N-糖肽的规模化质谱解析方法进展

蛋白质糖基化修饰的鉴定是蛋白质翻译后修饰分析中最具挑战性的任务之一,近几年尤其受到关注.快速发展的质谱技术为规模化的蛋白质糖基化修饰研究提供了有效的手段.与其他基于质谱技术的翻译后修饰鉴定相比,糖基化鉴定的难点在于糖链是大分子而且存在微观不均一性,另外糖链本身可以在串联质谱中碎裂且与肽段的碎裂规律不同,导致蛋白质组学的质谱解析方法和软件难以完整地鉴定肽段序列和糖链结构.完整N-糖肽的鉴定是糖基化分析的热点内容之一,针对N-糖肽的鉴定,近年来,人们开发了多种多样的质谱解析方法,其中包括用N-糖酰胺酶切除糖链后鉴定N-糖基化位点的方法、基于电子转运裂解的糖肽肽段鉴定、基于高能碰撞裂解与电子转运裂解联用或碰撞诱导裂解与三级谱联用的完整N-糖肽鉴定等等.本文对这些质谱解析方法进行了整理和综述,简要指出了目前完整糖肽鉴定软件存在的一些不足,展望了未来的发展方向.     

Peptide identification by database search of mixture tandem mass spectra

In high-throughput proteomics the development of computational methods and novel experimental strategies often rely on each other. In certain areas, mass spectrometry methods for data acquisition are ahead of computational methods to interpret the resulting tandem mass spectra. Particularly, although there are numerous situations in which a mixture tandem mass spectrum can contain fragment ions from two or more peptides, nearly all database search tools still make the assumption that each tandem mass spectrum comes from one peptide. Common examples include mixture spectra from co-eluting peptides in complex samples, spectra generated from data-independent acquisition methods, and spectra from peptides with complex post-translational modifications. We propose a new database search tool (MixDB) that is able to identify mixture tandem mass spectra from more than one peptide. We show that peptides can be reliably identified with up to 95% accuracy from mixture spectra while considering only a 0.01% of all possible peptide pairs (four orders of magnitude speedup). Comparison with current database search methods indicates that our approach has better or comparable sensitivity and precision at identifying single-peptide spectra while simultaneously being able to identify 38% more peptides from mixture spectra at significantly higher precision.     

Andromeda: a peptide search engine integrated into the MaxQuant environment

A key step in mass spectrometry (MS)-based proteomics is the identification of peptides in sequence databases by their fragmentation spectra. Here we describe Andromeda, a novel peptide search engine using a probabilistic scoring model. On proteome data, Andromeda performs as well as Mascot, a widely used commercial search engine, as judged by sensitivity and specificity analysis based on target decoy searches. Furthermore, it can handle data with arbitrarily high fragment mass accuracy, is able to assign and score complex patterns of post-translational modifications, such as highly phosphorylated peptides, and accommodates extremely large databases. The algorithms of Andromeda are provided. Andromeda can function independently or as an integrated search engine of the widely used MaxQuant computational proteomics platform and both are freely available at www.maxquant.org. The combination enables analysis of large data sets in a simple analysis workflow on a desktop computer. For searching individual spectra Andromeda is also accessible via a web server. We demonstrate the flexibility of the system by implementing the capability to identify cofragmented peptides, significantly improving the total number of identified peptides.     

Improved machine learning method for analysis of gas phase chemistry of peptides

Background  

Accurate peptide identification is important to high-throughput proteomics analyses that use mass spectrometry. Search programs compare fragmentation spectra (MS/MS) of peptides from complex digests with theoretically derived spectra from a database of protein sequences. Improved discrimination is achieved with theoretical spectra that are based on simulating gas phase chemistry of the peptides, but the limited understanding of those processes affects the accuracy of predictions from theoretical spectra.     

Glycoproteomics based on tandem mass spectrometry of glycopeptides

Next to the identification of proteins and the determination of their expression levels, the analysis of post-translational modifications (PTM) is becoming an increasingly important aspect in proteomics. Here, we review mass spectrometric (MS) techniques for the study of protein glycosylation at the glycopeptide level. Enrichment and separation techniques for glycoproteins and glycopeptides from complex (glyco-)protein mixtures and digests are summarized. Various tandem MS (MS/MS) techniques for the analysis of glycopeptides are described and compared with respect to the information they provide on peptide sequence, glycan attachment site and glycan structure. Approaches using electrospray ionization and matrix-assisted laser desorption/ionization (MALDI) of glycopeptides are presented and the following fragmentation techniques in glycopeptide analysis are compared: collision-induced fragmentation on different types of instruments, metastable fragmentation after MALDI ionization, infrared multi-photon dissociation, electron-capture dissociation and electron-transfer dissociation. This review discusses the potential and limitations of tandem mass spectrometry of glycopeptides as a tool in structural glycoproteomics.     

Automated identification of SUMOylation sites using mass spectrometry and SUMmOn pattern recognition software

Tandem mass spectrometry (MS/MS) allows for the rapid identification of many types of post-translational modifications (PTMs), especially those that can be detected by a diagnostic mass shift in one or more peptide fragment ions (for example, phosphorylation). But some PTMs (for example, SUMOs and other ubiquitin-like modifiers) themselves produce multiple fragment ions; combined with fragments from the modified target peptide, a complex overlapping fragmentation pattern is thus generated, which is uninterpretable by standard peptide sequencing software. Here we introduce SUMmOn, an automated pattern recognition tool that detects diagnostic PTM fragment ion series within complex MS/MS spectra, to identify modified peptides and modification sites within these peptides. Using SUMmOn, we demonstrate for the first time that human SUMO-1 multimerizes in vitro primarily via three N-terminal lysines, Lys7, Lys16 and Lys17. Notably, our method is theoretically applicable to any type of modification or chemical moiety generating a unique fragment ion pattern.     

The utility of ETD mass spectrometry in proteomic analysis

Mass spectrometry has played an integral role in the identification of proteins and their post-translational modifications (PTM). However, analysis of some PTMs, such as phosphorylation, sulfonation, and glycosylation, is difficult with collision-activated dissociation (CAD) since the modification is labile and preferentially lost over peptide backbone fragmentation, resulting in little to no peptide sequence information. The presence of multiple basic residues also makes peptides exceptionally difficult to sequence by conventional CAD mass spectrometry. Here we review the utility of electron transfer dissociation (ETD) mass spectrometry for sequence analysis of post-translationally modified and/or highly basic peptides. Phosphorylated, sulfonated, glycosylated, nitrosylated, disulfide bonded, methylated, acetylated, and highly basic peptides have been analyzed by CAD and ETD mass spectrometry. CAD fragmentation typically produced spectra showing limited peptide backbone fragmentation. However, when these peptides were fragmented using ETD, peptide backbone fragmentation produced a complete or almost complete series of ions and thus extensive peptide sequence information. In addition, labile PTMs remained intact. These examples illustrate the utility of ETD as an advantageous tool in proteomic research by readily identifying peptides resistant to analysis by CAD. A further benefit is the ability to analyze larger, non-tryptic peptides, allowing for the detection of multiple PTMs within the context of one another.     

A data-mining scheme for identifying peptide structural motifs responsible for different MS/MS fragmentation intensity patterns

Although tandem mass spectrometry (MS/MS) has become an integral part of proteomics, intensity patterns in MS/MS spectra are rarely weighted heavily in most widely used algorithms because they are not yet fully understood. Here a knowledge mining approach is demonstrated to discover fragmentation intensity patterns and elucidate the chemical factors behind such patterns. Fragmentation intensity information from 28 330 ion trap peptide MS/MS spectra of different charge states and sequences went through unsupervised clustering using a penalized K-means algorithm. Without any prior chemistry assumptions, four clusters with distinctive fragmentation patterns were obtained. A decision tree was generated to investigate peptide sequence motif and charge state status that caused these fragmentation patterns. This data-mining scheme is generally applicable for any large data sets. It bypasses the common prior knowledge constraints and reports on the overall peptide fragmentation behavior. It improves the understanding of gas-phase peptide dissociation and provides a foundation for new or improved protein identification algorithms.     

The spectral networks paradigm in high throughput mass spectrometry

High-throughput proteomics is made possible by a combination of modern mass spectrometry instruments capable of generating many millions of tandem mass (MS(2)) spectra on a daily basis and the increasingly sophisticated associated software for their automated identification. Despite the growing accumulation of collections of identified spectra and the regular generation of MS(2) data from related peptides, the mainstream approach for peptide identification is still the nearly two decades old approach of matching one MS(2) spectrum at a time against a database of protein sequences. Moreover, database search tools overwhelmingly continue to require that users guess in advance a small set of 4-6 post-translational modifications that may be present in their data in order to avoid incurring substantial false positive and negative rates. The spectral networks paradigm for analysis of MS(2) spectra differs from the mainstream database search paradigm in three fundamental ways. First, spectral networks are based on matching spectra against other spectra instead of against protein sequences. Second, spectral networks find spectra from related peptides even before considering their possible identifications. Third, spectral networks determine consensus identifications from sets of spectra from related peptides instead of separately attempting to identify one spectrum at a time. Even though spectral networks algorithms are still in their infancy, they have already delivered the longest and most accurate de novo sequences to date, revealed a new route for the discovery of unexpected post-translational modifications and highly-modified peptides, enabled automated sequencing of cyclic non-ribosomal peptides with unknown amino acids and are now defining a novel approach for mapping the entire molecular output of biological systems that is suitable for analysis with tandem mass spectrometry. Here we review the current state of spectral networks algorithms and discuss possible future directions for automated interpretation of spectra from any class of molecules.     

PTM MarkerFinder,a software tool to detect and validate spectra from peptides carrying post‐translational modifications

Mass spectrometry (MS) analysis of peptides carrying post‐translational modifications is challenging due to the instability of some modifications during MS analysis. However, glycopeptides as well as acetylated, methylated and other modified peptides release specific fragment ions during CID (collision‐induced dissociation) and HCD (higher energy collisional dissociation) fragmentation. These fragment ions can be used to validate the presence of the PTM on the peptide. Here, we present PTM MarkerFinder, a software tool that takes advantage of such marker ions. PTM MarkerFinder screens the MS/MS spectra in the output of a database search (i.e., Mascot) for marker ions specific for selected PTMs. Moreover, it reports and annotates the HCD and the corresponding electron transfer dissociation (ETD) spectrum (when present), and summarizes information on the type, number, and ratios of marker ions found in the data set. In the present work, a sample containing enriched N‐acetylhexosamine (HexNAc) glycopeptides from yeast has been analyzed by liquid chromatography‐mass spectrometry on an LTQ Orbitrap Velos using both HCD and ETD fragmentation techniques. The identification result (Mascot .dat file) was submitted as input to PTM MarkerFinder and screened for HexNAc oxonium ions. The software output has been used for high‐throughput validation of the identification results.     

Mass spectrometry of peptides and proteins

This tutorial article introduces mass spectrometry (MS) for peptide fragmentation and protein identification. The current approaches being used for protein identification include top-down and bottom-up sequencing. Top-down sequencing, a relatively new approach that involves fragmenting intact proteins directly, is briefly introduced. Bottom-up sequencing, a traditional approach that fragments peptides in the gas phase after protein digestion, is discussed in more detail. The most widely used ion activation and dissociation process, gas-phase collision-activated dissociation (CAD), is discussed from a practical point of view. Infrared multiphoton dissociation (IRMPD) and electron capture dissociation (ECD) are introduced as two alternative dissociation methods. For spectral interpretation, the common fragment ion types in peptide fragmentation and their structures are introduced; the influence of instrumental methods on the fragmentation pathways and final spectra are discussed. A discussion is also provided on the complications in sample preparation for MS analysis. The final section of this article provides a brief review of recent research efforts on different algorithmic approaches being developed to improve protein identification searches.     

Application of different fragmentation techniques for the analysis of phosphopeptides using a hybrid linear ion trap-FTICR mass spectrometer

Electron capture dissociation (ECD) and infrared multiphoton dissociation (IRMPD) present complementary techniques for the fragmentation of peptides and proteins in Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) in addition to the commonly used collisionally activated dissociation (CAD). Both IRMPD and ECD have been shown to be applicable for an efficient sequencing of peptides and proteins, whereas ECD has proven especially valuable for mapping labile posttranslational modifications (PTMs), such as phosphorylations. In this work, we compare the different fragmentation techniques and MS detection in a linear ion trap and the ICR cell with respect to their abilities to efficiently identify and characterize phosphorylated peptides. For optimizing fragmentation parameters, sets of synthetic peptides with molecular weights ranging from approximately 1 to 4 kDa and different levels of phosphorylation were analyzed. The influence of spectrum averaging for obtaining high-quality spectra was investigated. Our results show that the fragmentation methods CAD and ECD allow for a facilitated analysis of phosphopeptides; however, their general applicability for analyzing phosphopeptides has to be evaluated in each specific case with respect to the given analytical task. The major advantage of complementary peptide cleavages by combining different fragmentation methods is the increased amount of information that is obtained during MS/MS analysis of modified peptides. On the basis of the obtained results, we are planning to design LC time-scale compatible, data-dependent MS/MS methods using the different fragmentation techniques in order to improve the identification and characterization of phosphopeptides.     

Higher-energy C-trap dissociation for peptide modification analysis

Peptide sequencing is the basis of mass spectrometry-driven proteomics. Here we show that in the linear ion trap-orbitrap mass spectrometer (LTQ Orbitrap) peptide ions can be efficiently fragmented by high-accuracy and full-mass-range tandem mass spectrometry (MS/MS) via higher-energy C-trap dissociation (HCD). Immonium ions generated via HCD pinpoint modifications such as phosphotyrosine with very high confidence. Additionally we show that an added octopole collision cell facilitates de novo sequencing.     

VEMS 3.0: algorithms and computational tools for tandem mass spectrometry based identification of post-translational modifications in proteins

Protein and peptide mass analysis and amino acid sequencing by mass spectrometry is widely used for identification and annotation of post-translational modifications (PTMs) in proteins. Modification-specific mass increments, neutral losses or diagnostic fragment ions in peptide mass spectra provide direct evidence for the presence of post-translational modifications, such as phosphorylation, acetylation, methylation or glycosylation. However, the commonly used database search engines are not always practical for exhaustive searches for multiple modifications and concomitant missed proteolytic cleavage sites in large-scale proteomic datasets, since the search space is dramatically expanded. We present a formal definition of the problem of searching databases with tandem mass spectra of peptides that are partially (sub-stoichiometrically) modified. In addition, an improved search algorithm and peptide scoring scheme that includes modification specific ion information from MS/MS spectra was implemented and tested using the Virtual Expert Mass Spectrometrist (VEMS) software. A set of 2825 peptide MS/MS spectra were searched with 16 variable modifications and 6 missed cleavages. The scoring scheme returned a large set of post-translationally modified peptides including precise information on modification type and position. The scoring scheme was able to extract and distinguish the near-isobaric modifications of trimethylation and acetylation of lysine residues based on the presence and absence of diagnostic neutral losses and immonium ions. In addition, the VEMS software contains a range of new features for analysis of mass spectrometry data obtained in large-scale proteomic experiments. Windows binaries are available at http://www.yass.sdu.dk/.     

Analysis of the Arabidopsis cytosolic ribosome proteome provides detailed insights into its components and their post-translational modification

Finding gene-specific peptides by mass spectrometry analysis to pinpoint gene loci responsible for particular protein products is a major challenge in proteomics especially in highly conserved gene families in higher eukaryotes. We used a combination of in silico approaches coupled to mass spectrometry analysis to advance the proteomics insight into Arabidopsis cytosolic ribosomal composition and its post-translational modifications. In silico digestion of all 409 ribosomal protein sequences in Arabidopsis defined the proportion of theoretical gene-specific peptides for each gene family and highlighted the need for low m/z cutoffs of MS ion selection for MS/MS to characterize low molecular weight, highly basic ribosomal proteins. We undertook an extensive MS/MS survey of the cytosolic ribosome using trypsin and, when required, chymotrypsin and pepsin. We then used custom software to extract and filter peptide match information from Mascot result files and implement high confidence criteria for calling gene-specific identifications based on the highest quality unambiguous spectra matching exclusively to certain in silico predicted gene- or gene family-specific peptides. This provided an in-depth analysis of the protein composition based on 1446 high quality MS/MS spectra matching to 795 peptide sequences from ribosomal proteins. These identified peptides from five gene families of ribosomal proteins not identified previously, providing experimental data on 79 of the 80 different types of ribosomal subunits. We provide strong evidence for gene-specific identification of 87 different ribosomal proteins from these 79 families. We also provide new information on 30 specific sites of co- and post-translational modification of ribosomal proteins in Arabidopsis by initiator methionine removal, N-terminal acetylation, N-terminal methylation, lysine N-methylation, and phosphorylation. These site-specific modification data provide a wealth of resources for further assessment of the role of ribosome modification in influencing translation in Arabidopsis.     

Cycloquest: identification of cyclopeptides via database search of their mass spectra against genome databases

Hundreds of ribosomally synthesized cyclopeptides have been isolated from all domains of life, the vast majority having been reported in the last 15 years. Studies of cyclic peptides have highlighted their exceptional potential both as stable drug scaffolds and as biomedicines in their own right. Despite this, computational techniques for cyclopeptide identification are still in their infancy, with many such peptides remaining uncharacterized. Tandem mass spectrometry has occupied a niche role in cyclopeptide identification, taking over from traditional techniques such as nuclear magnetic resonance spectroscopy (NMR). MS/MS studies require only picogram quantities of peptide (compared to milligrams for NMR studies) and are applicable to complex samples, abolishing the requirement for time-consuming chromatographic purification. While database search tools such as Sequest and Mascot have become standard tools for the MS/MS identification of linear peptides, they are not applicable to cyclopeptides, due to the parent mass shift resulting from cyclization and different fragmentation patterns of cyclic peptides. In this paper, we describe the development of a novel database search methodology to aid in the identification of cyclopeptides by mass spectrometry and evaluate its utility in identifying two peptide rings from Helianthus annuus, a bacterial cannibalism factor from Bacillus subtilis, and a θ-defensin from Rhesus macaque.     

Enrichment and analysis of nonenzymatically glycated peptides: boronate affinity chromatography coupled with electron-transfer dissociation mass spectrometry

Nonenzymatic glycation of peptides and proteins by d-glucose has important implications in the pathogenesis of diabetes mellitus, particularly in the development of diabetic complications. However, no effective high-throughput methods exist for identifying proteins containing this low-abundance post-translational modification in bottom-up proteomic studies. In this report, phenylboronate affinity chromatography was used in a two-step enrichment scheme to selectively isolate first glycated proteins and then glycated, tryptic peptides from human serum glycated in vitro. Enriched peptides were subsequently analyzed by alternating electron-transfer dissociation (ETD) and collision induced dissociation (CID) tandem mass spectrometry. ETD fragmentation mode permitted identification of a significantly higher number of glycated peptides (87.6% of all identified peptides) versus CID mode (17.0% of all identified peptides), when utilizing enrichment on first the protein and then the peptide level. This study illustrates that phenylboronate affinity chromatography coupled with LC-MS/MS and using ETD as the fragmentation mode is an efficient approach for analysis of glycated proteins and may have broad application in studies of diabetes mellitus.     

Methods for analyzing peptides and proteins on a chromatographic timescale by electron-transfer dissociation mass spectrometry

Advancement in proteomics research relies on the development of new, innovative tools for identifying and characterizing proteins. Here, we describe a protocol for analyzing peptides and proteins on a chromatographic timescale by coupling nanoflow reverse-phase (RP) liquid chromatography (LC) to electron-transfer dissociation (ETD) mass spectrometry. For this protocol, proteins can be proteolytically digested before ETD analysis, although digestion is not necessary for all applications. Proteins 相似文献   

Recent developments and applications of electron transfer dissociation mass spectrometry in proteomics

Electron transfer dissociation (ETD) has been developed recently as an efficient ion fragmentation technique in mass spectrometry (MS), being presently considered a step forward in proteomics with real perspectives for improvement, upgrade and application. Available also on affordable ion trap mass spectrometers, ETD induces specific N–Cα bond cleavages of the peptide backbone with the preservation of the post-translational modifications and generation of product ions that are diagnostic for the modification site(s). In addition, in the last few years ETD contributed significantly to the development of top-down approaches which enable tandem MS of intact protein ions. The present review, covering the last 5 years highlights concisely the major achievements and the current applications of ETD fragmentation technique in proteomics. An ample part of the review is dedicated to ETD contribution in the elucidation of the most common posttranslational modifications, such as phosphorylation and glycosylation. Further, a brief section is devoted to top-down by ETD method applied to intact proteins. As the last few years have witnessed a major expansion of the microfluidics systems, a few considerations on ETD in combination with chip-based nanoelectrospray (nanoESI) as a platform for high throughput top-down proteomics are also presented.