Accurate mass tag retention time database for urine proteome analysis by chromatography-mass spectrometry

Information about peptides and proteins in urine can be used to search for biomarkers of early stages of various diseases. The main technology currently used for identification of peptides and proteins is tandem mass spectrometry, in which peptides are identified by mass spectra of their fragmentation products. However, the presence of the fragmentation stage decreases sensitivity of analysis and increases its duration. We have developed a method for identification of human urinary proteins and peptides. This method based on the accurate mass and time tag (AMT) method does not use tandem mass spectrometry. The database of AMT tags containing more than 1381 AMT tags of peptides has been constructed. The software for database filling with AMT tags, normalizing the chromatograms, database application for identification of proteins and peptides, and their quantitative estimation has been developed. The new procedures for peptide identification by tandem mass spectra and the AMT tag database are proposed. The paper also lists novel proteins that have been identified in human urine for the first time.     

Reproducibility of LC-MS-based protein identification

Traditional analysis of liquid chromatography-mass spectrometry (LC-MS) data, typically performed by reviewing chromatograms and the corresponding mass spectra, is both time-consuming and difficult. Detailed data analysis is therefore often omitted in proteomics applications. When analysing multiple proteomics samples, it is usually only the final list of identified proteins that is reviewed. This may lead to unnecessarily complex or even contradictory results because the content of the list of identified proteins depends heavily on the conditions for triggering the collection of tandem mass spectra. Small changes in the signal intensity of a peptide in different LC-MS experiments can lead to the collection of a tandem mass spectrum in one experiment but not in another. Also, the quality of the tandem mass spectrometry experiments can vary, leading to successful identification in some cases but not in others. Using a novel image analysis approach, it is possible to achieve repeat analysis with a very high reproducibility by matching peptides across different LC-MS experiments using the retention time and parent mass over charge (m/z). It is also easy to confirm the final result visually. This approach has been investigated by using tryptic digests of integral membrane proteins from organelle-enriched fractions from Arabidopsis thaliana and it has been demonstrated that very highly reproducible, consistent, and reliable LC-MS data interpretation can be made.     

Characterization of a digested protein complex with quantitative aspects: an approach based on accurate mass chromatographic analysis with Fourier transform-ion cyclotron resonance mass spectrometry

We describe a new approach for the characterization of a digested protein complex with quantitative aspects. Accurate masses of tryptic peptides in the digested complex were acquired by nano-liquid chromatography Fourier transform-ion cyclotron resonance mass spectrometry (MS). The conditions of the electrospray ion source were alternated to acquire normal and fragment-ion-rich mass spectra concurrently. This, alternating-scan method, which includes no tandem mass spectrometry (MS/MS), allowed us to retain the integrity of the mass chromatograms and averted missed peptides due to MS and MS/MS switching. Tentative assignments of accurate peptide masses were verified with the concurrently acquired fragment-ion-rich spectra, and the identities of the protein components were established. For each identified protein component, mass chromatograms attributable to the validated accurate peptide masses were extracted, and the peak areas of multiple mass chromatograms were standardized. The standardized peak areas appeared to reasonably reflect the molar ratio of the protein components in standard mixtures. This new approach was successfully applied to the characterization of a cyanobacterial photosystem II complex preparation. A clear difference in the standardized peak areas was observed between the two groups of identified components, namely eight stoichiometric photosystem II proteins and two minor copurified phycobiliproteins.     

Ultra-high intra-spectrum mass accuracy enables unambiguous identification of fragment reporter ions in isobaric multiplexed quantitative proteomics

Isobaric tagging using reagents such as tandem mass tags (TMT) and isobaric tags for relative and absolute quantification (iTRAQ) have become popular tools for mass spectrometry based quantitative proteomics. Because the peptide quantification information is collected in tandem mass spectra, the accuracy and precision of this method largely depend on the resolution with which precursor ions can be selected for the fragmentation and the specificity of the generated reporter ion. The latter can constitute an issue if near isobaric ion signals are present in such spectra because they may distort quantification results. We propose a simple remedy for this problem by identifying reporter ions via the accurate mass differences within a single tandem mass spectrum instead of applying fixed mass error tolerances for all tandem mass spectra. Our results show that this leads to unambiguous reporter ion identification and complete removal of interfering signals. This mode of data processing is easily implemented in software and offers advantages for protein quantification based on few peptides.     

Improving SWATH-MS analysis by deep-learning

Data-independent acquisition (DIA) of tandem mass spectrometry spectra has emerged as a promising technology to improve coverage and quantification of proteins in complex mixtures. The success of DIA experiments is dependent on the quality of spectral libraries used for data base searching. Frequently, these libraries need to be generated by labor and time intensive data dependent acquisition (DDA) experiments. Recently, several algorithms have been published that allow the generation of theoretical libraries by an efficient prediction of retention time and intensity of the fragment ions. Sequential windowed acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS) is a DIA method that can be applied at an unprecedented speed, but the fragmentation spectra suffer from a lower quality than data acquired on Orbitrap instruments. To reliably generate theoretical libraries that can be used in SWATH experiments, we developed deep-learning for SWATH analysis (dpSWATH), to improve the sensitivity and specificity of data generated by Q-TOF mass spectrometers. The theoretical library built by dpSWATH allowed us to increase the identification rate of proteins compared to traditional or library-free methods. Based on our analysis we conclude that dpSWATH is a superior prediction framework for SWATH-MS measurements than other algorithms based on Orbitrap data.     

Mapping preferred sites for fluorescent labeling by combining fluorescence and MS analysis of tryptic CNA35 protein digests

HPLC-MS analysis of tryptic protein digests in combination with fluorescence detection is presented as a convenient and quantitative method to gain insight into the relative reactivity of lysine side chains. In this scheme (tandem) mass spectrometry was used for identification of the modified residue, whereas fluorescence detection allowed determination of their relative abundance. Our method identified 'labeling hot-spots' at two flexible parts of the collagen-binding protein CNA35, positions that were consistent with all available structural and biochemical data on the collagen-binding properties of CNA35.     

基于数据非依赖采集的蛋白质组质谱数据解析方法研究进展

数据非依赖采集（DIA）是蛋白质组学领域近年来快速发展的质谱采集技术，其通过无偏碎裂隔离窗口内的所有母离子采集二级谱图，理论上可实现蛋白质样品的深度覆盖，同时具有高通量、高重现性和高灵敏度的优点。现有的DIA数据采集方法可以分为全窗口碎裂方法、隔离窗口序列碎裂方法和四维DIA数据采集方法（4D-DIA）3大类。针对DIA数据的不同特点，主要数据解析方法包括谱库搜索方法、蛋白质序列库直接搜索方法、伪二级谱图鉴定方法和从头测序方法4大类。解析得到的肽段鉴定结果需要进行可信度评估，包括使用机器学习方法的重排序和对报告结果集合的假发现率估计两个步骤，实现对数据解析结果的质控。本文对DIA数据的采集方法、数据解析方法及软件和鉴定结果可信度评估方法进行了整理和综述，并展望了未来的发展方向。     

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.     

Direct analysis of lipids on thin layer plates by matrix-assisted secondary ion mass spectrometry

A simple and rapid method for the analysis of lipids on a thin layer chromatography (TLC) plate by matrix-assisted secondary ion mass spectrometry (SI-MS) is reported. Analysis was performed without elution of the sample from the TLC plate. Mass spectra obtained by this method are free from interference due to the TLC plate absorbent and reagents used for the detection of the spots. About 1 micrograms of lipids applied on a TLC plate can be analyzed by this method. On scanning the plate, mass chromatograms of each lipid were obtained based on its migration distance along the plate.     

A hybrid method for peptide identification using integer linear optimization, local database search, and quadrupole time-of-flight or OrbiTrap tandem mass spectrometry

A novel hybrid methodology for the automated identification of peptides via de novo integer linear optimization, local database search, and tandem mass spectrometry is presented in this article. A modified version of the de novo identification algorithm PILOT, is utilized to construct accurate de novo peptide sequences. A modified version of the local database search tool FASTA is used to query these de novo predictions against the nonredundant protein database to resolve any low-confidence amino acids in the candidate sequences. The computational burden associated with performing several alignments is alleviated with the use of distributive computing. Extensive computational studies are presented for this new hybrid methodology, as well as comparisons with MASCOT for a set of 38 quadrupole time-of-flight (QTOF) and 380 OrbiTrap tandem mass spectra. The results for our proposed hybrid method for the OrbiTrap spectra are also compared with a modified version of PepNovo, which was trained for use on high-precision tandem mass spectra, and the tag-based method InsPecT. The de novo sequences of PILOT and PepNovo are also searched against the nonredundant protein database using CIDentify to compare with the alignments achieved by our modifications of FASTA. The comparative studies demonstrate the excellent peptide identification accuracy gained from combining the strengths of our de novo method, which is based on integer linear optimization, and database driven search methods.     

Incorporation of tandem mass spectrometric detection to the analysis of peptide mixtures by continuous flow fast atom bombardment mass spectrometry

The ability to acquire structurally informative daughter ion spectra for individual peptides undergoing separation and analysis by continuous flow fast atom bombardment (CF FAB) is demonstrated. To illustrate the potential of this methodology, tryptic and chymotryptic digests of the 29-residue peptide glucagon were analyzed by CF FAB using mass spectrometric and tandem mass spectrometric detection in consecutive analyses. Daughter ion spectra were recorded using B/E linked scans for the major hydrolysis products observed by liquid chromatography/mass spectrometry. The peptide mixtures were separated by gradient capillary high-performance liquid chromatography with the FAB matrix being added post-column using a coaxial flow interface between the column and flow probe. The entire effluent (3 microl min(-1)) was sampled by the mass spectrometer. Results obtained using less than 300 pmol of digested glucagon indicated several advantages to tandem mass spectrometric detection including the ability to confirm identities for products of enzymatic digestion and the potential use of this method for tandem sequence analysis of peptide mixtures.     

Algorithms for identifying protein cross-links via tandem mass spectrometry.

Cross-linking technology combined with tandem mass spectrometry (MS-MS) is a powerful method that provides a rapid solution to the discovery of protein-protein interactions and protein structures. We studied the problem of detecting cross-linked peptides and cross-linked amino acids from tandem mass spectral data. Our method consists of two steps: the first step finds two protein subsequences whose mass sum equals a given mass measured from the mass spectrometry; and the second step finds the best cross-linked amino acids in these two peptide sequences that are optimally correlated to a given tandem mass spectrum. We designed fast and space-efficient algorithms for these two steps and implemented and tested them on experimental data of cross-linked hemoglobin proteins. An interchain cross-link between two beta subunits was found in two tandem mass spectra. The length of the cross-linker (7.7 A) is very close to the actual distance (8.18 A) obtained from the molecular structure in PDB.     

Database-independent, database-dependent, and extended interpretation of peptide mass spectra in VEMS V2.0

The Virtual Expert Mass Spectrometrist (VEMS) program package was developed for flexible, automated, and manual de novo tandem mass spectrometry (MS/MS) protein sequencing, and includes accessory programs for matrix-assisted laser desorption/ionization-mass spectrometry (MS) interpretation, and generation of protein and peptide databases. VEMS V2.0 has been developed into a fast tool for combining database-independent and -dependent protein assignments in an extended analysis of MS/MS-peptide data. MS or MS/MS data can be directly recalibrated after the first search by fitting the data to the best search result using polynomial equations. The score function is an improvement of known scoring algorithms and can be adapted for any MS instrument type. In addition, VEMS offers a novel statistical model for evaluating the significance of the protein assignment. The novel features are illustrated by the analysis of the fragmentation spectra obtained by liquid chromatrography-MS/MS analysis of peptides from an anionic peroxidase enriched protein fraction from potato root tissue. The extended analysis mode resulted in the additional assignment of spectra for nine modified tryptic peptides and nine miscleaved peptides, in addition to the 45 spectra from regular tryptic peptides. Of the nine modified peptides, three were glycosylated.     

电喷雾串联质谱图的叠合与多肽序列分析

利用离子阱电喷雾串联质谱仪,在选择性改变某些食品参数的条件下对模式分子Met-脑啡肽和自行固相化学合成的7肽及其修饰产物、10肽和20肽进行碎裂处理,从而获得一系列具有一定差异的串联质谱图。选择具有适当互补性的图谱进行叠合处理,得到具有连贯性“三联套”（triplet）及“二联套”（doublet）碎片离子峰的叠合串联质谱图,据此可以方便准确地角析出多肽的氨基酸序列。实验结果表明,这种方法在多肽的质谱法测定中具有一定的实用性。     

Computational analysis of shotgun proteomics data

Proteomics technology is progressing at an incredible rate. The latest generation of tandem mass spectrometers can now acquire tens of thousands of fragmentation spectra in a matter of hours. Furthermore, quantitative proteomics methods have been developed that incorporate a stable isotope-labeled internal standard for every peptide within a complex protein mixture for the measurement of relative protein abundances. These developments have opened the doors for 'shotgun' proteomics, yet have also placed a burden on the computational approaches that manage the data. With each new method that is developed, the quantity of data that can be derived from a single experiment increases. To deal with this increase, new computational approaches are being developed to manage the data and assess false positives. This review discusses current approaches for analyzing proteomics data by mass spectrometry and identifies present computational limitations and bottlenecks.     

Human plasma proteome analysis by reversed sequence database search and molecular weight correlation based on a bacterial proteome analysis

In shotgun proteomics, proteins can be fractionated by 1-D gel electrophoresis and digested into peptides, followed by liquid chromatography to separate the peptide mixture. Mass spectrometry generates hundreds of thousands of tandem mass spectra from these fractions, and proteins are identified by database searching. However, the search scores are usually not sufficient to distinguish the correct peptides. In this study, we propose a confident protein identification method for high-throughput analysis of human proteome. To build a filtering protocol in database search, we chose Pseudomonas putida KT2440 as a reference because this bacterial proteome contains fewer modifications and is simpler than the human proteome. First, the P. putida KT2440 proteome was filtered by reversed sequence database search and correlated by the molecular weight in 1-D-gel band positions. The characterization protocol was then applied to determine the criteria for clustering of the human plasma proteome into three different groups. This protein filtering method, based on bacterial proteome data analysis, represents a rapid way to generate higher confidence protein list of the human proteome, which includes some of heavily modified and cleaved proteins.     

Quantification of steroid conjugates using fast atom bombardment mass spectrometry

Fast atom bombardment/mass spectrometry or liquid secondary ion mass spectrometry provides the capability for direct analysis of steroid conjugates (sulfates, glucuronides) without prior hydrolysis or derivatization. During the analysis of biologic extracts, limitations on the sensitivity of detection arise from the presence of co-extracted material which may suppress or obscure the analyte signal. A procedure is described for the quantitative determination of dehydroepiandrosterone sulfate in serum which achieved selective isolation of the analyte using immunoadsorption extraction and highly specific detection using tandem mass spectrometry. A stable isotope-labeled analog [( 2H2]dehydroepiandrosterone sulfate) was used as internal standard. Fast atom bombardment of dehydroepiandrosterone sulfate yielded abundant [M-H]- ions that fragmented following collisional activation to give HSO4-; m/z 97. During fast atom bombardment/tandem mass spectrometry of serum extracts, a scan of precursor ions fragmenting to give m/z 97 detected dehydroepiandrosterone sulfate and the [2H2]-labeled analog with a selectivity markedly superior to that observed using conventional mass spectrometry detection. Satisfactory agreement was observed between quantitative data obtained in this way and data obtained by gas chromatography/mass spectrometry of the heptafluorobutyrates of dehydroepiandrosterone sulfate and [2H2]dehydroepiandrosterone sulfate obtained by direct derivatization.     

Chemical probes and tandem mass spectrometry: a strategy for the quantitative analysis of proteomes and subproteomes

Quantitative proteome profiling using mass spectrometry and stable isotope dilution is being widely applied for the functional analysis of biological systems and for the detection of clinical, diagnostic or prognostic marker proteins. Because of the enormous complexity of proteomes, their comprehensive analysis is unlikely to be routinely achieved in the near future. However, in recent years, significant progress has been achieved focusing quantitative proteomic analyses on specific protein classes or subproteomes that are rich in biologically or clinically important information. Such projects typically combine the use of chemical probes that are specific for a targeted group of proteins and may contain stable isotope signatures for accurate quantification with automated tandem mass spectrometry and bioinformatics tools for data analysis. In this review, we summarize technical and conceptual advances in quantitative subproteome profiling based on tandem mass spectrometry and chemical probes.     

Adaptive discriminant function analysis and reranking of MS/MS database search results for improved peptide identification in shotgun proteomics

Robust statistical validation of peptide identifications obtained by tandem mass spectrometry and sequence database searching is an important task in shotgun proteomics. PeptideProphet is a commonly used computational tool that computes confidence measures for peptide identifications. In this paper, we investigate several limitations of the PeptideProphet modeling approach, including the use of fixed coefficients in computing the discriminant search score and selection of the top scoring peptide assignment per spectrum only. To address these limitations, we describe an adaptive method in which a new discriminant function is learned from the data in an iterative fashion. We extend the modeling framework to go beyond the top scoring peptide assignment per spectrum. We also investigate the effect of clustering the spectra according to their spectrum quality score followed by cluster-specific mixture modeling. The analysis is carried out using data acquired from a mixture of purified proteins on four different types of mass spectrometers, as well as using a complex human serum data set. A special emphasis is placed on the analysis of data generated on high mass accuracy instruments.     

Platform-independent and label-free quantitation of proteomic data using MS1 extracted ion chromatograms in skyline: application to protein acetylation and phosphorylation

Despite advances in metabolic and postmetabolic labeling methods for quantitative proteomics, there remains a need for improved label-free approaches. This need is particularly pressing for workflows that incorporate affinity enrichment at the peptide level, where isobaric chemical labels such as isobaric tags for relative and absolute quantitation and tandem mass tags may prove problematic or where stable isotope labeling with amino acids in cell culture labeling cannot be readily applied. Skyline is a freely available, open source software tool for quantitative data processing and proteomic analysis. We expanded the capabilities of Skyline to process ion intensity chromatograms of peptide analytes from full scan mass spectral data (MS1) acquired during HPLC MS/MS proteomic experiments. Moreover, unlike existing programs, Skyline MS1 filtering can be used with mass spectrometers from four major vendors, which allows results to be compared directly across laboratories. The new quantitative and graphical tools now available in Skyline specifically support interrogation of multiple acquisitions for MS1 filtering, including visual inspection of peak picking and both automated and manual integration, key features often lacking in existing software. In addition, Skyline MS1 filtering displays retention time indicators from underlying MS/MS data contained within the spectral library to ensure proper peak selection. The modular structure of Skyline also provides well defined, customizable data reports and thus allows users to directly connect to existing statistical programs for post hoc data analysis. To demonstrate the utility of the MS1 filtering approach, we have carried out experiments on several MS platforms and have specifically examined the performance of this method to quantify two important post-translational modifications: acetylation and phosphorylation, in peptide-centric affinity workflows of increasing complexity using mouse and human models.