteome of milk is more complex than has previously been reported and a significant fraction of minor milk proteins are involved in protection against infection.     

Comparison of MS/MS methods for protein identification from 2D-PAGE

We have compared the use of a low resolution MALDI-Ion Trap MS/MS and a high-resolution ESI-TOF-MS/MS for the analysis of spots from 2D gels. The main criteria were speed and accuracy of protein identification. The results obtained using the MALDI-MS/MS system are comparable to those from the LC-MS/MS system in terms of accuracy, but less low-level proteins are identified while the time required for the analysis is dramatically reduced.     

An integrated, directed mass spectrometric approach for in-depth characterization of complex peptide mixtures

LC-MS/MS has emerged as the method of choice for the identification and quantification of protein sample mixtures. For very complex samples such as complete proteomes, the most commonly used LC-MS/MS method, data-dependent acquisition (DDA) precursor selection, is of limited utility. The limited scan speed of current mass spectrometers along with the highly redundant selection of the most intense precursor ions generates a bias in the pool of identified proteins toward those of higher abundance. A directed LC-MS/MS approach that alleviates the limitations of DDA precursor ion selection by decoupling peak detection and sequencing of selected precursor ions is presented. In the first stage of the strategy, all detectable peptide ion signals are extracted from high resolution LC-MS feature maps or aligned sets of feature maps. The selected features or a subset thereof are subsequently sequenced in sequential, non-redundant directed LC-MS/MS experiments, and the MS/MS data are mapped back to the original LC-MS feature map in a fully automated manner. The strategy, implemented on an LTQ-FT MS platform, allowed the specific sequencing of 2,000 features per analysis and enabled the identification of more than 1,600 phosphorylation sites using a single reversed phase separation dimension without the need for time-consuming prefractionation steps. Compared with conventional DDA LC-MS/MS experiments, a substantially higher number of peptides could be identified from a sample, and this increase was more pronounced for low intensity precursor ions.     

Isolation of N-terminal protein sequence tags from cyanogen bromide cleaved proteins as a novel approach to investigate hydrophobic proteins

A novel method for the isolation of protein sequence tags to identify proteins in a complex mixture of hydrophobic proteins is described. The PST (Protein Sequence Tag) technology deals with the isolation and MS/MS based identification of one N-terminal peptide from each polypeptide fragment generated by cyanogen bromide cleavage of a mixture of proteins. PST sampling takes place after sub-cellular fractionation of a complex protein mixture to give enrichment of mitochondrial proteins. The method presented here combines effective sample preparation with a novel peptide isolation protocol involving chemical and enzymatic cleavage of proteins coupled to chemical labeling and selective capture procedures. The overall process has been very successful for the analysis of complex mixtures of hydrophobic proteins, particularly membrane proteins. This method substantially reduces the complexity of a protein digest by "sampling" the peptides present in the digest. The sampled digest is amenable to analysis by liquid chromatography tandem mass spectrometry (LC-MS/MS). Methods of "sampling" protein digests have great value' if they can provide sufficient information to identify substantially all of the proteins in the sample while reducing the complexity of the sample to maximize the efficient usage of LC-MS/MS capacity. The validity of the process is demonstrated for mitochondrial samples from S. cerevisiae. The proteins identified by the PST technology are compared to the proteins identified by the conventional technology 2-D gel electrophoresis as a control.     

iTRAQ结合2D LC-MS/MS技术在草菇不同生长发育时期蛋白质组分析中的应用

【目的】旨在采用iTRAQ标记结合二维液相色谱串联质谱技术对草菇不同生长发育阶段的差异蛋白质组进行研究。【方法】首先将提取的草菇不同生长阶段蛋白样品进行SDS-PAGE分析,其次将经二维液相色谱串联质谱技术获取的串联质谱数据通过MASCOT软件搜库,之后对鉴定蛋白质数据进行了主成分分析(Principal componentanalysis,PCA)、层次聚类(Hierarchy clustering)分析、K-均值(K-means)聚类和GeneOntology(GO)注释分析。【结果】试验结果显示,共计获得2 335个不同肽段,鉴定到1 039个蛋白质,其中1 030个蛋白质具有定量信息。在子实体阶段中显著上调蛋白质64个,下调蛋白质150个。生物信息学分析表明,iTRAQ标记技术结合二维液相色谱串联质谱可对不同生长发育时期的草菇蛋白样品进行有效地分离和鉴定。【结论】这一研究结果为深入研究草菇乃至其他大型担子菌子实体形成和发育的分子机制提供借鉴。     

草菇子实体不同成熟阶段的比较蛋白质组学分析

采用iTRAQ标记结合二维液相色谱串联质谱技术对草菇不同成熟阶段的差异蛋白质组进行研究。首先将提取的草菇不同成熟阶段蛋白样品进行SDS-PAGE分析,其次将经二维液相色谱串联质谱技术获取的串联质谱数据通过MASCOT软件搜库,之后对鉴定蛋白质数据进行了KEGG代谢通路分析。试验共计获得2 335个不同肽段, 鉴定到1 039个蛋白质,其中1 030个蛋白质具有定量信息。与蛋形期相比,在伸长期和成熟期阶段显著上调蛋白质85个,下调蛋白质103个。KEGG代谢通路分析结果显示,草菇不同成熟阶段中的68个差异蛋白质可定位于4种伞菌目模式真菌（灰盖鬼伞、双色蜡蘑、可可丛枝病菌和裂褶菌）的45个不同生物代谢途径,全景展示出草菇成熟阶段差异表达蛋白质定位的代谢网络。结果表明,iTRAQ标记技术结合二维液相色谱串联质谱可对不同生长发育时期的草菇蛋白样品进行有效地分离和鉴定。     

IsoformResolver: A peptide-centric algorithm for protein inference

When analyzing proteins in complex samples using tandem mass spectrometry of peptides generated by proteolysis, the inference of proteins can be ambiguous, even with well-validated peptides. Unresolved questions include whether to show all possible proteins vs a minimal list, what to do when proteins are inferred ambiguously, and how to quantify peptides that bridge multiple proteins, each with distinguishing evidence. Here we describe IsoformResolver, a peptide-centric protein inference algorithm that clusters proteins in two ways, one based on peptides experimentally identified from MS/MS spectra, and the other based on peptides derived from an in silico digest of the protein database. MS/MS-derived protein groups report minimal list proteins in the context of all possible proteins, without redundantly listing peptides. In silico-derived protein groups pull together functionally related proteins, providing stable identifiers. The peptide-centric grouping strategy used by IsoformResolver allows proteins to be displayed together when they share peptides in common, providing a comprehensive yet concise way to organize protein profiles. It also summarizes information on spectral counts and is especially useful for comparing results from multiple LC-MS/MS experiments. Finally, we examine the relatedness of proteins within IsoformResolver groups and compare its performance to other protein inference software.