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.     

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.     

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.     

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.     

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.     

Splitting the BLOSUM Score into Numbers of Biological Significance

Mathematical tools developed in the context of Shannon information theory were used to analyze the meaning of the BLOSUM score, which was split into three components termed as the BLOSUM spectrum (or BLOSpectrum). These relate respectively to the sequence convergence (the stochastic similarity of the two protein sequences), to the background frequency divergence (typicality of the amino acid probability distribution in each sequence), and to the target frequency divergence (compliance of the amino acid variations between the two sequences to the protein model implicit in the BLOCKS database). This treatment sharpens the protein sequence comparison, providing a rationale for the biological significance of the obtained score, and helps to identify weakly related sequences. Moreover, the BLOSpectrum can guide the choice of the most appropriate scoring matrix, tailoring it to the evolutionary divergence associated with the two sequences, or indicate if a compositionally adjusted matrix could perform better.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29]     

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.     

Analysis of Free Energy Signals Arising from Nucleotide Hybridization Between rRNA and mRNA Sequences during Translation in Eubacteria

A decoding algorithm is tested that mechanistically models the progressive alignments that arise as the mRNA moves past the rRNA tail during translation elongation. Each of these alignments provides an opportunity for hybridization between the single-stranded, -terminal nucleotides of the 16S rRNA and the spatially accessible window of mRNA sequence, from which a free energy value can be calculated. Using this algorithm we show that a periodic, energetic pattern of frequency 1/3 is revealed. This periodic signal exists in the majority of coding regions of eubacterial genes, but not in the non-coding regions encoding the 16S and 23S rRNAs. Signal analysis reveals that the population of coding regions of each bacterial species has a mean phase that is correlated in a statistically significant way with species () content. These results suggest that the periodic signal could function as a synchronization signal for the maintenance of reading frame and that codon usage provides a mechanism for manipulation of signal phase.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]     

Delineation of a Carcinogenic Helicobacter pylori Proteome

Helicobacter pylori is the strongest known risk factor for gastric adenocarcinoma, yet only a fraction of infected persons ever develop cancer. The extensive genetic diversity inherent to this pathogen has precluded comprehensive analyses of constituents that mediate carcinogenesis. We previously reported that in vivo adaptation of a non-carcinogenic H. pylori strain endowed the output derivative with the ability to induce adenocarcinoma, providing a unique opportunity to identify proteins selectively expressed by an oncogenic H. pylori strain. Using a global proteomics DIGE/MS approach, a novel missense mutation of the flagellar protein FlaA was identified that affects structure and function of this virulence-related organelle. Among 25 additional differentially abundant proteins, this approach also identified new proteins previously unassociated with gastric cancer, generating a profile of H. pylori proteins to use in vaccine development and for screening persons infected with strains most likely to induce severe disease.Helicobacter pylori is a Gram-negative bacterial species that selectively colonizes gastric epithelium and induces an inflammatory response within the stomach that persists for decades (1, 2). Biological costs incurred by the long term relationship between H. pylori and humans include an increased risk for distal gastric adenocarcinoma (3–8), and eradication of this pathogen significantly decreases cancer risk among infected individuals without premalignant lesions (9). However, only a fraction of colonized persons ever develop neoplasia, and enhanced cancer risk is related to H. pylori strain differences, inflammatory responses governed by host genetic diversity, and/or specific interactions between host and microbial determinants (10).H. pylori strains are remarkably diverse (11–15), and the genetic composition of strains can change over time within an individual colonized stomach (16, 17). Despite this diversity, several genetic loci have been identified that augment disease risk. The cag pathogenicity island encodes a type IV bacterial secretion system, and the product of the terminal gene in this island, CagA, is translocated into host epithelial cells by the cag secretion system following adherence (18–20). Within the host cell, CagA undergoes Src- and Abl-dependent tyrosine phosphorylation (21) and activates the eukaryotic phosphatase SHP-2, leading to dephosphorylation of host cell proteins and cellular morphological changes (19–21). CagA also dysregulates β-catenin signaling (22, 23) and apical-junctional complexes (24), events linked to increased cell motility and oncogenic transformation in several models (25, 26). Another H. pylori constituent linked to gastric cancer is the cytotoxin VacA, encoded by the gene vacA, which is present in virtually all H. pylori strains (27). In vitro, VacA induces the formation of intracellular vacuoles (27) and can induce apoptosis (28), and vacuolating activity is significantly associated with the presence of the cag pathogenicity island (3).Approximately 20% of H. pylori bind to gastric epithelial cells in vivo (29), and sequence analysis has revealed that the H. pylori genome contains an unusually high number of ORFs relative to its genome size that are predicted to encode outer membrane proteins (15). BabA, a member of a family of highly conserved outer membrane proteins and encoded by the strain-specific gene babA2, binds the Lewis^b histo-blood group antigen on gastric epithelial cells (30, 31), and H. pylori babA2⁺ strains are associated with an increased risk for gastric cancer (30). However, not all persons infected with cag⁺ babA2⁺ toxigenic strains develop gastric cancer, indicating that additional H. pylori constituents are important in carcinogenesis.We recently identified a strain of H. pylori, 7.13, that reproducibly induces gastric cancer in two rodent models of gastritis, Mongolian gerbils and hypergastrinemic INS-GAS mice (22). This strain was derived via in vivo adaptation of a clinical H. pylori strain, B128, which induces inflammation, but not cancer, in rodent gastric mucosa. The oncogenic 7.13 phenotype is not due to an enhanced ability of strain 7.13 to colonize as there were no significant differences in gastric colonization density or efficiency between strains B128 and 7.13 as assessed by either quantitative culture or histology. However, carcinogenic strain 7.13 binds more avidly to gastric epithelial cells in vitro than does strain B128, suggesting that the two strains may variably express different outer membrane proteins.To define proteins that may mediate the development of H. pylori-induced gastric cancer, we performed two-dimensional (2D)¹ DIGE coupled with MS to identify differentially abundant membrane-associated and cytosolic proteins from non-carcinogenic H. pylori strain B128 and its carcinogenic derivative, strain 7.13 (22). DIGE/MS is a well established proteomics technology based on conventional 2D gel protein separations whereby prelabeling samples with spectrally resolvable fluorescent dyes and multiplexing samples onto a series of gels that contain a mixture of all experimental samples (internal standard) provide quantitative data on abundance changes for thousands of intact proteins from multiple experimental conditions, each measured in replicate for statistical confidence (32–36). Techniques including DIGE/MS have recently been utilized to robustly define differences in protein abundance profiles between bacterial strains and to compare expression patterns of proteins harvested from bacteria maintained under different growth conditions (37, 38).Utilizing DIGE/MS, we detected and identified 26 proteins with statistically significant differences between strains B128 and 7.13, including a novel cysteine-to-arginine mutation in the H. pylori flagellar protein FlaA. We demonstrate that this FlaA mutation results in structural and functional aberrations. Application of this technique to two genetically related bacterial strains that induce distinct phenotypes also identified several novel candidate H. pylori virulence factors, providing a framework for studies targeting the pathogenesis of microbially induced cancer.