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.     

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.     

A New in Vivo Cross-linking Mass Spectrometry Platform to Define Protein–Protein Interactions in Living Cells

Protein–protein interactions (PPIs) are fundamental to the structure and function of protein complexes. Resolving the physical contacts between proteins as they occur in cells is critical to uncovering the molecular details underlying various cellular activities. To advance the study of PPIs in living cells, we have developed a new in vivo cross-linking mass spectrometry platform that couples a novel membrane-permeable, enrichable, and MS-cleavable cross-linker with multistage tandem mass spectrometry. This strategy permits the effective capture, enrichment, and identification of in vivo cross-linked products from mammalian cells and thus enables the determination of protein interaction interfaces. The utility of the developed method has been demonstrated by profiling PPIs in mammalian cells at the proteome scale and the targeted protein complex level. Our work represents a general approach for studying in vivo PPIs and provides a solid foundation for future studies toward the complete mapping of PPI networks in living systems.Protein–protein interactions (PPIs)¹ play a key role in defining protein functions in biological systems. Aberrant PPIs can have drastic effects on biochemical activities essential to cell homeostasis, growth, and proliferation, and thereby lead to various human diseases (1). Consequently, PPI interfaces have been recognized as a new paradigm for drug development. Therefore, mapping PPIs and their interaction interfaces in living cells is critical not only for a comprehensive understanding of protein function and regulation, but also for describing the molecular mechanisms underlying human pathologies and identifying potential targets for better therapeutics.Several strategies exist for identifying and mapping PPIs, including yeast two-hybrid, protein microarray, and affinity purification mass spectrometry (AP-MS) (2–5). Thanks to new developments in sample preparation strategies, mass spectrometry technologies, and bioinformatics tools, AP-MS has become a powerful and preferred method for studying PPIs at the systems level (6–9). Unlike other approaches, AP-MS experiments allow the capture of protein interactions directly from their natural cellular environment, thus better retaining native protein structures and biologically relevant interactions. In addition, a broader scope of PPI networks can be obtained with greater sensitivity, accuracy, versatility, and speed. Despite the success of this very promising technique, AP-MS experiments can lead to the loss of weak/transient interactions and/or the reorganization of protein interactions during biochemical manipulation under native purification conditions. To circumvent these problems, in vivo chemical cross-linking has been successfully employed to stabilize protein interactions in native cells or tissues prior to cell lysis (10–16). The resulting covalent bonds formed between interacting partners allow affinity purification under stringent and fully denaturing conditions, consequently reducing nonspecific background while preserving stable and weak/transient interactions (12–16). Subsequent mass spectrometric analysis can reveal not only the identities of interacting proteins, but also cross-linked amino acid residues. The latter provides direct molecular evidence describing the physical contacts between and within proteins (17). This information can be used for computational modeling to establish structural topologies of proteins and protein complexes (17–22), as well as for generating experimentally derived protein interaction network topology maps (23, 24). Thus, cross-linking mass spectrometry (XL-MS) strategies represent a powerful and emergent technology that possesses unparalleled capabilities for studying PPIs.Despite their great potential, current XL-MS studies that have aimed to identify cross-linked peptides have been mostly limited to in vitro cross-linking experiments, with few successfully identifying protein interaction interfaces in living cells (24, 25). This is largely because XL-MS studies remain challenging due to the inherent difficulty in the effective MS detection and accurate identification of cross-linked peptides, as well as in unambiguous assignment of cross-linked residues. In general, cross-linked products are heterogeneous and low in abundance relative to non-cross-linked products. In addition, their MS fragmentation is too complex to be interpreted using conventional database searching tools (17, 26). It is noted that almost all of the current in vivo PPI studies utilize formaldehyde cross-linking because of its membrane permeability and fast kinetics (10–16). However, in comparison to the most commonly used amine reactive NHS ester cross-linkers, identification of formaldehyde cross-linked peptides is even more challenging because of its promiscuous nonspecific reactivity and extremely short spacer length (27). Therefore, further developments in reagents and methods are urgently needed to enable simple MS detection and effective identification of in vivo cross-linked products, and thus allow the mapping of authentic protein contact sites as established in cells, especially for protein complexes.Various efforts have been made to address the limitations of XL-MS studies, resulting in new developments in bioinformatics tools for improved data interpretation (28–32) and new designs of cross-linking reagents for enhanced MS analysis of cross-linked peptides (24, 33–39). Among these approaches, the development of new cross-linking reagents holds great promise for mapping PPIs on the systems level. One class of cross-linking reagents containing an enrichment handle have been shown to allow selective isolation of cross-linked products from complex mixtures, boosting their detectability by MS (33–35, 40–42). A second class of cross-linkers containing MS-cleavable bonds have proven to be effective in facilitating the unambiguous identification of cross-linked peptides (36–39, 43, 44), as the resulting cross-linked products can be identified based on their characteristic and simplified fragmentation behavior during MS analysis. Therefore, an ideal cross-linking reagent would possess the combined features of both classes of cross-linkers. To advance the study of in vivo PPIs, we have developed a new XL-MS platform based on a novel membrane-permeable, enrichable, and MS-cleavable cross-linker, Azide-A-DSBSO (azide-tagged, acid-cleavable disuccinimidyl bis-sulfoxide), and multistage tandem mass spectrometry (MSⁿ). This new XL-MS strategy has been successfully employed to map in vivo PPIs from mammalian cells at both the proteome scale and the targeted protein complex level.     

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.     

JUMP: A Tag-based Database Search Tool for Peptide Identification with High Sensitivity and Accuracy

Database search programs are essential tools for identifying peptides via mass spectrometry (MS) in shotgun proteomics. Simultaneously achieving high sensitivity and high specificity during a database search is crucial for improving proteome coverage. Here we present JUMP, a new hybrid database search program that generates amino acid tags and ranks peptide spectrum matches (PSMs) by an integrated score from the tags and pattern matching. In a typical run of liquid chromatography coupled with high-resolution tandem MS, more than 95% of MS/MS spectra can generate at least one tag, whereas the remaining spectra are usually too poor to derive genuine PSMs. To enhance search sensitivity, the JUMP program enables the use of tags as short as one amino acid. Using a target-decoy strategy, we compared JUMP with other programs (e.g. SEQUEST, Mascot, PEAKS DB, and InsPecT) in the analysis of multiple datasets and found that JUMP outperformed these preexisting programs. JUMP also permitted the analysis of multiple co-fragmented peptides from “mixture spectra” to further increase PSMs. In addition, JUMP-derived tags allowed partial de novo sequencing and facilitated the unambiguous assignment of modified residues. In summary, JUMP is an effective database search algorithm complementary to current search programs.Peptide identification by tandem mass spectra is a critical step in mass spectrometry (MS)-based¹ proteomics (1). Numerous computational algorithms and software tools have been developed for this purpose (2–6). These algorithms can be classified into three categories: (i) pattern-based database search, (ii) de novo sequencing, and (iii) hybrid search that combines database search and de novo sequencing. With the continuous development of high-performance liquid chromatography and high-resolution mass spectrometers, it is now possible to analyze almost all protein components in mammalian cells (7). In contrast to rapid data collection, it remains a challenge to extract accurate information from the raw data to identify peptides with low false positive rates (specificity) and minimal false negatives (sensitivity) (8).Database search methods usually assign peptide sequences by comparing MS/MS spectra to theoretical peptide spectra predicted from a protein database, as exemplified in SEQUEST (9), Mascot (10), OMSSA (11), X!Tandem (12), Spectrum Mill (13), ProteinProspector (14), MyriMatch (15), Crux (16), MS-GFDB (17), Andromeda (18), BaMS² (19), and Morpheus (20). Some other programs, such as SpectraST (21) and Pepitome (22), utilize a spectral library composed of experimentally identified and validated MS/MS spectra. These methods use a variety of scoring algorithms to rank potential peptide spectrum matches (PSMs) and select the top hit as a putative PSM. However, not all PSMs are correctly assigned. For example, false peptides may be assigned to MS/MS spectra with numerous noisy peaks and poor fragmentation patterns. If the samples contain unknown protein modifications, mutations, and contaminants, the related MS/MS spectra also result in false positives, as their corresponding peptides are not in the database. Other false positives may be generated simply by random matches. Therefore, it is of importance to remove these false PSMs to improve dataset quality. One common approach is to filter putative PSMs to achieve a final list with a predefined false discovery rate (FDR) via a target-decoy strategy, in which decoy proteins are merged with target proteins in the same database for estimating false PSMs (23–26). However, the true and false PSMs are not always distinguishable based on matching scores. It is a problem to set up an appropriate score threshold to achieve maximal sensitivity and high specificity (13, 27, 28).De novo methods, including Lutefisk (29), PEAKS (30), NovoHMM (31), PepNovo (32), pNovo (33), Vonovo (34), and UniNovo (35), identify peptide sequences directly from MS/MS spectra. These methods can be used to derive novel peptides and post-translational modifications without a database, which is useful, especially when the related genome is not sequenced. High-resolution MS/MS spectra greatly facilitate the generation of peptide sequences in these de novo methods. However, because MS/MS fragmentation cannot always produce all predicted product ions, only a portion of collected MS/MS spectra have sufficient quality to extract partial or full peptide sequences, leading to lower sensitivity than achieved with the database search methods.To improve the sensitivity of the de novo methods, a hybrid approach has been proposed to integrate peptide sequence tags into PSM scoring during database searches (36). Numerous software packages have been developed, such as GutenTag (37), InsPecT (38), Byonic (39), DirecTag (40), and PEAKS DB (41). These methods use peptide tag sequences to filter a protein database, followed by error-tolerant database searching. One restriction in most of these algorithms is the requirement of a minimum tag length of three amino acids for matching protein sequences in the database. This restriction reduces the sensitivity of the database search, because it filters out some high-quality spectra in which consecutive tags cannot be generated.In this paper, we describe JUMP, a novel tag-based hybrid algorithm for peptide identification. The program is optimized to balance sensitivity and specificity during tag derivation and MS/MS pattern matching. JUMP can use all potential sequence tags, including tags consisting of only one amino acid. When we compared its performance to that of two widely used search algorithms, SEQUEST and Mascot, JUMP identified ∼30% more PSMs at the same FDR threshold. In addition, the program provides two additional features: (i) using tag sequences to improve modification site assignment, and (ii) analyzing co-fragmented peptides from mixture MS/MS spectra.     

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.     

A Double-Barrel Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) System to Quantify 96 Interactomes per Day

The field of proteomics has evolved hand-in-hand with technological advances in LC-MS/MS systems, now enabling the analysis of very deep proteomes in a reasonable time. However, most applications do not deal with full cell or tissue proteomes but rather with restricted subproteomes relevant for the research context at hand or resulting from extensive fractionation. At the same time, investigation of many conditions or perturbations puts a strain on measurement capacity. Here, we develop a high-throughput workflow capable of dealing with large numbers of low or medium complexity samples and specifically aim at the analysis of 96-well plates in a single day (15 min per sample). We combine parallel sample processing with a modified liquid chromatography platform driving two analytical columns in tandem, which are coupled to a quadrupole Orbitrap mass spectrometer (Q Exactive HF). The modified LC platform eliminates idle time between measurements, and the high sequencing speed of the Q Exactive HF reduces required measurement time. We apply the pipeline to the yeast chromatin remodeling landscape and demonstrate quantification of 96 pull-downs of chromatin complexes in about 1 day. This is achieved with only 500 μg input material, enabling yeast cultivation in a 96-well format. Our system retrieved known complex-members and the high throughput allowed probing with many bait proteins. Even alternative complex compositions were detectable in these very short gradients. Thus, sample throughput, sensitivity and LC/MS-MS duty cycle are improved severalfold compared with established workflows. The pipeline can be extended to different types of interaction studies and to other medium complexity proteomes.Shotgun proteomics is concerned with the identification and quantification of proteins (1–3). Prior to analysis, the proteins are digested into peptides, resulting in highly complex mixtures. To deal with this complexity, the peptides are separated by liquid chromatography followed by online analysis with mass spectrometry (MS), today facilitating the characterization of almost complete cell line proteomes in a short time (3–5). In addition to the characterization of entire proteomes, there is also a great demand for analyzing low or medium complexity samples. Given the trend toward a systems biology view, relatively larges sets of samples often have to be measured. One such category of lower complexity protein mixtures occurs in the determination of physical interaction partners of a protein of interest, which requires the identification and quantification of the proteins “pulled-down” or immunoprecipitated via a bait protein. Protein interactions are essential for almost all biological processes and orchestrate a cell''s behavior by regulating enzymes, forming macromolecular assemblies and functionalizing multiprotein complexes that are capable of more complex behavior than the sum of their parts. The human genome has almost 20,000 protein encoding genes, and it has been estimated that 80% of the proteins engage in complex interactions and that 130,000 to 650,000 protein interactions can take place in a human cell (6, 7). These numbers demonstrate a clear need for systematic and high-throughput mapping of protein–protein interactions (PPIs) to understand these complexes.The introduction of generic methods to detect PPIs, such as the yeast two-hybrid screen (Y2H) (8) or affinity purification combined with mass spectrometry (AP-MS)¹ (9), have revolutionized the protein interactomics field. AP-MS in particular has emerged as an important tool to catalogue interactions with the aim of better understanding basic biochemical mechanisms in many different organisms (10–17). It can be performed under near-physiological conditions and is capable of identifying functional protein complexes (18). In addition, the combination of affinity purification with quantitative mass spectrometry has greatly improved the discrimination of true interactors from unspecific background binders, a long-standing challenge in the AP-MS field (19–21). Nowadays, quantitative AP-MS is employed to address many different biological questions, such as detection of dynamic changes in PPIs upon perturbation (22–25) or the impact of posttranslational signaling on PPIs (26, 27). Recent developments even make it possible to provide abundances and stoichiometry information of the bait and prey proteins under study, combined with quantitative data from very deep cellular proteomes. Furthermore, sample preparation in AP-MS can now be performed in high-throughput formats capable of producing hundreds of samples per day. With such throughput in sample generation, the LC-MS/MS part of the AP-MS pipeline has become a major bottleneck for large studies, limiting throughput to a small fraction of the available samples. In principle, this limitation could be circumvented by multiplexing analysis via isotope-labeling strategies (28, 29) or by drastically reducing the measurement time per sample (30–32). The former strategy requires exquisite control of the processing steps and has not been widely implemented yet. The latter strategy depends on mass spectrometers with sufficiently high sequencing speed to deal with the pull-down in a very short time. Since its introduction about 10 years ago (33), the Orbitrap mass spectrometer has featured ever-faster sequencing capabilities, with the Q Exactive HF now reaching a peptide sequencing speed of up to 17 Hz (34). This should now make it feasible to substantially lower the amount of time spent per measurement.Although very short LC-MS/MS runs can in principle be used for high-throughput analyses, they usually lead to a drop in LC-MS duty cycle. This is because each sample needs initial washing, loading, and equilibration steps, independent of gradient time, which takes a substantial percentage for most LC setups - typically at least 15–20 min. To achieve a more efficient LC-MS duty cycle, while maintaining high sensitivity, a second analytical column can be introduced. This enables the parallelization of several steps related to sample loading and to the LC operating steps, including valve switching. Such dual analytical column or “double-barrel: setups have been described for various applications and platforms (30, 35–39).Starting from the reported performance and throughput of workflows that are standard today (16, 21, 40–42), we asked if it would be possible to obtain a severalfold increase in both sample throughput and sensitivity, as well as a considerable reduction in overall wet lab costs and working time. Specifically, our goal was to quantify 96 medium complexity samples in a single day. Such a number of samples can be processed with a 96-well plate, which currently is the format of choice for highly parallelized sample preparation workflows, often with a high degree of automation. We investigated which advances were needed in sample preparation, liquid chromatography, and mass spectrometry. Based on our findings, we developed a parallelized platform for high-throughput sample preparation and LC-MS/MS analysis, which we applied to pull-down samples from the yeast chromatin remodeling landscape. The extent of retrieval of known complex members served as a quality control of the developed pipeline.     

Peptide Identification from Mixture Tandem Mass Spectra

The success of high-throughput proteomics hinges on the ability of computational methods to identify peptides from tandem mass spectra (MS/MS). However, a common limitation of most peptide identification approaches is the nearly ubiquitous assumption that each MS/MS spectrum is generated from a single peptide. We propose a new computational approach for the identification of mixture spectra generated from more than one peptide. Capitalizing on the growing availability of large libraries of single-peptide spectra (spectral libraries), our quantitative approach is able to identify up to 98% of all mixture spectra from equally abundant peptides and automatically adjust to varying abundance ratios of up to 10:1. Furthermore, we show how theoretical bounds on spectral similarity avoid the need to compare each experimental spectrum against all possible combinations of candidate peptides (achieving speedups of over five orders of magnitude) and demonstrate that mixture-spectra can be identified in a matter of seconds against proteome-scale spectral libraries. Although our approach was developed for and is demonstrated on peptide spectra, we argue that the generality of the methods allows for their direct application to other types of spectral libraries and mixture spectra.The success of tandem MS (MS/MS¹) approaches to peptide identification is partly due to advances in computational techniques allowing for the reliable interpretation of MS/MS spectra. Mainstream computational techniques mainly fall into two categories: database search approaches that score each spectrum against peptides in a sequence database (1–4) or de novo techniques that directly reconstruct the peptide sequence from each spectrum (5–8). The combination of these methods with advances in high-throughput MS/MS have promoted the accelerated growth of spectral libraries, collections of peptide MS/MS spectra the identification of which were validated by accepted statistical methods (9, 10) and often also manually confirmed by mass spectrometry experts. The similar concept of spectral archives was also recently proposed to denote spectral libraries including “interesting” nonidentified spectra (11) (i.e. recurring spectra with good de novo reconstructions but no database match). The growing availability of these large collections of MS/MS spectra has reignited the development of alternative peptide identification approaches based on spectral matching (12–14) and alignment (15–17) algorithms.However, mainstream approaches were developed under the (often unstated) assumption that each MS/MS spectrum is generated from a single peptide. Although chromatographic procedures greatly contribute to making this a reasonable assumption, there are several situations where it is difficult or even impossible to separate pairs of peptides. Examples include certain permutations of the peptide sequence or post-translational modifications (see (18) for examples of co-eluting histone modification variants). In addition, innovative experimental setups have demonstrated the potential for increased throughput in peptide identification using mixture spectra; examples include data-independent acquisition (19) ion-mobility MS (20), and MS^E strategies (21).To alleviate the algorithmic bottleneck in such scenarios, we describe a computational approach, M-SPLIT (mixture-spectrum partitioning using library of identified tandem mass spectra), that is able to reliably and efficiently identify peptides from mixture spectra, which are generated from a pair of peptides. In brief, a mixture spectrum is modeled as linear combination of two single-peptide spectra, and peptide identification is done by searching against a spectral library. We show that efficient filtration and accurate branch-and-bound strategies can be used to avoid the huge computational cost of searching all possible pairs. Thus equipped, our approach is able to identify the correct matches by considering only a minuscule fraction of all possible matches. Beyond potentially enhancing the identification capabilities of current MS/MS acquisition setups, we argue that the availability of methods to reliably identify MS/MS spectra from mixtures of peptides could enable the collection of MS/MS data using accelerated chromatography setups to obtain the same or better peptide identification results in a fraction of the experimental time currently required for exhaustive peptide separation.     

Identification and Quantification of Glycoproteins Using Ion-Pairing Normal-phase Liquid Chromatography and Mass Spectrometry

Glycoprotein structure determination and quantification by MS requires efficient isolation of glycopeptides from a proteolytic digest of complex protein mixtures. Here we describe that the use of acids as ion-pairing reagents in normal-phase chromatography (IP-NPLC) considerably increases the hydrophobicity differences between non-glycopeptides and glycopeptides, thereby resulting in the reproducible isolation of N-linked high mannose type and sialylated glycopeptides from the tryptic digest of a ribonuclease B and fetuin mixture. The elution order of non-glycopeptides relative to glycopeptides in IP-NPLC is predictable by their hydrophobicity values calculated using the Wimley-White water/octanol hydrophobicity scale. O-linked glycopeptides can be efficiently isolated from fetuin tryptic digests using IP-NPLC when N-glycans are first removed with PNGase. IP-NPLC recovers close to 100% of bacterial N-linked glycopeptides modified with non-sialylated heptasaccharides from tryptic digests of periplasmic protein extracts from Campylobacter jejuni 11168 and its pglD mutant. Label-free nano-flow reversed-phase LC-MS is used for quantification of differentially expressed glycopeptides from the C. jejuni wild-type and pglD mutant followed by identification of these glycoproteins using multiple stage tandem MS. This method further confirms the acetyltransferase activity of PglD and demonstrates for the first time that heptasaccharides containing monoacetylated bacillosamine are transferred to proteins in both the wild-type and mutant strains. We believe that IP-NPLC will be a useful tool for quantitative glycoproteomics.Protein glycosylation is a biologically significant and complex post-translational modification, involved in cell-cell and receptor-ligand interactions (1–4). In fact, clinical biomarkers and therapeutic targets are often glycoproteins (5–9). Comprehensive glycoprotein characterization, involving glycosylation site identification, glycan structure determination, site occupancy, and glycan isoform distribution, is a technical challenge particularly for quantitative profiling of complex protein mixtures (10–13). Both N- and O-glycans are structurally heterogeneous (i.e. a single site may have different glycans attached or be only partially occupied). Therefore, the MS¹ signals from glycopeptides originating from a glycoprotein are often weaker than from non-glycopeptides. In addition, the ionization efficiency of glycopeptides is low compared with that of non-glycopeptides and is often suppressed in the presence of non-glycopeptides (11–13). When the MS signals of glycopeptides are relatively high in simple protein digests then diagnostic sugar oxonium ion fragments produced by, for example, front-end collisional activation can be used to detect them. However, when peptides and glycopeptides co-elute, parent ion scanning is required to selectively detect the glycopeptides (14). This can be problematic in terms of sensitivity, especially for detecting glycopeptides in digests of complex protein extracts.Isolation of glycopeptides from proteolytic digests of complex protein mixtures can greatly enhance the MS signals of glycopeptides using reversed-phase LC-ESI-MS (RPLC-ESI-MS) or MALDI-MS (15–24). Hydrazide chemistry is used to isolate, identify, and quantify N-linked glycopeptides effectively, but this method involves lengthy chemical procedures and does not preserve the glycan moieties thereby losing valuable information on glycan structure and site occupancy (15–17). Capturing glycopeptides with lectins has been widely used, but restricted specificities and unspecific binding are major drawbacks of this method (18–21). Under reversed-phase LC conditions, glycopeptides from tryptic digests of gel-separated glycoproteins have been enriched using graphite powder medium (22). In this case, however, a second digestion with proteinase K is required for trimming down the peptide moieties of tryptic glycopeptides so that the glycopeptides (typically <5 amino acid residues) essentially resemble the glycans with respect to hydrophilicity for subsequent separation. Moreover, the short peptide sequences of the proteinase K digest are often inadequate for de novo sequencing of the glycopeptides.Glycopeptide enrichment under normal-phase LC (NPLC) conditions has been demonstrated using various hydrophilic media and different capture and elution conditions (23–28). NPLC allows either direct enrichment of peptides modified by various N-linked glycan structures using a ZIC®-HILIC column (23–27) or targeting sialylated glycopeptides using a titanium dioxide micro-column (28). However, NPLC is neither effective for enriching less hydrophilic glycopeptides, e.g. the five high mannose type glycopeptides modified by 7–11 monosaccharide units from a tryptic digest of ribonuclease b (RNase B), nor for enriching O-linked glycopeptides of bovine fetuin using a ZIC-HILIC column (23). The use of Sepharose medium for enriching glycopeptides yielded only modest recovery of glycopeptides (28). In addition, binding of hydrophilic non-glycopeptides with these hydrophilic media contaminates the enriched glycopeptides (23, 28).We have recently developed an ion-pairing normal-phase LC (IP-NPLC) method to enrich glycopeptides from complex tryptic digests using Sepharose medium and salts or bases as ion-pairing reagents (29). Though reasonably effective the technique still left room for significant improvement. For example, the method demonstrated relatively modest glycopeptide selectivity, providing only 16% recovery for high mannose type glycopeptides (29). Here we report on a new IP-NPLC method using acids as ion-pairing reagents and polyhydroxyethyl aspartamide (A) as the stationary phase for the effective isolation of tryptic glycopeptides. The method was developed and evaluated using a tryptic digest of RNase B and fetuin mixture. In addition, we demonstrate that O-linked glycopeptides can be effectively isolated from a fetuin tryptic digest by IP-NPLC after removal of the N-linked glycans by PNGase F.The new IP-NPLC method was used to enrich N-linked glycopeptides from the tryptic digests of protein extracts of wild-type (wt) and PglD mutant strains of Campylobacter jejuni NCTC 11168. C. jejuni has a unique N-glycosylation system that glycosylates periplasmic and inner membrane proteins containing the extended N-linked sequon, D/E-X-N-X-S/T, where X is any amino acid other than proline (30–32). The N-linked glycan of C. jejuni has been previously determined to be GalNAc-α1,4-GalNAc-α1,4-[Glcβ1,3]-GalNAc-α1,4-GalNAc-α1,4-GalNAc-α1,3-Bac-β1 (BacGalNAc₅Glc residue mass: 1406 Da), where Bac is 2,4-diacetamido-2,4,6-trideoxyglucopyranose (30). In addition, the glycan structure of C. jejuni is conserved, unlike in eukaryotic systems (30–32). IP-NPLC recovered close to 100% of the bacterial N-linked glycopeptides with virtually no contamination of non-glycopeptides. Furthermore, we demonstrate for the first time that acetylation of bacillosamine is incomplete in the wt using IP-NPLC and label-free MS.     

Online Peptide Fractionation Using a Multiphasic Microfluidic Liquid Chromatography Chip Improves Reproducibility and Detection Limits for Quantitation in Discovery and Targeted Proteomics

Comprehensive proteomic profiling of biological specimens usually requires multidimensional chromatographic peptide fractionation prior to mass spectrometry. However, this approach can suffer from poor reproducibility because of the lack of standardization and automation of the entire workflow, thus compromising performance of quantitative proteomic investigations. To address these variables we developed an online peptide fractionation system comprising a multiphasic liquid chromatography (LC) chip that integrates reversed phase and strong cation exchange chromatography upstream of the mass spectrometer (MS). We showed superiority of this system for standardizing discovery and targeted proteomic workflows using cancer cell lysates and nondepleted human plasma. Five-step multiphase chip LC MS/MS acquisition showed clear advantages over analyses of unfractionated samples by identifying more peptides, consuming less sample and often improving the lower limits of quantitation, all in highly reproducible, automated, online configuration. We further showed that multiphase chip LC fractionation provided a facile means to detect many N- and C-terminal peptides (including acetylated N terminus) that are challenging to identify in complex tryptic peptide matrices because of less favorable ionization characteristics. Given as much as 95% of peptides were detected in only a single salt fraction from cell lysates we exploited this high reproducibility and coupled it with multiple reaction monitoring on a high-resolution MS instrument (MRM-HR). This approach increased target analyte peak area and improved lower limits of quantitation without negatively influencing variance or bias. Further, we showed a strategy to use multiphase LC chip fractionation LC-MS/MS for ion library generation to integrate with SWATH^TM data-independent acquisition quantitative workflows. All MS data are available via ProteomeXchange with identifier PXD001464.Mass spectrometry based proteomic quantitation is an essential technique used for contemporary, integrative biological studies. Whether used in discovery experiments or for targeted biomarker applications, quantitative proteomic studies require high reproducibility at many levels. It requires reproducible run-to-run peptide detection, reproducible peptide quantitation, reproducible depth of proteome coverage, and ideally, a high degree of cross-laboratory analytical reproducibility. Mass spectrometry centered proteomics has evolved steadily over the past decade, now mature enough to derive extensive draft maps of the human proteome (1, 2). Nonetheless, a key requirement yet to be realized is to ensure that quantitative proteomics can be carried out in a timely manner while satisfying the aforementioned challenges associated with reproducibility. This is especially important for recent developments using data independent MS quantitation and multiple reaction monitoring on high-resolution MS (MRM-HR)¹ as they are both highly dependent on LC peptide retention time reproducibility and precursor detectability, while attempting to maximize proteome coverage (3). Strategies usually employed to increase the depth of proteome coverage utilize various sample fractionation methods including gel-based separation, affinity enrichment or depletion, protein or peptide chemical modification-based enrichment, and various peptide chromatography methods, particularly ion exchange chromatography (4–10). In comparison to an unfractionated “naive” sample, the trade-off in using these enrichments/fractionation approaches are higher risk of sample losses, introduction of undesired chemical modifications (e.g. oxidation, deamidation, N-terminal lactam formation), and the potential for result skewing and bias, as well as numerous time and human resources required to perform the sample preparation tasks. Online-coupled approaches aim to minimize those risks and address resource constraints. A widely practiced example of the benefits of online sample fractionation has been the decade long use of combining strong cation exchange chromatography (SCX) with C18 reversed-phase (RP) for peptide fractionation (known as MudPIT – multidimensional protein identification technology), where SCX and RP is performed under the same buffer conditions and the SCX elution performed with volatile organic cations compatible with reversed phase separation (11). This approach greatly increases analyte detection while avoiding sample handling losses. The MudPIT approach has been widely used for discovery proteomics (12–14), and we have previously shown that multiphasic separations also have utility for targeted proteomics when configured for selected reaction monitoring MS (SRM-MS). We showed substantial advantages of MudPIT-SRM-MS with reduced ion suppression, increased peak areas and lower limits of detection (LLOD) compared with conventional RP-SRM-MS (15).To improve the reproducibility of proteomic workflows, increase throughput and minimize sample loss, numerous microfluidic devices have been developed and integrated for proteomic applications (16, 17). These devices can broadly be classified into two groups: (1) microfluidic chips for peptide separation (18–25) and; (2) proteome reactors that combine enzymatic processing with peptide based fractionation (26–30). Because of the small dimension of these devices, they are readily able to integrate into nanoLC workflows. Various applications have been described including increasing proteome coverage (22, 27, 28) and targeting of phosphopeptides (24, 31, 32), glycopeptides and released glycans (29, 33, 34).In this work, we set out to take advantage of the benefits of multiphasic peptide separations and address the reproducibility needs required for high-throughput comparative proteomics using a variety of workflows. We integrated a multiphasic SCX and RP column in a “plug-and-play” microfluidic chip format for online fractionation, eliminating the need for users to make minimal dead volume connections between traps and columns. We show the flexibility of this format to provide robust peptide separation and reproducibility using conventional and topical mass spectrometry workflows. This was undertaken by coupling the multiphase liquid chromatography (LC) chip to a fast scanning Q-ToF mass spectrometer for data dependent MS/MS, data independent MS (SWATH) and for targeted proteomics using MRM-HR, showing clear advantages for repeatable analyses compared with conventional proteomic workflows.     

Quantitative Protein Topography Analysis and High-Resolution Structure Prediction Using Hydroxyl Radical Labeling and Tandem-Ion Mass Spectrometry (MS)

Hydroxyl radical footprinting based MS for protein structure assessment has the goal of understanding ligand induced conformational changes and macromolecular interactions, for example, protein tertiary and quaternary structure, but the structural resolution provided by typical peptide-level quantification is limiting. In this work, we present experimental strategies using tandem-MS fragmentation to increase the spatial resolution of the technique to the single residue level to provide a high precision tool for molecular biophysics research. Overall, in this study we demonstrated an eightfold increase in structural resolution compared with peptide level assessments. In addition, to provide a quantitative analysis of residue based solvent accessibility and protein topography as a basis for high-resolution structure prediction; we illustrate strategies of data transformation using the relative reactivity of side chains as a normalization strategy and predict side-chain surface area from the footprinting data. We tested the methods by examination of Ca⁺²-calmodulin showing highly significant correlations between surface area and side-chain contact predictions for individual side chains and the crystal structure. Tandem ion based hydroxyl radical footprinting-MS provides quantitative high-resolution protein topology information in solution that can fill existing gaps in structure determination for large proteins and macromolecular complexes.Hydroxyl radical footprinting (HRF)¹ is valuable for assessing the structure of macromolecules. Single nucleotide resolution data enabled by the similar reactivity of the OH radical with each and every backbone position has helped solve important problems in the nucleic acids field, such as understanding RNA folding and ribosome assembly (1–5). Applications of HRF to probe protein structure are a subset of a family of structural MS approaches, including the use of reversible deuterium labeling or irreversible covalent labeling, including labeling with OH radicals (6–13). Hydrogen-deuterium exchange MS (HDX-MS) is particularly suited to measure secondary and tertiary structure stability through backbone exchange, whereas HRF-MS has been effective at measuring the relative solvent accessibility of specific amino acid side chains mediated by intramolecular tertiary and intermolecular quaternary structure interactions. Hydroxyl radicals can be generated by a variety of methods in each case the chemistry has been shown to be quite similar and the radicals react with side chains of surface residues resulting in well characterized oxidation products (7, 10, 11). As up to 18 side chains are potential probes, the overall protein coverage and resolution of the method is theoretically high.Both HDX-MS and HRF-MS utilize a “bottom-up” proteomics approach where proteins are digested to peptide states after labeling, and mass shifts of the resultant peptides are read-out to pinpoint sites of conformational change. Although this usually can provide 90% or more coverage across the entire protein length, in fact the structural resolution is limited as the size of the peptide fragments and the data report the average behavior of the individual residues across the entire peptide, which are typically in the range of five–20 residues (14). MS2 based quantification is in principle a general solution to the problem of increasing structural resolution, and has been attempted for HDX-MS, but the scrambling of the labels in the gas phase has been difficult to overcome using collision induced dissociation (15, 16). Alternative approaches for HDX-MS site localization, like electron transfer dissociation to achieve single residue resolution have potential promise but are typically limited to larger peptides that can access higher charge states easily (17, 18). MS2 strategies to enhance the resolution for covalent labeling experiments have been attempted with some success, as scrambling is not a limitation in covalent labeling experiments (7, 19–21). On the other hand, MS1 based strategies to enhance structural resolution for both HDX and covalent labeling approaches using overlapping protease fragments are also a promising route to providing subpeptide resolution in many cases (7, 20–27).In this work, we present a coupled set of high-throughput experimental and computational approaches to extend previous MS2 based HRF-MS strategies and provide a quantitative topographical structure assessment for proteins at the individual side chain level. The combined approach permits quantification of modifications through examination of a tandem-ion based ladder of peptide fragments and combining the ion abundances from both MS1 and MS2 quantification. The high-resolution information is transformed using the knowledge of the relative reactivity of side chains to predict side-chain surface area for the structurally well-characterized Ca²⁺ bound form of Calmodulin (CaM). In addition, we explored a statistical approach using random forest regression methods to predict solvent accessible surface area at the residue level. Overall, these studies provide a novel approach to provide high-resolution single-residue surface accessibility data with at least eightfold higher spatial resolution than peptide based measures for accurate protein topography predictions.     

A Universal Chemical Enrichment Method for Mapping the Yeast N-glycoproteome by Mass Spectrometry (MS)

Glycosylation is one of the most common and important protein modifications in biological systems. Many glycoproteins naturally occur at low abundances, which makes comprehensive analysis extremely difficult. Additionally, glycans are highly heterogeneous, which further complicates analysis in complex samples. Lectin enrichment has been commonly used, but each lectin is inherently specific to one or several carbohydrates, and thus no single or collection of lectin(s) can bind to all glycans. Here we have employed a boronic acid-based chemical method to universally enrich glycopeptides. The reaction between boronic acids and sugars has been extensively investigated, and it is well known that the interaction between boronic acid and diols is one of the strongest reversible covalent bond interactions in an aqueous environment. This strong covalent interaction provides a great opportunity to catch glycopeptides and glycoproteins by boronic acid, whereas the reversible property allows their release without side effects. More importantly, the boronic acid-diol recognition is universal, which provides great capability and potential for comprehensively mapping glycosylation sites in complex biological samples. By combining boronic acid enrichment with PNGase F treatment in heavy-oxygen water and MS, we have identified 816 N-glycosylation sites in 332 yeast proteins, among which 675 sites were well-localized with greater than 99% confidence. The results demonstrated that the boronic acid-based chemical method can effectively enrich glycopeptides for comprehensive analysis of protein glycosylation. A general trend seen within the large data set was that there were fewer glycosylation sites toward the C termini of proteins. Of the 332 glycoproteins identified in yeast, 194 were membrane proteins. Many proteins get glycosylated in the high-mannose N-glycan biosynthetic and GPI anchor biosynthetic pathways. Compared with lectin enrichment, the current method is more cost-efficient, generic, and effective. This method can be extensively applied to different complex samples for the comprehensive analysis of protein glycosylation.Glycosylation is an extremely important protein modification that frequently regulates protein folding, trafficking, and stability. It is also involved in a wide range of cellular events (1) such as immune response (2, 3), cell proliferation (4), cell-cell interactions (5), and signal transduction (6). Aberrant protein glycosylation is believed to have a direct correlation with the development of several diseases, including diabetes, infectious diseases, and cancer (7–11). Secretory proteins frequently get glycosylated, including those in body fluids such as blood, saliva, and urine (12, 13). Samples containing these proteins can be easily obtained and used for diagnostic and therapeutic purposes. Several glycoproteins have previously been identified as biomarkers, including Her2/Neu in breast cancer (14), prostate-specific antigen (PSA) in prostate cancer (15), and CA125 in ovarian cancer (16, 17), which highlights the clinical importance of identifying glycoproteins as indicators or biomarkers of diseases. Therefore, effective methods for systematic analysis of protein glycosylation are essential to understand the mechanisms of glycobiology, identify drug targets and discover biomarkers.Approximately half of mammalian cell proteins are estimated to be glycosylated at any given time (18). There have been many reports regarding identification of protein glycosylation sites and elucidation of glycan structures (19–30). Glycan structure analysis can lead to potential therapeutic and diagnostic applications (31, 32), but it is also critical to identify which proteins are glycosylated as well as the sites at which the modification occurs. Despite progress in recent years, the large-scale analysis of protein glycosylation sites using MS-based proteomics methods is still a challenge. Without an effective enrichment method, the low abundance of glycoproteins prohibits the identification of the majority of sites using the popular intensity-dependent MS sequence method.About a decade ago, a very beautiful and elegant method based on hydrazide chemistry was developed to enrich glycopeptides. Hydrazide conjugated beads reacted with aldehydes formed from the oxidation of cis-diols in glycans (33). This method has been extensively applied to many different types of biological samples (34–41). Besides the hydrazide-based enrichment method, lectins have also been frequently used to enrich glycopeptides or glycoproteins before MS analysis (28, 29, 42–46). However, there are many different types of lectins, and each is specific to certain glycans (47, 48). Therefore, no combination of lectins can bind to all glycosylated peptides or proteins, which prevents comprehensive analysis of protein glycosylation. Because of the complexity of biological samples, effective enrichment methods are critical for the comprehensive analysis of protein glycosylation before MS analysis.One common feature of all glycoproteins and glycopeptides is that they contain multiple hydroxyl groups in their glycans. From a chemistry point of view, this can be exploited to effectively enrich them. Ideally, chemical enrichment probes must have both strong and specific interactions with multiple hydroxyl groups. The reaction between boronic acids and 1,2- or 1,3-cis-diols in sugars has been extensively studied (49–52) and applied for the small-scale analysis of glycoproteins (53–55). Furthermore, boronate affinity chromatography has been employed for the analysis of nonenzymatically glycated peptides (56, 57). Boronic acid-based chemical enrichment methods are expected to have great potential for global analysis of glycopeptides when combined with modern MS-based proteomics techniques. However, the method has not yet been used for the comprehensive analysis of protein N-glycosylation in complex biological samples (58).Yeast is an excellent model biological system that has been extensively used in a wide range of experiments. Last year, two papers reported the large-scale analysis of protein N-glycosylation in yeast (59, 60). In one study, a new MS-based method was developed based on N-glycopeptide mass envelopes with a pattern via metabolic incorporation of a defined mixture of N-acetylglucosamine isotopologs into N-glycans. Peptides with the recoded envelopes were specifically targeted for fragmentation, facilitating high confidence site mapping (59). Using this method, 133 N-glycosylation sites were confidently identified in 58 yeast proteins. When combined with an effective enrichment method, this MS-based analysis will provide a more complete coverage of the N-glycoproteome. The other work combined lectin enrichment with digestion by two enzymes (Glu_c and trypsin) to increase the peptide coverage, and 516 well-localized N-glycosylation sites were identified in 214 yeast proteins by MS (60).Here we have comprehensively identified protein N-glycosylation sites in yeast by combining a boronic acid-based chemical enrichment method with MS-based proteomics techniques. Magnetic beads conjugated with boronic acid were systematically optimized to selectively enrich glycosylated peptides from yeast whole cell lysates. The enriched peptides were subsequently treated with Peptide-N4-(N-acetyl-beta-glucosaminyl)asparagine amidase (PNGase F)¹ in heavy-oxygen water. Finally, peptides were analyzed by an on-line LC-MS system. Over 800 protein N-glycosylation sites were identified in the yeast proteome, which clearly demonstrates that the boronic acid-based chemical method is an effective enrichment method for large-scale analysis of protein glycosylation by MS.     

From Whole-body Sections Down to Cellular Level,Multiscale Imaging of Phospholipids by MALDI Mass Spectrometry

Significant progress in instrumentation and sample preparation approaches have recently expanded the potential of MALDI imaging mass spectrometry to the analysis of phospholipids and other endogenous metabolites naturally occurring in tissue specimens. Here we explore some of the requirements necessary for the successful analysis and imaging of phospholipids from thin tissue sections of various dimensions by MALDI time-of-flight mass spectrometry. We address methodology issues relative to the imaging of whole-body sections such as those cut from model laboratory animals, sections of intermediate dimensions typically prepared from individual organs, as well as the requirements for imaging areas of interests from these sections at a cellular scale spatial resolution. We also review existing limitations of MALDI imaging MS technology relative to compound identification. Finally, we conclude with a perspective on important issues relative to data exploitation and management that need to be solved to maximize biological understanding of the tissue specimen investigated.Since its introduction in the late 90s (1), MALDI imaging mass spectrometry (MS) technology has witnessed a phenomenal expansion. Initially introduced for the mapping of intact proteins from fresh frozen tissue sections (2), imaging MS is now routinely applied to a wide range of different compounds including peptides, proteins, lipids, metabolites, and xenobiotics (3–7). Numerous compound-specific sample preparation protocols and analytical strategies have been developed. These include tissue sectioning and handling (8–14), automated matrix deposition approaches and data acquisition strategies (15–21), and the emergence of in situ tissue chemistries (22–25). Originally performed on sections cut from fresh frozen tissue specimens, methodologies incorporating an in situ enzymatic digestion step prior to matrix application have been optimized to access the proteome locked in formalin-fixed paraffin-embedded tissue biopsies (25–29). The possibility to use tissues preserved using non-cross-linking approaches has also been demonstrated (30–32). These methodologies are of high importance for the study of numerous diseases because they potentially allow the retrospective analysis for biomarker validation and discovery of the millions of tissue biopsies currently stored worldwide in tissue banks and repositories.In the past decade, instrumentation for imaging MS has also greatly evolved. Whereas the first MS images were collected with time-of-flight instruments (TOF) capable of repetition rates of a few hertz, modern systems are today capable of acquiring data in the kilohertz range and above with improved sensitivity, mass resolving power, and accuracy, significantly reducing acquisition time and improving image quality (33, 34). Beyond time-of-flight analyzers, other MALDI-based instruments have been used such as ion traps (35–37), Qq TOF instruments (38–40), and trap-TOF (16, 41). Ion mobility technology has also been used in conjunction with imaging MS (42–44). More recently, MALDI FT/ICR and Orbitrap mass spectrometers have been demonstrated to be extremely valuable instruments for the performance of imaging MS at very high mass resolving power (45–47). These non-TOF-based systems have proven to be extremely powerful for the imaging of lower molecular weight compounds such as lipids, drugs, and metabolites. Home-built instrumentation and analytical approaches to probe tissues at higher spatial resolution (1–10 μm) have also been described (48–50). In parallel to instrumentation developments, automated data acquisition, image visualization, and processing software packages have now also been developed by most manufacturers.To date, a wide range of biological systems have been studied using imaging MS as a primary methodology. Of strong interest are the organization and identification of the molecular composition of diseased tissues in direct correlation with the underlying histology and how it differs from healthy tissues. Such an approach has been used for the study of cancers (51–54), neurologic disorders (55–57), and other diseases (58, 59). The clinical potential of the imaging MS technology is enormous (7, 60, 61). Results give insights into the onset and progression of diseases, identify novel sets of disease-specific markers, and can provide a molecular confirmation of diagnosis as well as aide in outcome prediction (62–64). Imaging MS has also been extensively used to study the development, functioning, and aging of different organs such as the kidney, prostate, epididymis, and eye lens (65–70). Beyond the study of isolated tissues or organs, whole-body sections from several model animals such as leeches, mice, and rats have been investigated (71–74). For these analyses, specialized instrumentation and protocols are necessary for tissue sectioning and handling (72, 73). Whole-body imaging MS opens the door to the study of the localization and accumulation of administered pharmaceuticals and their known metabolites at the level of entire organisms as well as the monitoring of their efficacy or toxicity as a function of time or dose (72, 73, 75, 76).There is considerable interest in determining the identification and localization of small biomolecules such as lipids in tissues because they are involved in many essential biological functions including cell signaling, energy storage, and membrane structure and function. Defects in lipid metabolism play a role in many diseases such as muscular dystrophy and cardiovascular disease. Phospholipids in tissues have been intensively studied by several groups (37, 40, 77–83). In this respect, for optimal recovery of signal, several variables such as the choice of matrix for both imaging and fragmentation, solvent system, and instrument polarity have been investigated (20, 84). Particularly, the use of lithium cation adducts to facilitate phospholipid identification by tandem MS directly from tissue has also been reported (85). Of significant interest is the recent emergence of two new solvent-free matrix deposition approaches that perform exceptionally well for phospholipid imaging analyses. The first approach, described by Hankin et al. (86), consists in depositing the matrix on the sections through a sublimation process. The described sublimation system consists of sublimation glassware, a heated sand or oil bath (100–200 °C), and a primary vacuum pump (∼5 × 10⁻² torr). Within a few minutes of initiating the sublimation process, an exceptionally homogeneous film of matrix forms on the section. The thickness of the matrix may be controlled by regulating pressure, temperature, and sublimation time. The second approach, described by Puolitaival et al.(87), uses a fine mesh sieve (≤20 μm) to filter finely ground matrix on the tissue sections. Agitation of the sieve results in passage of the matrix through the mesh and the deposition of a fairly homogeneous layer of submicrometer matrix crystals of the surface of the sections. The matrix density on the sections is controlled by direct observation using a standard light microscope. This matrix deposition approach was also found to be ideal to image certain drug compounds (88, 89). Both strategies allow very rapid production of homogeneous matrix coatings on tissue sections with a fairly inexpensive setup. Signal recovery was found to be comparable with those obtained by conventional spray deposition. With the appropriate size sublimation device or sieve, larger sections with dimensions of several centimeters such as those cut from mouse or rat whole bodies can also be rapidly and homogeneously coated.Here we present several examples of MALDI imaging MS of phospholipids from tissue sections using TOF mass spectrometers over a wide range of dimensions from whole-body sections (several centimeters), to individual organs (several millimeters), down to high spatial resolution imaging of selected tissue areas (hundreds of micrometers) at 10-μm lateral resolution and below. For all of these dimension ranges, technological considerations and practical aspects are discussed. In light of the imaging MS results, we also address issues faced for compound identification by tandem MS analysis performed directly on the sections. Finally, we discuss under “Perspective” our vision of the future of the field as well as the technological improvements and analytical tools that need to be improved upon and developed.