Identification Of Glycans Research Articles

Resolving Isomeric Structures of Native Glycans by Nanoflow Porous Graphitized Carbon Chromatography-Mass Spectrometry.

Characterization of the structural diversity of glycans by liquid chromatography-tandem mass spectrometry (LC-MS/MS) remains an analytical challenge in large-scale glycomics applications because of the presence of heterogeneous composition, ubiquitous isomers, lability of post-translational glycan modifications, and complexity of data interpretation. High-resolution separation of glycan isomers differentiating from positional, linkage, branching, and anomeric structures is often a prerequisite to ensure the comprehensive glycan identification. Here, we developed a straightforward method using self-packed capillary porous graphitic carbon (PGC) columns for nanoflow LC-MS/MS analyses of native glycans released from glycoproteins. The technique enables highly resolved chromatographic separation of over 20 high-mannose glycan isomers in ribonuclease B and a diverse range of hybrid and complex-type sialoglycoforms of fetuin. The distinct structures of anomeric glycans and linkage sialoglycan isomers, α2,3 and α2,6, were identified by the characteristic MS/MS fragment ions. A glycan sequencing strategy utilizing diagnostic ions and complementary fragments specific to branching residues was established to simplify the MS/MS data interpretation of closely related isomeric structures. To promote the PGC-LC-MS/MS-based method for glycome-wide applications, we extended analyses to native sulfoglycans from the egg-propagated and cell culture-derived influenza vaccines and demonstrate the high-resolution separation and structural characterization of underivatized neutral and anionic glycoforms including oligomannosidic glycan anomers, sialoglycan linkage isomers, and regioisomers of afucosylated and fucosylated sulfoglycans containing sulfated-6-GlcNAc and sulfated-4-GalNAc residues.

Accurate Identification of Isomeric Glycans by Trapped Ion Mobility Spectrometry-Electronic Excitation Dissociation Tandem Mass Spectrometry.

Ion mobility-mass spectrometry (IM-MS) has become a powerful tool for glycan structural characterization due to its ability to separate isomers and provide collision cross section (CCS) values that facilitate structural assignment. However, IM-based isomer analysis may be complicated by the presence of multiple gas-phase conformations of a single structure that not only increases difficulty in isomer separation but can also introduce the possibility for misinterpretation of conformers as isomers. Here, the ion mobility behavior of several sets of isomeric glycans, analyzed as their permethylated derivatives, in both nonreduced and reduced forms, was investigated by gated-trapped ion mobility spectrometry (G-TIMS). Notably, reducing-end reduction, commonly performed to remove anomerism-induced chromatographic peak splitting, did not eliminate the conformational heterogeneity of permethylated glycans in the gas phase. At a mobility resolving power of ∼100, 14 out of 22 structures showed more than one conformation. These results highlight the need to use IMS devices with high mobility resolving power for better separation of isomers and to acquire additional structural information that can differentiate isomers from conformers. Online electronic excitation dissociation (EED) MS/MS analysis of isomeric glycan mixtures following G-TIMS separation showed that EED can generate isomer-specific fragments while producing nearly identical tandem mass spectra for conformers, thus allowing confident identification of isomers with minimal evidence of any ambiguity resulting from the presence of conformers. G-TIMS EED MS/MS analysis of N-linked glycans released from ovalbumin revealed that several mobility features previously thought to arise from isomeric structures were conformers of a single structure. Finally, analysis of ovalbumin N-glycans from different sources showed that the G-TIMS EED MS/MS approach can accurately determine the batch-to-batch variations in glycosylation profiles at the isomer level, with confident assignment of each isomeric structure.

Clustering and curation of electropherograms: an efficient method for analyzing large cohorts of capillary electrophoresis glycomic profiles for bioprocessing operations.

The accurate assessment of antibody glycosylation during bioprocessing requires the high-throughput generation of large amounts of glycomics data. This allows bioprocess engineers to identify critical process parameters that control the glycosylation critical quality attributes. The advances made in protocols for capillary electrophoresis-laser-induced fluorescence (CE-LIF) measurements of antibody N-glycans have increased the potential for generating large datasets of N-glycosylation values for assessment. With large cohorts of CE-LIF data, peak picking and peak area calculations still remain a problem for fast and accurate quantitation, despite the presence of internal and external standards to reduce misalignment for the qualitative analysis. The peak picking and area calculation problems are often due to fluctuations introduced by varying process conditions resulting in heterogeneous peak shapes. Additionally, peaks with co-eluting glycans can produce peaks of a non-Gaussian nature in some process conditions and not in others. Here, we describe an approach to quantitatively and qualitatively curate large cohort CE-LIF glycomics data. For glycan identification, a previously reported method based on internal triple standards is used. For determining the glycan relative quantities our method uses a clustering algorithm to ‘divide and conquer’ highly heterogeneous electropherograms into similar groups, making it easier to define peaks manually. Open-source software is then used to determine peak areas of the manually defined peaks. We successfully applied this semi-automated method to a dataset (containing 391 glycoprofiles) of monoclonal antibody biosimilars from a bioreactor optimization study. The key advantage of this computational approach is that all runs can be analyzed simultaneously with high accuracy in glycan identification and quantitation and there is no theoretical limit to the scale of this method.

Enhanced protocol for quantitative N-linked glycomics analysis using Individuality Normalization when Labeling with Isotopic Glycan Hydrazide Tags (INLIGHT)™.

The analysis of N-linked glycans using liquid chromatography and mass spectrometry (LC-MS) presents significant challenges, particularly owing to their hydrophilic nature. To address these difficulties, a variety of derivatization methods have been developed to facilitate improved ionization and detection sensitivity. One such method, the Individuality Normalization when Labeling with Isotopic Glycan Hydrazide Tags (INLIGHT)™ strategy for labeling glycans, has previously been utilized in the analysis of N- and O-linked glycans in biological samples. To assess the maximum sensitivity and separability of the INLIGHT™ preparation and analysis pipeline, several critical steps were investigated. First, recombinant and nonrecombinant sources of PNGase F were compared to assess variations in the released glycans. Second, modifications in the INLIGHT™ derivatization step were evaluated including temperature optimization, solvent composition changes, reaction condition length and tag concentration. Optimization of the modified method resulted in 20-100 times greater peak areas for the detected N-linked glycans in fetuin and horseradish peroxidase compared with the standard method. Furthermore, the identification of low-abundance glycans, such as (Fuc)1(Gal)2(GlcNAc)4(Man)3(NeuAc)1 and (Gal)3(GlcNAc)5(Man)3(NeuAc)3, was possible. Finally, the optimal LC setup for the INLIGHT™ derivatized N-linked glycan analyses was found to be a C18 reverse-phase (RP) column with mobile phases typical of RPLC.

More comprehensive standards for monitoring glycosylation

Biologics manufacturers must continually monitor the attachment of carbohydrates, called glycans, to their products, because any variability can impact safety and efficacy. To help the industry meet this challenge, the United States Pharmacopeial Convention (USP) offers glycan reference standards and validated methods for glycoprofiling using high-performance liquid chromatography (HPLC). The industry has recently adopted more advanced technologies for glycan analysis, including ultra-high performance liquid chromatography (UHPLC) and mass spectrometry. In this study, we confirm that USP's glycan reference standards are compatible with UHPLC by demonstrating comparable peak separation and glycan identification to HPLC methods. The improved resolving power and shorter run-times of UHPLC also allowed us to identify many of the minor glycan components present in USP's glycan reference standards. These more comprehensively characterized glycan reference standards will enable manufacturers to assess the micro-heterogeneity that can negatively impact the safety and efficacy of biological products.

On-MALDI-Target N-Glycan Nonreductive Amination by 2-Aminobenzoic Acid.

2-Aminobenzoic acid (2-AA) is widely used as a labeling reagent to derivatize released N-glycans at their free reducing terminus by reductive amination. 2-AA-labeled glycans have increased mass spectrometric sensitivity for their identification and enable fluorescence-chromatography-based glycan quantification. Drawbacks are that the labeling process is labor intensive and time consuming. Clean up of labeled glycans via removal of excess of labeling reagents often leads to sample losses. Here, we report use of 2-AA for labeling N-glycans on a MALDI target through nonreductive amination, while simultaneously functioning as a matrix in MALDI-MS glycan analysis. Coupling 2-AA to glycans results in significant increases of glycan anionic signals as compared to that using the traditional 2,5-dihydroxybenzoic acid (2,5-DHB) matrix. The on-MALDI-target sample preparation is a single-step protocol with high derivatization efficiency. It is also noticed that 2-AA-labeled glycan generated dominant deprotonated molecular anions with much fewer and low-intensity sodium adducts and therefore greatly simplified glycan profiles. We further explored its application in the N-glycan profile of a biotherapeutic monoclonal antibody and was able to achieve sensitive glycan identification at a low microgram level of glycoprotein. This 2-AA on-MALDI-target glycan derivatization eliminates tedious sample preparation and avoids sample loss. It is generally applicable for other applications (e.g., glycomics), where limited amounts of glycoproteins are available for analysis.

Abstract C032: Distinguishing lethal from indolent prostate cancer using N-glycan imaging mass spectrometry in a racial tissue microarray cohort

Abstract Changes in cell surface protein glycosylation are common alterations that occur with tumor progression and reflect the use of many cancer biomarkers like PSA and CA19-9. However, identification of specific glycans associated with tumor regions is still poorly defined. Our group has developed a two-dimensional glycan tissue imaging mass spectrometry approach that can be used with any clinical formalin-fixed, paraffin-embedded tumor tissue used in pathology. Based on the analysis of over one thousand prostate cancer FFPE tissue blocks and tissue microarray samples across the spectrum of disease, it was found that the presence of multi-fucosylated branched N-glycans is associated with advanced tumors with neuroendocrine and metastatic features. These glycans are not present in indolent and lower-grade adenocarcinomas. The hypothesis currently being tested is to determine whether detection of higher numbers of these fucosylated structures predicts a worse prognosis for progressive metastatic disease. Race could be a factor for increased presentation at the time of diagnosis with more advanced disease. The goal of the present study was to assess whether more advanced tumors containing multi-fucosylated N-glycans are detected more frequently in a racial cohort of 307 samples. A series of 14 prostate tumor tissue microarrays (TMA) representing African-American (n=105), Hispanic (n=101) and Caucasian (n=101) subjects was evaluated with this method. The 307 individual tumor samples represented the spectrum of tumor stage, Gleason grade, and status of disease recurrence. For select cases, the original source tumor block tissues were analyzed to confirm the TMA core results. Each TMA slide was processed for antigen retrieval and peptide N-glycosidase F digestions to release N-glycans. Samples were analyzed by MALDI-FTICR mass spectrometry, and data were visualized and analyzed by SCiLS Lab software. Tumor tissues having increased levels of fucosylation were detected in each cohort, but with an overall increase in numbers detected in the African-American cohort. Multitiered analyses are ongoing to identify glycan signatures associated with age, grade, stage, race, and recurrence. In summary, the presence and detection of a distinct panel of multi-fucosylated tissue N-glycans associated with the most lethal forms of prostate cancer can be detected in low-grade tumor samples at the time of diagnosis. This could be developed into a tissue-based prognostic biomarker panel to be applied at the time of initial diagnosis, and impact earlier treatment decisions. Citation Format: Richard R. Drake, Fred David, Cameron Miller, Melanie Jefferson, Laura Spruill, Michael Liss, Brandi Weaver, Peggi M. Angel, Robin Leach, Chanita Hughes-Halbert. Distinguishing lethal from indolent prostate cancer using N-glycan imaging mass spectrometry in a racial tissue microarray cohort [abstract]. In: Proceedings of the Eleventh AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2018 Nov 2-5; New Orleans, LA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl):Abstract nr C032.

Negatively Charged Red-Emitting Acridine Dyes for Facile Reductive Amination, Separation, and Fluorescent Detection of Glycans.

Capillary gel electrophoresis with laser-induced fluorescence detection (CGE-LIF) has become a key method in high-throughput glycan analysis. At present, CGE-LIF relies on the green fluorophore 8-aminopyrene-1,3,6-trisulfonic acid (APTS). However, APTS has moderate reactivity in labeling of glycans and a fixed selectivity profile. Here, we report synthesis of red-emitting and highly reactive fluorescent tags for glycan derivatization. The design is based on a 9-aminoacridine scaffold with various acceptor groups at C-2 (CN, SO2R) and a primary amino group at C-7 for conjugation via reductive amination. These reactive dyes exhibit absorption maxima close to 450 nm and emission above 600 nm. They readily undergo conjugation with reducing sugars at the desired 1:1 stoichiometry. The red emission of conjugates with a maximum at 610–630 nm can be observed under excitation with 488 nm light and detected separately from the APTS-labeled oligosaccharides. Phosphorylated 7,9-diaminoacridine-2-SO2R derivatives with variable amounts of negative charges provide high mobilities of glycoconjugates on polyacrylamide gel electrophoresis (PAGE), as compared with those of APTS. We further demonstrate their utility by labeling and separating a maltodextrin ladder and sialyllactose isomers. The new dyes are expected to cross-validate and increase the glycan identification precision in CGE-LIF and help to reveal “heavy” glycans, yet undetectable with the APTS label.

Identifying glycan motifs using a novel subtree mining approach

BackgroundGlycans are complex sugar chains, crucial to many biological processes. By participating in binding interactions with proteins, glycans often play key roles in host–pathogen interactions. The specificities of glycan-binding proteins, such as lectins and antibodies, are governed by motifs within larger glycan structures, and improved characterisations of these determinants would aid research into human diseases. Identification of motifs has previously been approached as a frequent subtree mining problem, and we extend these approaches with a glycan notation that allows recognition of terminal motifs.ResultsIn this work, we customised a frequent subtree mining approach by altering the glycan notation to include information on terminal connections. This allows specific identification of terminal residues as potential motifs, better capturing the complexity of glycan-binding interactions. We achieved this by including additional nodes in a graph representation of the glycan structure to indicate the presence or absence of a linkage at particular backbone carbon positions. Combining this frequent subtree mining approach with a state-of-the-art feature selection algorithm termed minimum-redundancy, maximum-relevance (mRMR), we have generated a classification pipeline that is trained on data from a glycan microarray. When applied to a set of commonly used lectins, the identified motifs were consistent with known binding determinants. Furthermore, logistic regression classifiers trained using these motifs performed well across most lectins examined, with a median AUC value of 0.89.ConclusionsWe present here a new subtree mining approach for the classification of glycan binding and identification of potential binding motifs. The Carbohydrate Classification Accounting for Restricted Linkages (CCARL) method will assist in the interpretation of glycan microarray experiments and will aid in the discovery of novel binding motifs for further experimental characterisation.

Identification of glycan branching patterns using multistage mass spectrometry with spectra tree analysis

Glycans are crucial to a wide range of biological processes, and their biological activities are closely related to the branching patterns of structures. Different from the simple linear chains of proteins, branching patterns of glycans are more complicated, making their identification extremely challenging. Tandem mass spectrometry (MS2) cannot provide sufficient structural information to deduce glycan branching patterns even with the assistance of various bioinformatic tools and algorithms.The promising technology to identify glycan branching patterns is multi-stage mass spectrometry (MSn). The production-relationship among MSn spectra of a glycan is essentially a tree, making deducing glycan structures from MSn spectra a great challenge. In the present study, we report an approach called glyBranch (glycan Branching pattern identification based on spectra tree) to fully exploit the information contained in the MSn spectra tree for glycan identification. Using 14 glycan standards, including 2 pairs with isomeric sequence, and 16 complex N-glycans isolated from RNase B and IgG, we demonstrated the successful application of glyBranch to branching pattern analysis.The source code of glyBranch is available at https://github.com/bigict/glyBranch/. We have also developed a web-server, which is freely accessible at http://glycan.ict.ac.cn/glyBranch/. SignificanceGlycans are crucial in various biological processes and their functions are closely related to the details of their structures; thus, the identification of glycan branching patterns is of great significance to biological studies. Multistage mass spectrometry (MSn) can provide detailed structural information by generating multiple-level fragments through consecutive fragmentation; however, the interpretation of numerous MSn spectra is extremely challenging. In this study, we present an approach called glyBranch (glycan Branching pattern identification based on spectra tree) to exploit the information contained in MSn spectra tree for glycan identification. This approach will greatly facilitate the automated identification of glycan structures and related biological studies.

Combining Cryogenic Infrared Spectroscopy with Selective Enzymatic Cleavage for Determining Glycan Primary Structure.

Given the biological relevance and intrinsic structural complexity of glycans, increasing efforts are being directed toward developing a general glycan database that includes information from different analytical methods. As recently demonstrated, cryogenic infrared (IR) spectroscopy is a promising technique for glycan analysis, as it provides unique vibrational fingerprints of specific glycan isomer ions. One of the main goals of a glycan database is the identification and detailed characterization of unknown species. In this work, we combine enzymatic digestion with cryogenic IR-spectroscopy and demonstrate how it can be used for glycan identification. We measured the IR-spectra of a series of cationic glycan standards of increasing complexity and compared them with spectra of the same species after enzymatic cleavage of larger glycans. We show that the cryogenic IR spectra of the cleaved glycans are highly structured and virtually identical to those of standards after both single and multiple cleavages. Our results suggest that the combination of these methods represents a potentially powerful and specific approach for the characterization of unknown glycans.

Identification of LCA-binding Glycans as a Novel Biomarker for Esophageal Cancer Metastasis using a Lectin Array-based Strategy.

Esophageal cancer (EC) is a unique and heterogeneous disease diagnosed mostly at advanced stages. Altered glycans presented on cell surfaces are involved in the occurrence and development of malignancy. However, the effects of glycans on EC progression are largely unexplored. Here, a lectin array was utilized to detect the glycan profiling of the normal esophageal mucosal epithelial cell line and two EC cell lines. The binding of Lens culinaris lectin (LCA) to EC cells was found to be stronger than that of the normal cells. Lectin immunohistochemical staining revealed that LCA-binding glycans were markedly elevated in EC tissues compared to adjacent non-cancerous tissues. LCA staining was significantly associated with lymph node metastasis, depth of invasion, TNM stage and poor overall survival of EC patients. Added LCA to block LCA recognized glycans could inhibit the migration and invasion of EC cells. Further analysis revealed that blocking the biosynthesis of LCA-binding glycans by tunicamycin attenuated cellular migratory and invasive abilities. Additionally, a membrane glycoprotein CD147 was recognized as a binder of LCA. There was a positive correlation between LCA-binding glycans and CD147 expression in clinical samples. Interestingly, CD147 inhibition also reduced cell migration and invasion. These findings indicated that LCA-binding glycans may function as a novel indicator to predict metastasis for patients with EC.

Glucose unit index (GUI) of permethylated glycans for effective identification of glycans and glycan isomers.

Retention time is the most common and widely used criterion to report the separation of glycans using Liquid Chromatography (LC), but it varies widely across different columns, instruments and laboratories. This variation is problematic when inter-laboratory data is compared. Furthermore, it influences reproducibility and hampers efficient data interpretation. In our endeavor to overcome this variance, we propose the use of the Glucose Unit Index (GUI) on C18 and PGC column-based separation of reduced and permethylated glycans. GUI has previously been utilized for retention time normalization of native and labeled glycans. We evaluated this method with reduced and permethylated glycans derived from model glycoproteins fetuin and ribonuclease B (RNase B), and then implemented it to human blood serum to generate C18 and PGC column-based isomeric glycan libraries. GUI values for glycan compositions were calculated with respect to the glucose units derived from dextrin, which was employed as an elution standard. The GUI values were validated on three different LC systems (UltiMate 3000 Nano UHPLC systems) in two laboratories to ensure the reliability and reproducibility of the method. Applicability on real samples was demonstrated using human breast cancer cell lines. A total of 116 permethylated N-glycans separated on a C18 column and 134 glycans separated on a PGC column were compiled in a library. Overall, the established GUI method and the demonstration of reproducible inter- and intra-laboratory GUI values would aid the future development of automated glycan and isomeric glycan identification methods.

N-Glycosylation profiling of intact target proteins by high-resolution mass spectrometry (MS) and glycan analysis using ion mobility-MS/MS.

Glycosylation influences the structure and functionality of glycoproteins, and is regulated by genetic and environmental factors. The types and abundance of glycans on glycoproteins can vary due to diseases such as cancer, inflammation, autoimmune and neurodegenerative disorders. Due to the crucial role glycans play in modulating protein function, glycosylation analysis could lead to the discovery of novel biomarkers and is of prime importance in controlling the quality of glycoprotein biopharmaceuticals. Here, we present a method for the identification and quantification of glycoforms directly on intact proteins, after immunoaffinity purification from biological fluids. The method was validated and applied to serum transferrin and the biopharmaceutical trastuzumab. The accuracy of the method, expressed as the relative error (RE), ranged from 2.1 (at high concentrations) to 7.9% (at low concentrations), and intra- and inter-day precision, expressed as relative standard deviation (RSD), was 3.2 and 8.2%, respectively. The sensitivity and linearity of the method were suitable for serum analysis and the LOQ was calculated to be 3.1 and 4.4 μg mL-1 for transferrin (TFN) and trastuzumab (TRA), respectively. Its application to transferrin from five healthy human serum samples yielded concentrations between 1.61 and 3.17 mg mL-1, which are in agreement with blood reference levels. In parallel, the structure of the identified glycans was determined by ion mobility spectrometry coupled with tandem mass spectrometry. No chromatographic separation was required and sample preparation was performed in a semi-automatic manner, facilitating the handling of up to 12 samples at a time. This method should be useful for clinical laboratories and for the quality control of large batches of biopharmaceuticals.

Glycosylator: a Python framework for the rapid modeling of glycans

BackgroundCarbohydrates are a class of large and diverse biomolecules, ranging from a simple monosaccharide to large multi-branching glycan structures. The covalent linkage of a carbohydrate to the nitrogen atom of an asparagine, a process referred to as N-linked glycosylation, plays an important role in the physiology of many living organisms. Most software for glycan modeling on a personal desktop computer requires knowledge of molecular dynamics to interface with specialized programs such as CHARMM or AMBER. There are a number of popular web-based tools that are available for modeling glycans (e.g., GLYCAM-WEB (http://https://dev.glycam.org/gp/) or Glycosciences.db (http://www.glycosciences.de/)). However, these web-based tools are generally limited to a few canonical glycan conformations and do not allow the user to incorporate glycan modeling into their protein structure modeling workflow.ResultsHere, we present Glycosylator, a Python framework for the identification, modeling and modification of glycans in protein structure that can be used directly in a Python script through its application programming interface (API) or through its graphical user interface (GUI). The GUI provides a straightforward two-dimensional (2D) rendering of a glycoprotein that allows for a quick visual inspection of the glycosylation state of all the sequons on a protein structure. Modeled glycans can be further refined by a genetic algorithm for removing clashes and sampling alternative conformations. Glycosylator can also identify specific three-dimensional (3D) glycans on a protein structure using a library of predefined templates.ConclusionsGlycosylator was used to generate models of glycosylated protein without steric clashes. Since the molecular topology is based on the CHARMM force field, new complex sugar moieties can be generated without modifying the internals of the code. Glycosylator provides more functionality for analyzing and modeling glycans than any other available software or webserver at present. Glycosylator will be a valuable tool for the glycoinformatics and biomolecular modeling communities.

1-(2-Aminoethyl)-3-methyl-1H-imidazol-3-ium tetrafluoroborate: synthesis and application in carbohydrate analysis

Abstract Reductive alkylation of the carbonyl group of carbohydrates with fluorescence or ionizing labels is a prerequisite for the sensitive analysis of carbohydrates by chromatographic and mass spectrometric techniques. Herein, 1-(2-aminoethyl)-3-methyl-1H-imidazol-3-ium tetrafluoroborate ([MIEA][BF4]) was successfully synthesized using tert-butyl N-(2-bromoethyl)carbamate and N-methylimidazole as starting materials. MIEA+ was then investigated as a multifunctional oligosaccharide label for glycan profiling and identification using LC-ESI-ToF and by MALDI-ToF mass spectrometry. The reductive amination of this diazole with carbohydrates was exemplified by labeling N-glycans from the model glycoproteins horseradish peroxidase, RNase B, and bovine lactoferrin. The produced MIEA+ glycan profiles were comparable to the corresponding 2AB labeled glycan derivatives and showed improved ESI-MS ionization efficiency over the respective 2AB derivatives, with detection sensitivity in the low picomol to the high femtomol range.

Automatic Full Glycan Structural Determination through Logically Derived Sequence Tandem Mass Spectrometry.

Glycans have diverse functions and play vital roles in many biological systems, such as influenza, vaccines, and cancer biomarkers. However, full structural identification of glycans remains challenging. The glycan structure was conventionally determined by chemical methods or NMR spectroscopy, which require a large amount of sample and are not readily applicable for glycans extracted from biological samples. Although it has high sensitivity and is widely used for structural determination of molecules, current mass spectrometry can only reveal parts of the glycan structure. Herein, the full structures of glycans, including diastereomers, the anomericity of each monosaccharide, and the linkage position of each glycosidic bond, which can be determined by using tandem mass spectrometry guided by a logically derived sequence (LODES), are shown. This new method provides de novo oligosaccharide structural identification with high sensitivity and has been applied to automatic in situ structural determination of oligosaccharides eluted by means of HPLC. It is shown that the structure of a given trisaccharide from a trisaccharide mixture and bovine milk were determined from nearly 3000 isomers by using 6-7 logically selected collision-induced dissociation spectra. The entire procedure for mass spectrometry measurement guided by LODES can be programmed in a computer for automatic full glycan structure identification.

Glycointeractome of Neisseria gonorrhoeae: Identification of Host Glycans Targeted by the Gonococcus To Facilitate Adherence to Cervical and Urethral Epithelial Cells.

Neisseria gonorrhoeae is a significant threat to global health for which a vaccine and novel treatment options are urgently needed. Glycans expressed by human cells are commonly targeted by pathogens to facilitate interactions with the host, and thus characterization of these interactions can aid identification of bacterial receptors that can be exploited as vaccine and/or drug targets. Using glycan array analysis, we identified 247 specific interactions between N. gonorrhoeae and glycans representative of those found on human cells. Interactions included those with mannosylated, fucosylated, and sialylated glycans, glycosaminoglycans (GAGs), and glycans terminating with galactose (Gal), N-acetylgalactosamine (GalNAc), and N-acetylglucosamine (GlcNAc). By investigating the kinetics of interactions with selected glycans, we demonstrate that whole-cell N. gonorrhoeae has a high affinity for mannosylated glycans (dissociation constant [KD ], 0.14 to 0.59 μM), which are expressed on the surface of cervical and urethral epithelial cells. Using chromatography coupled with mass spectrometric (MS) analysis, we identified potential mannose-binding proteins in N. gonorrhoeae Pretreatment of cells with mannose-specific lectin (concanavalin A) or free mannose competitor (α-methyl-d-mannopyranoside) substantially reduced gonococcal adherence to epithelial cells. This suggests that N. gonorrhoeae targets mannosyl glycans to facilitate adherence to host cells and that mannosides or similar compounds have the potential to be used as a novel treatment option for N. gonorrhoeaeIMPORTANCE Multidrug-resistant strains of Neisseria gonorrhoeae are emerging worldwide, and novel treatment and prevention strategies are needed. Glycans are ubiquitously expressed by all human cells and can be specifically targeted by pathogens to facilitate association with host cells. Here we identify and characterize the N. gonorrhoeae host-glycan binding profile (glycointeractome), which revealed numerous interactions, including high-affinity binding to mannosyl glycans. We identify gonococcal potential mannose-binding proteins and show that N. gonorrhoeae uses mannosyl glycans expressed on the surface of cervical and urethral epithelia to facilitate adherence. Furthermore, a mannose-binding lectin or a mannoside compound was able to reduce this adherence. By characterizing the glycointeractome of N. gonorrhoeae, we were able to elucidate a novel mechanism used by this important pathogen to interact with human cells, and this interaction could be exploited to develop novel therapeutics to treat antibiotic-resistant gonorrhea.

Abstract 3008: PSMA glycosylation and aggressive prostate cancer progression

Abstract Introduction: Prostate cancer has a heterogeneous spectrum of clinical outcomes with phenotypes ranging from indolent asymptomatic cases to very aggressive metastatic and lethal forms. Our long term objective is to identify molecules and characterize mechanisms for PCa progression to aggressive lethal disease. PSMA, a membrane bound glycoprotein is significantly over-expressed in more aggressive and metastatic prostate carcinomas with a negative correlation with patient prognosis. The role of its glycans in disease progression and in the development of biomarkers for the disease and potential therapeutics are currently unknown. Aberrant glycosylation of glycoproteins has been observed in many malignancies, and these changes influence disease progression. Our rationale is that differential glycosylation of PSMA correlates with PCa aggressive disease progression. In this study, we characterize N-linked glycosylation profiles in disease stratified PCa cells and prostate proximal fluids show differential expression of specific PSMA conjugated glycan structures that correlates with aggressive phenotypes. Methods/Results: PSMA was isolation from PCa cell lysates and post-DRE urines by column based affinity chromatography followed by SDS-PAGE and Western Blot and Coomassie staining. The fractionated PSMA protein band was excised and processed for proteomic and glycomic analysis. Isolated PSMA was trypsin digested and treated with PNGaseF and other glycosidases to cleave of N-linked glycans from the peptides. Isolated glycans were subjected to permethylation before MALDI-TOF-MS and high resolution, high mass accuracy and high sensitivity LC/MS/MS on an Orbitrap Fusion Lumos Tribrid MS instrument with multiple fragmentation capabilities (CID, HCD, ETD and EThcD) for glycan identification and quantitation. Validation of differential glycan expression was further performed by targeted glycan based MS and lectin based biochemical technologies. Conclusions: Our preliminary studies show that there is differential expression of PSMA N-linked glycans with disease severity in prostate cancer cells and post DRE urine samples. Further analyses are currently underway using an extensive cohort of post DRE urine samples and additional studies are focusing on uncovering the mechanisms that are modulated by PSMA glycosylation that are responsible for PCa disease progression. These could assist in the development of novel diagnostic and therapeutic strategies for the disease. Citation Format: Tanya C. Burch, Stephen S. Mackay, Ian O. Oduor, Joseph J. Otto, Raymond S. Lance, Dean A. Troyer, Oliver John Semmes, Julius O. Nyalwidhe. PSMA glycosylation and aggressive prostate cancer progression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3008.

Identification of N-linked glycans as specific mediators of neuronal uptake of acetylated α-Synuclein.

Cell-to-cell transmission of toxic forms of α-Synuclein (αS) is thought to underlie disease progression in Parkinson disease. αS in humans is constitutively N-terminally acetylated (αSacetyl), although the impact of this modification is relatively unexplored. Here, we report that αSacetyl is more effective at inducing intracellular aggregation in primary neurons than unmodified αS (αSun). We identify complex N-linked glycans as binding partners for αSacetyl and demonstrate that cellular internalization of αSacetyl is reduced significantly upon cleavage of extracellular N-linked glycans, but not other carbohydrates. We verify binding of αSacetyl to N-linked glycans in vitro, using both isolated glycans and cell-derived proteoliposomes. Finally, we identify neurexin 1β, a neuronal glycoprotein, as capable of driving glycan-dependent uptake of αSacetyl. Importantly, our results are specific to αSacetyl because αSun does not demonstrate sensitivity for N-linked glycans in any of our assays. Our study identifies extracellular N-linked glycans—and the glycoprotein neurexin 1β specifically—as key modulators of neuronal uptake of αSacetyl, drawing attention to the potential therapeutic value of αSacetyl-glycan interactions.