Unravelling Glucan Recognition Systems by Glycome Microarrays Using the Designer Approach and Mass Spectrometry

Glucans are polymers of d-glucose with differing linkages in linear or branched sequences. They are constituents of microbial and plant cell-walls and involved in important bio-recognition processes, including immunomodulation, anticancer activities, pathogen virulence, and plant cell-wall biodegradation. Translational possibilities for these activities in medicine and biotechnology are considerable. High-throughput micro-methods are needed to screen proteins for recognition of specific glucan sequences as a lead to structure–function studies and their exploitation. We describe construction of a “glucome” microarray, the first sequence-defined glycome-scale microarray, using a “designer” approach from targeted ligand-bearing glucans in conjunction with a novel high-sensitivity mass spectrometric sequencing method, as a screening tool to assign glucan recognition motifs. The glucome microarray comprises 153 oligosaccharide probes with high purity, representing major sequences in glucans. Negative-ion electrospray tandem mass spectrometry with collision-induced dissociation was used for complete linkage analysis of gluco-oligosaccharides in linear “homo” and “hetero” and branched sequences. The system is validated using antibodies and carbohydrate-binding modules known to target α- or β-glucans in different biological contexts, extending knowledge on their specificities, and applied to reveal new information on glucan recognition by two signaling molecules of the immune system against pathogens: Dectin-1 and DC-SIGN. The sequencing of the glucan oligosaccharides by the MS method and their interrogation on the microarrays provides detailed information on linkage, sequence and chain length requirements of glucan-recognizing proteins, and are a sensitive means of revealing unsuspected sequences in the polysaccharides.Glucan polysaccharides are polymers of d-glucose with differing linkages in linear or branched sequences. They occur as storage materials in animals, secreted virulence factors of bacteria, and conserved structural components of cell walls of yeasts, fungi, some bacteria, and plants. Polysaccharides of this type are of considerable interest in biology, medicine, and biotechnology and are acknowledged for their immunostimulatory, anticancer, and health-promoting activities (1, 2); for their elicitor activities in defense responses and signaling in plants (3); and for acting as functional ingredients in human nutrition (4). Unraveling recognition systems that mediate these activities is highly desirable as a lead to effective translational applications.Recognition systems involving glucan polysaccharides include those in mammals, such as recognition of fungal β-glucans by Dectin-1, the major receptor of the innate immune system against fungal pathogens (5), and by natural or vaccine-induced protective antifungal antibodies (6, 7); also recognition of mycobacterial α-glucan by the innate immune receptor DC-SIGN (dendritic cell-specific ICAM-3-grabbing nonintegrin) (8); those in insects, such as the Drosophila Gram-negative binding protein 3 (GNBP3) sensor protein, which binds β-glucans (9); and those in bacteria, such as Brucella abortus, where cyclic β-glucans can serve as virulence factors (10).Another important class of glucan-recognizing proteins comprises noncatalytic carbohydrate-binding modules (CBMs)¹ of bacterial glycoside hydrolases that mediate association with substrate and increase catalytic activity, likely through a targeting mechanism or by driving enzyme specificity (11, 12). Notable examples are CBMs of bacterial cellulolytic enzymes that promote enzymatic deconstruction of intact plant cell walls and that are of industrial significance in the biofuel and bioprocessing sectors (13, 14) and CBMs of rumen or commensal human microbiota with roles in animal and human health (14, 15). CBMs also have roles in other systems: for example, CBM-containing enzymes as virulence factors of bacterial pathogens (16) and CBM-containing human laforin that regulates glycogen metabolism and for which mutations can lead to neurodegenerative disease (17). The number of putative glucan-binding CBMs that have been identified and classified in the Carbohydrate-Active enZyme (CAZy) database (http://www.cazy.org) is expanding, but relatively few have been experimentally investigated for details of carbohydrate binding and fine specificity (11).Searching for and assigning the specificities of glucan-recognizing proteins has thus become increasingly important. It is desirable to have high-throughput and sensitive micro-methods to screen for and characterize ligands for structure–function studies toward effective exploitation in modern therapeutic, nutritional, agricultural, and biofuel-related technologies. Carbohydrate microarrays have served to advance knowledge on specificities of diverse carbohydrate-recognition systems (18–22). Where the desired oligosaccharide probes are unavailable, microarrays need to be generated from ligand-bearing glycomes (23). Using a prototype of such designer microarrays of neoglycolipid (NGL)-probes (23) derived from oligosaccharide fragments of glucans rich in β1,3- or β1,6-linked sequences, we showed that linear β1,3-linked glucose sequences with degree of polymerization (DP) 10 or longer are bound by Dectin-1 (24). Recognition of other types of glucan sequences by Dectin-1 and the applicability of microarrays of diverse gluco-oligosaccharide sequences to other glucan-recognizing proteins required investigation. Cummings, Smith, and colleagues have developed the shotgun strategy (20) to create glycome-scale “gangliome” and “human milk glycome” microarrays. In the shotgun microarrays, the printed probes may not be sequence-defined before array construction and require metadata-assisted glycan sequencing (MAGS), which combines MS analysis (25), binding data with glycan-binding proteins or antibodies, and exoglycosidase treatment after printing (26, 27).Mass spectrometry has become a primary technique in carbohydrate structural analysis (28), and electrospray mass spectrometry (ESI-MS) has been used to provide sequence and partial linkage information on various types of oligosaccharides (29–33). For neutral oligosaccharides, we have found that tandem MS with collision-induced dissociation (CID-MS/MS) in the negative-ion mode is particularly useful and have successfully applied for oligosaccharide chain and blood-group typing (34, 35) and for branching pattern analysis (36).This is because that some important linkages at certain monosaccharide residues can be unambiguously determined with high sensitivity without the need for derivatization and anion complexation as previously recognized, e.g. in the area of gluco-oligosaccharides, Cl⁻-anion adduction has been used to determine sequences of tetrasaccharides of dextran (37).Here, we describe a strategy using the designer approach combined with negative-ion ESI-CID-MS/MS for constructing a microarray of sequence-defined gluco-oligosaccharides representing major sequences in glucans (glucome microarray) as a tool for screening glucan-recognizing proteins and assigning their recognition motifs (Fig. 1). We selected a comprehensive panel of glucan polysaccharides isolated from plants, fungi, and bacteria with different sequences to represent the glucome. We used finely tuned chemical and enzymatic methods to partially depolymerize the polysaccharides and prepare gluco-oligosaccharide fragments with different chain lengths (up to DP-13 or DP-16). We developed a ESI-CID-MS/MS method that enables linkage and sequence determination of linear or branched gluco-oligosaccharides at high-sensitivity and applied this to the sequencing of oligosaccharide fragments prepared. These sequence-defined gluco-oligosaccharides were then converted into NGL probes and used for construction of the microarray. The oligosaccharides encompassed linear sequences with homo (single) linkages: 1,2-, 1,3-, 1,4-, or 1,6- with α or β configurations; and hetero (multiple) linkages: 1,3-, 1,4, or 1,6-; also branched oligosaccharide sequences with 1,3 and 1,6-linkages.Open in a separate windowFig. 1.Neoglycolipid (NGL)-based designer glucome microarray with mass spectrometry as a tool to assign carbohydrate ligands in glucan recognition. Ligand-bearing glucan polysaccharides, described in supplemental Fig. S1 and Table S1, were selected as sources of gluco-oligosaccharides for construction of the microarray. A total of 121 gluco-oligosaccharide fractions were obtained with different DP after partial depolymerization of polysaccharides and fractionation. ESI-CID-MS/MS method was developed using gluco-oligosaccharides with known sequences and applied to determination of sequences of oligosaccharide fragments from polysaccharides. Gluco-oligosaccharides were converted to NGL probes for microarray construction and interrogation with the glucan-recognizing proteins described in supplemental Table S2.To our knowledge, this is the first sequence-defined glycome-scale microarray constructed. We used 12 selected proteins (antibodies and CBMs) known to target α- or β-glucans to validate the approach. We then applied the microarray analysis to Dectin-1 and DC-SIGN, which revealed new insights into the specificities of these signaling molecules of the innate immune system.     

Platform Dependencies in Bottom-up Hydrogen/Deuterium Exchange Mass Spectrometry

Hydrogen-deuterium exchange mass spectrometry is an important method for protein structure-function analysis. The bottom-up approach uses protein digestion to localize deuteration to higher resolution, and the essential measurement involves centroid mass determinations on a very large set of peptides. In the course of evaluating systems for various projects, we established two (HDX-MS) platforms that consisted of a FT-MS and a high-resolution QTOF mass spectrometer, each with matched front-end fluidic systems. Digests of proteins spanning a 20–110 kDa range were deuterated to equilibrium, and figures-of-merit for a typical bottom-up (HDX-MS) experiment were compared for each platform. The Orbitrap Velos identified 64% more peptides than the 5600 QTOF, with a 42% overlap between the two systems, independent of protein size. Precision in deuterium measurements using the Orbitrap marginally exceeded that of the QTOF, depending on the Orbitrap resolution setting. However, the unique nature of FT-MS data generates situations where deuteration measurements can be inaccurate, because of destructive interference arising from mismatches in elemental mass defects. This is shown through the analysis of the peptides common to both platforms, where deuteration values can be as low as 35% of the expected values, depending on FT-MS resolution, peptide length and charge state. These findings are supported by simulations of Orbitrap transients, and highlight that caution should be exercised in deriving centroid mass values from FT transients that do not support baseline separation of the full isotopic composition.Hydrogen-deuterium exchange mass spectrometry (HDX-MS)¹ provides a powerful means to study the link between protein structure and function (1). The method involves a chemical process in which labile hydrogens within a protein are exchanged with hydrogen from bulk water. When D₂O is used in place of H₂O, a mass shift results at every point of exchange, but it is the backbone amide hydrogens that offer exchange rates on a measurable timescale (2, 3). Measuring an amide hydrogen exchange rate can provide access to conformational dynamics, stability, and the interaction characteristics in that location of structure (4, 5). H/D exchange rates have be used to explore mechanisms of protein folding (6), determine the allosteric impact of post-translational modifications and ligand binding (7, 8), define truncation points for enhancing crystallization success (9), and they have also found a role in mapping interactions between proteins (10). Applications have stepped outside of primary research to include the characterization of protein drugs for stability and similarity testing (11–13). The capacity to provide such information has attracted increased attention from regulatory bodies and is generating a push for standardizing HDX methods.Mass spectrometers are very effective tools for measuring exchange rates, from whole proteins down to the individual amide levels. Classical methods of rate measurement have used NMR (3), but mass spectrometry offers all the advantages of speed, sensitivity and scale that have made the tool so useful in proteomics. Measurements at the peptide level provide an important intermediate resolution. As with bottom-up proteomics, rendering deuterated proteins into smaller peptides through digestion provides opportunities to analyze protein systems of considerable complexity, and at the same time support analysis at higher structural resolution through MS/MS methods (14, 15). A considerable amount of effort has been applied by the research community and instrument manufacturers to produce instrument configurations that are suitable for managing the many processing steps required for labeling, digesting, separating and introducing deuterated peptides into the mass spectrometer (16). This has been supported by parallel efforts to develop software tools for the detection of deuterated peptides and the extraction of deuteration data (17–19).A successful application of the bottom-up HDX-MS method requires a full peptide sequence map of the protein, so that deuteration rates at every point in protein structure can be quantified and related back to structure. Once the peptide is identified, the primary measurement is the peptide centroid mass of the deuterated state, relative to the unlabeled state. It requires intensity measurements for a minimum of two peaks in the isotopic cluster to determine when the centroid mass changes (20), although most often the full distribution is quantified in HDX-MS applications. As the range of applications continues to grow, particularly in the regulatory area, it is important to better understand how various elements of the HDX platform deliver the essential data (21, 22). In the current study, we are interested in the contribution of the mass spectrometer alone. Most users of the HDX-MS method are migrating from low resolution to high resolution systems, operated in a single-stage MS mode. This includes FT-MS and higher-resolution QTOF platforms, therefore in this study, we explore how an LTQ Orbitrap Velos (Thermo) and a 5600 TripleTOF (AB Sciex) influence the measurement of deuteration data for proteins of increasing size. Identical front-end fluidic systems and protein digests, as well as back-end analysis procedures, allow us to perform a direct comparison of performance in areas of sequence mapping, centroid measurement precision and centroid mass accuracy. We demonstrate that the Orbitrap system returns greater sequencing depth and marginally better precision than the 5600, however the measurement accuracy is strongly influenced by destructive interference arising from unequal mass defects between ¹³C and ²H. This has implications for any application that involves centroid mass determinations, beyond HDX-MS.     

Nepenthesin from Monkey Cups for Hydrogen/Deuterium Exchange Mass Spectrometry

Studies of protein dynamics, structure and interactions using hydrogen/deuterium exchange mass spectrometry (HDX-MS) have sharply increased over the past 5–10 years. The predominant technology requires fast digestion at pH 2–3 to retain deuterium label. Pepsin is used almost exclusively, but it provides relatively low efficiency under the constraints of the experiment, and a selectivity profile that renders poor coverage of intrinsically disordered regions. In this study we present nepenthesin-containing secretions of the pitcher plant Nepenthes, commonly called monkey cups, for use in HDX-MS. We show that nepenthesin is at least 1400-fold more efficient than pepsin under HDX-competent conditions, with a selectivity profile that mimics pepsin in part, but also includes efficient cleavage C-terminal to “forbidden” residues K, R, H, and P. High efficiency permits a solution-based analysis with no detectable autolysis, avoiding the complication of immobilized enzyme reactors. Relaxed selectivity promotes high coverage of disordered regions and the ability to “tune” the mass map for regions of interest. Nepenthesin-enriched secretions were applied to an analysis of protein complexes in the nonhomologous end-joining DNA repair pathway. The analysis of XRCC4 binding to the BRCT domains of Ligase IV points to secondary interactions between the disordered C-terminal tail of XRCC4 and remote regions of the BRCT domains, which could only be identified with a nepenthesin-based workflow. HDX data suggest that stalk-binding to XRCC4 primes a BRCT conformation in these remote regions to support tail interaction, an event which may be phosphoregulated. We conclude that nepenthesin is an effective alternative to pepsin for all HDX-MS applications, and especially for the analysis of structural transitions among intrinsically disordered proteins and their binding partners.Mass spectrometry has served the biochemical and biological communities by providing the capacity for protein identification and characterization, but in the last several years it has also become a powerful tool for interrogating protein structure and dynamics (1, 2). Solution-phase hydrogen/deuterium exchange (HDX)¹, when coupled with mass spectrometry (MS), provides rich sets of data that can be mined to extract structural and dynamic parameters from proteins (3–7). In many cases, the technique is used in experimental situations in which x-ray diffraction analysis or other biophysical techniques (e.g. NMR, cryoEM) are difficult to apply, which is particularly true in the structure-function analysis of protein interactions (8). Most applications of the method involve deuteration of a protein in two or more states, and differential labeling data is extracted at the highest structural resolution possible. Although there have been some impressive developments in top-down protein analysis using newer ion fragmentation methods for label localization (9, 10), most studies continue to employ a bottom-up strategy, in which the protein is digested with an enzyme, and the label is quantified by mass analysis of the resulting peptides.The reasons for the prominence of the bottom-up approach to HDX-MS are shared with the corresponding proteomics method. Peptides may be detected with more sensitivity than proteins, and samples of considerably higher complexity can be interrogated (11). Analytically, this shifts the focus toward optimizing protein digestion, to cover 100% of the sequence and generate a high degree of overlapping fragments to increase opportunities for localizing the deuterium label at high resolution (12–14).The unique requirements of the HDX-MS workflow unfortunately place restrictions on the digestion enzymes that may be used. To avoid label loss through back-exchange to nondeuterated solvent, the kinetics of exchange must be dramatically slowed by pH and temperature reduction, and even under these conditions the digestion must be done rapidly. Conventional methods employ a pH of ∼2.5 and temperatures of 4–10 °C. The aspartic protease pepsin can function under such conditions, which has led to its prominence for HDX-MS applications. This does not mean the enzyme is ideal. Several laboratories have sought to identify other enzymes or develop analytical solutions that address its shortcomings, which include extensive autolysis, modest efficiency, and nonideal substrate specificity. Currently, most methods involve either enzyme microreactors presenting high concentrations of pepsin in a flow-through system (15), or solution-phase digestions using pepsin and protease XIII in separate experiments (16, 17). The latter enzyme is also an aspartic protease with a sequence specificity that partially overlaps pepsin, thus the two maps together tend to somewhat improve sequence coverage (18). A method that fuses the two strategies has recently been described, involving tandem pepsin and protease XIII microreactors (13).Neither strategy is likely to be ideal when applied to protein complexes of far greater complexity, to support of structure-building activities or dynamics analysis of multiprotein “machines.” The microreactor approach complicates the front-end fluidic system, and can lead to sample loss and carryover (19). The solution-phase method requires large amounts of enzyme resulting in contamination because of enzyme autolysis (18). More importantly, neither fully overcomes the low efficiency of these enzymes. In many cases, changing the presentation of substrate can change the sequence map considerably. For example, the sequence map of a protein can be distorted when bound to a second protein (20). A map dependent on the protein load complicates the comparison of deuteration levels for the protein in different states. This alteration suggests a level of substrate inhibition (21), and probably reflects a wide range of specificity constants (k_cat/K_m) across the many individual cleavage sites presented in a protein substrate (22). Similar issues have been noted with trypsin (23). Overall, the sequence maps generated using these methods are serviceable for samples of lower complexity, but low enzymatic efficiency of the available proteases remains an important limitation and a key driver in the search for novel proteases (24).In this study, we characterize the proteolytic activity of secretions from the Nepenthes genus (25), arising from the aspartic protease nepenthesin (26), and evaluate the enzyme for use within HDX applications. Nepenthesin displays remarkably high cleavage efficiency for a broad range of substrates at low pH and temperature, which promotes high sequence coverage for a collection of proteins selected from ongoing HDX projects in our laboratories. Globally, we demonstrate that it outperforms pepsin in sequence coverage and can be used in a simple workflow for broad sequence coverage, or targeted toward a desired area of protein sequence. This new tool was applied to an HDX-MS characterization of a protein complex involved in the nonhomologous end-joining (NHEJ) pathway of DNA damage repair, and the results support a model of the complex proposed from SAXS data (27).     

Identification of Proteins at Active,Stalled, and Collapsed Replication Forks Using Isolation of Proteins on Nascent DNA (iPOND) Coupled with Mass Spectrometry

Both DNA and chromatin need to be duplicated during each cell division cycle. Replication happens in the context of defects in the DNA template and other forms of replication stress that present challenges to both genetic and epigenetic inheritance. The replication machinery is highly regulated by replication stress responses to accomplish this goal. To identify important replication and stress response proteins, we combined isolation of proteins on nascent DNA (iPOND) with quantitative mass spectrometry. We identified 290 proteins enriched on newly replicated DNA at active, stalled, and collapsed replication forks. Approximately 16% of these proteins are known replication or DNA damage response proteins. Genetic analysis indicates that several of the newly identified proteins are needed to facilitate DNA replication, especially under stressed conditions. Our data provide a useful resource for investigators studying DNA replication and the replication stress response and validate the use of iPOND combined with mass spectrometry as a discovery tool.     

Dynamics of Ribosomal Protein S1 on a Bacterial Ribosome with Cross-Linking and Mass Spectrometry

Ribosomal protein S1 has been shown to be a significant effector of prokaryotic translation. The protein is in fact capable of efficiently initiating translation, regardless of the presence of a Shine-Dalgarno sequence in mRNA. Structural insights into this process have remained elusive, as S1 is recalcitrant to traditional techniques of structural analysis, such as x-ray crystallography. Through the application of protein cross-linking and high resolution mass spectrometry, we have detailed the ribosomal binding site of S1 and have observed evidence of its dynamics. Our results support a previous hypothesis that S1 acts as the mRNA catching arm of the prokaryotic ribosome. We also demonstrate that in solution the major domains of the 30S subunit are remarkably flexible, capable of moving 30–50Å with respect to one another.Initiation of translation is often the rate-limiting step of protein biosynthesis (1). In prokaryotes, this process is widely recognized to be directed by the Shine-Dalgarno (S.D.)¹ sequence of mRNA and its complementation with the 3′ end of 16S rRNA (2). However, binding of the S.D. sequence to the ribosome is not obligatory for initiation. Ribosomal protein S1, widely conserved in prokaryotes, (3) has been shown to efficiently initiate translation, regardless of the presence of an S.D. sequence (4, 5).S1 is a strikingly atyptical ribosomal protein, being both the largest (61 kDa) and the most acidic (pI 4.7) (6). The protein is composed of six homologous repeats each forming beta barrel domains (3) that in solution comprise a highly elongated structure spanning up to ca. 230 Å (7). This length is comparable to the diameter of the ribosome itself. In addition to these anomalous characteristics, S1 is also one of only two ribosomal proteins that has been attributed functional significance (6). Ribosomal protein S1, for instance, has no apparent role in the assembly of the ribosome, (2) yet is critical for translation in E. coli (8, 9). The functional significance of S1 is related to its most pronounced characteristic, the ability to simultaneously bind mRNA and the ribosome. Analysis of fragments produced by limited proteolysis and chemical cleavage of S1 has shown that an N-terminal fragment of S1 (residues 1–193) binds the ribosome (10) but not RNA (11). Likewise, a C-terminal fragment (res 172–557) binds RNA (12, 13) but not the ribosome (6, 10). By nature of this bi-functional structure, S1 enhances the E. coli ribosome''s affinity for RNA ∼5000 fold (14) and can directly mediate initiation of translation by binding the 5′ UTR of mRNA (4, 5). These observations have led to the hypothesis that S1 acts as a catching arm for the prokaryotic ribosome, working to bring mRNA to the proximity of the ribosome and thereby facilitate initiation (6).Unfortunately, structural analyses capturing how S1 is able to function in this manner remain elusive. A high-resolution crystal structure of ribosome bound S1, or even free S1, does not exist, because S1 is recalcitrant to crystallography (6). Preparation of ribosomes for x-ray crystallography actually involves the deliberate removal of ribosomal protein S1 as a means to improve the reproducibility of crystallization and the quality of the ribosome crystals formed (15–17). The structure and interactions of the protein have nevertheless intrigued structural biologists for decades. However, studies completed to date have failed to convincingly demonstrate the interaction between S1 and the rest of the 30S subunit, because they were incapable of localizing the individual S1 domains (16, 18–20).We have studied the binding of S1 to the 30S subunit by combining cross-linking with mass spectrometry. Chemical cross-linking has long been appreciated as a technique to probe protein-protein interactions (21, 22). With the advent of modern mass spectrometers, it can be very effectively employed to confidently identify the exact residues involved in linkages (23–28). In most cross-linking analyses, protein residues are targeted for covalent modification with a molecule that contains two reactive groups separated by a spacer arm of known length. Only protein residues closer than the length of the spacer arm are capable of being linked. Identification of cross-linked residues thereby provides distance constraints for structural modeling. In this work, the novel amidinating protein cross-linker, DEST (diethyl suberthioimidate), was employed (29, 30). This amine reactive reagent, unlike commercially available reagents, preserves the native basicity of the residues it modifies while being effective at physiological pH. Use of the reagent is unlikely to perturb protein structure and the modifications it imparts are compatible with ionization for mass spectrometry. We have additionally shown that the cross-links it forms can be efficiently enriched from other components of proteolytic digests using strong cation exchange (SCX) chromatography, (30) and that DEST cross-linking of ribosomes yields structural information in excellent agreement with x-ray crystallography (29). Although DEST is an 11Å spacer arm cross-linker, it links alpha carbons up to 24Å apart because of the length and flexibility of lysine side chains. Nevertheless, this is sufficient resolution to approximate the binding positions of the 10kDa domains of S1. Furthermore, multiple cross-linking of a single domain significantly enhances the resolution with which it can be localized.Here, through the application of protein cross-linking and high resolution mass spectrometry, we show that S1 binds to the 30S subunit near the anti-S.D. motif of the 16S rRNA, demonstrate that it is highly elongated even when bound to the ribosome, and provide evidence that its C-terminal mRNA binding region is remarkably dynamic. Our results thus indicate S1 is structurally poised, as previously hypothesized, (6) to act as the mRNA catching arm of the prokaryotic ribosome.     

DeMix Workflow for Efficient Identification of Cofragmented Peptides in High Resolution Data-dependent Tandem Mass Spectrometry

Based on conventional data-dependent acquisition strategy of shotgun proteomics, we present a new workflow DeMix, which significantly increases the efficiency of peptide identification for in-depth shotgun analysis of complex proteomes. Capitalizing on the high resolution and mass accuracy of Orbitrap-based tandem mass spectrometry, we developed a simple deconvolution method of “cloning” chimeric tandem spectra for cofragmented peptides. Additional to a database search, a simple rescoring scheme utilizes mass accuracy and converts the unwanted cofragmenting events into a surprising advantage of multiplexing. With the combination of cloning and rescoring, we obtained on average nine peptide-spectrum matches per second on a Q-Exactive workbench, whereas the actual MS/MS acquisition rate was close to seven spectra per second. This efficiency boost to 1.24 identified peptides per MS/MS spectrum enabled analysis of over 5000 human proteins in single-dimensional LC-MS/MS shotgun experiments with an only two-hour gradient. These findings suggest a change in the dominant “one MS/MS spectrum - one peptide” paradigm for data acquisition and analysis in shotgun data-dependent proteomics. DeMix also demonstrated higher robustness than conventional approaches in terms of lower variation among the results of consecutive LC-MS/MS runs.Shotgun proteomics analysis based on a combination of high performance liquid chromatography and tandem mass spectrometry (MS/MS) (1) has achieved remarkable speed and efficiency (2–7). In a single four-hour long high performance liquid chromatography-MS/MS run, over 40,000 peptides and 5000 proteins can be identified using a high-resolution Orbitrap mass spectrometer with data-dependent acquisition (DDA)¹ (2, 3). However, in a typical LC-MS analysis of unfractionated human cell lysate, over 100,000 individual peptide isotopic patterns can be detected (4), which corresponds to simultaneous elution of hundreds of peptides. With this complexity, a mass spectrometer needs to achieve ≥25 Hz MS/MS acquisition rate to fully sample all the detectable peptides, and ≥17 Hz to cover reasonably abundant ones (4). Although this acquisition rate is reachable by modern time-of-flight (TOF) instruments, the reported DDA identification results do not encompass all expected peptides. Recently, the next-generation Orbitrap instrument, working at 20 Hz MS/MS acquisition rate, demonstrated nearly full profiling of yeast proteome using an 80 min gradient, which opened the way for comprehensive analysis of human proteome in a time efficient manner (5).During the high performance liquid chromatography-MS/MS DDA analysis of complex samples, high density of co-eluting peptides results in a high probability for two or more peptides to overlap within an MS/MS isolation window. With the commonly used ±1.0–2.0 Th isolation windows, most MS/MS spectra are chimeric (4, 8–10), with cofragmenting precursors being naturally multiplexed. However, as has been discussed previously (9, 10), the cofragmentation events are currently ignored in most of the conventional analysis workflows. According to the prevailing assumption of “one MS/MS spectrum–one peptide,” chimeric MS/MS spectra are generally unwelcome in DDA, because the product ions from different precursors may interfere with the assignment of MS/MS fragment identities, increasing the rate of false discoveries in database search (8, 9). In some studies, the precursor isolation width was set as narrow as ±0.35 Th to prevent unwanted ions from being coselected, fragmented or detected (4, 5).On the contrary, multiplexing by cofragmentation is considered to be one of the solid advantages in data-independent acquisition (DIA) (10–13). In several commonly used DIA methods, the precursor ion selection windows are set much wider than in DDA: from 25 Th as in SWATH (12), to extremely broad range as in AIF (13). In order to use the benefit of MS/MS multiplexing in DDA, several approaches have been proposed to deconvolute chimeric MS/MS spectra. In “alternative peptide identification” method implemented in Percolator (14), a machine learning algorithm reranks and rescores peptide-spectrum matches (PSMs) obtained from one or more MS/MS search engines. But the deconvolution in Percolator is limited to cofragmented peptides with masses differing from the target peptide by the tolerance of the database search, which can be as narrow as a few ppm. The “active demultiplexing” method proposed by Ledvina et al. (15) actively separates MS/MS data from several precursors using masses of complementary fragments. However, higher-energy collisional dissociation often produces MS/MS spectra with too few complementary pairs for reliable peptide identification. The “MixDB” method introduces a sophisticated new search engine, also with a machine learning algorithm (9). And the “second peptide identification” method implemented in Andromeda/MaxQuant workflow (16) submits the same dataset to the search engine several times based on the list of chromatographic peptide features, subtracting assigned MS/MS peaks after each identification round. This approach is similar to the ProbIDTree search engine that also performed iterative identification while removing assigned peaks after each round of identification (17).One important factor for spectral deconvolution that has not been fully utilized in most conventional workflows is the excellent mass accuracy achievable with modern high-resolution mass spectrometry (18). An Orbitrap Fourier-transform mass spectrometer can provide mass accuracy in the range of hundreds of ppb (parts per billion) for mass peaks with high signal-to-noise (S/N) ratio (19). However, the mass error of peaks with lower S/N ratios can be significantly higher and exceed 1 ppm. Despite this dependence of the mass accuracy from the S/N level, most MS and MS/MS search engines only allow users to set hard cut-off values for the mass error tolerances. Moreover, some search engines do not provide the option of choosing a relative error tolerance for MS/MS fragments. Such negligent treatment of mass accuracy reduces the analytical power of high accuracy experiments (18).Identification results coming from different MS/MS search engines are sometimes not consistent because of different statistical assumptions used in scoring PSMs. Introduction of tools integrating the results of different search engines (14, 20, 21) makes the data interpretation even more complex and opaque for the user. The opposite trend—simplification of MS/MS data interpretation—is therefore a welcome development. For example, an extremely straightforward algorithm recently proposed by Wenger et al. (22) demonstrated a surprisingly high performance in peptide identification, even though it is only marginally more complex than simply counting the number of matches of theoretical fragment peaks in high resolution MS/MS, without any a priori statistical assumption.In order to take advantage of natural multiplexing of MS/MS spectra in DDA, as well as properly utilize high accuracy of Orbitrap-based mass spectrometry, we developed a simple and robust data analysis workflow DeMix. It is presented in Fig. 1 as an expansion of the conventional workflow. Principles of some of the processes used by the workflow are borrowed from other approaches, including the custom-made mass peak centroiding (20), chromatographic feature detection (19, 20), and two-pass database search with the first limited pass to provide a “software lock mass” for mass scale recalibration (23).Open in a separate windowFig. 1.An overview of the DeMix workflow that expands the conventional workflow, shown by the dashed line. Processes are colored in purple for TOPP, red for search engine (Morpheus/Mascot/MS-GF+), and blue for in-house programs.In DeMix workflow, the deconvolution of chimeric MS/MS spectra consists of simply “cloning” an MS/MS spectrum if a potential cofragmented peptide is detected. The list of candidate peptide precursors is generated from chromatographic feature detection, as in the MaxQuant/Andromeda workflow (16, 19), but using The OpenMS Proteomics Pipeline (TOPP) (20, 24). During the cloning, the precursor is replaced by the new candidate, but no changes in the MS/MS fragment list are made, and therefore the cloned MS/MS spectra remain chimeric. Processing such spectra requires a search engine tolerant to the presence of unassigned peaks, as such peaks are always expected when multiple precursors cofragment. Thus, we chose Morpheus (22) as a search engine. Based on the original search algorithm, we implement a reformed scoring scheme: Morpheus-AS (advanced scoring). It inherits all the basic principles from Morpheus but deeper utilizes the high mass accuracy of the data. This kind of database search removes the necessity of spectral processing for physical separation of MS/MS data into multiple subspectra (15), or consecutive subtraction of peaks (16, 17).Despite the fact that DeMix workflow is largely a combination of known approaches, it provides remarkable improvement compared with the state-of-the-art. On our Orbitrap Q-Exactive workbench, testing on a benchmark dataset of two-hour single-dimension LC-MS/MS experiments from HeLa cell lysate, we identified on average 1.24 peptide per MS/MS spectrum, breaking the “one MS/MS spectrum–one peptide” paradigm on the level of whole data set. At 1% false discovery rate (FDR), we obtained on average nine PSMs per second (at the actual acquisition rate of ca. seven MS/MS spectra per second), and detected 40 human proteins per minute.     

Targeted Proteomic Quantification on Quadrupole-Orbitrap Mass Spectrometer

There is an immediate need for improved methods to systematically and precisely quantify large sets of peptides in complex biological samples. To date protein quantification in biological samples has been routinely performed on triple quadrupole instruments operated in selected reaction monitoring mode (SRM), and two major challenges remain. Firstly, the number of peptides to be included in one survey experiment needs to be increased to routinely reach several hundreds, and secondly, the degree of selectivity should be improved so as to reliably discriminate the targeted analytes from background interferences. High resolution and accurate mass (HR/AM) analysis on the recently developed Q-Exactive mass spectrometer can potentially address these issues. This instrument presents a unique configuration: it is constituted of an orbitrap mass analyzer equipped with a quadrupole mass filter as the front-end for precursor ion mass selection. This configuration enables new quantitative methods based on HR/AM measurements, including targeted analysis in MS mode (single ion monitoring) and in MS/MS mode (parallel reaction monitoring). The ability of the quadrupole to select a restricted m/z range allows one to overcome the dynamic range limitations associated with trapping devices, and the MS/MS mode provides an additional stage of selectivity. When applied to targeted protein quantification in urine samples and benchmarked with the reference SRM technique, the quadrupole-orbitrap instrument exhibits similar or better performance in terms of selectivity, dynamic range, and sensitivity. This high performance is further enhanced by leveraging the multiplexing capability of the instrument to design novel acquisition methods and apply them to large targeted proteomic studies for the first time, as demonstrated on 770 tryptic yeast peptides analyzed in one 60-min experiment. The increased quality of quadrupole-orbitrap data has the potential to improve existing protein quantification methods in complex samples and address the pressing demand of systems biology or biomarker evaluation studies.Shotgun proteomics has emerged over the past decade as the most effective method for the qualitative study of complex proteomes (i.e., the identification of the protein content), as illustrated by a wealth of publications (1, 2). In this approach, after enzymatic digestion of the proteins, the generated peptides are analyzed by means of liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS)¹ in a data dependent mode. However, the complexity of the digested proteomes under investigation and the wide range of protein abundances limit the reproducibility and the sensitivity of this stochastic approach (3), which is critical if one aims at the systematic quantification of the proteins. Thus, alternative MS approaches have emerged for the systematic quantitative study of complex proteomes, the MS-based targeted proteomics (4). In this hypothesis-driven approach, only specific subsets of analytes (a few targeted peptides used as surrogates for the proteins of interest) are selectively measured in predefined m/z ranges and retention time windows, which overcomes the bias toward most abundant compounds commonly observed with shotgun proteomics. When applied to complex biological samples—for example, bodily fluids such as urine or plasma—targeted proteomics requires high performance instruments allowing measurements of a wide dynamic range (many orders of magnitude), with high sensitivity in order to detect peptides in the low amol range and sufficient selectivity to cope with massive biochemical background (5). Selected reaction monitoring (SRM) on triple quadrupole (6) or triple quadrupole-linear ion trap mass spectrometers (7) has emerged as a means to conduct such analyses (8). Initially applied in the MS analysis of small molecules (9, 10), SRM has gradually emerged as the reference quantitative technique for analyzing proteins (or peptides) in biological samples. When coupled with the isotope dilution strategy (11, 12), this very effective technique allows the precise quantification of proteins (13–18). However, despite the increased selectivity provided by the two-stage mass filtering of SRM (at the precursor and fragment ion levels), the low resolution of mass selection does not allow the systematic removal of interferences (19, 20). Moreover, in proteomics, the biochemical background has a composition similar to that of the analytes of interest, which remains a major hurdle limiting the sensitivity of assays, especially in a bodily fluid matrix. High resolution/accurate mass (HR/AM) analysis represents a promising alternative approach that might more efficiently distinguish the compounds of interest from interferences in targeted proteomics. Such analyses can be conducted on orbitrap-based mass spectrometers because of their high sensitivity and high mass accuracy capabilities (21). The introduction of the benchtop standalone orbitrap mass spectrometer (Exactive) (22) further strengthened the attractiveness of the approach, especially in the field of small molecule analysis (23, 24). However, as quantification using trapping devices intrinsically suffers from a limited dynamic range because of the overall ion capacity, the complexity of biological samples remains very challenging even with the HR/AM approach (25). Targeted protein analysis with triple quadrupole mass spectrometers keeps on showing significant superiority for such samples.² The recently developed quadrupole-orbitrap mass spectrometer (Q-Exactive) can potentially address this issue.³ It is constituted of an orbitrap mass analyzer equipped with a quadrupole mass filter as the front-end for precursor ion mass selection (26, 27). This configuration combines advantages of triple quadrupole instruments for mass filtering and orbitrap-based mass spectrometers for HR/AM measurement. The ability of the instrument to select a restricted m/z range or (sequentially) a small number of precursor ions offers new opportunities for quantification in complex samples by selectively enriching low abundant components. The resulting data, acquired in the so-called single ion monitoring (SIM) mode, fully benefit from the trapping capability while keeping a high acquisition rate as a result of the fast switching time between targeted precursor ions of the quadrupole. Although this mode of data acquisition is possible with a configuration combining a linear ion trap with the orbitrap (as in the LTQ-Orbitrap mass spectrometer), its effectiveness is far more limited in this case. The quadrupole-orbitrap configuration presents significant benefits by selectively isolating a narrow population of precursor ions. Other features of the instrument include its multiplexed trapping capability (26) using either the C-trap or the higher energy collisional dissociation (HCD) cell (28, 29), which opens new avenues in the design of innovative acquisition methods for quantification studies. For the first time, a panel of acquisition methods is designed and applied to targeted quantification at the MS and MS/MS levels. In the latter case, the simultaneous monitoring of multiple MS/MS fragmentation channels, also called parallel reaction monitoring⁴ (PRM), is particularly promising for quantifying large sets of peptides with increased selectivity.     

Comparative Analyses of Data Independent Acquisition Mass Spectrometric Approaches: DIA,WiSIM‐DIA,and Untargeted DIA

Data‐independent acquisition (DIA) is an emerging technology for quantitative proteomics. Current DIA focusses on the identification and quantitation of fragment ions that are generated from multiple peptides contained in the same selection window of several to tens of m/z. An alternative approach is WiSIM‐DIA, which combines conventional DIA with wide‐SIM (wide selected‐ion monitoring) windows to partition the precursor m/z space to produce high‐quality precursor ion chromatograms. However, WiSIM‐DIA has been underexplored; it remains unclear if it is a viable alternative to DIA. We demonstrate that WiSIM‐DIA quantified more than 24 000 unique peptides over five orders of magnitude in a single 2 h analysis of a neuronal synapse‐enriched fraction, compared to 31 000 in DIA. There is a strong correlation between abundance values of peptides quantified in both the DIA and WiSIM‐DIA datasets. Interestingly, the S/N ratio of these peptides is not correlated. We further show that peptide identification directly from DIA spectra identified >2000 proteins, which included unique peptides not found in spectral libraries generated by DDA.     

In situ Quantification of Pancreatic Beta-cell Mass in Mice

Tracing changes of specific cell populations in health and disease is an important goal of biomedical research. The process of monitoring pancreatic beta-cell proliferation and islet growth is particularly challenging. We have developed a method to capture the distribution of beta-cells in the intact pancreas of transgenic mice with fluorescence-tagged beta-cells with a macro written for ImageJ (rsb.info.nih.gov/ij/). Following pancreatic dissection and tissue clearing, the entire pancreas is captured as a virtual slice, after which the GFP-tagged beta-cells are examined. The analysis includes the quantification of total beta-cell area, islet number and size distribution with reference to specific parameters and locations for each islet and for small clusters of beta-cells. The entire distribution of islets can be plotted in three dimensions, and the information from the distribution on the size and shape of each islet allows a quantitative and qualitative comparison of changes in overall beta-cell area at a glance.Download video file.^{(98M, mp4)}     

Improving Statistical Certainty of Glycosylation Similarity between Influenza A Virus Variants Using Data-Independent Acquisition Mass Spectrometry

Amino acid sequences of immunodominant domains of hemagglutinin (HA) on the surface of influenza A virus (IAV) evolve rapidly, producing viral variants. HA mediates receptor recognition, binding and cell entry, and serves as the target for IAV vaccines. Glycosylation, a post-translational modification that places large branched polysaccharide molecules on proteins, can modulate the function of HA and shield antigenic regions allowing for viral evasion from immune responses. Our previous work showed that subtle changes in the HA protein sequence can have a measurable change in glycosylation. Thus, being able to quantitatively measure glycosylation changes in variants is critical for understanding how HA function may change throughout viral evolution. Moreover, understanding quantitatively how the choice of viral expression systems affects glycosylation can help in the process of vaccine design and manufacture. Although IAV vaccines are most commonly expressed in chicken eggs, cell-based vaccines have many advantages, and the adoption of more cell-based vaccines would be an important step in mitigating seasonal influenza and protecting against future pandemics. Here, we have investigated the use of data-independent acquisition (DIA) mass spectrometry for quantitative glycoproteomics. We found that DIA improved the sensitivity of glycopeptide detection for four variants of A/Switzerland/9715293/2013 (H3N2): WT and mutant, each expressed in embryonated chicken eggs and Madin–Darby canine kidney cells. We used the Tanimoto similarity metric to quantify changes in glycosylation between WT and mutant and between egg-expressed and cell-expressed virus. Our DIA site-specific glycosylation similarity comparison of WT and mutant expressed in eggs confirmed our previous analysis while achieving greater depth of coverage. We found that sequence variations and changing viral expression systems affected distinct glycosylation sites of HA. Our methods can be applied to track glycosylation changes in circulating IAV variants to bolster genomic surveillance already being done, for a more complete understanding of IAV evolution.     

SYBR Green I实时荧光定量RT-PCR测定猴免疫缺陷病毒RNA拷贝数方法的建立

目的建立SYBR Green I荧光染料实时定量RT-PCR方法,测定猴免疫缺陷病毒(SIV)RNA拷贝数。方法巢式RT-PCR扩增SIV病毒RNAgag基因上1360-1837之间的长度为477 bp的片段,将该片段克隆到pGEMT载体上,构建pGEM-SIVgag477质粒。该质粒经限制性内切酶NotⅠ酶切后,进行体外转录,转录出的RNA产物(RS)纯化后10倍系列稀释,作出标准曲线,作为SIV病毒RNA荧光定量检测的外标准品。结果应用Qiagen公司QuantiTect SYBR GREEN RT-PCR Kit,该标准品可精确定量到100 copies/μL。结论制备的RS外标准品纯度高,SYBR Green I荧光染料实时定量RT-PCR法特异性、敏感性高,稳定性好,可用于定量测定猴免疫缺陷病毒(SIV)RNA拷贝数。     

Targeted Surface Expression of an Exogenous Antigen in Stably Transfected Babesia bovis

Babesia bovis is a tick-borne intraerythocytic protozoan responsible for acute disease in cattle which can be controlled by vaccination with attenuated B. bovis strains. Emerging B. bovis transfection technologies may increase the usefulness of these live vaccines. One use of transfected B. bovis parasites may be as a vaccine delivery platform. Previous transfection methods for B. bovis were limited by single expression sites and intracellular expression of transfected antigens. This study describes a novel transfection system in which two exogenous genes are expressed: one for selection and the other for a selected antigen designed to be delivered to the surface of the parasites. The strategy for duplicating the number of transfected genes was based on the use of the putative bidirectional promoter of the B. bovis 1.4 Kb ef-1α intergenic region. The ability of this region to regulate two independent expression sites was demonstrated using a luciferase assay on transiently transfected B. bovis parasites and then incorporated into a stable transfection plasmid to control independent expression of the selectable marker GFP-BSD and another gene of interest. A chimeric gene was synthetized using sequences from the protective B-cell epitopes of Rhipicephalus microplus tick antigen Bm86 along with sequences from the surface exposed B. bovis major surface antigen-1. This chimeric gene was then cloned into the additional expression site of the transfection plasmid. Transfection of the B. bovis Mo7 strain with this plasmid resulted in stable insertion into the ef-1α locus and simultaneous expression of both exogenous genes. Expression of the Bm86 epitopes on the surface of transfected merozoites was demonstrated using immunofluorescence analyses. The ability to independently express multiple genes by the inclusion of a bidirectional promoter and the achievement of surface expression of foreign epitopes advances the potential of transfected B. bovis as a future vaccine delivery platform.     

Using Data Independent Acquisition (DIA) to Model High-responding Peptides for Targeted Proteomics Experiments

Targeted mass spectrometry is an essential tool for detecting quantitative changes in low abundant proteins throughout the proteome. Although selected reaction monitoring (SRM) is the preferred method for quantifying peptides in complex samples, the process of designing SRM assays is laborious. Peptides have widely varying signal responses dictated by sequence-specific physiochemical properties; one major challenge is in selecting representative peptides to target as a proxy for protein abundance. Here we present PREGO, a software tool that predicts high-responding peptides for SRM experiments. PREGO predicts peptide responses with an artificial neural network trained using 11 minimally redundant, maximally relevant properties. Crucial to its success, PREGO is trained using fragment ion intensities of equimolar synthetic peptides extracted from data independent acquisition experiments. Because of similarities in instrumentation and the nature of data collection, relative peptide responses from data independent acquisition experiments are a suitable substitute for SRM experiments because they both make quantitative measurements from integrated fragment ion chromatograms. Using an SRM experiment containing 12,973 peptides from 724 synthetic proteins, PREGO exhibits a 40–85% improvement over previously published approaches at selecting high-responding peptides. These results also represent a dramatic improvement over the rules-based peptide selection approaches commonly used in the literature.Targeted proteomics using selected reaction monitoring (SRM)¹ and parallel reaction monitoring (PRM) is increasingly becoming the gold-standard method for peptide quantitation within complex biological matrices (1, 2). By focusing on monitoring only a handful of transitions (associated precursor and fragment ions) for targeted peptides, SRM experiments filter out background signals, which in turn increases the signal to noise ratio. SRM experiments are almost exclusively performed on triple-quadrupole instruments. These instruments can isolate single transitions as an ion beam and measure that beam with extremely sensitive ion-striking detectors. As a result, SRM experiments generally exhibit significantly more accurate quantitation when compared with similarly powered discovery based proteomics experiments, and frequently benefit from a much wider linear range of quantitation (3). SRM experiments often require less fractionation and can be run in shorter time on less expensive instrumentation. These factors allow researchers to greatly scale up the number of samples they can run, which in turn increases the power of their experiment.However, the process of developing an effective SRM assay is often cumbersome, as subtle differences in peptide sequence can have a profound impact on the physiochemical properties and subsquent SRM responses of a peptide. To successfully develop an SRM assay for a protein of interest, unique peptide sequences must be chosen that also produce a high SRM signal (e.g. high-responding peptides). Once identified, these high-responding peptides are often synthesized or purchased, and independently analyzed to determine the most sensitive transition pairs. Finally, the selected peptide and transition pairs must be tested in complex mixtures to screen for transitions with chemical noise interference and to validate the sensitivity of the assay within a particular sample matrix. Peptides and transitions that survive this lengthy screening process can then undergo absolute quantitation by calibrating the signal intensity against standards of known quantity.Although experimental methods have been developed to empirically determine a set of best responding peptides (4), these strategies can be time consuming and require analytical standards, which are currently unavailable for all proteins. More often than not, representative peptides are essentially chosen at random, using only a small number of criteria, such as having a reasonable length for detection in the mass spectrometer, a lack of methionine, and a preference for peptides containing proline (5). It is not uncommon for SRM assays to fail at the final validation steps simply because the peptides chosen in the first assay creation step happened to be unexpectedly poor responding peptides.In an effort to speed up the process of generating robust assays, several groups (6–9) have designed approaches to predict sets of proteotypic peptides using machine-learning algorithms. Proteotypic peptides are peptides commonly identified in shotgun proteomics experiments for a variety of reasons including high signal, low interference, and search engine compatible fragmentation. Enhanced Signature Peptide (ESP) Predictor (7) was the first successful modification of this prediction approach to use proteotypic peptides as a proxy for high-responding peptides for SRM-based quantitation. In brief, Fusaro et al. built a training data set from data-dependent acquired (DDA) yeast peptides and a proxy for their response was quantitated using extracted precursor ion chromatograms (XICs). The authors calculated 550 physiochemical properties for each peptide based on sequence alone and built a random forest classifier to differentiate between the high and low response groups. Other peptide prediction tools follow the same general methodology for developing training data sets. CONSeQuence (8) applies several machine learning strategies and a pared down list of 50 distinct peptide properties. Alternately, Peptide Prediction with Abundance (9) (PPA) uses a back-propagation neural network (10) trained with 15 distinct peptide properties selected from ESP Predictor''s 550. The authors of CONSeQuence and PPA found that their approaches outperformed the ESP Predictor on a variety of data sets.As with most machine learning-based tools, the generality of the training set to real-world data is key to the effectiveness of the resulting prediction tool. Although MS1 intensities extracted from DDA data can be useful for predicting high-responding peptides (11, 12), several factors make them less than ideal for generalizing to SRM and PRM experiments. In particular, DDA peptides must be identified before being quantified and key biochemical features beneficial for targeted analysis of transitions can reduce overall identification rates by producing fragment spectra that are difficult to interpret with typical search engines. By building training data sets on precursor intensities alone these tools ignore the fact that targeted assays actually use fragment ions for quantification. We propose that constructing training sets from DIA fragment intensities (13) will produce machine-learning tools that are more effective at modeling peptides that produce detectible transitions, rather than just proteotypic peptides.The use of digested proteins in training sets presents additional concerns. The observed variance in peptide intensities is confounded by variation in protein abundance. Converting peptide intensities to ranks can remove the dependence on varying protein levels at the cost of corrupting the training set with proteins that biochemically contain no high-responding peptides. PPA attempts to ease this concern by training with Intensity Based Absolute Quantitation values (14) for DDA peptides estimated from XICs. We hypothesize that constructing a training set from equimolar synthetic peptides removes most adverse effects of digestion from the training set, making it possible to construct a more generalizable tool.     

Simultaneous Quantification of Multiple Urinary Naphthalene Metabolites by Liquid Chromatography Tandem Mass Spectrometry

Naphthalene is an environmental toxicant to which humans are exposed. Naphthalene causes dose-dependent cytotoxicity to murine airway epithelial cells but a link between exposure and human pulmonary disease has not been established. Naphthalene toxicity in rodents depends on P450 metabolism. Subsequent biotransformation results in urinary elimination of several conjugated metabolites. Glucuronide and sulfate conjugates of naphthols have been used as markers of naphthalene exposure but, as the current studies demonstrate, these assays provide a limited view of the range of metabolites generated from the parent hydrocarbon. Here, we present a liquid chromatography tandem mass spectrometry method for measurement of the glucuronide and sulfate conjugates of 1-naphthol as well as the mercapturic acids and N-acetyl glutathione conjugates from naphthalene epoxide. Standard curves were linear over 2 log orders. On column detection limits varied from 0.91 to 3.4 ng; limits of quantitation from 1.8 to 6.4 ng. The accuracy of measurement of spiked urine standards was -13.1 to + 5.2% of target and intra-day and inter-day variability averaged 7.2 (± 4.5) and 6.8 (± 5.0) %, respectively. Application of the method to urine collected from mice exposed to naphthalene at 15 ppm (4 hrs) showed that glutathione-derived metabolites accounted for 60-70% of the total measured metabolites and sulfate and glucuronide conjugates were eliminated in equal amounts. The method is robust and directly measures several major naphthalene metabolites including those derived from glutathione conjugation of naphthalene epoxide. The assays do not require enzymatic deconjugation, extraction or derivatization thus simplifying sample work up.     

Using Long-Term Volunteer Records to Examine Dormouse ( Muscardinus avellanarius ) Nestbox Selection

Within ecology, there are unanswered questions about species-habitat interactions, which could potentially be resolved by a pragmatic analysis of a long-term volunteer-collected dataset. Here, we analysed 18 years of volunteer-collected data from a UK dormouse nestbox monitoring programme to determine the influence of habitat variables on nestbox choice by common dormice ( Muscardinus avellanarius ). We measured a range of habitat variables in a coppiced woodland in Gloucestershire, UK, and analysed these in relation to dormouse nestbox occupancy records (by dormice, other small mammals, and birds) collected by volunteers. While some characteristics of the woodland had changed over 18 years, simple transformation of the data and interpretation of the results indicated that the dataset was informative. Using stepwise regressions, multiple environmental and ecological factors were found to determine nestbox selection. Distance from the edge of the wood was the most influential (this did not change over 18 years), with boxes in the woodland interior being selected preferentially. There was a significant negative relationship with the presence of ferns (indicative of damp shady conditions). The presence of oak (a long-lived species), and the clumped structural complexity of the canopy were also important factors in the final model. There was no evidence of competition between dormice and birds or other mammals. The results provide greater understanding of artificial dormouse nest-site requirements and indicate that, in terms of habitat selection, long-term volunteer-collected datasets contribute usefully to understanding the requirements of species with an important conservation status.     

Binding of the Heterogeneous Ribonucleoprotein K (hnRNP K) to the Epstein-Barr Virus Nuclear Antigen 2 (EBNA2) Enhances Viral LMP2A Expression

The Epstein-Barr Virus (EBV) -encoded EBNA2 protein, which is essential for the in vitro transformation of B-lymphocytes, interferes with cellular processes by binding to proteins via conserved sequence motifs. Its Arginine-Glycine (RG) repeat element contains either symmetrically or asymmetrically di-methylated arginine residues (SDMA and ADMA, respectively). EBNA2 binds via its SDMA-modified RG-repeat to the survival motor neurons protein (SMN) and via the ADMA-RG-repeat to the NP9 protein of the human endogenous retrovirus K (HERV-K (HML-2) Type 1). The hypothesis of this work was that the methylated RG-repeat mimics an epitope shared with cellular proteins that is used for interaction with target structures. With monoclonal antibodies against the modified RG-repeat, we indeed identified cellular homologues that apparently have the same surface structure as methylated EBNA2. With the SDMA-specific antibodies, we precipitated the Sm protein D3 (SmD3) which, like EBNA2, binds via its SDMA-modified RG-repeat to SMN. With the ADMA-specific antibodies, we precipitated the heterogeneous ribonucleoprotein K (hnRNP K). Specific binding of the ADMA- antibody to hnRNP K was demonstrated using E. coli expressed/ADMA-methylated hnRNP K. In addition, we show that EBNA2 and hnRNP K form a complex in EBV- infected B-cells. Finally, hnRNP K, when co-expressed with EBNA2, strongly enhances viral latent membrane protein 2A (LMP2A) expression by an unknown mechanism as we did not detect a direct association of hnRNP K with DNA-bound EBNA2 in gel shift experiments. Our data support the notion that the methylated surface of EBNA2 mimics the surface structure of cellular proteins to interfere with or co-opt their functional properties.