Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis.

Glycoproteomics is a powerful yet analytically challenging research tool. Software packages aiding the interpretation of complex glycopeptide tandem mass spectra have appeared, but their relative performance remains untested. Conducted through the HUPO Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates solutions for system-wide glycopeptide analysis. The same mass spectrometrybased glycoproteomics datasets from human serum were shared with participants and the relative team performance for N- and O-glycopeptide data analysis was comprehensively established by orthogonal performance tests. Although the results were variable, several high-performance glycoproteomics informatics strategies were identified. Deep analysis of the data revealed key performance-associated search parameters and led to recommendations for improved 'high-coverage' and 'high-accuracy' glycoproteomics search solutions. This study concludes that diverse software packages for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies and specifies key variables that will guide future software developments and assist informatics decision-making in glycoproteomics.

Quantitative Data-Independent Acquisition Glycoproteomics of Sparkling Wine.

Sparkling wine is an alcoholic beverage enjoyed around the world. The sensory properties of sparkling wine depend on a complex interplay between the chemical and biochemical components in the final product. Glycoproteins have been linked to positive and negative qualities in sparkling wine, but the glycosylation profiles of sparkling wine have not been previously investigated in detail. We analyzed the glycoproteome of sparkling wines using protein- and glycopeptide-centric approaches. We developed an automated workflow that created ion libraries to analyze sequential window acquisition of all theoretical mass spectra data-independent acquisition mass spectrometry data based on glycopeptides identified by Byonic (Protein Metrics; version 2.13.17). We applied our workflow to three pairs of experimental sparkling wines to assess the effects of aging on lees and of different yeast strains used in the liqueur de tirage for secondary fermentation. We found that aging a cuvée on lees for 24 months compared with 8 months led to a dramatic decrease in overall protein abundance and an enrichment in large glycans at specific sites in some proteins. Secondary fermentation of a Riesling wine with Saccharomyces cerevisiae yeast strain Siha4 produced more yeast proteins and glycoproteins than with S. cerevisiae yeast strain DV10. The abundance and glycosylation profiles of grape glycoproteins were also different between grape varieties. To our knowledge, this work represents the first in-depth study into protein- and peptide-specific glycosylation in sparkling wines and describes a quantitative glycoproteomic sequential window acquisition of all theoretical mass spectra/data-independent acquisition workflow that is broadly applicable to other sample types.

Peak Filtering, Peak Annotation, and Wildcard Search for Glycoproteomics.

Glycopeptides in peptide or digested protein samples pose a number of analytical and bioinformatics challenges beyond those posed by unmodified peptides or peptides with smaller posttranslational modifications. Exact structural elucidation of glycans is generally beyond the capability of a single mass spectrometry experiment, so a reasonable level of identification for tandem mass spectrometry, taken by several glycopeptide software tools, is that of peptide sequence and glycan composition, meaning the number of monosaccharides of each distinct mass, e.g., HexNAc(2)Hex(5) rather than man5. Even at this level, however, glycopeptide analysis poses challenges: finding glycopeptide spectra when they are a tiny fraction of the total spectra; assigning spectra with unanticipated glycans, not in the initial glycan database; and finding, scoring, and labeling diagnostic peaks in tandem mass spectra. Here, we discuss recent improvements to Byonic, a glycoproteomics search program, that address these three issues. Byonic now supports filtering spectra by m/z peaks, so that the user can limit attention to spectra with diagnostic peaks, e.g., at least two out of three of 204.087 for HexNAc, 274.092 for NeuAc (with water loss), and 366.139 for HexNAc-Hex, all within a set mass tolerance, e.g., ± 0.01 Da. Also, new is glycan "wildcard" search, which allows an unspecified mass within a user-set mass range to be applied to N- or O-linked glycans and enables assignment of spectra with unanticipated glycans. Finally, the next release of Byonic supports user-specified peak annotations from user-defined posttranslational modifications. We demonstrate the utility of these new software features by finding previously unrecognized glycopeptides in publicly available data, including glycosylated neuropeptides from rat brain.

Alphabet Projection of Spectra.

In the metabolomics, glycomics, and mass spectrometry of structured small molecules, the combinatoric nature of the problem renders a database impossibly large, and thus de novo analysis is necessary. De novo analysis requires an alphabet of mass difference values used to link peaks in fragmentation spectra when they are different by a mass in the alphabet divided by a charge. Often, this alphabet is not known, prohibiting de novo analysis. A method is proposed that, given fragmentation mass spectra, identifies an alphabet of m/z differences that can build large connected graphs from many intense peaks in each spectrum from a collection. We then introduce a novel approach to efficiently find recurring substructures in the de novo graph results.

Differential Quantitative Determination of Site-Specific Intact N-Glycopeptides in Serum Haptoglobin between Hepatocellular Carcinoma and Cirrhosis Using LC-EThcD-MS/MS.

Intact N-glycopeptide analysis remains challenging due to the complexity of glycopeptide structures, low abundance of glycopeptides in protein digests, and difficulties in data interpretation/quantitation. Herein, we developed a workflow that involved advanced methodologies, the EThcD-MS/MS fragmentation method and data interpretation software, for differential analysis of the microheterogeneity of site-specific intact N-glycopeptides of serum haptoglobin between early hepatocellular carcinoma (HCC) and liver cirrhosis. Haptoglobin was immunopurified from 20 µL of serum in patients with early HCC, liver cirrhosis, and healthy controls, respectively, followed by trypsin/GluC digestion, glycopeptide enrichment, and LC-EThcD-MS/MS analysis. Identification and differential quantitation of site-specific N-glycopeptides were performed using a combination of Byonic and Byologic software. In total, 93, 87, and 68 site-specific N-glycopeptides were identified in early HCC, liver cirrhosis, and healthy controls, respectively, with high confidence. The increased variety of N-glycopeptides in liver diseases compared to healthy controls was due to increased branching with hyper-fucosylation and sialylation. Differential quantitation analysis showed that 5 site-specific N-glycopeptides on sites N184 and N241 were significantly elevated in early HCC compared to cirrhosis ( p < 0.05) and normal controls ( p ≤ 0.001). The result demonstrates that the workflow provides a strategy for detailed profiles of N-glycopeptides of patient samples as well as for relative quantitation to determine the level changes in site-specific N-glycopeptides between disease states.

Native and Denaturing MS Protein Deconvolution for Biopharma: Monoclonal Antibodies and Antibody-Drug Conjugates to Polydisperse Membrane Proteins and Beyond.

Electrospray ionization mass spectrometry (ESI-MS) is a ubiquitously used analytical method applied across multiple departments in biopharma, ranging from early research discovery to process development. Accurate, efficient, and consistent protein MS spectral deconvolution across multiple instrument and detector platforms (time-of-flight, Orbitrap, Fourier-transform ion cyclotron resonance) is essential. When proteins are ionized during the ESI process, a distribution of consecutive multiply charged ions are observed on the m/z scale, either positive [M + nH]n+ or negative [M - nH]n- depending on the ionization polarity. The manual calculation of the neutral molecular weight (MW) of single proteins measured by ESI-MS is simple; however, algorithmic deconvolution is required for more complex protein mixtures to derive accurate MWs. Multiple deconvolution algorithms have evolved over the past two decades, all of which have their advantages and disadvantages, in terms of speed, user-input parameters (or ideally lack thereof), and whether they perform optimally on proteins analyzed under denatured or native-MS and solution conditions. Herein, we describe the utility of a parsimonious deconvolution algorithm (explaining the observed spectra with a minimum number of masses) to process a wide range of highly diverse biopharma relevant and research grade proteins and complexes (PEG-GCSF; an IgG1k; IgG1- and IgG2-biotin covalent conjugates; the membrane protein complex AqpZ; a highly polydisperse empty MSP1D1 nanodisc and the tetradecameric chaperone protein complex GroEL) analyzed under native-MS, denaturing LC-MS, and positive and negative modes of ionization, using multiple instruments and therefore multiple data formats. The implementation of a comb filter and peak sharpening option is also demonstrated to be highly effective for deconvolution of highly polydisperse and enhanced separation of a low level lysine glycation post-translational modification (+162.1 Da), partially processed heavy chain lysine residues (+128.1 Da), and loss of N-acetylglucosamine (GlcNAc; -203.1 Da).

Extending Proteome Coverage by Combining MS/MS Methods and a Modified Bioinformatics Platform Adapted for Database Searching of Positive and Negative Polarity 193 nm Ultraviolet Photodissociation Mass Spectra.

To extend proteome coverage obtained from bottom-up mass spectrometry approaches, three complementary ion activation methods, higher energy collision dissociation (HCD), ultraviolet photodissociation (UVPD), and negative mode UVPD (NUVPD), are used to interrogate the tryptic peptides in a human hepatocyte lysate using a high performance Orbitrap mass spectrometer. The utility of combining results from multiple activation techniques (HCD+UVPD+NUVPD) is analyzed for total depth and breadth of proteome coverage. This study also benchmarks a new version of the Byonic algorithm, which has been customized for database searches of UVPD and NUVPD data. Searches utilizing the customized algorithm resulted in over 50% more peptide identifications for UVPD and NUVPD tryptic peptide data sets compared to other search algorithms. Inclusion of UVPD and NUVPD spectra resulted in over 600 additional protein identifications relative to HCD alone.

Parsimonious Charge Deconvolution for Native Mass Spectrometry.

Charge deconvolution infers the mass from mass over charge (m/z) measurements in electrospray ionization mass spectra. When applied over a wide input m/z or broad target mass range, charge-deconvolution algorithms can produce artifacts, such as false masses at one-half or one-third of the correct mass. Indeed, a maximum entropy term in the objective function of MaxEnt, the most commonly used charge deconvolution algorithm, favors a deconvolved spectrum with many peaks over one with fewer peaks. Here we describe a new "parsimonious" charge deconvolution algorithm that produces fewer artifacts. The algorithm is especially well-suited to high-resolution native mass spectrometry of intact glycoproteins and protein complexes. Deconvolution of native mass spectra poses special challenges due to salt and small molecule adducts, multimers, wide mass ranges, and fewer and lower charge states. We demonstrate the performance of the new deconvolution algorithm on a range of samples. On the heavily glycosylated plasma properdin glycoprotein, the new algorithm could deconvolve monomer and dimer simultaneously and, when focused on the m/z range of the monomer, gave accurate and interpretable masses for glycoforms that had previously been analyzed manually using m/z peaks rather than deconvolved masses. On therapeutic antibodies, the new algorithm facilitated the analysis of extensions, truncations, and Fab glycosylation. The algorithm facilitates the use of native mass spectrometry for the qualitative and quantitative analysis of protein and protein assemblies.

Localization of Protein Complex Bound Ligands by Surface-Induced Dissociation High-Resolution Mass Spectrometry.

Surface-induced dissociation (SID) is a powerful means of deciphering protein complex quaternary structures due to its capability of yielding dissociation products that reflect the native structures of protein complexes in solution. Here we explore the suitability of SID to locate the ligand binding sites in protein complexes. We studied C-reactive protein (CRP) pentamer, which contains a ligand binding site within each subunit, and cholera toxin B (CTB) pentamer, which contains a ligand binding site between each adjacent subunit. SID dissects ligand-bound CRP into subcomplexes with each subunit carrying predominantly one ligand. In contrast, SID of ligand-bound CTB results in the generation of subcomplexes with a ligand distribution reflective of two subunits contributing to each ligand binding site. SID thus has potential application in localizing sites of small ligand binding for multisubunit protein-ligand complexes.

Expansion for the Brachylophosaurus canadensis Collagen I Sequence and Additional Evidence of the Preservation of Cretaceous Protein.

Sequence data from biomolecules such as DNA and proteins, which provide critical information for evolutionary studies, have been assumed to be forever outside the reach of dinosaur paleontology. Proteins, which are predicted to have greater longevity than DNA, have been recovered from two nonavian dinosaurs, but these results remain controversial. For proteomic data derived from extinct Mesozoic organisms to reach their greatest potential for investigating questions of phylogeny and paleobiology, it must be shown that peptide sequences can be reliably and reproducibly obtained from fossils and that fragmentary sequences for ancient proteins can be increasingly expanded. To test the hypothesis that peptides can be repeatedly detected and validated from fossil tissues many millions of years old, we applied updated extraction methodology, high-resolution mass spectrometry, and bioinformatics analyses on a Brachylophosaurus canadensis specimen (MOR 2598) from which collagen I peptides were recovered in 2009. We recovered eight peptide sequences of collagen I: two identical to peptides recovered in 2009 and six new peptides. Phylogenetic analyses place the recovered sequences within basal archosauria. When only the new sequences are considered, B. canadensis is grouped more closely to crocodylians, but when all sequences (current and those reported in 2009) are analyzed, B. canadensis is placed more closely to basal birds. The data robustly support the hypothesis of an endogenous origin for these peptides, confirm the idea that peptides can survive in specimens tens of millions of years old, and bolster the validity of the 2009 study. Furthermore, the new data expand the coverage of B. canadensis collagen I (a 33.6% increase in collagen I alpha 1 and 116.7% in alpha 2). Finally, this study demonstrates the importance of reexamining previously studied specimens with updated methods and instrumentation, as we obtained roughly the same amount of sequence data as the previous study with substantially less sample material. Data are available via ProteomeXchange with identifier PXD005087.

Glycoproteomics Reveals Decorin Peptides With Anti-Myostatin Activity in Human Atrial Fibrillation.

BACKGROUND: Myocardial fibrosis is a feature of many cardiac diseases. We used proteomics to profile glycoproteins in the human cardiac extracellular matrix (ECM). METHODS: Atrial specimens were analyzed by mass spectrometry after extraction of ECM proteins and enrichment for glycoproteins or glycopeptides. RESULTS: ECM-related glycoproteins were identified in left and right atrial appendages from the same patients. Several known glycosylation sites were confirmed. In addition, putative and novel glycosylation sites were detected. On enrichment for glycoproteins, peptides of the small leucine-rich proteoglycan decorin were identified consistently in the flowthrough. Of all ECM proteins identified, decorin was found to be the most fragmented. Within its protein core, 18 different cleavage sites were identified. In contrast, less cleavage was observed for biglycan, the most closely related proteoglycan. Decorin processing differed between human ventricles and atria and was altered in disease. The C-terminus of decorin, important for the interaction with connective tissue growth factor, was detected predominantly in ventricles in comparison with atria. In contrast, atrial appendages from patients in persistent atrial fibrillation had greater levels of full-length decorin but also harbored a cleavage site that was not found in atrial appendages from patients in sinus rhythm. This cleavage site preceded the N-terminal domain of decorin that controls muscle growth by altering the binding capacity for myostatin. Myostatin expression was decreased in atrial appendages of patients with persistent atrial fibrillation and hearts of decorin null mice. A synthetic peptide corresponding to this decorin region dose-dependently inhibited the response to myostatin in cardiomyocytes and in perfused mouse hearts. CONCLUSIONS: This proteomics study is the first to analyze the human cardiac ECM. Novel processed forms of decorin protein core, uncovered in human atrial appendages, can regulate the local bioavailability of antihypertrophic and profibrotic growth factors.

Towards an automated analysis of bacterial peptidoglycan structure.

Peptidoglycan (PG) is an essential component of the bacterial cell envelope. This macromolecule consists of glycan chains alternating N-acetylglucosamine and N-acetylmuramic acid, cross-linked by short peptides containing nonstandard amino acids. Structural analysis of PG usually involves enzymatic digestion of glycan strands and separation of disaccharide peptides by reversed-phase HPLC followed by collection of individual peaks for MALDI-TOF and/or tandem mass spectrometry. Here, we report a novel strategy using shotgun proteomics techniques for a systematic and unbiased structural analysis of PG using high-resolution mass spectrometry and automated analysis of HCD and ETD fragmentation spectra with the Byonic software. Using the PG of the nosocomial pathogen Clostridium difficile as a proof of concept, we show that this high-throughput approach allows the identification of all PG monomers and dimers previously described, leaving only disambiguation of 3-3 and 4-3 cross-linking as a manual step. Our analysis confirms previous findings that C. difficile peptidoglycans include mainly deacetylated N-acetylglucosamine residues and 3-3 cross-links. The analysis also revealed a number of low abundance muropeptides with peptide sequences not previously reported. Graphical Abstract The bacterial cell envelope includes plasma membrane, peptidoglycan, and surface layer. Peptidoglycan is unique to bacteria and the target of the most important antibiotics; here it is analyzed by mass spectrometry.

Glycan motif profiling reveals plasma sialyl-lewis x elevations in pancreatic cancers that are negative for sialyl-lewis A.

The sialyl-Lewis A (sLeA) glycan forms the basis of the CA19-9 assay and is the current best biomarker for pancreatic cancer, but because it is not elevated in ∼25% of pancreatic cancers, it is not useful for early diagnosis. We hypothesized that sLeA-low tumors secrete glycans that are related to sLeA but not detectable by CA19-9 antibodies. We used a method called motif profiling to predict that a structural isomer of sLeA called sialyl-Lewis X (sLeX) is elevated in the plasma of some sLeA-low cancers. We corroborated this prediction in a set of 48 plasma samples and in a blinded set of 200 samples. An antibody sandwich assay formed by the capture and detection of sLeX was elevated in 13 of 69 cancers that were not elevated in sLeA, and a novel hybrid assay of sLeA capture and sLeX detected 24 of 69 sLeA-low cancers. A two-marker panel based on combined sLeA and sLeX detection differentiated 109 pancreatic cancers from 91 benign pancreatic diseases with 79% accuracy (74% sensitivity and 78% specificity), significantly better than sLeA alone, which yielded 68% accuracy (65% sensitivity and 71% specificity). Furthermore, sLeX staining was evident in tumors that do not elevate plasma sLeA, including those with poorly differentiated ductal adenocarcinoma. Thus, glycan-based biomarkers could characterize distinct subgroups of patients. In addition, the combined use of sLeA and sLeX, or related glycans, could lead to a biomarker panel that is useful in the clinical diagnosis of pancreatic cancer. Précis: This paper shows that a structural isomer of the current best biomarker for pancreatic cancer, CA19-9, is elevated in the plasma of patients who are low in CA19-9, potentially enabling more comprehensive detection and classification of pancreatic cancers.

A disulfide tether stabilizes the block of sodium channels by the conotoxin µO§-GVIIJ.

A cone snail venom peptide, µO§-conotoxin GVIIJ from Conus geographus, has a unique posttranslational modification, S-cysteinylated cysteine, which makes possible formation of a covalent tether of peptide to its target Na channels at a distinct ligand-binding site. µO§-conotoxin GVIIJ is a 35-aa peptide, with 7 cysteine residues; six of the cysteines form 3 disulfide cross-links, and one (Cys24) is S-cysteinylated. Due to limited availability of native GVIIJ, we primarily used a synthetic analog whose Cys24 was S-glutathionylated (abbreviated GVIIJSSG). The peptide-channel complex is stabilized by a disulfide tether between Cys24 of the peptide and Cys910 of rat (r) NaV1.2. A mutant channel of rNaV1.2 lacking a cysteine near the pore loop of domain II (C910L), was >10(3)-fold less sensitive to GVIIJSSG than was wild-type rNaV1.2. In contrast, although rNaV1.5 was >10(4)-fold less sensitive to GVIIJSSG than NaV1.2, an rNaV1.5 mutant with a cysteine in the homologous location, rNaV1.5[L869C], was >10(3)-fold more sensitive than wild-type rNaV1.5. The susceptibility of rNaV1.2 to GVIIJSSG was significantly altered by treating the channels with thiol-oxidizing or disulfide-reducing agents. Furthermore, coexpression of rNaVß2 or rNaVß4, but not that of rNaVß1 or rNaVß3, protected rNaV1.1 to -1.7 (excluding NaV1.5) against block by GVIIJSSG. Thus, GVIIJ-related peptides may serve as probes for both the redox state of extracellular cysteines and for assessing which NaVß- and NaVα-subunits are present in native neurons.

Full-Featured Search Algorithm for Negative Electron-Transfer Dissociation.

Negative electron-transfer dissociation (NETD) has emerged as a premier tool for peptide anion analysis, offering access to acidic post-translational modifications and regions of the proteome that are intractable with traditional positive-mode approaches. Whole-proteome scale characterization is now possible with NETD, but proper informatic tools are needed to capitalize on advances in instrumentation. Currently only one database search algorithm (OMSSA) can process NETD data. Here we implement NETD search capabilities into the Byonic platform to improve the sensitivity of negative-mode data analyses, and we benchmark these improvements using 90 min LC-MS/MS analyses of tryptic peptides from human embryonic stem cells. With this new algorithm for searching NETD data, we improved the number of successfully identified spectra by as much as 80% and identified 8665 unique peptides, 24 639 peptide spectral matches, and 1338 proteins in activated-ion NETD analyses, more than doubling identifications from previous negative-mode characterizations of the human proteome. Furthermore, we reanalyzed our recently published large-scale, multienzyme negative-mode yeast proteome data, improving peptide and peptide spectral match identifications and considerably increasing protein sequence coverage. In all, we show that new informatics tools, in combination with recent advances in data acquisition, can significantly improve proteome characterization in negative-mode approaches.

Toward Automated N-Glycopeptide Identification in Glycoproteomics.

Advances in software-driven glycopeptide identification have facilitated N-glycoproteomics studies reporting thousands of intact N-glycopeptides, i.e., N-glycan-conjugated peptides, but the automated identification process remains to be scrutinized. Herein, we compare the site-specific glycoprofiling efficiency of the PTM-centric search engine Byonic relative to manual expert annotation utilizing typical glycoproteomics acquisition and data analysis strategies but with a single glycoprotein, the uncharacterized multiple N-glycosylated human basigin. Detailed site-specific reference glycoprofiles of purified basigin were manually established using ion-trap CID-MS/MS and high-resolution Q-Exactive Orbitrap HCD-MS/MS of tryptic N-glycopeptides and released N-glycans. The micro- and macroheterogeneous basigin N-glycosylation was site-specifically glycoprofiled using Byonic with or without a background of complex peptides using Q-Exactive Orbitrap HCD-MS/MS. The automated glycoprofiling efficiencies were assessed against the site-specific reference glycoprofiles and target/decoy proteome databases. Within the limits of this single glycoprotein analysis, the search criteria and confidence thresholds (Byonic scores) recommended by the vendor provided high glycoprofiling accuracy and coverage (both >80%) and low peptide FDRs (<1%). The data complexity, search parameters including search space (proteome/glycome size), mass tolerance and peptide modifications, and confidence thresholds affected the automated glycoprofiling efficiency and analysis time. Correct identification of ambiguous peptide modifications (methionine oxidation/carbamidomethylation) whose mass differences coincide with several monosaccharide mass differences (Fuc/Hex/HexNAc) and of ambiguous isobaric (Hex1NeuAc1-R/Fuc1NeuGc1-R) or near-isobaric (NeuAc1-R/Fuc2-R) monosaccharide subcompositions remains challenging in automated glycoprofiling, arguing particular attention paid to N-glycopeptides displaying such "difficult-to-identify" features. This study provides valuable insights into the automated glycopeptide identification process, stimulating further developments in FDR-based glycoproteomics.

Characterizing Protein Glycosylation through On-Chip Glycan Modification and Probing.

Glycans are critical to protein biology and are useful as disease biomarkers. Many studies of glycans rely on clinical specimens, but the low amount of sample available for some specimens limits the experimental options. Here we present a method to obtain information about protein glycosylation using a minimal amount of protein. We treat proteins that were captured or directly spotted in small microarrays (2.2 mm × 2.2 mm) with exoglycosidases to successively expose underlying features, and then we probe the native or exposed features using a panel of lectins or glycan-binding reagents. We developed an algorithm to interpret the data and provide predictions about the glycan motifs that are present in the sample. We demonstrated the efficacy of the method to characterize differences between glycoproteins in their sialic acid linkages and N-linked glycan branching, and we validated the assignments by comparing results from mass spectrometry and chromatography. The amount of protein used on-chip was about 11 ng. The method also proved effective for analyzing the glycosylation of a cancer biomarker in human plasma, MUC5AC, using only 20 µL of the plasma. A glycan on MUC5AC that is associated with cancer had mostly 2,3-linked sialic acid, whereas other glycans on MUC5AC had a 2,6 linkage of sialic acid. The on-chip glycan modification and probing (on-chip GMAP) method provides a platform for analyzing protein glycosylation in clinical specimens and could complement the existing toolkit for studying glycosylation in disease.

Mass Spectrometry and Antibody-Based Characterization of Blood Vessels from Brachylophosaurus canadensis.

Structures similar to blood vessels in location, morphology, flexibility, and transparency have been recovered after demineralization of multiple dinosaur cortical bone fragments from multiple specimens, some of which are as old as 80 Ma. These structures were hypothesized to be either endogenous to the bone (i.e., of vascular origin) or the result of biofilm colonizing the empty osteonal network after degradation of original organic components. Here, we test the hypothesis that these structures are endogenous and thus retain proteins in common with extant archosaur blood vessels that can be detected with high-resolution mass spectrometry and confirmed by immunofluorescence. Two lines of evidence support this hypothesis. First, peptide sequencing of Brachylophosaurus canadensis blood vessel extracts is consistent with peptides comprising extant archosaurian blood vessels and is not consistent with a bacterial, cellular slime mold, or fungal origin. Second, proteins identified by mass spectrometry can be localized to the tissues using antibodies specific to these proteins, validating their identity. Data are available via ProteomeXchange with identifier PXD001738.

Upregulation of glycans containing 3' fucose in a subset of pancreatic cancers uncovered using fusion-tagged lectins.

The fucose post-translational modification is frequently increased in pancreatic cancer, thus forming the basis for promising biomarkers, but a subset of pancreatic cancer patients does not elevate the known fucose-containing biomarkers. We hypothesized that such patients elevate glycan motifs with fucose in linkages and contexts different from the known fucose-containing biomarkers. We used a database of glycan array data to identify the lectins CCL2 to detect glycan motifs with fucose in a 3' linkage; CGL2 for motifs with fucose in a 2' linkage; and RSL for fucose in all linkages. We used several practical methods to test the lectins and determine the optimal mode of detection, and we then tested whether the lectins detected glycans in pancreatic cancer patients who did not elevate the sialyl-Lewis A glycan, which is upregulated in ∼75% of pancreatic adenocarcinomas. Patients who did not upregulate sialyl-Lewis A, which contains fucose in a 4' linkage, tended to upregulate fucose in a 3' linkage, as detected by CCL2, but they did not upregulate total fucose or fucose in a 2' linkage. CCL2 binding was high in cancerous epithelia from pancreatic tumors, including areas negative for sialyl-Lewis A and a related motif containing 3' fucose, sialyl-Lewis X. Thus, glycans containing 3' fucose may complement sialyl-Lewis A to contribute to improved detection of pancreatic cancer. Furthermore, the use of panels of recombinant lectins may uncover details about glycosylation that could be important for characterizing and detecting cancer.