Electron transfer dissociation mass spectrometry in proteomics

Mass spectrometry has rapidly evolved to become the platform of choice for proteomic analysis. While CID remains the major fragmentation method for peptide sequencing, electron transfer dissociation (ETD) is emerging as a complementary method for the characterization of peptides and post-translational modifications (PTMs). Here, we review the evolution of ETD and some of its newer applications including characterization of PTMs, non-tryptic peptides and intact proteins. We will also discuss some of the unique features of ETD such as its complementarity with CID and the use of alternating CID/ETD along with issues pertaining to analysis of ETD data. The potential of ETD for applications such as multiple reaction monitoring and proteogenomics in the future will also be discussed.     

Effectiveness of CID, HCD, and ETD with FT MS/MS for degradomic-peptidomic analysis: comparison of peptide identification methods

We report on the effectiveness of CID, HCD, and ETD for LC-FT MS/MS analysis of peptides using a tandem linear ion trap-Orbitrap mass spectrometer. A range of software tools and analysis parameters were employed to explore the use of CID, HCD, and ETD to identify peptides (isolated from human blood plasma) without the use of specific "enzyme rules". In the evaluation of an FDR-controlled SEQUEST scoring method, the use of accurate masses for fragments increased the number of identified peptides (by ~50%) compared to the use of conventional low accuracy fragment mass information, and CID provided the largest contribution to the identified peptide data sets compared to HCD and ETD. The FDR-controlled Mascot scoring method provided significantly fewer peptide identifications than SEQUEST (by 1.3-2.3 fold) and CID, HCD, and ETD provided similar contributions to identified peptides. Evaluation of de novo sequencing and the UStags method for more intense fragment ions revealed that HCD afforded more contiguous residues (e.g., ≥ 7 amino acids) than either CID or ETD. Both the FDR-controlled SEQUEST and Mascot scoring methods provided peptide data sets that were affected by the decoy database used and mass tolerances applied (e.g., identical peptides between data sets could be limited to ~70%), while the UStags method provided the most consistent peptide data sets (>90% overlap). The m/z ranges in which CID, HCD, and ETD contributed the largest number of peptide identifications were substantially overlapping. This work suggests that the three peptide ion fragmentation methods are complementary and that maximizing the number of peptide identifications benefits significantly from a careful match with the informatics tools and methods applied. These results also suggest that the decoy strategy may inaccurately estimate identification FDRs.     

Improved peptide identification by targeted fragmentation using CID, HCD and ETD on an LTQ-Orbitrap Velos

Over the past decade peptide sequencing by collision induced dissociation (CID) has become the method of choice in mass spectrometry-based proteomics. The development of alternative fragmentation techniques such as electron transfer dissociation (ETD) has extended the possibilities within tandem mass spectrometry. Recent advances in instrumentation allow peptide fragment ions to be detected with high speed and sensitivity (e.g., in a 2D or 3D ion trap) or at high resolution and high mass accuracy (e.g., an Orbitrap or a ToF). Here, we describe a comprehensive experimental comparison of using ETD, ion-trap CID, and beam type CID (HCD) in combination with either linear ion trap or Orbitrap readout for the large-scale analysis of tryptic peptides. We investigate which combination of fragmentation technique and mass analyzer provides the best performance for the analysis of distinct peptide populations such as N-acetylated, phosphorylated, and tryptic peptides with up to two missed cleavages. We found that HCD provides more peptide identifications than CID and ETD for doubly charged peptides. In terms of Mascot score, ETD FT outperforms the other techniques for peptides with charge states higher than 2. Our data shows that there is a trade-off between spectral quality and speed when using the Orbitrap for fragment ion detection. We conclude that a decision-tree regulated combination of higher-energy collisional dissociation (HCD) and ETD can improve the average Mascot score.     

Large-scale Identification of Endogenous Secretory Peptides Using Electron Transfer Dissociation Mass Spectrometry

Mass spectrometry-based unbiased analysis of the full complement of secretory peptides is expected to facilitate the identification of unknown biologically active peptides. However, tandem MS sequencing of endogenous peptides in their native form has proven difficult because they show size heterogeneity and contain multiple internal basic residues, the characteristics not found in peptide fragments produced by in vitro digestion. Endogenous peptides remain largely unexplored by electron transfer dissociation (ETD), despite its widespread use in bottom-up proteomics. We used ETD, in comparison to collision induced dissociation (CID), to identify endogenous peptides derived from secretory granules of a human endocrine cell line. For mass accuracy, both MS and tandem MS were analyzed on an Orbitrap. CID and ETD, performed in different LC-MS runs, resulted in the identification of 795 and 569 unique peptides (ranging from 1000 to 15000 Da), respectively, with an overlap of 397. Peptides larger than 3000 Da accounted for 54% in CID and 46% in ETD identifications. Although numerically outperformed by CID, ETD provided more extensive fragmentation, leading to the identification of peptides that are not reached by CID. This advantage was demonstrated in identifying a new antimicrobial peptide from neurosecretory protein VGF (non-acronymic), VGF[554–577]-NH₂, or in differentiating nearly isobaric peptides (mass difference less than 2 ppm) that arise from alternatively spliced exons of the gastrin-releasing peptide gene. CID and ETD complemented each other to add to our knowledge of the proteolytic processing sites of proteins implicated in the regulated secretory pathway. An advantage of the use of both fragmentation methods was also noted in localization of phosphorylation sites. These findings point to the utility of ETD mass spectrometry in the global study of endogenous peptides, or peptidomics.Biologically active peptides, commonly known as peptide hormones and antimicrobial peptides, belong to a defined set of endogenous peptides that gain specialized functions not ascribed to original precursor proteins. For a precursor protein to generate such peptides, it must undergo specific cleavages and in some cases needs to be modified at specific sites (1). This limited cleavage, or proteolytic processing, represents an important cellular mechanism by which molecular diversity of proteins is increased at the post-translational level. In the postgenome era, it is being recognized that localization of processing sites in secretory proteins facilitates the identification of biologically active peptides. A standard approach to determining such sites is to use a panel of antibodies directed against different regions of a target protein (2). However, it is practically impossible to prepare antibodies that can thoroughly cover potential processing products arising from the precursor. Alternatively, mass spectrometry-assisted unbiased analysis of endogenous peptides may be a major step toward elucidating proteolytic processing (3).In neurons and endocrine cells, a majority of biologically active peptides are released via the regulated secretory pathway. They are stored in secretory granules and await secretion until the cells receive an exocytotic stimulus. Owing to their compartmentalization, secretory peptides can be noninvasively recovered in culture supernatant. We have shown that a data set of endogenous peptide sequences that are collected by this procedure is applicable to infer processing sites, as well as to identify bona fide processing products (4). Rather than being digested, every endogenous peptide should be analyzed in its native form to understand how the peptide is generated and subsequently degraded. However, it remains a challenge to identify endogenous peptides because of size heterogeneity (ranging from 3 aa to 100 aa). For example, thyrotropin-releasing hormone is a small 3-aa peptide, human adrenomedullin occurs as a 52-aa peptide, and a 98-aa N-terminal propeptide from the atrial natriuretic peptide precursor is found in the circulation. Unlike digested protein fragments used in bottom-up proteomics, C termini of these endogenous peptides are not restricted to specific residues. Furthermore, proteolytic processing leads to the production of peptides containing multiple internal basic residues, for which collision induced dissociation (CID)¹ shows limited performance (5).A solution to address this issue in endogenous peptide sequencing might be the use of electron transfer dissociation (ETD) tandem mass spectrometry, which has been shown to provide a more complete series of fragment ions and hence a more confident sequence identification, along with the ability to leave labile post-translational modifications intact (6–10). The benefit of ETD in bottom-up proteomics has been increasingly documented, whereas endogenous peptides remain largely unexplored by ETD, despite the expectation that ETD would improve sequencing for larger peptides. In the few studies on endogenous peptides (11, 12), ETD did not cover large peptides exceeding 5000 Da. Because we have used CID to facilitate the discovery of previously unknown biologically active peptides (3, 13, 14), we were interested to see if ETD would be helpful to identify endogenous peptides that have escaped identification by CID. Here we conducted a large-scale identification of endogenous secretory peptides, ranging from 1000 to 15000 Da, using CID and ETD. We describe the merits of using ETD, in connection with CID, in peptidomics studies. The most significant finding is the identification of a previously unknown peptide, VGF[554–577]-NH₂, which was sequenced solely by ETD. This peptide was found to have antimicrobial activity.     

On-line LC-MS approach combining collision-induced dissociation (CID), electron-transfer dissociation (ETD), and CID of an isolated charge-reduced species for the trace-level characterization of proteins with post-translational modifications

We have expanded our recent on-line LC-MS platform for large peptide analysis to combine collision-induced dissociation (CID), electron-transfer dissociation (ETD), and CID of an isolated charge-reduced (CRCID) species derived from ETD to determine sites of phosphorylation and glycosylation modifications, as well as the sequence of large peptide fragments (i.e., 2000-10,000 Da) from complex proteins, such as beta-casein, epidermal growth factor receptor (EGFR), and tissue plasminogen activator (t-PA) at the low femtomol level. The incorporation of an additional CID activation step for a charge-reduced species, isolated from ETD fragment ions, improved ETD fragmentation when precursor ions with high m/z (approximately >1000) were automatically selected for fragmentation. Specifically, the identification of the exact phosphorylation sites was strengthened by the extensive coverage of the peptide sequence with a near-continuous product ion series. The identification of N-linked glycosylation sites in EGFR and an O-linked glycosylation site in t-PA were also improved through the enhanced identification of the peptide backbone sequence of the glycosylated precursors. The new strategy is a good starting survey scan to characterize enzymatic peptide mixtures over a broad range of masses using LC-MS with data-dependent acquisition, as the three activation steps can provide complementary information to each other. In general, large peptides can be extensively characterized by the ETD and CRCID steps, including sites of modification from the generated, near-continuous product ion series, supplemented by the CID-MS2 step. At the same time, small peptides (e.g., 相似文献   

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.     

Systematic evaluation of alternating CID and ETD fragmentation for phosphorylated peptides

CID has become a routine method for fragmentation of peptides in shotgun proteomics, whereas electron transfer dissociation (ETD) has been described as a preferred method for peptides carrying labile PTMs. Though both of these fragmentation techniques have their obvious advantages, they also have their own drawbacks. By combining data from CID and ETD fragmentation, some of these disadvantages can potentially be overcome because of the complementarity of fragment ions produced. To evaluate alternating CID and ETD fragmentation, we analyzed a complex mixture of phosphopeptides on an LTQ-Orbitrap mass spectrometer. When the CID and ETD-derived spectra were searched separately, we observed 2504, 491, 2584, and 3249 phosphopeptide-spectrum matches from CID alone, ETD alone, decision tree-based CID/ETD, and alternating CID and ETD, respectively. Combining CID and ETD spectra prior to database searching should, intuitively, be superior to either method alone. However, when spectra from the alternating CID and ETD method were merged prior to database searching, we observed a reduction in the number of phosphopeptide-spectrum matches. The poorer identification rates observed after merging CID and ETD spectra are a reflection of a lack of optimized search algorithms for carrying out such searches and perhaps inherent weaknesses of this approach. Thus, although alternating CID and ETD experiments for phosphopeptide identification are desirable for increasing the confidence of identifications, merging spectra prior to database search has to be carefully evaluated further in the context of the various algorithms before adopting it as a routine strategy.     

Electron transfer dissociation of iTRAQ labeled peptide ions

Triply and doubly charged iTRAQ ( isobaric tagging for relative and absolute quantitation) labeled peptide cations from a tryptic peptide mixture of bovine carbonic anhydrase II were subjected to electron transfer ion/ion reactions to investigate the effect of charge bearing modifications associated with iTRAQ on the fragmentation pattern. It was noted that electron transfer dissociation (ETD) of triply charged or activated ETD (ETD and supplemental collisional activation of intact electron transfer species) of doubly charged iTRAQ tagged peptide ions yielded extensive sequence information, in analogy with ETD of unmodified peptide ions. That is, addition of the fixed charge iTRAQ tag showed relatively little deleterious effect on the ETD performance of the modified peptides. ETD of the triply charged iTRAQ labeled peptide ions followed by collision-induced dissociation (CID) of the product ion at m/ z 162 yielded the reporter ion at m/ z 116, which is the reporter ion used for quantitation via CID of the same precursor ions. The reporter ion formed via the two-step activation process is expected to provide quantitative information similar to that directly produced from CID. A 103 Da neutral loss species observed in the ETD spectra of all the triply and doubly charged iTRAQ labeled peptide ions is unique to the 116 Da iTRAQ reagent, which implies that this process also has potential for quantitation of peptides/proteins. Therefore, ETD with or without supplemental collisional activation, depending on the precursor ion charge state, has the potential to directly identify and quantify the peptides/proteins simultaneously using existing iTRAQ reagents.     

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.     

Enhanced peptide identification by electron transfer dissociation using an improved Mascot Percolator

Peptide identification using tandem mass spectrometry is a core technology in proteomics. Latest generations of mass spectrometry instruments enable the use of electron transfer dissociation (ETD) to complement collision induced dissociation (CID) for peptide fragmentation. However, a critical limitation to the use of ETD has been optimal database search software. Percolator is a post-search algorithm, which uses semi-supervised machine learning to improve the rate of peptide spectrum identifications (PSMs) together with providing reliable significance measures. We have previously interfaced the Mascot search engine with Percolator and demonstrated sensitivity and specificity benefits with CID data. Here, we report recent developments in the Mascot Percolator V2.0 software including an improved feature calculator and support for a wider range of ion series. The updated software is applied to the analysis of several CID and ETD fragmented peptide data sets. This version of Mascot Percolator increases the number of CID PSMs by up to 80% and ETD PSMs by up to 60% at a 0.01 q-value (1% false discovery rate) threshold over a standard Mascot search, notably recovering PSMs from high charge state precursor ions. The greatly increased number of PSMs and peptide coverage afforded by Mascot Percolator has enabled a fuller assessment of CID/ETD complementarity to be performed. Using a data set of CID and ETcaD spectral pairs, we find that at a 1% false discovery rate, the overlap in peptide identifications by CID and ETD is 83%, which is significantly higher than that obtained using either stand-alone Mascot (69%) or OMSSA (39%). We conclude that Mascot Percolator is a highly sensitive and accurate post-search algorithm for peptide identification and allows direct comparison of peptide identifications using multiple alternative fragmentation techniques.     

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.     

The Generating Function of CID,ETD, and CID/ETD Pairs of Tandem Mass Spectra: Applications to Database Search

Recent emergence of new mass spectrometry techniques (e.g. electron transfer dissociation, ETD) and improved availability of additional proteases (e.g. Lys-N) for protein digestion in high-throughput experiments raised the challenge of designing new algorithms for interpreting the resulting new types of tandem mass (MS/MS) spectra. Traditional MS/MS database search algorithms such as SEQUEST and Mascot were originally designed for collision induced dissociation (CID) of tryptic peptides and are largely based on expert knowledge about fragmentation of tryptic peptides (rather than machine learning techniques) to design CID-specific scoring functions. As a result, the performance of these algorithms is suboptimal for new mass spectrometry technologies or nontryptic peptides. We recently proposed the generating function approach (MS-GF) for CID spectra of tryptic peptides. In this study, we extend MS-GF to automatically derive scoring parameters from a set of annotated MS/MS spectra of any type (e.g. CID, ETD, etc.), and present a new database search tool MS-GFDB based on MS-GF. We show that MS-GFDB outperforms Mascot for ETD spectra or peptides digested with Lys-N. For example, in the case of ETD spectra, the number of tryptic and Lys-N peptides identified by MS-GFDB increased by a factor of 2.7 and 2.6 as compared with Mascot. Moreover, even following a decade of Mascot developments for analyzing CID spectra of tryptic peptides, MS-GFDB (that is not particularly tailored for CID spectra or tryptic peptides) resulted in 28% increase over Mascot in the number of peptide identifications. Finally, we propose a statistical framework for analyzing multiple spectra from the same precursor (e.g. CID/ETD spectral pairs) and assigning p values to peptide-spectrum-spectrum matches.Since the introduction of electron capture dissociation (ECD)1 in 1998 (1), electron-based peptide dissociation technologies have played an important role in analyzing intact proteins and post-translational modifications (2). However, until recently, this research-grade technology was available only to a small number of laboratories because it was commercially unavailable, required experience for operation, and could be implemented only with expensive FT-ICR instruments. The discovery of electron-transfer dissociation (ETD) (3) enabled an ECD-like technology to be implemented in (relatively cheap) ion-trap instruments. Nowadays, many researchers are employing the ETD technology for tandem mass spectra generation (4–9).Although the hardware technologies to generate ETD spectra are maturing rapidly, software technologies to analyze ETD spectra are still in infancy. There are two major approaches to analyzing tandem mass spectra: de novo sequencing and database search. Both approaches find the best-scoring peptide either among all possible peptides (de novo sequencing) or among all peptides in a protein database (database search). Although de novo sequencing is emerging as an alternative to database search, database search remains a more accurate (and thus preferred) method of spectral interpretation, so here we focus on the database search approach.Numerous database search engines are currently available, including SEQUEST (10), Mascot (11), OMSSA (12), X!Tandem (13), and InsPecT (14). However, most of them are inadequate for the analysis of ETD spectra because they are optimized for collision induced dissociation (CID) spectra that show different fragmentation propensities than those of ETD spectra. Additionally, the existing tandem mass spectrometry (MS/MS) tools are biased toward the analysis of tryptic peptides because trypsin is usually used for CID, and thus not suitable for the analysis of nontryptic peptides that are common for ETD. Therefore, even though some database search engines support the analysis of ETD spectra (e.g. SEQUEST, Mascot, and OMSSA), their performance remains suboptimal when it comes to analyzing ETD spectra. Recently, an ETD-specific database search tool (Z-Core) was developed; however it does not significantly improve over OMSSA (15).We present a new database search tool (MS-GFDB) that significantly outperforms existing database search engines in the analysis of ETD spectra, and performs equally well on nontryptic peptides. MS-GFDB employs the generating function approach (MS-GF) that computes rigorous p values of peptide-spectrum matches (PSMs) based on the spectrum-specific score histogram of all peptides (16).² MS-GF p values are dependent only on the PSM (and not on the database), thus can be used as an alternative scoring function for the database search.Computing p values requires a scoring model evaluating qualities of PSMs. MS-GF adopts a probabilistic scoring model (MS-Dictionary scoring model) described in Kim et al., 2009 (17), considering multiple features including product ion types, peak intensities and mass errors. To define the parameters of this scoring model, MS-GF only needs a set of training PSMs.³ This set of PSMs can be obtained in a variety of ways: for example, one can generate CID/ETD pairs and use peptides identified by CID to form PSMs for ETD. Alternatively, one can generate spectra from a purified protein (when PSMs can be inferred from the accurate parent mass alone) or use a previously developed (not necessary optimal) tool to generate training PSMs. From these training PSMs, MS-GF automatically derives scoring parameters without assuming any prior knowledge about the specifics of a particular peptide fragmentation method (e.g. ETD, CID, etc.) and/or proteolytic origin of the peptides. MS-GF was originally designed for the analysis of CID spectra, but now it has been extended to other types of spectra generated by various fragmentation techniques and/or various enzymes. We show that MS-GF can be successfully applied to novel types of spectra (e.g. ETD of Lys-N peptides (18, 19)) by simply retraining scoring parameters without any modification. Note that although the same scoring model is used for different types of spectra, the parameters derived to score different types of spectra are dissimilar.We compared the performance of MS-GFDB with Mascot on a large ETD data set and found that it generated many more peptide identifications for the same false discovery rates (FDR). For example, at 1% peptide level FDR, MS-GFDB identified 9450 unique peptides from 81,864 ETD spectra of Lys-N peptides whereas Mascot only identified 3672 unique peptides, ≈160% increase in the number of peptide identifications (a similar improvement is observed for ETD spectra of tryptic peptides).⁴ MS-GFDB also showed a significant 28% improvement in the number of identified peptides from CID spectra of tryptic peptides (16,203 peptides as compared with 12,658 peptides identified by Mascot).The ETD technology complements rather than replaces CID because both technologies have some advantages: CID for smaller peptides with small charges, ETD for larger and multiply charged peptides (20, 21). An alternative way to utilize ETD is to use it in conjunction with CID because CID and ETD generate complementary sequence information (20, 22, 23). ETD-enabled instruments often support generating both CID and ETD spectra (CID/ETD pairs) for the same peptide. Although the CID/ETD pairs promise a great improvement in peptide identification, the full potential of such pairs has not been fully realized yet. In the case of de novo sequencing, de novo sequencing tools utilizing CID/ETD pairs indeed result in more accurate de novo peptide sequencing than traditional CID-based algorithms (23, 24, 25). However, in the case of database search, the argument that the use of CID/ETD pairs improves peptide identifications remains poorly substantiated. A few tools are developed to use CID/ETD (or CID/ECD) pairs for the database search but they are limited to preprocessing/postprocessing of the spectral data before or following running a traditional database search tool (26, 27). Nielsen et al., 2005 (22) pioneered the combined use of CID and ECD for the database search. Given a CID/ECD pair, they generated a combined spectrum comprised only of complementary pairs of peaks, and searched it with Mascot.⁵ However, this approach is hard to generalize to less accurate CID/ETD pairs generated by ion-trap instruments because there is a higher chance that the identified complementary pairs of peaks are spurious. More importantly, using traditional MS/MS tools (such as Mascot) for the database search of the combined spectrum is inappropriate, because they are not optimized for analyzing such combined spectra; a better approach would be to develop a new database search tool tailored for the combined spectrum. Recently, Molina et al., 2008 (26) studied database search of CID/ETD pairs using Spectrum Mill (Agilent Technologies, Santa Clara, CA) and came to a counterintuitive conclusion that using only CID spectra identifies 12% more unique peptides than using CID/ETD pairs. We believe that it is an acknowledgment of limitations of the traditional MS/MS database search tools for the analysis of multiple spectra generated from a single peptide.In this paper, we modify the generating function approach for interpreting CID/ETD pairs and further apply it to improve the database search with CID/ETD pairs. In contrast to previous approaches, our scoring is specially designed to interpret CID/ETD pairs and can be generalized to analyzing any type of multiple spectra generated from a single peptide. When CID/ETD pairs from trypsin digests are used, MS-GFDB identified 13% and 27% more peptides compared with the case when only CID spectra and only ETD spectra are used, respectively. The difference was even more prominent when CID/ETD pairs from Lys-N digests were used, with 41% and 33% improvement over CID only and ETD only, respectively.Assigning a p value to a PSM greatly helped researchers to evaluate the quality of peptide identifications. We now turn to the problem of assigning a p value to a peptide-spectrum-spectrum match (PS²M) when two spectra in PS²M are generated by different fragmentation technologies (e.g. ETD and CID). We argue that assigning statistical significance to a PS²M (or even PSⁿM) is a prerequisite for rigorous CID/ETD analyses. To our knowledge, MS-GFDB is the first tool to generate statistically rigorous p values of PSⁿMs.The MS-GFDB executable and source code is available at the website of Center for Computational Mass Spectrometry at UCSD (http://proteomics.ucsd.edu). It takes a set of spectra (CID, ETD, or CID/ETD pairs) and a protein database as an input and outputs peptide matches. If the input is a set of CID/ETD pairs, it outputs the best scoring peptide matches and their p values (1) using only CID spectra, (2) using only ETD spectra, and (3) using combined spectra of CID/ETD pairs.     

Decision tree-driven tandem mass spectrometry for shotgun proteomics

Mass spectrometry has become a key technology for modern large-scale protein sequencing. Tandem mass spectrometry, the process of peptide ion dissociation followed by mass-to-charge ratio (m/z) analysis, is the critical component for peptide identification. Recent advances in mass spectrometry now permit two discrete, and complementary, types of peptide ion fragmentation: collision-activated dissociation (CAD) and electron transfer dissociation (ETD) on a single instrument. To exploit this complementarity and increase sequencing success rates, we designed and embedded a data-dependent decision tree algorithm (DT) to make unsupervised, real-time decisions of which fragmentation method to use based on precursor charge and m/z. Applying the DT to large-scale proteome analyses of Saccharomyces cerevisiae and human embryonic stem cells, we identified 53,055 peptides in total, which was greater than by using CAD (38,293) or ETD (39,507) alone. In addition, the DT method also identified 7,422 phosphopeptides, compared to either 2,801 (CAD) or 5,874 (ETD) phosphopeptides.     

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.     

生物活性肽蛋白质组分分离与鉴定方法的建立

目的:评估大规模蛋白质组分离与鉴定技术策略在生物活性肽研究中的应用价值。方法:采用全溶液酶解及胶内分离与酶解方法分离生物活性肽;肽段离子阱串联质谱鉴定时,采用碰撞诱导解离与电子转移解离2种互补的肽段碎裂模式。结果:几种方法联用,鉴定到复杂生物活性肽样品中236个多肽大分子;不同分离和鉴定策略显示出良好的互补性,基于凝胶电泳分离的策略提供了最好的鉴定效果。结论:大规模的蛋白质组学分离与鉴定技术策略可以有效应用于生物活性肽组分的表征。     

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.     

De novo peptide sequencing using CID and HCD spectra pairs

In tandem mass spectrometry (MS/MS), there are several different fragmentation techniques possible, including, collision‐induced dissociation (CID) higher energy collisional dissociation (HCD), electron‐capture dissociation (ECD), and electron transfer dissociation (ETD). When using pairs of spectra for de novo peptide sequencing, the most popular methods are designed for CID (or HCD) and ECD (or ETD) spectra because of the complementarity between them. Less attention has been paid to the use of CID and HCD spectra pairs. In this study, a new de novo peptide sequencing method is proposed for these spectra pairs. This method includes a CID and HCD spectra merging criterion and a parent mass correction step, along with improvements to our previously proposed algorithm for sequencing merged spectra. Three pairs of spectral datasets were used to investigate and compare the performance of the proposed method with other existing methods designed for single spectrum (HCD or CID) sequencing. Experimental results showed that full‐length peptide sequencing accuracy was increased significantly by using spectra pairs in the proposed method, with the highest accuracy reaching 81.31%.     

Large Scale Localization of Protein Phosphorylation by Use of Electron Capture Dissociation Mass Spectrometry

We used on-line electron capture dissociation (ECD) for the large scale identification and localization of sites of phosphorylation. Each FT-ICR ECD event was paired with a linear ion trap collision-induced dissociation (CID) event, allowing a direct comparison of the relative merits of ECD and CID for phosphopeptide identification and site localization. Linear ion trap CID was shown to be most efficient for phosphopeptide identification, whereas FT-ICR ECD was superior for localization of sites of phosphorylation. The combination of confident CID and ECD identification and confident CID and ECD localization is particularly valuable in cases where a phosphopeptide is identified just once within a phosphoproteomics experiment.Phosphorylation is an important protein post-translational modification. Phosphoproteomics experiments have successfully identified thousands of phosphorylation sites, predominantly using CID with relatively low resolution ion trap detection (1–3). For phosphoproteomics data to be of most use to the wider biology community, two key criteria should be met: the phosphopeptide identifications should be correct, and the sites of phosphorylation should be correctly localized. In practice it is not possible to guarantee the accuracy of identifications and site localizations; however, it is possible to include some measure of the confidence in both these results for each phosphopeptide. Database search algorithms give output such as expectation values or similar scores, which can be used to gauge the strength of an identification (4, 5). Recently algorithms have been introduced that give similar confidence scores for phosphorylation site localization (2, 3, 6–8).Electron capture dissociation (ECD)¹ is a radical-driven fragmentation technique that provides an alternative to slow heating CID fragmentation (9). In contrast to CID fragmentation, labile modifications are usually retained intact upon ECD peptide backbone cleavage. ECD has therefore been applied to the analysis of post-translationally modified proteins almost since its inception (10–13). ECD efficiency has improved to the point where on-line LC-MS/MS experiments are feasible; however, the amount of precursor required for such analyses remains significantly greater than for corresponding CID experiments (14–16). ECD is effectively restricted to FT-ICR mass spectrometers. Although ECD has been demonstrated in ion trap instruments, to date these demonstrations have consisted only of direct infusion of known standards (17, 18). The recently developed technique of electron transfer dissociation (ETD) has allowed similar radical fragmentation to be obtained in ion trap mass spectrometers (19). Large scale comparisons of CID and ETD have been carried out for unmodified peptides (20, 21). The increase in speed and sensitivity, albeit at the expense of resolution, has also allowed ETD to be used in phosphoproteomics analyses (22, 23). These studies demonstrated that ETD can efficiently identify phosphopeptides on a chromatographic time scale. Molina et al. (22) compared alternating CID and ETD fragmentation of the same precursors (for an unspecified number of precursors) and found that ETD gave greater peptide sequence coverage. This was assumed to result in improved phosphorylation site localization; however, neither study calculated confidence scores for site localization.The benefits of ECD fragmentation have been demonstrated for various single phosphoproteins and simple mixtures (24–29); however, no large scale comparison of CID and ECD for phosphoprotein analysis has been carried out. In this context, we present a phosphoproteomics data set obtained using both CID and ECD tandem mass spectrometric techniques. Particular attention was paid to the confident localization of sites of phosphorylation within the identified phosphopeptides.     

Comparison of vacuum matrix-assisted laser desorption/ionization (MALDI) and atmospheric pressure MALDI (AP-MALDI) tandem mass spectrometry of 2-dimensional separated and trypsin-digested glomerular proteins for database search derived identification

Mass spectrometric based sequencing of enzymatic generated peptides is widely used to obtain specific sequence tags allowing the unambiguous identification of proteins. In the present study, two types of desorption/ionization techniques combined with different modes of ion dissociation, namely vacuum matrix-assisted laser desorption/ionization (vMALDI) high energy collision induced dissociation (CID) and post-source decay (PSD) as well as atmospheric pressure (AP)-MALDI low energy CID, were applied for the fragmentation of singly protonated peptide ions, which were derived from two-dimensional separated, silver-stained and trypsin-digested hydrophilic as well as hydrophobic glomerular proteins. Thereby, defined properties of the individual fragmentation pattern generated by the specified modes could be observed. Furthermore, the compatibility of the varying PSD and CID (MS/MS) data with database search derived identification using two public accessible search algorithms has been evaluated. The peptide sequence tag information obtained by PSD and high energy CID enabled in the majority of cases an unambiguous identification. In contrast, part of the data obtained by low energy CID were not assignable using similar search parameters and therefore no clear results were obtainable. The knowledge of the properties of available MALDI-based fragmentation techniques presents an important factor for data interpretation using public accessible search algorithms and moreover for the identification of two-dimensional gel separated proteins.     

Improving Software Performance for Peptide Electron Transfer Dissociation Data Analysis by Implementation of Charge State- and Sequence-Dependent Scoring

The use of electron transfer dissociation (ETD) fragmentation for analysis of peptides eluting in liquid chromatography tandem mass spectrometry experiments is increasingly common and can allow identification of many peptides and proteins in complex mixtures. Peptide identification is performed through the use of search engines that attempt to match spectra to peptides from proteins in a database. However, software for the analysis of ETD fragmentation data is currently less developed than equivalent algorithms for the analysis of the more ubiquitous collision-induced dissociation fragmentation spectra. In this study, a new scoring system was developed for analysis of peptide ETD fragmentation data that varies the ion type weighting depending on the precursor ion charge state and peptide sequence. This new scoring regime was applied to the analysis of data from previously published results where four search engines (Mascot, Open Mass Spectrometry Search Algorithm (OMSSA), Spectrum Mill, and X!Tandem) were compared (Kandasamy, K., Pandey, A., and Molina, H. (2009) Evaluation of several MS/MS search algorithms for analysis of spectra derived from electron transfer dissociation experiments. Anal. Chem. 81, 7170–7180). Protein Prospector identified 80% more spectra at a 1% false discovery rate than the most successful alternative searching engine in this previous publication. These results suggest that other search engines would benefit from the application of similar rules.The recently developed fragmentation approach of electron transfer dissociation (ETD)¹ has become a genuine alternative to the more ubiquitous collision-induced dissociation (CID) for high throughput and high sensitivity proteomic analysis (1–3). ETD (4) and the related fragmentation process electron capture dissociation (ECD) (5) have been demonstrated to have particular advantages for the analysis of large peptides and small proteins (6–8) as well as the analysis of peptides bearing labile post-translational modifications (9–11). The results achieved through ETD and ECD analysis have been shown to be highly complementary to those obtained through CID fragmentation analysis, both through increasing confidence in particular identifications of peptides and also by allowing identification of extra components in complex mixtures (10, 12, 13). As CID and ETD can be sequentially or alternatively performed on precursor ions in the same mass spectrometric run, it is expected that the combined use of these two fragmentation analysis techniques will become increasingly common to enable more comprehensive sample analysis.Software for analysis of CID spectra is significantly more advanced than that for ECD/ETD data. This is partly because the behavior of peptides under CID fragmentation is better characterized and understood so software has been developed that is better able to predict the fragment ions expected. The fragment ion types observed in ETD and ECD are largely known (5, 14, 15), but information about the frequency and peak intensities of the different ion types observed is less well documented.We recently performed a study to characterize how frequently the different fragment ion types are detected in ETD spectra when analyzing complex digest mixtures produced by proteolytic enzymes or chemical cleavage reagents of different sequence specificity (16). These results were analyzed with respect to precursor charge state and location of basic residues, which were both shown to be significant factors in controlling the fragment ion types observed. The results showed that ETD spectra of doubly charged precursor ions produced very different fragment ions depending on the location of a basic residue in the sequence.Based on this statistical analysis of ETD data from a diverse range of peptides (16), in the present study, a new scoring system was developed and implemented in the search engine Batch-Tag within Protein Prospector that adjusts the weighting for different fragment ion types based on the precursor charge state and the presence of basic amino acid residues at either peptide terminus. The results using this new scoring system were compared with the previous generation of Batch-Tag, which used ion score weightings based on the average frequency of observation of different fragment types in ETD spectra of tryptic peptides and used the same scoring irrespective of precursor charge and sequence. The performance of this new scoring was also compared with those reported by other search engines using results previously published from a large standard data set (17). The new scoring system allowed identification of significantly more spectra than achieved with the previous scoring system. It also assigned 80% more spectra than the most successful of the compared search engines when using the same false discovery rate threshold.