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.     

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.     

High-throughput Database Search and Large-scale Negative Polarity Liquid Chromatography–Tandem Mass Spectrometry with Ultraviolet Photodissociation for Complex Proteomic Samples

The use of ultraviolet photodissociation (UVPD) for the activation and dissociation of peptide anions is evaluated for broader coverage of the proteome. To facilitate interpretation and assignment of the resulting UVPD mass spectra of peptide anions, the MassMatrix database search algorithm was modified to allow automated analysis of negative polarity MS/MS spectra. The new UVPD algorithms were developed based on the MassMatrix database search engine by adding specific fragmentation pathways for UVPD. The new UVPD fragmentation pathways in MassMatrix were rigorously and statistically optimized using two large data sets with high mass accuracy and high mass resolution for both MS¹ and MS² data acquired on an Orbitrap mass spectrometer for complex Halobacterium and HeLa proteome samples. Negative mode UVPD led to the identification of 3663 and 2350 peptides for the Halo and HeLa tryptic digests, respectively, corresponding to 655 and 645 peptides that were unique when compared with electron transfer dissociation (ETD), higher energy collision-induced dissociation, and collision-induced dissociation results for the same digests analyzed in the positive mode. In sum, 805 and 619 proteins were identified via UVPD for the Halobacterium and HeLa samples, respectively, with 49 and 50 unique proteins identified in contrast to the more conventional MS/MS methods. The algorithm also features automated charge determination for low mass accuracy data, precursor filtering (including intact charge-reduced peaks), and the ability to combine both positive and negative MS/MS spectra into a single search, and it is freely open to the public. The accuracy and specificity of the MassMatrix UVPD search algorithm was also assessed for low resolution, low mass accuracy data on a linear ion trap. Analysis of a known mixture of three mitogen-activated kinases yielded similar sequence coverage percentages for UVPD of peptide anions versus conventional collision-induced dissociation of peptide cations, and when these methods were combined into a single search, an increase of up to 13% sequence coverage was observed for the kinases. The ability to sequence peptide anions and cations in alternating scans in the same chromatographic run was also demonstrated. Because ETD has a significant bias toward identifying highly basic peptides, negative UVPD was used to improve the identification of the more acidic peptides in conjunction with positive ETD for the more basic species. In this case, tryptic peptides from the cytosolic section of HeLa cells were analyzed by polarity switching nanoLC-MS/MS utilizing ETD for cation sequencing and UVPD for anion sequencing. Relative to searching using ETD alone, positive/negative polarity switching significantly improved sequence coverages across identified proteins, resulting in a 33% increase in unique peptide identifications and more than twice the number of peptide spectral matches.The advent of new high-performance tandem mass spectrometers equipped with the most versatile collision- and electron-based activation methods and ever more powerful database search algorithms has catalyzed tremendous progress in the field of proteomics (1–4). Despite these advances in instrumentation and methodologies, there are few methods that fully exploit the information available from the acidic proteome or acidic regions of proteins. Typical high-throughput, bottom-up workflows consist of the chromatographic separation of complex mixtures of digested proteins followed by online mass spectrometry (MS) and MSⁿ analysis. This bottom-up approach remains the most popular strategy for protein identification, biomarker discovery, quantitative proteomics, and elucidation of post-translational modifications. To date, proteome characterization via mass spectrometry has overwhelmingly focused on the analysis of peptide cations (5), resulting in an inherent bias toward basic peptides that easily ionize under acidic mobile phase conditions and positive polarity MS settings. Given that ∼50% of peptides/proteins are naturally acidic (6) and that many of the most important post-translational modifications (e.g. phosphorylation, acetylation, sulfonation, etc.) significantly decrease the isoelectric points of peptides (7, 8), there is a compelling need for better analytical methodologies for characterization of the acidic proteome.A principal reason for the shortage of methods for peptide anion characterization is the lack of MS/MS techniques suitable for the efficient and predictable dissociation of peptide anions. Although there are a growing array of new ion activation methods for the dissociation of peptides, most have been developed for the analysis of positively charged peptides. Collision-induced dissociation (CID)¹ of peptide anions, for example, often yields unpredictable or uninformative fragmentation behavior, with spectra dominated by neutral losses from both precursor and product ions (9), resulting in insufficient peptide sequence information. The two most promising new electron-based methods, electron-capture dissociation and electron-transfer dissociation (ETD), are applicable only to positively charged ions, not to anions (10–13). Because of the known inadequacy of CID and the lack of feasibility of electron-capture dissociation and ETD for peptide anion sequencing, several alternative MSⁿ methods have been developed recently. Electron detachment dissociation using high-energy electrons to induce backbone cleavages was developed for peptide anions (14, 15). Another new technique, negative ETD, entails reactions of radical cation reagents with peptide anions to promote electron transfer from the peptide to the reagent that causes radical-directed dissociation (16, 17). Activated-electron photodetachment dissociation, an MS³ technique, uses UV irradiation to produce intact peptide radical anions, which are then collisionally activated (18, 19). Although they represent inroads in the characterization of peptide anions, these methods also suffer from several significant shortcomings. Electron detachment dissociation and activated-electron photodetachment dissociation are both low-efficiency methods that require long averaging cycles and activation times that range from half a second to multiple seconds, impeding the integration of these methods with chromatographic timescales (14–19). In addition, the fragmentation patterns frequently yield many high-abundance neutral losses from product ions, which clutter the spectra (14–17), and few sequence ions (14, 18, 19). Recently, we reported the use of 193-nm photons (ultraviolet photodissociation (UVPD)) for peptide anion activation, which was shown to yield rich and predictable fragmentation patterns with high sequence coverage on a fast liquid chromatographic timeline (20). This method showed promise for a range of peptide charge states (i.e. from 3- to 1-), as well as for both unmodified and phosphorylated species.Several widely used or commercial database searching techniques are available for automated “bottom-up” analysis of peptide cations; SEQUEST (21), MASCOT (22), OMSSA (23), X! Tandem (24), and MASPIC (25) are all popular choices and yield comparable results (26). MassMatrix (27), a recently introduced searching algorithm, uses a mass accuracy sensitive probability-based scoring scheme for both the total number of matched product ions and the total abundance of matched products. This searching method also utilizes LC retention times to filter false positive peptide matches (28) and has been shown to yield results comparable to or better than those obtained with SEQUEST, MASCOT, OMSSA, and X! Tandem (29). Despite the ongoing innovation in automated peptide cation analysis, there is a lack of publically available methods for automated peptide anion analysis.In this work, we have modified the mass accuracy sensitive probabilistic MassMatrix algorithms to allow database searching of negative polarity MS/MS spectra. The algorithm is specific to the fragmentation behavior generated from 193-nm UVPD of peptide anions. The UVPD pathways in MassMatrix were rigorously and statistically optimized using two large data sets with high mass accuracy and high mass resolution for both MS¹ and MS² data acquired on an Orbitrap mass spectrometer for complex HeLa and Halo proteome samples. For low mass accuracy/low mass resolution data, we also incorporated a charge-state-filtering algorithm that identifies the charge state of each MS/MS spectrum based on the fragmentation patterns prior to searching. MassMatrix not only can analyze both positive and negative polarity LC-MS/MS files separately, but also can combine files from different polarities and different dissociation methods into a single search, thus maximizing the information content for a given proteomics experiment. The explicit incorporation of mass accuracy in the scores for the UVPD MS/MS spectra of peptide anions increases peptide assignments and identifications. Finally, we showcase the utility of integrating MassMatrix searching with positive/negative polarity MS/MS switching (i.e. data-dependent positive ETD and negative UVPD during a single proteomic LC-MS/MS run). MassMatrix is available to the public as a free search engine online.     

Endogenous Peptide Discovery of the Rat Circadian Clock: A FOCUSED STUDY OF THE SUPRACHIASMATIC NUCLEUS BY ULTRAHIGH PERFORMANCE TANDEM MASS SPECTROMETRY*

Understanding how a small brain region, the suprachiasmatic nucleus (SCN), can synchronize the body''s circadian rhythms is an ongoing research area. This important time-keeping system requires a complex suite of peptide hormones and transmitters that remain incompletely characterized. Here, capillary liquid chromatography and FTMS have been coupled with tailored software for the analysis of endogenous peptides present in the SCN of the rat brain. After ex vivo processing of brain slices, peptide extraction, identification, and characterization from tandem FTMS data with <5-ppm mass accuracy produced a hyperconfident list of 102 endogenous peptides, including 33 previously unidentified peptides, and 12 peptides that were post-translationally modified with amidation, phosphorylation, pyroglutamylation, or acetylation. This characterization of endogenous peptides from the SCN will aid in understanding the molecular mechanisms that mediate rhythmic behaviors in mammals.Central nervous system neuropeptides function in cell-to-cell signaling and are involved in many physiological processes such as circadian rhythms, pain, hunger, feeding, and body weight regulation (1–4). Neuropeptides are produced from larger protein precursors by the selective action of endopeptidases, which cleave at mono- or dibasic sites and then remove the C-terminal basic residues (1, 2). Some neuropeptides undergo functionally important post-translational modifications (PTMs),1 including amidation, phosphorylation, pyroglutamylation, or acetylation. These aspects of peptide synthesis impact the properties of neuropeptides, further expanding their diverse physiological implications. Therefore, unveiling new peptides and unreported peptide properties is critical to advancing our understanding of nervous system function.Historically, the analysis of neuropeptides was performed by Edman degradation in which the N-terminal amino acid is sequentially removed. However, analysis by this method is slow and does not allow for sequencing of the peptides containing N-terminal PTMs (5). Immunological techniques, such as radioimmunoassay and immunohistochemistry, are used for measuring relative peptide levels and spatial localization, but these methods only detect peptide sequences with known structure (6). More direct, high throughput methods of analyzing brain regions can be used.Mass spectrometry, a rapid and sensitive method that has been used for the analysis of complex biological samples, can detect and identify the precise forms of neuropeptides without prior knowledge of peptide identity, with these approaches making up the field of peptidomics (7–12). The direct tissue and single neuron analysis by MALDI MS has enabled the discovery of hundreds of neuropeptides in the last decade, and the neuronal homogenate analysis by fractionation and subsequent ESI or MALDI MS has yielded an equivalent number of new brain peptides (5). Several recent peptidome studies, including the work by Dowell et al. (10), have used the specificity of FTMS for peptide discovery (10, 13–15). Here, we combine the ability to fragment ions at ultrahigh mass accuracy (16) with a software pipeline designed for neuropeptide discovery. We use nanocapillary reversed-phase LC coupled to 12 Tesla FTMS for the analysis of peptides present in the suprachiasmatic nucleus (SCN) of rat brain.A relatively small, paired brain nucleus located at the base of the hypothalamus directly above the optic chiasm, the SCN contains a biological clock that generates circadian rhythms in behaviors and homeostatic functions (17, 18). The SCN comprises ∼10,000 cellular clocks that are integrated as a tissue level clock which, in turn, orchestrates circadian rhythms throughout the brain and body. It is sensitive to incoming signals from the light-sensing retina and other brain regions, which cause temporal adjustments that align the SCN appropriately with changes in environmental or behavioral state. Previous physiological studies have implicated peptides as critical synchronizers of normal SCN function as well as mediators of SCN inputs, internal signal processing, and outputs; however, only a small number of peptides have been identified and explored in the SCN, leaving unresolved many circadian mechanisms that may involve peptide function.Most peptide expression in the SCN has only been studied through indirect antibody-based techniques (19–29), although we recently used MS approaches to characterize several peptides detected in SCN releasates (30). Previous studies indicate that the SCN expresses a rich diversity of peptides relative to other brain regions studied with the same techniques. Previously used immunohistochemical approaches are not only inadequate for comprehensively evaluating PTMs and alternate isoforms of known peptides but are also incapable of exhaustively examining the full peptide complement of this complex biological network of peptidergic inputs and intrinsic components. A comprehensive study of SCN peptidomics is required that utilizes high resolution strategies for directly analyzing the peptide content of the neuronal networks comprising the SCN.In our study, the SCN was obtained from ex vivo coronal brain slices via tissue punch and subjected to multistage peptide extraction. The SCN tissue extract was analyzed by FTMS/MS, and the high resolution MS and MS/MS data were processed using ProSightPC 2.0 (16), which allows the identification and characterization of peptides or proteins from high mass accuracy MS/MS data. In addition, the Sequence Gazer included in ProSightPC was used for manually determining PTMs (31, 32). As a result, a total of 102 endogenous peptides were identified, including 33 that were previously unidentified, and 12 PTMs (including amidation, phosphorylation, pyroglutamylation, and acetylation) were found. The present study is the first comprehensive peptidomics study for identifying peptides present within the mammalian SCN. In fact, this is one of the first peptidome studies to work with discrete brain nuclei as opposed to larger brain structures and follows up on our recent report using LC-ion trap for analysis of the peptides in the supraoptic nucleus (33); here, the use of FTMS allows a greater range of PTMs to be confirmed and allows higher confidence in the peptide assignments. This information on the peptides in the SCN will serve as a basis to more exhaustively explore the extent that previously unreported SCN neuropeptides may function in SCN regulation of mammalian circadian physiology.     

Facilitating Protein Disulfide Mapping by a Combination of Pepsin Digestion,Electron Transfer Higher Energy Dissociation (EThcD), and a Dedicated Search Algorithm SlinkS

Disulfide bond identification is important for a detailed understanding of protein structures, which directly affect their biological functions. Here we describe an integrated workflow for the fast and accurate identification of authentic protein disulfide bridges. This novel workflow incorporates acidic proteolytic digestion using pepsin to eliminate undesirable disulfide reshuffling during sample preparation and a novel search engine, SlinkS, to directly identify disulfide-bridged peptides isolated via electron transfer higher energy dissociation (EThcD). In EThcD fragmentation of disulfide-bridged peptides, electron transfer dissociation preferentially leads to the cleavage of the S–S bonds, generating two intense disulfide-cleaved peptides as primary fragment ions. Subsequently, higher energy collision dissociation primarily targets unreacted and charge-reduced precursor ions, inducing peptide backbone fragmentation. SlinkS is able to provide the accurate monoisotopic precursor masses of the two disulfide-cleaved peptides and the sequence of each linked peptide by matching the remaining EThcD product ions against a linear peptide database. The workflow was validated using a protein mixture containing six proteins rich in natural disulfide bridges. Using this pepsin-based workflow, we were able to efficiently and confidently identify a total of 31 unique Cys–Cys bonds (out of 43 disulfide bridges present), with no disulfide reshuffling products detected. Pepsin digestion not only outperformed trypsin digestion in terms of the number of detected authentic Cys–Cys bonds, but, more important, prevented the formation of artificially reshuffled disulfide bridges due to protein digestion under neutral pH. Our new workflow therefore provides a precise and generic approach for disulfide bridge mapping, which can be used to study protein folding, structure, and stability.Disulfide bridges are one of the most common post-translational modifications in proteins (1). The formation of disulfide bonds between cysteine residues is a crucial component in the process of protein folding and plays an important role in stabilizing the tertiary and quaternary structures of proteins (2, 3). Therefore, detecting and characterizing the exact locations of disulfide bonds is an important aspect of proteomics, especially in the context of gaining a comprehensive understanding of protein folding and three-dimensional structures. Moreover, in the use of protein therapeutics (e.g. antibodies), it is also of interest to monitor the reshuffling of disulfide bonds during formulation, storage, and usage, which reflects the antibody structure, stability, and biological function (4).Most knowledge about protein disulfide bridges comes from detailed molecular structures obtained via x-ray crystallography and NMR spectroscopy (5, 6), although regrettably such data are mostly obtained from overexpressed recombinant proteins. Mass spectrometry is gaining importance in the identification and characterization of protein disulfide bridges (7, 8). Some advantages of MS-based approaches include relatively easy sample preparation, short analysis time, and the capability to deal with more complex protein mixtures from endogenous sources. However, the detection of disulfide bridges remains challenging for a few reasons.Firstly, the presence of free sulfhydryl groups can induce undesired sulfhydryl-disulfide reshuffling, especially under neutral and alkaline pH condition. As most standard proteomic strategies use enzymatic digestion in a pH range of 7.5–8.5, undesirable disulfide reshuffling can occur during sample handling (8). Secondly, most of the widely applied database searching programs, such as SEQUEST and Mascot, are not developed, and thus are not suitable, for analyzing fragmentation spectra originating from disulfide-bridged peptides (9).Efforts have been directed at tackling these obstacles and facilitating the identification of authentic disulfide bridges. With respect to sample handling, it has been demonstrated by several groups that disulfide reshuffling can be reduced by (i) blocking free cysteines using alkylating reagents before denaturing the protein, (ii) lowering the pH to 6.0 to 7.0 during tryptic digestion (8, 10–13), and (iii) using the enzyme pepsin under acidic conditions for proteolytic digestion (13–17). Unfortunately, trypsin becomes less efficient and less specific at more acidic pH, and pepsin, which has an optimal pH range of 1–3, tremendously increases the complexity of both protein digests and data analysis (8). Regarding data analysis, one of the current approaches used for the identification of disulfide bridges involves chromatographic comparison between reduced and non-reduced protein digests, with disulfide-bridged peptides appearing only in non-reduced samples (8, 12). Alternatively, disulfide bonds can be identified directly from non-reduced protein digests using an electron transfer dissociation (ETD)¹ MS² and collision-induced dissociation (CID)/higher energy collision dissociation (HCD) MS³ fragmentation scheme (termed the ETD-MS² CID/HCD-MS³ approach) (13, 18, 19). Thereby, ETD aids in the preferential cleavage of S–S linkages, generating two disulfide-cleaved peptides, which can be subsequently isolated and further fragmented via CID/HCD for sequence information. In addition, substantial efforts have been made to develop novel strategies specifically for interpreting spectra from disulfide-bridged peptides, including de novo sequencing approaches (20, 21) and database search engines such as MassMatrix and Dbond (9, 22).A combined dual fragmentation scheme, referred to as electron-transfer and higher-energy collision dissociation (EThcD), was introduced by our group recently as implemented on an Orbitrap Elite (23–25) and will become available for the Orbitrap Fusion. In this approach, an initial ETD step is applied to fragment the isolated MS precursor, and subsequently all resulting ions are subjected to HCD fragmentation, generating a mixture of b/y and c/z ions. Here we explored the use of EThcD for disulfide bridge analysis. We reasoned that the previously reported ETD-MS² CID/HCD-MS³ method could be integrated into a single EThcD experiment, with ETD applied first to preferentially break the disulfide bond and HCD employed next to enhance the number of peptide backbone fragments. Based on the fact that all the ions resulting from the ETD process are subjected to HCD simultaneously and thus no MS³ isolation is necessary, the sensitivity and duty cycle of the EThcD workflow should potentially be improved relative to the previous MS³ strategy.In this work, we describe a fast and accurate framework for both intrapeptide and interpeptide disulfide bridge identification, including the acidic digestion procedure using pepsin, the usage of the dual-fragmentation scheme EThcD, and the development of a novel search engine, SlinkS. The workflow described herein diminishes issues induced by disulfide reshuffling during sample preparation and provides direct and efficient identification of intrapeptide and interpeptide disulfide bonds from LC/MS² experiments. We evaluated the integrated workflow using a mixture of six standard proteins and confirmed that this approach enables reliable and robust identification of authentic disulfide bridges from protein mixtures. Furthermore, we assessed the capability of the workflow to quantitatively monitor the changes of disulfide bridges in stress-induced therapeutic antibodies.     

A Study into the Collision-induced Dissociation (CID) Behavior of Cross-Linked Peptides

Cross-linking/mass spectrometry resolves protein–protein interactions or protein folds by help of distance constraints. Cross-linkers with specific properties such as isotope-labeled or collision-induced dissociation (CID)-cleavable cross-linkers are in frequent use to simplify the identification of cross-linked peptides. Here, we analyzed the mass spectrometric behavior of 910 unique cross-linked peptides in high-resolution MS1 and MS2 from published data and validate the observation by a ninefold larger set from currently unpublished data to explore if detailed understanding of their fragmentation behavior would allow computational delivery of information that otherwise would be obtained via isotope labels or CID cleavage of cross-linkers. Isotope-labeled cross-linkers reveal cross-linked and linear fragments in fragmentation spectra. We show that fragment mass and charge alone provide this information, alleviating the need for isotope-labeling for this purpose. Isotope-labeled cross-linkers also indicate cross-linker-containing, albeit not specifically cross-linked, peptides in MS1. We observed that acquisition can be guided to better than twofold enrich cross-linked peptides with minimal losses based on peptide mass and charge alone. By help of CID-cleavable cross-linkers, individual spectra with only linear fragments can be recorded for each peptide in a cross-link. We show that cross-linked fragments of ordinary cross-linked peptides can be linearized computationally and that a simplified subspectrum can be extracted that is enriched in information on one of the two linked peptides. This allows identifying candidates for this peptide in a simplified database search as we propose in a search strategy here. We conclude that the specific behavior of cross-linked peptides in mass spectrometers can be exploited to relax the requirements on cross-linkers.Cross-linking/mass spectrometry extends the use of mass-spectrometry-based proteomics from identification (1, 2), quantification (3), and characterization of protein complexes (4) into resolving protein structures and protein–protein interactions (5–8). Chemical reagents (cross-linkers) covalently connect amino acid pairs that are within a cross-linker-specific distance range in the native three-dimensional structure of a protein or protein complex. A cross-linking/mass spectrometry experiment is typically conducted in four steps: (1) cross-linking of the target protein or complex, (2) protein digestion (usually with trypsin), (3) LC-MS analysis, and (4) database search. The digested peptide mixture consists of linear and cross-linked peptides, and the latter can be enriched by strong cation exchange (9) or size exclusion chromatography (10). Cross-linked peptides are of high value as they provide direct information on the structure and interactions of proteins.Cross-linked peptides fragment under collision-induced dissociation (CID) conditions primarily into b- and y-ions, as do their linear counterparts. An important difference regarding database searches between linear and cross-linked peptides stems from not knowing which peptides might be cross-linked. Therefore, one has to consider each single peptide and all pairwise combinations of peptides in the database. Having n peptides leads to (n2 + n)/2 possible pairwise combinations. This leads to two major challenges: With increasing size of the database, search time and the risk of identifying false positives increases. One way of circumventing these problems is to use MS2-cleavable cross-linkers (11, 12), at the cost of limited experimental design and choice of cross-linker.In a first database search approach (13), all pairwise combinations of peptides in a database were considered in a concatenated and linearized form. Thereby, all possible single bond fragments are considered in one of the two database entries per peptide pair, and the cross-link can be identified by a normal protein identification algorithm. Already, the second search approach split the peptides for the purpose of their identification (14). Linear fragments were used to retrieve candidate peptides from the database that are then matched based on the known mass of the cross-linked pair and scored as a pair against the spectrum. Isotope-labeled cross-linkers were used to sort the linear and cross-linked fragments apart. Many other search tools and approaches have been developed since (10, 15–19); see (20) for a more detailed list, at least some of which follow the general idea of an open modification search (21–24).As a general concept for open modification search of cross-linked peptides, cross-linked peptides represent two peptides, each with an unknown modification given by the mass of the other peptide and the cross-linker. One identifies both peptides individually and then matches them based on knowing the mass of cross-linked pair (14, 22, 24). Alternatively, one peptide is identified first and, using that peptide and the cross-linker as a modification mass, the second peptide is identified from the database (21, 23). An important element of the open modification search approach is that it essentially converts the quadratic search space of the cross-linked peptides into a linear search space of modified peptides. Still, many peptides and many modification positions have to be considered, especially when working with large databases or when using highly reactive cross-linkers with limited amino acid selectivity (25).We hypothesize that detailed knowledge of the fragmentation behavior of cross-linked peptides might reveal ways to improve the identification of cross-linked peptides. Detailed analyses of the fragmentation behavior of linear peptides exist (26–28), and the analysis of the fragmentation behavior of cross-linked peptides has guided the design of scores (24, 29). Further, cross-link-specific ions have been observed from higher energy collision dissociation (HCD) data (30). Isotope-labeled cross-linkers are used to distinguish cross-linked from linear fragments, generally in low-resolution MS2 of cross-linked peptides (14).We compared the mass spectrometric behavior of cross-linked peptides to that of linear peptides, using 910 high-resolution fragment spectra matched to unique cross-linked peptides from multiple different public datasets at 5% peptide-spectrum match (PSM)¹ false discovery rate (FDR). In addition, we repeated all experiments with a larger sample set that contains 8,301 spectra—also including data from ongoing studies from our lab (Supplemental material S9-S12). This paper presents the mass spectrometric signature of cross-linked peptides that we identified in our analysis and the resulting heuristics that are incorporated into an integrated strategy for the analysis and identification of cross-linked peptides. We present computational strategies that indicate the possibility of alleviating the need for mass-spectrometrically restricted cross-linker choice.     

High-definition De Novo Sequencing of Crustacean Hyperglycemic Hormone (CHH)-family Neuropeptides

A complete understanding of the biological functions of large signaling peptides (>4 kDa) requires comprehensive characterization of their amino acid sequences and post-translational modifications, which presents significant analytical challenges. In the past decade, there has been great success with mass spectrometry-based de novo sequencing of small neuropeptides. However, these approaches are less applicable to larger neuropeptides because of the inefficient fragmentation of peptides larger than 4 kDa and their lower endogenous abundance. The conventional proteomics approach focuses on large-scale determination of protein identities via database searching, lacking the ability for in-depth elucidation of individual amino acid residues. Here, we present a multifaceted MS approach for identification and characterization of large crustacean hyperglycemic hormone (CHH)-family neuropeptides, a class of peptide hormones that play central roles in the regulation of many important physiological processes of crustaceans. Six crustacean CHH-family neuropeptides (8–9.5 kDa), including two novel peptides with extensive disulfide linkages and PTMs, were fully sequenced without reference to genomic databases. High-definition de novo sequencing was achieved by a combination of bottom-up, off-line top-down, and on-line top-down tandem MS methods. Statistical evaluation indicated that these methods provided complementary information for sequence interpretation and increased the local identification confidence of each amino acid. Further investigations by MALDI imaging MS mapped the spatial distribution and colocalization patterns of various CHH-family neuropeptides in the neuroendocrine organs, revealing that two CHH-subfamilies are involved in distinct signaling pathways.Neuropeptides and hormones comprise a diverse class of signaling molecules involved in numerous essential physiological processes, including analgesia, reward, food intake, learning and memory (1). Disorders of the neurosecretory and neuroendocrine systems influence many pathological processes. For example, obesity results from failure of energy homeostasis in association with endocrine alterations (2, 3). Previous work from our lab used crustaceans as model organisms found that multiple neuropeptides were implicated in control of food intake, including RFamides, tachykinin related peptides, RYamides, and pyrokinins (4–6).Crustacean hyperglycemic hormone (CHH)¹ family neuropeptides play a central role in energy homeostasis of crustaceans (7–17). Hyperglycemic response of the CHHs was first reported after injection of crude eyestalk extract in crustaceans. Based on their preprohormone organization, the CHH family can be grouped into two sub-families: subfamily-I containing CHH, and subfamily-II containing molt-inhibiting hormone (MIH) and mandibular organ-inhibiting hormone (MOIH). The preprohormones of the subfamily-I have a CHH precursor related peptide (CPRP) that is cleaved off during processing; and preprohormones of the subfamily-II lack the CPRP (9). Uncovering their physiological functions will provide new insights into neuroendocrine regulation of energy homeostasis.Characterization of CHH-family neuropeptides is challenging. They are comprised of more than 70 amino acids and often contain multiple post-translational modifications (PTMs) and complex disulfide bridge connections (7). In addition, physiological concentrations of these peptide hormones are typically below picomolar level, and most crustacean species do not have available genome and proteome databases to assist MS-based sequencing.MS-based neuropeptidomics provides a powerful tool for rapid discovery and analysis of a large number of endogenous peptides from the brain and the central nervous system. Our group and others have greatly expanded the peptidomes of many model organisms (3, 18–33). For example, we have discovered more than 200 neuropeptides with several neuropeptide families consisting of as many as 20–40 members in a simple crustacean model system (5, 6, 25–31, 34). However, a majority of these neuropeptides are small peptides with 5–15 amino acid residues long, leaving a gap of identifying larger signaling peptides from organisms without sequenced genome. The observed lack of larger size peptide hormones can be attributed to the lack of effective de novo sequencing strategies for neuropeptides larger than 4 kDa, which are inherently more difficult to fragment using conventional techniques (34–37). Although classical proteomics studies examine larger proteins, these tools are limited to identification based on database searching with one or more peptides matching without complete amino acid sequence coverage (36, 38).Large populations of neuropeptides from 4–10 kDa exist in the nervous systems of both vertebrates and invertebrates (9, 39, 40). Understanding their functional roles requires sufficient molecular knowledge and a unique analytical approach. Therefore, developing effective and reliable methods for de novo sequencing of large neuropeptides at the individual amino acid residue level is an urgent gap to fill in neurobiology. In this study, we present a multifaceted MS strategy aimed at high-definition de novo sequencing and comprehensive characterization of the CHH-family neuropeptides in crustacean central nervous system. The high-definition de novo sequencing was achieved by a combination of three methods: (1) enzymatic digestion and LC-tandem mass spectrometry (MS/MS) bottom-up analysis to generate detailed sequences of proteolytic peptides; (2) off-line LC fractionation and subsequent top-down MS/MS to obtain high-quality fragmentation maps of intact peptides; and (3) on-line LC coupled to top-down MS/MS to allow rapid sequence analysis of low abundance peptides. Combining the three methods overcomes the limitations of each, and thus offers complementary and high-confidence determination of amino acid residues. We report the complete sequence analysis of six CHH-family neuropeptides including the discovery of two novel peptides. With the accurate molecular information, MALDI imaging and ion mobility MS were conducted for the first time to explore their anatomical distribution and biochemical properties.     

Sampling From the Proteome to the Human Leukocyte Antigen-DR (HLA-DR) Ligandome Proceeds Via High Specificity

Comprehensive analysis of the complex nature of the Human Leukocyte Antigen (HLA) class II ligandome is of utmost importance to understand the basis for CD4⁺ T cell mediated immunity and tolerance. Here, we implemented important improvements in the analysis of the repertoire of HLA-DR-presented peptides, using hybrid mass spectrometry-based peptide fragmentation techniques on a ligandome sample isolated from matured human monocyte-derived dendritic cells (DC). The reported data set constitutes nearly 14 thousand unique high-confident peptides, i.e. the largest single inventory of human DC derived HLA-DR ligands to date. From a technical viewpoint the most prominent finding is that no single peptide fragmentation technique could elucidate the majority of HLA-DR ligands, because of the wide range of physical chemical properties displayed by the HLA-DR ligandome. Our in-depth profiling allowed us to reveal a strikingly poor correlation between the source proteins identified in the HLA class II ligandome and the DC cellular proteome. Important selective sieving from the sampled proteome to the ligandome was evidenced by specificity in the sequences of the core regions both at their N- and C- termini, hence not only reflecting binding motifs but also dominant protease activity associated to the endolysosomal compartments. Moreover, we demonstrate that the HLA-DR ligandome reflects a surface representation of cell-compartments specific for biological events linked to the maturation of monocytes into antigen presenting cells. Our results present new perspectives into the complex nature of the HLA class II system and will aid future immunological studies in characterizing the full breadth of potential CD4⁺ T cell epitopes relevant in health and disease.Human Leukocyte Antigen (HLA)¹ class II molecules on professional antigen presenting cells such as dendritic cells (DC) expose peptide fragments derived from exogenous and endogenous proteins to be screened by CD4⁺ T cells (1, 2). The activation and recruitment of CD4⁺ T cells recognizing disease-related peptide antigens is critical for the development of efficient antipathogen or antitumor immunity. Furthermore, the presentation of self-peptides and their interaction with CD4⁺ T cells is essential to maintain immunological tolerance and homeostasis (3). Knowledge of the nature of HLA class II-presented peptides on DC is of great importance to understand the rules of antigen processing and peptide binding motifs (4), whereas the identity of disease-related antigens may provide new knowledge on immunogenicity and leads for the development of vaccines and immunotherapy (5, 6).Mass spectrometry (MS) has proven effective for the analysis HLA class II-presented peptides (4, 7, 8). MS-based ligandome studies have demonstrated that HLA class II molecules predominantly present peptides derived from exogenous proteins that entered the cells by endocytosis and endogenous proteins that are associated with the endo-lysosomal compartments (4). Yet proteins residing in the cytosol, nucleus or mitochondria can also be presented by HLA class II molecules, primarily through autophagy (9–11). Multiple studies have mapped the HLA class II ligandome of antigen presenting cells in the context of infectious pathogens (12), autoimmune diseases (13–17) or cancer (14, 18, 19), or those that are essential for self-tolerance in the human thymus (3, 20). Notwithstanding these efforts, and certainly not in line with the extensive knowledge on the HLA class I ligandome (21), the nature of the HLA class II-presented peptide repertoire and particular its relationship to the cellular source proteome remains poorly understood.To advance our knowledge on the HLA-DR ligandome on activated DC without having to deal with limitations in cell yield from peripheral human blood (12, 21, 22) or tissue isolates (3), we explored the use of MUTZ-3 cells. This cell line has been used as a model of human monocyte-derived DCs. MUTZ-3 cells can be matured to act as antigen presenting cells and express then high levels of HLA class II molecules, and can be propagated in vitro to large cell densities (23–25). We also evaluated the performance of complementary and hybrid MS fragmentation techniques electron-transfer dissociation (ETD), electron-transfer/higher-energy collision dissociation (EThcD) (26), and higher-energy collision dissociation (HCD) to sequence and identify the HLA class II ligandome. Together this workflow allowed for the identification of an unprecedented large set of about 14 thousand unique peptide sequences presented by DC derived HLA-DR molecules, providing an in-depth view of the complexity of the HLA class II ligandome, revealing underlying features of antigen processing and surface-presentation to CD4⁺ T cells.     

Simultaneous Glycan-Peptide Characterization Using Hydrophilic Interaction Chromatography and Parallel Fragmentation by CID,Higher Energy Collisional Dissociation,and Electron Transfer Dissociation MS Applied to the N-Linked Glycoproteome of Campylobacter jejuni

Campylobacter jejuni is a gastrointestinal pathogen that is able to modify membrane and periplasmic proteins by the N-linked addition of a 7-residue glycan at the strict attachment motif (D/E)XNX(S/T). Strategies for a comprehensive analysis of the targets of glycosylation, however, are hampered by the resistance of the glycan-peptide bond to enzymatic digestion or β-elimination and have previously concentrated on soluble glycoproteins compatible with lectin affinity and gel-based approaches. We developed strategies for enriching C. jejuni HB93-13 glycopeptides using zwitterionic hydrophilic interaction chromatography and examined novel fragmentation, including collision-induced dissociation (CID) and higher energy collisional (C-trap) dissociation (HCD) as well as CID/electron transfer dissociation (ETD) mass spectrometry. CID/HCD enabled the identification of glycan structure and peptide backbone, allowing glycopeptide identification, whereas CID/ETD enabled the elucidation of glycosylation sites by maintaining the glycan-peptide linkage. A total of 130 glycopeptides, representing 75 glycosylation sites, were identified from LC-MS/MS using zwitterionic hydrophilic interaction chromatography coupled to CID/HCD and CID/ETD. CID/HCD provided the majority of the identifications (73 sites) compared with ETD (26 sites). We also examined soluble glycoproteins by soybean agglutinin affinity and two-dimensional electrophoresis and identified a further six glycosylation sites. This study more than doubles the number of confirmed N-linked glycosylation sites in C. jejuni and is the first to utilize HCD fragmentation for glycopeptide identification with intact glycan. We also show that hydrophobic integral membrane proteins are significant targets of glycosylation in this organism. Our data demonstrate that peptide-centric approaches coupled to novel mass spectrometric fragmentation techniques may be suitable for application to eukaryotic glycoproteins for simultaneous elucidation of glycan structures and peptide sequence.Campylobacter jejuni is a Gram-negative, microaerophilic, spiral-shaped, motile bacterium that is the most common cause of food- and water-borne diarrheal illness worldwide (1). Typical infections are acquired via the consumption of undercooked poultry where C. jejuni is found commensally (2). Symptoms in humans range from mild, non-inflammatory diarrhea to severe abdominal cramps, vomiting, and inflammation (3). Prior infection with C. jejuni is a common antecedent of two chronic immune-mediated disorders: Guillain-Barré syndrome (4) and immunoproliferative small intestine disease (5). A unique molecular trait of C. jejuni is the ability to post-translationally modify proteins by the N-linked addition of a 7-residue glycan (GalNAc-α1,4-GalNAc-α1,4-(Glcβ1,3)- GalNAc-α1,4-GalNAc-α1,4-GalNAc-α1,3-Bac-β1 where Bac is bacillosamine (2,4-diacetamido-2,4,6-trideoxyglucopyranose)) (6) at the consensus sequon (D/E)XNX(S/T) where X is any amino acid except proline (7).The N-linked C. jejuni heptasaccharide is encoded by the pgl (protein glycosylation) gene cluster (8–10), and the glycan is transferred to proteins by the PglB oligosaccharyltransferase (11) at the periplasmic face of the inner membrane (12). Removal of the N-glycosylation gene cluster (or indeed pglB alone) results in C. jejuni that displays poor adherence to and invasion of epithelial cell lines (13) and reduced colonization of the chicken gastrointestinal tract (14). Although this demonstrates a requirement for glycosylation in virulence, the proteins that mediate this are still unknown, and the overall role of glycan attachment remains to be elucidated. Our current understanding of the structural context of glycosylation in C. jejuni suggests that it does not play a role in steric stabilization by conferring structural rigidity as seen in eukaryotes (15) but occurs preferably on flexible loops and unordered regions of proteins (16–18). To investigate the role of glycosylation in protein function, recent studies have utilized mutagenesis to remove the N-linked sequon from three glycoproteins: Cj1496c (19), Cj0143c (20), and VirB10 (21). Removal of glycosylation from Cj1496c and Cj0143c had little effect on protein function; however, glycan attachment was required for correct localization of VirB10. Although the exact role of the glycan remains largely unknown, it appears to be site-specific with a single site, Asn⁹⁷, influencing localization of VirB10, whereas a second site, Asn³², is dispensable (21). It is clear that a more comprehensive analysis of the C. jejuni glycoproteome is required. A further complication in the elucidation of N-linked glycosylation is the use of the NCTC 11168 strain, which because of laboratory passage (22, 23) may not be the most appropriate model in which to study the virulence properties of glycan attachment. For example, we have recently shown that a surface-exposed virulence factor, JlpA, is glycosylated at two sites (Asn¹⁴⁶ and Asn¹⁰⁷) in all sequenced C. jejuni strains except NCTC 11168, which contains only Asn¹⁴⁶ (24).Glycoproteomics in C. jejuni is also a major technical challenge. Unlike eukaryotic N-linked glycans, the C. jejuni glycan is resistant to removal by protein N-glycosidase F (24) and chemical liberation via β-elimination (6) possibly because of the structure of the unique linking sugar, bacillosamine (25). Analysis therefore requires complementary methodology to elucidate the sites of glycosylation in the presence of the glycan. Preferential fragmentation of the glycan itself during collision-induced dissociation (CID) generally results in poor recovery of peptide fragment ions, and thus identification of the underlying protein and site of attachment remains problematic. MS³ has been attempted for site identification (6, 26); however, the data are limited by the requirement for sufficient ions for two rounds of tandem MS. We have also shown previously that C. jejuni encodes several hydrophobic integral membrane and outer membrane proteins possessing multiple transmembrane-spanning regions that are not amenable to gel-based approaches (27), particularly those using lectins for glycoprotein purification (28). We hypothesize that N-linked glycosylation is more widespread than previously demonstrated (6, 7, 26) because these studies examined only soluble proteins (6, 26) or used lectin affinity (6, 7), which limits the amount and type of detergents that can be used. Recent work (26) has demonstrated the potential of exploiting the hydrophilic nature of the C. jejuni glycan to enable glycopeptide enrichment.The ability to generate product ions useful for the identification of a glycosylated peptide is governed by three factors: the peptide backbone, the glycan, and the fragmentation approach. Multiple strategies exist to separately exploit the first two of these parameters (29, 30), but it is only recently that selective fragmentation of modified peptides has been available through electron transfer dissociation (ETD)¹ and electron capture dissociation (31, 32). ETD/electron capture dissociation enable the selective cleavage of the peptide while maintaining the carbohydrate structure, and this has been demonstrated using eukaryotic glycopeptides (33, 34) and more recently glycopeptides isolated from the pathogen Neisseria gonorrhoeae (35). A more recent fragmentation approach is higher energy collisional (C-trap) dissociation (HCD), which uses higher fragmentation energies than standard CID and enables identification of modifications, such as phosphotyrosine (36), via diagnostic immonium ions and high mass accuracy over the full mass range in MS/MS. HCD has not previously been applied to glycopeptides.We applied several enrichment and MS fragmentation approaches to the characterization of the glycoproteome of C. jejuni HB93-13. Sequence analysis determined that the HB93-13 genome contains 510 N-linked sequons ((D/E)XNX(S/T)) in 382 proteins of which 261 (with 371 potential N-linked sites) are predicted to pass through the inner membrane and are therefore the subset that may be glycosylated. We examined trypsin digests of whole cell and membrane protein preparations using zwitterionic hydrophilic interaction chromatography (ZIC-HILIC) and graphite enrichment of gel-separated proteins using several mass spectrometric techniques (CID, HCD, and ETD). This is the first study to demonstrate the potential of using the high energy fragmentation of HCD to overcome the signal disruption caused by labile glycan fragmentation and to provide peptide sequencing within a single step. Manual data analysis was also simplified as the GalNAc fragment ion (204.086 Da) provides a signature that can be used to highlight glycopeptides within a complex mixture. We identified 81 glycosylation sites, including 47 not described previously in the literature and a single site that cannot be unambiguously assigned. The majority of these are present on proteins not amenable to traditional gel-based analyses, such as hydrophobic transmembrane proteins. Our work more than doubles the previously known N-linked C. jejuni glycoproteome and provides a clear rationale for other studies where the peptide and glycan need to remain associated.     

Affinity Enrichment and Characterization of Mucin Core-1 Type Glycopeptides from Bovine Serum

The lack of consensus sequence, common core structure, and universal endoglycosidase for the release of O-linked oligosaccharides makes O-glycosylation more difficult to tackle than N-glycosylation. Structural elucidation by mass spectrometry is usually inconclusive as the CID spectra of most glycopeptides are dominated by carbohydrate-related fragments, preventing peptide identification. In addition, O-linked structures also undergo a gas-phase rearrangement reaction, which eliminates the sugar without leaving a telltale sign at its former attachment site. In the present study we report the enrichment and mass spectrometric analysis of proteins from bovine serum bearing Galβ1–3GalNAcα (mucin core-1 type) structures and the analysis of O-linked glycopeptides utilizing electron transfer dissociation and high resolution, high mass accuracy precursor ion measurements. Electron transfer dissociation (ETD) analysis of intact glycopeptides provided sufficient information for the identification of several glycosylation sites. However, glycopeptides frequently feature precursor ions of low charge density (m/z > ∼850) that will not undergo efficient ETD fragmentation. Exoglycosidase digestion was utilized to reduce the mass of the molecules while retaining their charge. ETD analysis of species modified by a single GalNAc at each site was significantly more successful in the characterization of multiply modified molecules. We report the unambiguous identification of 21 novel glycosylation sites. We also detail the limitations of the enrichment method as well as the ETD analysis.Glycosylation is among the most prevalent post-translational modifications of proteins; it is estimated that over half of all proteins undergo glycosylation during their lifespan (1). Glycosylation of secreted proteins and the extracellular part of membrane proteins occurs in the endoplasmic reticulum and the contiguous Golgi complex. The side chains of Trp, Asn, and Thr/Ser residues can be modified, termed as C-, N-, and O-glycosylation, respectively (2, 3). In addition, O-glycosylation also occurs within the nucleus and the cytosol: a single GlcNAc residue modifies Ser and Thr residues. O-GlcNAc glycosylation fulfills a regulatory/signaling function similar to phosphorylation (4).From an analytical point of view, C-glycosylation is the simplest. A consensus sequence has been defined: WXXW where the first Trp is modified, and the modification, a Man moiety, readily survives sample preparation and mass spectrometric analysis, including collisional activation (5). Investigation of N-glycosylation is also facilitated by several factors. First, N-glycosylation again has a well defined consensus sequence: NX(S/T/C) where the middle amino acid cannot be Pro (6). Second, there is a universal core glycan structure: GlcNAc₂Man₃; and this core is conserved across species. Third, a specific endoglycosidase, peptide N-glycosidase F, has been identified. This enzyme cleaves the carbohydrate structure from the peptide, leaving behind a diagnostic sign: the Asn residue is hydrolyzed to Asp, inducing a mass shift of +1 Da. By contrast, analysis of O-glycosylation is hampered by a lack of (i) a consensus sequence, (ii) a universal core structure, and (iii) a universal endoglycosidase or gentle chemical hydrolysis method to facilitate analysis.Glycosylation shows a high degree of species and tissue specificity; the same site may be modified by a wide variety of different glycan structures, and unmodified variants of the protein may occur simultaneously (7–9). Disease and physiological changes also may alter the glycosylation pattern (10–12). The biological role(s) of glycosylation has been studied extensively (13–15), although such studies are seriously hampered by the difficulties of glycosylation analysis.Most secreted proteins are glycosylated; and thus, mammalian serum is rich in glycoproteins. On the other hand, O-linked glycoproteins represent a small percentage of the serum protein content. Glycoproteins may display a befuddling heterogeneity both in site specificity and site occupancy. Thus, the enrichment of modified proteins or peptides is necessary for their characterization, and different techniques have been tested for this purpose. Lectin affinity chromatography is a popular method for selective isolation of glycoproteins and glycopeptides. Concanavalin A can be used to isolate oligomannose type glycopeptides (16), wheat germ agglutinin is applied for GlcNAc-containing compounds (16, 17), and jacalin is selective for core-1 type O-glycopeptides (18, 19). Lectins with preferential affinity for fucosylated and sialylated structures can also be utilized (12). Non-selective capture of glycopeptides can be performed using hydrophilic interaction chromatography (20, 21) or size exclusion chromatography (22). A recent approach applies porous graphite columns for semiselective enrichment (23), whereas the acidic character of sialylated glycopeptides has also been exploited via titanium dioxide-mediated enrichment (24). Finally vicinal cis-diols can be selectively captured using boronic acid derivatives (25–27). All methods described here provide some glycopeptide enrichment from non-glycosylated peptide background, but all also suffer from significant non-selective binding. N-Linked glycoproteins may also be selectively captured on hydrazide resin following periodate oxidation (28). This approach requires enzymatic deglycosylation to release the captured peptides for analysis, therefore excluding the determination of the carbohydrate structure.Intact glycopeptide characterization still represents a significant challenge. Edman degradation, either alone or in combination with mass spectrometry, has been utilized for such tasks (29, 30). CID analysis of O-linked glycopeptides has limited utility. (i) MS/MS analysis cannot differentiate between the isomeric carbohydrate units and usually does not reveal the linkage positions and the configuration of the glycosidic bonds. (ii) Such spectra are typically dominated by abundant product ions associated with carbohydrate fragmentation, namely non-reducing end oxonium ions and product ions formed via sequential neutral losses of sugar residues from the precursor ions. (iii) The glycan is cleaved from the peptide via a gas-phase rearrangement reaction, and as a result the peptide itself and most peptide fragments (if any) are detected partially or completely deglycosylated (31–33). Recently a different approach, the combination of positive and negative ion mode infrared multiphoton dissociation, was found to provide conclusive structural assignment for some O-linked glycopeptides (34). However, two novel MS/MS techniques, electron capture dissociation (ECD),¹ which is performed in FT-ICR mass spectrometers (35), and electron transfer dissociation (ETD), which is performed in various ion trapping devices (36), may represent the real breakthrough. In both cases an electron is transferred to multiply protonated peptide cations, triggering peptide fragmentation at the covalent bond between the amino group and the α-carbon, producing mostly c and radical z· product ions while leaving the side chains intact. ETD is typically more efficient than ECD and thus leads to more comprehensive fragmentation. In addition, ETD can be performed in ion traps and thus, at a higher sensitivity level, especially in a linear ion trap. Because it has been observed that there are instances when the electron transfer is efficient and still no significant fragmentation occurs, ETD is usually combined with supplementary (and gentle) CID activation (37). O-Glycosylation analysis using these new dissociative techniques has been investigated (38, 39). However, because of the complexity of extracellular O-glycosylation, analysis of complex mixtures is rarely attempted (18), and the above techniques are usually restricted to the analysis of purified proteins.In this study we present the analysis of secreted O-linked glycopeptides. Lectin (jacalin) affinity chromatography was used to achieve some enrichment of core-1 O-GalNAcα type carbohydrate-carrying glycopeptides from bovine serum. The glycopeptide fractions were subjected to CID and ETD analysis. These experiments were performed on a linear ion trap-Orbitrap hybrid mass spectrometer (40). The Orbitrap delivered high resolution, high mass accuracy for the precursor ions, whereas the linear trap provided high sensitivity MS/MS analyses. Some fractions were also subjected to sequential exoglycosidase digestions, and glycopeptides retaining only the proximal GalNAc residues were analyzed. ProteinProspector v5.2.1, developed to accommodate ETD product ion spectra, aided data interpretation (41). We identified 26 glycosylation sites from bovine serum unambiguously; 21 of these sites have never been reported by any other study. No other single study to date has yielded so much information about O-linked glycosylation sites.     

Development of a Novel Cross-linking Strategy for Fast and Accurate Identification of Cross-linked Peptides of Protein Complexes

Knowledge of elaborate structures of protein complexes is fundamental for understanding their functions and regulations. Although cross-linking coupled with mass spectrometry (MS) has been presented as a feasible strategy for structural elucidation of large multisubunit protein complexes, this method has proven challenging because of technical difficulties in unambiguous identification of cross-linked peptides and determination of cross-linked sites by MS analysis. In this work, we developed a novel cross-linking strategy using a newly designed MS-cleavable cross-linker, disuccinimidyl sulfoxide (DSSO). DSSO contains two symmetric collision-induced dissociation (CID)-cleavable sites that allow effective identification of DSSO-cross-linked peptides based on their distinct fragmentation patterns unique to cross-linking types (i.e. interlink, intralink, and dead end). The CID-induced separation of interlinked peptides in MS/MS permits MS³ analysis of single peptide chain fragment ions with defined modifications (due to DSSO remnants) for easy interpretation and unambiguous identification using existing database searching tools. Integration of data analyses from three generated data sets (MS, MS/MS, and MS³) allows high confidence identification of DSSO cross-linked peptides. The efficacy of the newly developed DSSO-based cross-linking strategy was demonstrated using model peptides and proteins. In addition, this method was successfully used for structural characterization of the yeast 20 S proteasome complex. In total, 13 non-redundant interlinked peptides of the 20 S proteasome were identified, representing the first application of an MS-cleavable cross-linker for the characterization of a multisubunit protein complex. Given its effectiveness and simplicity, this cross-linking strategy can find a broad range of applications in elucidating the structural topology of proteins and protein complexes.Proteins form stable and dynamic multisubunit complexes under different physiological conditions to maintain cell viability and normal cell homeostasis. Detailed knowledge of protein interactions and protein complex structures is fundamental to understanding how individual proteins function within a complex and how the complex functions as a whole. However, structural elucidation of large multisubunit protein complexes has been difficult because of a lack of technologies that can effectively handle their dynamic and heterogeneous nature. Traditional methods such as nuclear magnetic resonance (NMR) analysis and x-ray crystallography can yield detailed information on protein structures; however, NMR spectroscopy requires large quantities of pure protein in a specific solvent, whereas x-ray crystallography is often limited by the crystallization process.In recent years, chemical cross-linking coupled with mass spectrometry (MS) has become a powerful method for studying protein interactions (1–3). Chemical cross-linking stabilizes protein interactions through the formation of covalent bonds and allows the detection of stable, weak, and/or transient protein-protein interactions in native cells or tissues (4–9). In addition to capturing protein interacting partners, many studies have shown that chemical cross-linking can yield low resolution structural information about the constraints within a molecule (2, 3, 10) or protein complex (11–13). The application of chemical cross-linking, enzymatic digestion, and subsequent mass spectrometric and computational analyses for the elucidation of three-dimensional protein structures offers distinct advantages over traditional methods because of its speed, sensitivity, and versatility. Identification of cross-linked peptides provides distance constraints that aid in constructing the structural topology of proteins and/or protein complexes. Although this approach has been successful, effective detection and accurate identification of cross-linked peptides as well as unambiguous assignment of cross-linked sites remain extremely challenging due to their low abundance and complicated fragmentation behavior in MS analysis (2, 3, 10, 14). Therefore, new reagents and methods are urgently needed to allow unambiguous identification of cross-linked products and to improve the speed and accuracy of data analysis to facilitate its application in structural elucidation of large protein complexes.A number of approaches have been developed to facilitate MS detection of low abundance cross-linked peptides from complex mixtures. These include selective enrichment using affinity purification with biotinylated cross-linkers (15–17) and click chemistry with alkyne-tagged (18) or azide-tagged (19, 20) cross-linkers. In addition, Staudinger ligation has recently been shown to be effective for selective enrichment of azide-tagged cross-linked peptides (21). Apart from enrichment, detection of cross-linked peptides can be achieved by isotope-labeled (22–24), fluorescently labeled (25), and mass tag-labeled cross-linking reagents (16, 26). These methods can identify cross-linked peptides with MS analysis, but interpretation of the data generated from interlinked peptides (two peptides connected with the cross-link) by automated database searching remains difficult. Several bioinformatics tools have thus been developed to interpret MS/MS data and determine interlinked peptide sequences from complex mixtures (12, 14, 27–32). Although promising, further developments are still needed to make such data analyses as robust and reliable as analyzing MS/MS data of single peptide sequences using existing database searching tools (e.g. Protein Prospector, Mascot, or SEQUEST).Various types of cleavable cross-linkers with distinct chemical properties have been developed to facilitate MS identification and characterization of cross-linked peptides. These include UV photocleavable (33), chemical cleavable (19), isotopically coded cleavable (24), and MS-cleavable reagents (16, 26, 34–38). MS-cleavable cross-linkers have received considerable attention because the resulting cross-linked products can be identified based on their characteristic fragmentation behavior observed during MS analysis. Gas-phase cleavage sites result in the detection of a “reporter” ion (26), single peptide chain fragment ions (35–38), or both reporter and fragment ions (16, 34). In each case, further structural characterization of the peptide product ions generated during the cleavage reaction can be accomplished by subsequent MSⁿ1 analysis. Among these linkers, the “fixed charge” sulfonium ion-containing cross-linker developed by Lu et al. (37) appears to be the most attractive as it allows specific and selective fragmentation of cross-linked peptides regardless of their charge and amino acid composition based on their studies with model peptides.Despite the availability of multiple types of cleavable cross-linkers, most of the applications have been limited to the study of model peptides and single proteins. Additionally, complicated synthesis and fragmentation patterns have impeded most of the known MS-cleavable cross-linkers from wide adaptation by the community. Here we describe the design and characterization of a novel and simple MS-cleavable cross-linker, DSSO, and its application to model peptides and proteins and the yeast 20 S proteasome complex. In combination with new software developed for data integration, we were able to identify DSSO-cross-linked peptides from complex peptide mixtures with speed and accuracy. Given its effectiveness and simplicity, we anticipate a broader application of this MS-cleavable cross-linker in the study of structural topology of other protein complexes using cross-linking and mass spectrometry.     

A Mixed Integer Linear Optimization Framework for the Identification and Quantification of Targeted Post-translational Modifications of Highly Modified Proteins Using Multiplexed Electron Transfer Dissociation Tandem Mass Spectrometry

Here we present a novel methodology for the identification of the targeted post-translational modifications present in highly modified proteins using mixed integer linear optimization and electron transfer dissociation (ETD) tandem mass spectrometry. For a given ETD tandem mass spectrum, the rigorous set of modified forms that satisfy the mass of the precursor ion, within some tolerance error, are enumerated by solving a feasibility problem via mixed integer linear optimization. The enumeration of the entire superset of modified forms enables the method to normalize the relative contributions of the individual modification sites. Given the entire set of modified forms, a superposition problem is then formulated using mixed integer linear optimization to determine the relative fractions of the modified forms that are present in the multiplexed ETD tandem mass spectrum. Chromatographic information in the mass and time dimension is utilized to assess the likelihood of the assigned modification states, to average several tandem mass spectra for confident identification of lower level forms, and to infer modification states of partially assigned spectra. The utility of the proposed computational framework is demonstrated on an entire LC-MS/MS ETD experiment corresponding to a mixture of highly modified histone peptides. This new computational method will facilitate the unprecedented LC-MS/MS ETD analysis of many hypermodified proteins and offer novel biological insight into these previously understudied systems.Accurate identification of post-translational modifications (PTMs)¹ is a critical and often difficult task in proteomics. Most standard mass spectrometry-based techniques for the identification of protein modifications utilize a “bottom up” approach where the proteins are enzymatically digested into smaller peptides that are subsequently ionized and fragmented via CID to derive their sequence information (1–9). The identification of all the modifications present in a protein hinges on the successful identification of the PTM modifications of its corresponding peptides. This protocol can be limited by (a) insufficient elution and detection of all the peptides that cover the entire sequence of the protein, (b) false or incomplete identifications at the peptide level, and (c) the existence of different modification states of the same protein. Additional complications arise when using CID to study labile PTMs such as phosphorylation, glycosylation, or sulfonation. In these instances, the preferred reaction is often the cleavage of the PTM as opposed to the backbone of the peptide, resulting in a high intensity peak corresponding to the difference of the parent mass and the cleaved modification. The advent of electron capture dissociation (ECD) (10, 11) and electron transfer dissociation (ETD) (12–15) has enabled researchers to address the aforementioned issues associated with bottom up approaches using CID by adopting a complementary top down or middle down analysis strategy.ECD and ETD both involve the reaction of an electron with a highly protonated cation to form an odd electron peptide. This process induces large amounts of backbone cleavage to yield c and z· ions that are analogous to the b and y ion series typically encountered in CID tandem mass spectra. Unlike CID, ECD/ETD cleavage is weakly affected by the composition and number of amino acids in the peptide and for certain systems can provide more fragmentation coverage than CID alone, especially for bigger peptides with higher charge states. Both ECD and ETD also prevent the cleavage of labile modifications, and thus PTMs are retained on the corresponding c and z· ions. The aforementioned benefits make ECD/ETD particularly well suited for the LC-MS/MS top down and middle down analysis of post-translationally modified proteins. These top down and middle down approaches also enable the approximate inference of protein abundance from the chromatogram and MS¹ information because the full protein sequence elutes from the column (16).In recent years, there has been significant interest in the identification of highly modified proteins, such as histones. Histone proteins are key regulators of many important DNA processes in eukaryotes, and recent studies have elucidated complex relationships between histone modifications and many nuclear events. It has also been shown that differences in global histone modifications in tissues can be used to predict the clinical outcome of cancer patients (17). Early MS or immunoassay studies were only able to analyze these modifications on a site-by-site basis and as a result lost important connectivity information on the molecular level because several modified forms of the same protein exist concurrently. In MS-based applications, the use of traditional reversed phase HPLC for the separation of a highly modified protein results in poor chromatographic resolution because all the modified forms are physically similar. Successful off-line techniques for the separation of highly modified histone forms have been achieved using cation exchange hydrophilic interaction chromatography (HILIC) (18), which separates the modified species primarily by the number of acetyl groups and secondly by the degree of methylation. The separation must be conducted off line because the mobile phase additives used are non-volatile components, and subsequent fractionation is necessary for mass spectrometric analysis. This protocol has made it possible to analyze the first 50 amino acids of the N-terminal tail of histone H3 and provided important insight regarding connectivity information between the modification sites. A major disadvantage of this approach is that the off-line nature of the experimental protocol is extremely time-consuming (on the order of months) and thus prohibits the ability to conduct multiple runs for high throughput studies and statistical validation. Additionally, other off-line techniques have been successful in the extraction and purification of modified histone proteins using acid-urea gel electrophoresis (19) but suffer from similar throughput constraints.We have recently developed chromatography that is particularly suited for LC-MS ETD analysis of highly modified polypeptides with successful applications to histone proteins (20). The protocol uses a “saltless” pH gradient to elute the various modified forms in a weak cation exchange HILIC. Unprecedented separation of the modified histone forms is achieved within a single LC-MS/MS ETD experiment, thereby introducing important chromatographic information that can be utilized in the subsequent identification and quantification of these post-translational modifications. Although the achieved separation is exceptional in comparison with previous attempts, the complexity and relative similarity of the modified forms still results in minor species co-eluting with similar mass and retention times, thus resulting in multiplexed tandem mass spectra. The term “multiplexed” as used here refers to the fact that several species are dissociated and measured in a single tandem mass spectrum (21) and should not be confused with the multiplex experimental protocols. Computational methodologies that utilize the extensive and complementary information contained within these LC-MS/MS data sets are nonexistent as the technology has only recently been developed.In this work, we present a novel mixed integer linear optimization (MILP) computational framework for the identification and quantification of highly modified proteins using LC-MS and ETD tandem mass spectrometry. Key concepts of the proposed framework are illustrated using histone H3.2 as an example system. For a given primary sequence, the entire set of post-translational modifications that satisfy a precursor mass are enumerated by solving an MILP feasibility problem. Given this set of PTM forms, an MILP superposition problem is then solved to determine the relative fractions of the modified forms that are present in the multiplexed ETD tandem mass spectrum. An important aspect of the proposed framework is that chromatographic information is used to correlate the modification states as a function of modification position, mass, and time. The proposed computational framework is applied to an entire LC-MS/MS ETD experiment corresponding to a mixture of highly modified histone peptides to demonstrate its utility.     

Phosphoproteome Analysis Reveals Regulatory Sites in Major Pathways of Cardiac Mitochondria

Mitochondrial functions are dynamically regulated in the heart. In particular, protein phosphorylation has been shown to be a key mechanism modulating mitochondrial function in diverse cardiovascular phenotypes. However, site-specific phosphorylation information remains scarce for this organ. Accordingly, we performed a comprehensive characterization of murine cardiac mitochondrial phosphoproteome in the context of mitochondrial functional pathways. A platform using the complementary fragmentation technologies of collision-induced dissociation (CID) and electron transfer dissociation (ETD) demonstrated successful identification of a total of 236 phosphorylation sites in the murine heart; 210 of these sites were novel. These 236 sites were mapped to 181 phosphoproteins and 203 phosphopeptides. Among those identified, 45 phosphorylation sites were captured only by CID, whereas 185 phosphorylation sites, including a novel modification on ubiquinol-cytochrome c reductase protein 1 (Ser-212), were identified only by ETD, underscoring the advantage of a combined CID and ETD approach. The biological significance of the cardiac mitochondrial phosphoproteome was evaluated. Our investigations illustrated key regulatory sites in murine cardiac mitochondrial pathways as targets of phosphorylation regulation, including components of the electron transport chain (ETC) complexes and enzymes involved in metabolic pathways (e.g. tricarboxylic acid cycle). Furthermore, calcium overload injured cardiac mitochondrial ETC function, whereas enhanced phosphorylation of ETC via application of phosphatase inhibitors restored calcium-attenuated ETC complex I and complex III activities, demonstrating positive regulation of ETC function by phosphorylation. Moreover, in silico analyses of the identified phosphopeptide motifs illuminated the molecular nature of participating kinases, which included several known mitochondrial kinases (e.g. pyruvate dehydrogenase kinase) as well as kinases whose mitochondrial location was not previously appreciated (e.g. Src). In conclusion, the phosphorylation events defined herein advance our understanding of cardiac mitochondrial biology, facilitating the integration of the still fragmentary knowledge about mitochondrial signaling networks, metabolic pathways, and intrinsic mechanisms of functional regulation in the heart.Mitochondria are the source of energy to sustain life. In addition to their evolutionary origin as an energy-producing organelle, their functionality has integrated into every aspect of life, including the cell cycle, ROS¹ production, apoptosis, and ion balance (1, 2). Our understanding of mitochondrial biology is still growing. Several systems biology approaches have been dedicated to exploring the molecular infrastructure and dynamics of the functional versatility associated with this organelle (3–5).To meet tissue-specific functional demands, mitochondria acquire heterogeneous properties in individual organs, a first statement of their plasticity in function and proteome composition (1, 6). The heterogeneity is evident even in an individual cardiomyocyte (7). A catalogue of the cardiac mitochondrial proteome is emerging via a joint effort (3–5). The dynamics of the mitochondrial proteome manifest at multiple levels, including post-translational modifications, such as phosphorylation. Our investigative goal is to decode this organellar proteome and its post-translational modification in a biological and functional context. In cardiomyocytes, mitochondria are also constantly exposed to fluctuation in energy demands and in ionic conditions. The capacity of mitochondria to cope with such a dynamic environment is essential for the functional role of mitochondria in normal and disease phenotypes (8–10). Unique protein features enabling the mitochondrial proteome to adapt to these biological changes can be interrogated by proteomics tools (10–12). Protein phosphorylation as a rapid and reversible chemical event is an integral component of these protein features (12–14).It has been estimated that one-third of cellular proteins exist in a phosphorylated state at least one time in their lifetime (15). However, only a handful of phosphorylation events have been identified to tune mitochondrial functionality (13, 14, 16) despite the fact that the first demonstration of phosphorylation was reported on a mitochondrial protein more than 5 decades ago (17). Kinases and phosphatases comprise nearly 3% of the human genome (18, 19). In mitochondria, ∼30 kinases and phosphatases have been identified thus far within the expected organellar proteome of a few thousand (3–5, 16). The number of identified mitochondrial phosphoproteins is far below one-third of its proteome size (20). Thus, it appears that the current pool of reported phosphoproteins represents only a small fraction of the anticipated mitochondrial phosphoproteome. The seminal studies from several groups (12–14, 16) demonstrated the prevalence as well as the dynamic nature of phosphorylation in cardiac mitochondria, suggesting that obtaining a comprehensive map of the mitochondrial phosphoproteome is feasible.In this study, we took a systematic approach to tackle the phosphorylation of murine cardiac mitochondrial pathways. We applied the unique strengths of both electron transfer dissociation (ETD) and collision-induced dissociation (CID) LC-MS/MS to screen phosphorylation events in a site-specific fashion. A total of 236 phosphorylation sites in 203 unique phosphopeptides were identified and mapped to 181 phosphoproteins. Novel phosphorylation modifications were discovered in diverse pathways of mitochondrial biology, including ion balance, proteolysis, and apoptosis. Consistent with the role of mitochondria as the major source of energy production under delicate control, metabolic pathways claimed one-third of phosphorylation sites captured in this analysis. To study molecular players steering mitochondrial phosphorylation, we probed the effects of calcium loading on phosphorylation. In addition, a number of kinases with previously unappreciated mitochondrial residence are suggested as potential players modulating mitochondrial pathways. Taken together, the cohort of novel phosphorylation events discovered in this study constitutes an essential step toward the full delineation of the cardiac mitochondrial phosphoproteome.     

Development and Evaluation of Normalization Methods for Label-free Relative Quantification of Endogenous Peptides

The performances of 10 different normalization methods on data of endogenous brain peptides produced with label-free nano-LC-MS were evaluated. Data sets originating from three different species (mouse, rat, and Japanese quail), each consisting of 35–45 individual LC-MS analyses, were used in the study. Each sample set contained both technical and biological replicates, and the LC-MS analyses were performed in a randomized block fashion. Peptides in all three data sets were found to display LC-MS analysis order-dependent bias. Global normalization methods will only to some extent correct this type of bias. Only the novel normalization procedure RegrRun (linear regression followed by analysis order normalization) corrected for this type of bias. The RegrRun procedure performed the best of the normalization methods tested and decreased the median S.D. by 43% on average compared with raw data. This method also produced the smallest fraction of peptides with interblock differences while producing the largest fraction of differentially expressed peaks between treatment groups in all three data sets. Linear regression normalization (Regr) performed second best and decreased median S.D. by 38% on average compared with raw data. All other examined methods reduced median S.D. by 20–30% on average compared with raw data.Peptidomics is defined as the analysis of the peptide content within an organism, tissue, or cell (1–3). The proteome and peptidome have common features, but there are also prominent differences. Proteomics generally identifies proteins by using the information of biologically inactive peptides derived from tryptic digestion, whereas peptidomics tries to identify endogenous peptides using single peptide sequence information only (4). Endogenous neuropeptides are peptides used for intracellular signaling that can act as neurotransmitters or neuromodulators in the nervous system. These polypeptides of 3–100 amino acids can be abundantly produced in large neural populations or in trace levels from single neurons (5) and are often generated through the cleavage of precursor proteins. However, unwanted peptides can also be created through post-mortem induced proteolysis (6). The later aspect complicates the technical analysis of neuropeptides as post-mortem conditions increase the number of degradation peptides. The possibility to detect, identify, and quantify lowly expressed neuropeptides using label-free LC-MS techniques has improved with the development of new sample preparation techniques including rapid heating of the tissue, which prevents protein degradation and inhibition of post-mortem proteolytic activity (7, 8).It has been suggested by us (4, 5) and others (9) that comparing the peptidome between samples of e.g. diseased and normal tissue may lead to the discovery of biologically relevant peptides of certain pathological or pharmacological events. However, differences in relative peptide abundance measurements may not only originate from biological differences but also from systematic bias and noise. To reduce the effects of experimentally induced variability it is common to normalize the raw data. This is a concept well known in the area of genomics studies using gene expression microarrays (10–12). As a consequence, many methods developed for microarray data have also been adapted for normalizing peptide data produced with LC-MS techniques (10–16). Normally the underlying assumption for applying these techniques is that the total or mean/median peak abundances should be equal across different experiments, in this case between LC-MS analyses. Global normalization methods refer to cases where all peak abundances are used to determine a single normalization factor between experiments (13, 15, 16), a subset of peaks assumed to be similarly abundant between experiments (16) is used, or spiked-in peptides are used as internal standards. In a study by Callister et al. (14), normalization methods for tryptic LC-FTICR-MS peptide data were compared. The authors concluded that global or iterative linear regression works best in most cases but also recommended that the best procedure should be selected for each data set individually. Methods used for normalizing LC-MS data have been reviewed previously (14, 17, 18), but to our knowledge only Callister et al. (14) have used small data sets to systematically evaluate such methods. None of these studies have targeted data of endogenous peptides.In this study, the effects of 10 different normalization methods were evaluated on data produced by a nano-LC system coupled to an electrospray Q-TOF or linear trap quadrupole (LTQ)¹ mass spectrometer. Normalization methods that originally were developed for gene expression data were used, and one novel method, linear regression followed by analysis order normalization (RegrRun), is presented. The normalization methods were evaluated using three data sets of endogenous brain peptides originating from three different species (mouse, rat, and Japanese quail), each consisting of 35–45 individual LC-MS analyses. Each data set contained both technical and biological replicates.     

Impact of Temperature Dependent Sampling Procedures in Proteomics and Peptidomics – A Characterization of the Liver and Pancreas Post Mortem Degradome

Little is known about the nature of post mortem degradation of proteins and peptides on a global level, the so-called degradome. This is especially true for nonneural tissues. Degradome properties in relation to sampling procedures on different tissues are of great importance for the studies of, for instance, post translational modifications and/or the establishment of clinical biobanks. Here, snap freezing of fresh (<2 min post mortem time) mouse liver and pancreas tissue is compared with rapid heat stabilization with regard to effects on the proteome (using two-dimensional differential in-gel electrophoresis) and peptidome (using label free liquid chromatography). We report several proteins and peptides that exhibit heightened degradation sensitivity, for instance superoxide dismutase in liver, and peptidyl-prolyl cis-trans isomerase and insulin C-peptides in pancreas. Tissue sampling based on snap freezing produces a greater amount of degradation products and lower levels of endogenous peptides than rapid heat stabilization. We also demonstrate that solely snap freezing related degradation can be attenuated by subsequent heat stabilization. We conclude that tissue sampling involving a rapid heat stabilization step is preferable to freezing with regard to proteomic and peptidomic sample quality.The evolving maturation of the field of proteomics has, in the same way as in genomics, highlighted the need of better sampling procedures and sample preparation methodologies to minimize the effect of post mortem alterations. The aspect of sample quality is not new in any way and is relevant in most biomedical fields but has only lately started to receive adequate attention. The main factors influencing sample quality is storage temperature of the body until tissue removal (foremost a problem in clinical settings and extraction of less accessible tissue samples from model organisms) and post mortem interval (PMI)¹ (1–3). Post mortem degradation in during PMI is a well known compromising problem when studying endogenous peptides (2, 3) and has also been proven to affect the results of polypeptide (here defined as proteins larger than 10 kDa) studies (3–8). PMI degradation has mainly been studied on human or mouse brain tissue, using two-dimensional electrophoresis (2-DE), SDS-PAGE, and immunoblotting (1, 3–12). There are also a few proteomic studies on muscle tissue degradation in livestock (13–16).We and others have previously explored the effect of focused microwave irradiation with regard to sample quality, demonstrating that this method is more reliable than snap freezing in liquid nitrogen, especially with regard to post-translational modification (PTM) stability (2, 3, 17–20). An alternative method based on cryostat dissection with subsequent heat treatment through boiling has also been reported to improve endogenous peptide sample quality (21). Besides focused microwave irradiation, which is specifically used for rodent brain tissue sampling, we have also demonstrated the efficiency of rapid heat stabilization through conductivity with regard to sample degradation (3, 22). Although somewhat constrained by its dependence on how quickly the tissue is harvested from the body, the latter procedure has the added advantage that it can be used on any type of tissue and species, fresh as well as frozen. This study will compare effects of sampling procedures on the liver and pancreas degradome following rapid heat stabilization, the more traditional snap freezing, or the combination of snap freezing with subsequent heat stabilization.To summarize, this study investigated the effects of post mortem degradation in pancreas and liver. Both tissues are well studied because of their multiple functions in the body and their involvement in different diseases such as diabetes or hepatocarcinoma. Pancreas is especially interesting in this context as it displays endocrine secretion of peptides, and exocrine secretion of digestive enzymes, the later making it a protease rich tissue. We used both two-dimensional difference in gel electrophoresis (2D-DIGE) and label free liquid chromatography mass spectrometry (LC-MS) based differential peptide display (2, 18), the later to better investigate changes in small molecular fragment that are not easily detectable by gel-based methods. 2D-DIGE is an unrivaled methodology to characterize alterations in isoform patterns, which is an important aspect considering that post-translational modifications (PTMs) such as phosphorylations are especially sensitive to post mortem influence within a few minutes PMI (3). The peptidomics approach has been used in several studies to point out early post mortem changes and protein degradation that tissue undergo following sampling and is therefore a well-suited method (3, 18, 22).     

Proteomic Analyses Reveal Divergent Ubiquitylation Site Patterns in Murine Tissues

Posttranslational modifications of proteins increase the complexity of the cellular proteome and enable rapid regulation of protein functions in response to environmental changes. Protein ubiquitylation is a central regulatory posttranslational modification that controls numerous biological processes including proteasomal degradation of proteins, DNA damage repair and innate immune responses. Here we combine high-resolution mass spectrometry with single-step immunoenrichment of di-glycine modified peptides for mapping of endogenous putative ubiquitylation sites in murine tissues. We identify more than 20,000 unique ubiquitylation sites on proteins involved in diverse biological processes. Our data reveals that ubiquitylation regulates core signaling pathways common for each of the studied tissues. In addition, we discover that ubiquitylation regulates tissue-specific signaling networks. Many tissue-specific ubiquitylation sites were obtained from brain highlighting the complexity and unique physiology of this organ. We further demonstrate that different di-glycine-lysine-specific monoclonal antibodies exhibit sequence preferences, and that their complementary use increases the depth of ubiquitylation site analysis, thereby providing a more unbiased view of protein ubiquitylation.Ubiquitin is a small 76-amino-acid protein that is conjugated to the ε-amino group of lysines in a highly orchestrated enzymatic cascade involving ubiquitin activating (E1), ubiquitin conjugating (E2), and ubiquitin ligase (E3) enzymes (1). Ubiquitylation is involved in the regulation of diverse cellular processes including protein degradation (2, 3, 4), DNA damage repair (5, 6), DNA replication (7), cell surface receptor endocytosis, and innate immune signaling (8, 9). Deregulation of protein ubiquitylation is implicated in the development of cancer and neurodegenerative diseases (10, 11). Inhibitors targeting the ubiquitin proteasome system are used in the treatment of hematologic malignancies such as multiple myeloma (12, 13).Recent developments in the mass spectrometry (MS)-based proteomics have greatly expedited proteome-wide analysis of posttranslational modifications (PTMs) (14–17). Large-scale mapping of ubiquitylation sites by mass spectrometry is based on the identification of the di-glycine remnant that results from trypsin digestion of ubiquitylated proteins and remains attached to ubiquitylated lysines (18). Recently, two monoclonal antibodies were developed that specifically recognize di-glycine remnant modified peptides enabling their efficient enrichment from complex peptide mixtures (19, 20). These antibodies have been used to identify thousands of endogenous ubiquitylation sites in human cells, and to quantify site-specific changes in ubiquitylation in response to different cellular perturbations (20–22). It should be noted that the di-glycine remnant is not specific for proteins modified by ubiquitin but also proteins modified by NEDD8 or ISG15 generate an identical di-glycine remnant on modified lysines making it impossible to distinguish between these modifications by mass spectrometry. However, expression of NEDD8 in mouse tissues was shown to be developmentally down-regulated (23), and ISG15 expression in bovine tissues is low in the absence of interferon stimulation (24). In cell culture experiments it was shown that a great majority of sites identified using di-glycine-lysine-specific antibodies stems from ubiquitylated peptides (20).The rates of cell proliferation and protein turnover in mammals vary dramatically between different tissues. Immortalized cell lines, often derived from cancer, are selected for high proliferation rates and fail to represent the complex conditions in tissues. Tissue proteomics can help to gain a more comprehensive understanding of physiological processes in multicellular organisms. Analysis of tissue proteome and PTMs can provide important insights into tissue-specific processes and signaling networks that regulate these processes (25–32). In addition, development of mass spectrometric methods for analysis of PTMs in diseased tissues might lead to the identification of biomarkers.In this study, we combined high-resolution mass spectrometry with immunoenrichment of di-glycine modified peptides to investigate endogenous ubiquitylation sites in murine tissues. We identified more than 20,000 ubiquitylation sites from five different murine tissues and report the largest ubiquitylation dataset obtained from mammalian tissues to date. Furthermore, we compared the performance of the two monoclonal di-glycine-lysine-specific antibodies available for enrichment of ubiquitylated peptides, and reveal their relative preferences for different amino acids flanking ubiquitylation sites.