Predicting glycan structure from tandem mass spectrometry via deep learning

Glycans constitute the most complicated post-translational modification, modulating protein activity in health and disease. However, structural annotation from tandem mass spectrometry (MS/MS) data is a bottleneck in glycomics, preventing high-throughput endeavors and relegating glycomics to a few experts. Trained on a newly curated set of 500,000 annotated MS/MS spectra, here we present CandyCrunch, a dilated residual neural network predicting glycan structure from raw liquid chromatography-MS/MS data in seconds (top-1 accuracy: 90.3%). We developed an open-access Python-based workflow of raw data conversion and prediction, followed by automated curation and fragment annotation, with predictions recapitulating and extending expert annotation. We demonstrate that this can be used for de novo annotation, diagnostic fragment identification and high-throughput glycomics. For maximum impact, this entire pipeline is tightly interlaced with our glycowork platform and can be easily tested at https://colab.research.google.com/github/BojarLab/CandyCrunch/blob/main/CandyCrunch.ipynb . We envision CandyCrunch to democratize structural glycomics and the elucidation of biological roles of glycans.

Labeling of Mucin-Type O-Glycans for Quantification Using Liquid Chromatography and Fluorescence Detection

O-glycosylation is a common post-translational modification that is essential for the defensive properties of mucus barriers. Incomplete and altered O-glycosylation is often linked to severe diseases, such as cancer, cystic fibrosis, and chronic obstructive pulmonary disease. Originating from a nontemplate-driven biosynthesis, mucin-type O-glycan structures are very complex. They are often present as heterogeneous mixtures containing multiple isomers. Therefore, the analysis of complex O-glycan mixtures usually requires hyphenation of orthogonal techniques such as liquid chromatography (LC), ion mobility spectrometry, and mass spectrometry (MS). However, MS-based techniques are mainly qualitative. Moreover, LC separation of O-glycans often lacks reproducibility and requires sophisticated data treatment and analysis. Here we present a mucin-type O-glycomics analysis workflow that utilizes hydrophilic interaction liquid chromatography for separation and fluorescence labeling for detection and quantification. In combination with mass spectrometry, a detailed analysis on the relative abundance of specific mucin-type O-glycan compositions and features, such as fucose, sialic acids, and sulfates, is performed. Furthermore, the average number of monosaccharide units of O-glycans in different samples was determined. To demonstrate universal applicability, the method was tested on mucins from different tissue types and mammals, such as bovine submaxillary mucins, porcine gastric mucins, and human milk mucins. To account for day-to-day retention time shifts in O-glycan separations and increase the comparability between different instruments and laboratories, we included fluorescently labeled dextran ladders in our workflow. In addition, we set up a library of glucose unit values for all identified O-glycans, which can be used to simplify the identification process of glycans in future analyses.

An Updated Overview of Existing Cancer Databases and Identified Needs

Our search of existing cancer databases aimed to assess the current landscape and identify key needs. We analyzed 71 databases, focusing on genomics, proteomics, lipidomics, and glycomics. We found a lack of cancer-related lipidomic and glycomic databases, indicating a need for further development in these areas. Proteomic databases dedicated to cancer research were also limited. To assess overall progress, we included human non-cancer databases in proteomics, lipidomics, and glycomics for comparison. This provided insights into advancements in these fields over the past eight years. We also analyzed other types of cancer databases, such as clinical trial databases and web servers. Evaluating user-friendliness, we used the FAIRness principle to assess findability, accessibility, interoperability, and reusability. This ensured databases were easily accessible and usable. Our search summary highlights significant growth in cancer databases while identifying gaps and needs. These insights are valuable for researchers, clinicians, and database developers, guiding efforts to enhance accessibility, integration, and usability. Addressing these needs will support advancements in cancer research and benefit the wider cancer community.

Worldwide Glycoscience Informatics Infrastructure: The GlySpace Alliance

The GlySpace Alliance was formed in 2018 among the principal investigators of three major glycoscience portals: Glyco@Expasy, GlyCosmos, and GlyGen, representing Europe, Asia, and the United States, respectively. While each of these portals has its unique user interface, the aim is to provide the same basic data set of glycan-related omics data. These portals will be introduced with the aim to enable users to find their target information in the most efficient manner, in particular, in terms of the chemical structures of glycans and their functions.

Aeromonas salmonicida binds α2-6 linked sialic acid, which is absent among the glycosphingolipid repertoires from skin, gill, stomach, pyloric caecum, and intestine

Carbohydrates can both protect against infection and act as targets promoting infection. Mucins are major components of the slimy mucus layer covering the fish epithelia. Mucins can act as decoys for intimate pathogen interaction with the host afforded by binding to glycosphingolipids in the host cell membrane. We isolated and characterized glycosphingolipids from Atlantic salmon skin, gill, stomach, pyloric caeca, and intestine. We characterized the glycosphingolipids using liquid chromatography – mass spectrometry and tandem mass spectrometry and the glycan repertoire was compared with the glycan repertoire of mucins from the same epithelia. We also investigated Aeromonas salmonicida binding using chromatogram and microtiter well based binding assays. We identified 29 glycosphingolipids. All detected acid glycans were of the ganglio-series (unless shorter) and showed a high degree of polysialylation. The non-acid glycans were mostly composed of the neolacto, globo, and ganglio core structures. The glycosphingolipid repertoire differed between epithelia and the proportion of the terminal moieties of the glycosphingolipids did not reflect the terminal moieties on the mucins from the same epithelia. A. salmonicida did not bind the Atlantic salmon glycosphingolipids. Instead, we identified that A. salmonicida binding to sialic acid occurred to α2–6 Neu5Ac but not to α2–3 Neu5Ac. α2–6 Neu5Ac was present on mucins whereas mainly α2–3 Neu5Ac was found on the glycosphingolipids, explaining the difference in A. salmonicida binding ability between these host glycoconjugates. A. salmonicida´s ability to bind to Atlantic salmon mucins, but not the glycosphingolipids, is likely part of the host defence against this pathogen.

A Complex Connection Between the Diversity of Human Gastric Mucin O-Glycans, Helicobacter pylori Binding, Helicobacter Infection and Fucosylation

Helicobacter pylori colonizes the stomach of half of the human population. Most H. pylori are located in the mucus layer, which is mainly comprised by glycosylated mucins. Using mass spectrometry, we identified 631 glycans (whereof 145 were fully characterized and the remainder assigned as compositions) on mucins isolated from 14 Helicobacter spp.-infected and 14 Helicobacter spp.-noninfected stomachs. Only six identified glycans were common to all individuals, from a total of 60 to 189 glycans in each individual. An increased number of unique glycan structures together with an increased intraindividual diversity and larger interindividual variation were identified among O-glycans from Helicobacter spp.-infected stomachs compared with noninfected stomachs. H. pylori strain J99, which carries the blood group antigen-binding adhesin (BabA), the sialic acid-binding adhesin (SabA), and the LacdiNAc-binding adhesin, bound both to Lewis b (Leb)-positive and Leb-negative mucins. Among Leb-positive mucins, H. pylori J99 binding was higher to mucins from Helicobacter spp.-infected individuals than noninfected individuals. Statistical correlation analysis, binding experiments with J99 wt, and J99ΔbabAΔsabA and inhibition experiments using synthetic glycoconjugates demonstrated that the differences in H. pylori-binding ability among these four groups were governed by BabA-dependent binding to fucosylated structures. LacdiNAc levels were lower in mucins that bound to J99 lacking BabA and SabA than in mucins that did not, suggesting that LacdiNAc did not significantly contribute to the binding. We identified 24 O-glycans from Leb-negative mucins that correlated well with H. pylori binding whereof 23 contained α1,2-linked fucosylation. The large and diverse gastric glycan library identified, including structures that correlated with H. pylori binding, could be used to select glycodeterminants to experimentally investigate further for their importance in host-pathogen interactions and as candidates to develop glycan-based therapies.

Streptococcus oralis Employs Multiple Mechanisms of Salivary Mucin Binding That Differ Between Strains

Streptococcus oralis is an oral commensal and opportunistic pathogen that can enter the bloodstream and cause bacteremia and infective endocarditis. Here, we investigated the mechanisms of S. oralis binding to oral mucins using clinical isolates, isogenic mutants and glycoconjugates. S. oralis bound to both MUC5B and MUC7, with a higher level of binding to MUC7. Mass spectrometry identified 128 glycans on MUC5B, MUC7 and the salivary agglutinin (SAG). MUC7/SAG contained a higher relative abundance of Lewis type structures, including Lewis b/y, sialyl-Lewis a/x and α2,3-linked sialic acid, compared to MUC5B. S. oralis subsp. oralis binding to MUC5B and MUC7/SAG was inhibited by Lewis b and Lacto-N-tetraose glycoconjugates. In addition, S. oralis binding to MUC7/SAG was inhibited by sialyl Lewis x. Binding was not inhibited by Lacto-N-fucopentaose, H type 2 and Lewis x conjugates. These data suggest that three distinct carbohydrate binding specificities are involved in S. oralis subsp. oralis binding to oral mucins and that the mechanisms of binding MUC5B and MUC7 differ. Efficient binding of S. oralis subsp. oralis to MUC5B and MUC7 required the gene encoding sortase A, suggesting that the adhesin(s) are LPXTG-containing surface protein(s). Further investigation demonstrated that one of these adhesins is the sialic acid binding protein AsaA.

Integrated N- and O-Glycomics of Acute Myeloid Leukemia (AML) Cell Lines

Acute myeloid leukemia (AML) is characterized by a dysregulated expansion of poorly differentiated myeloid cells. Although patients are usually treated effectively by chemotherapy, a high rate of relapsed or refractory disease poses a major hurdle in its treatment. Recently, several studies have proposed implications of protein glycosylation in the pathobiology of AML including chemoresistance. Accordingly, associations have been found between specific glycan epitopes and the outcome of the disease. To advance this poorly studied field, we performed an exploratory glycomics study characterizing 21 widely used AML cell lines. Exploiting the benefits of porous graphitized carbon chromatography coupled to tandem mass spectrometry (PGC nano-LC-MS²), we qualitatively and quantitatively profiled N- and O-linked glycans. AML cell lines exhibited distinct glycan fingerprints differing in relevant glycan traits correlating with their cellular phenotype as classified by the FAB system. By implementing transcriptomics data, specific glycosyltransferases and hematopoietic transcription factors were identified, which are candidate drivers of the glycan phenotype of these cells. In conclusion, we report the varying expression of glycan structures across a high number of AML cell lines, including those associated with poor prognosis, identified underlying glycosyltransferases and transcription factors, and provide insights into the regulation of the AML glycan repertoire.

Stimulated saliva composition in patients with cancer of the head and neck region

BACKGROUND

To analyse over time changes in stimulated whole saliva regarding total protein, Immunoglobulin A (IgA), and mucin type O-glycans (mostly MUC5B and MUC7) in head and neck cancer patients.

METHODS

29 dentate patients (20 men and 9 women, 59 ± 8 years) treated with curative radiation therapy and chemotherapy for cancer of the head and neck region were included. The stimulated whole salivary secretion rate was determined and saliva collected at four time-points: at pretreatment, and at 6 months, 1 and 2 years post treatment. The total protein concentration was determined spectrophotometrically by using Bicinchoninic Acid assay and Immunoglobulin A (IgA) by using ELISA technique. Glycosylation pattern of salivary mucins was determined in samples collected pre- and post treatment by using LC/MS electrospray and mucin content quantified using SDS-AgPAGE gels and PAS staining.

RESULTS

Compared with pretreatment, the total protein concentration was increased already at 6 months post treatment (p < 0.01), and continued to increase up to 2 years post treatment (p < 0.001). During that period no significant changes in IgA concentration was detected. At pretreatment, the output/min of both total protein and IgA was significantly higher than at all time-points post treatment. Saliva from the cancer patients showed a low abundance/no detectable MUC7, while the MUC5B level remained, compared to saliva from a healthy control. The glycomic analysis showed that the percentage of core 2 O-glycans was increased as core 1, 3 and 4 O-glycans were decreased. The level of sialylation was higher at 6 months post treatment, while sulfation was lower.

CONCLUSION

A decreased output per minute of proteins at decreased salivary secretion rate, as well as reduced sulfation of MUC5B at 6 months post treatment tended to correlate with the patients' experience of sticky saliva and oral dryness. At 2 years post treatment, the decreased amount of IgA combined with a lowered salivary secretion rate indicate a reduced oral defense with increased risk of oral infections.

Glycoinformatics Tools for Comprehensive Characterization of Glycans Enzymatically Released from Proteins

Glycosylation is important in biology, contributing to both protein conformation and function. Structurally, glycosylation is complex and diverse. This complexity is reflected in the topology, composition, monosaccharide linkages, and isomerism of each oligosaccharide. Glycoanalytics is a discipline that addresses the understanding and characterization of this complexity and its correlation with biology. It includes analytical steps such as sample preparation, instrument measurements, and data analyses. Of these, data analysis has emerged as a critical bottleneck because data collection has increasingly become high-throughput. This has resulted in data-rich workflows that lack rapid and automated data analytics. To address this issue, the field has been developing software for interpretation of quantitative glycomics studies. Here, we describe a protocol using available informatics tools for analysis of data from analysis of released glycans using high-/ultraperformance liquid chromatography (H/UPLC) coupled with mass spectrometry (MS).

A single sulfatase is required to access colonic mucin by a gut bacterium

Humans have co-evolved with a dense community of microbial symbionts that inhabit the lower intestine. In the colon, secreted mucus creates a barrier that separates these microorganisms from the intestinal epithelium1. Some gut bacteria are able to utilize mucin glycoproteins, the main mucus component, as a nutrient source. However, it remains unclear which bacterial enzymes initiate degradation of the complex O-glycans found in mucins. In the distal colon, these glycans are heavily sulfated, but specific sulfatases that are active on colonic mucins have not been identified. Here we show that sulfatases are essential to the utilization of distal colonic mucin O-glycans by the human gut symbiont Bacteroides thetaiotaomicron. We characterized the activity of 12 different sulfatases produced by this species, showing that they are collectively active on all known sulfate linkages in O-glycans. Crystal structures of three enzymes provide mechanistic insight into the molecular basis of substrate specificity. Unexpectedly, we found that a single sulfatase is essential for utilization of sulfated O-glycans in vitro and also has a major role in vivo. Our results provide insight into the mechanisms of mucin degradation by a prominent group of gut bacteria, an important process for both normal microbial gut colonization2 and diseases such as inflammatory bowel disease3.

Towards a more complete glycome: Advances in ion chromatography-mass spectrometry (IC-MS) for improved separation and analysis of carbohydrates

To date, few tools are available for the analysis of the glycome without derivatization, a process which is known to introduce issues such as differential loss of sialic acid and incomplete labeling. We have previously reported the use of ion chromatography-mass spectrometry (IC-MS) to analyze native sialylated and sulfated glycans. Here, we introduce improvements to IC column technology, enabling the separation of neutral glycans while maintaining charge separation capabilities. When implemented in an IC-MS workflow, this enables the structural characterization of a broad array of chemically distinct glycans. With the newly developed IC column and modified IC-MS instrumentation configuration, we qualitatively investigated O-glycome profiles in bovine fetuin and porcine gastric mucins. The improved chromatographic resolution in combination with high-resolution MS data present a powerful tool for glycan structural identification.

Importance of evaluating protein glycosylation in pluripotent stem cell-derived cardiomyocytes for research and clinical applications

Proper protein glycosylation is critical to normal cardiomyocyte physiology. Aberrant glycosylation can alter protein localization, structure, drug interactions, and cellular function. The in vitro differentiation of human pluripotent stem cells into cardiomyocytes (hPSC-CM) has become increasingly important to the study of protein function and to the fields of cardiac disease modeling, drug testing, drug discovery, and regenerative medicine. Here, we offer our perspective on the importance of protein glycosylation in hPSC-CM. Protein glycosylation is dynamic in hPSC-CM, but the timing and extent of glycosylation are still poorly defined. We provide new data highlighting how observed changes in hPSC-CM glycosylation may be caused by underlying differences in the protein or transcript abundance of enzymes involved in building and trimming the glycan structures or glycoprotein gene products. We also provide evidence that alternative splicing results in altered sites of glycosylation within the protein sequence. Our findings suggest the need to precisely define protein glycosylation events that may have a critical impact on the function and maturation state of hPSC-CM. Finally, we provide an overview of analytical strategies available for studying protein glycosylation and identify opportunities for the development of new bioinformatic approaches to integrate diverse protein glycosylation data types. We predict that these tools will promote the accurate assessment of protein glycosylation in future studies of hPSC-CM that will ultimately be of significant experimental and clinical benefit.

The glycoconjugate ontology (GlycoCoO) for standardizing the annotation of glycoconjugate data and its application

Recent years have seen great advances in the development of glycoproteomics protocols and methods resulting in a sustainable increase in the reporting proteins, their attached glycans and glycosylation sites. However, only very few of these reports find their way into databases or data repositories. One of the major reasons is the absence of digital standard to represent glycoproteins and the challenging annotations with glycans. Depending on the experimental method, such a standard must be able to represent glycans as complete structures or as compositions, store not just single glycans but also represent glycoforms on a specific glycosylation side, deal with partially missing site information if no site mapping was performed, and store abundances or ratios of glycans within a glycoform of a specific site. To support the above, we have developed the GlycoConjugate Ontology (GlycoCoO) as a standard semantic framework to describe and represent glycoproteomics data. GlycoCoO can be used to represent glycoproteomics data in triplestores and can serve as a basis for data exchange formats. The ontology, database providers and supporting documentation are available online (https://github.com/glycoinfo/GlycoCoO).

Stress Impairs Skin Barrier Function and Induces α2-3 Linked N-Acetylneuraminic Acid and Core 1 O-Glycans on Skin Mucins in Atlantic Salmon, Salmo salar

The skin barrier consists of mucus, primarily comprising highly glycosylated mucins, and the epithelium. Host mucin glycosylation governs interactions with pathogens and stress is associated with impaired epithelial barrier function. We characterized Atlantic salmon skin barrier function during chronic stress (high density) and mucin O-glycosylation changes in response to acute and chronic stress. Fish held at low (LD: 14–30 kg/m³) and high densities (HD: 50-80 kg/m³) were subjected to acute stress 24 h before sampling at 17 and 21 weeks after start of the experiment. Blood parameters indicated primary and secondary stress responses at both sampling points. At the second sampling, skin barrier function towards molecules was reduced in the HD compared to the LD group (P_app mannitol; p < 0.01). Liquid chromatography–mass spectrometry revealed 81 O-glycan structures from the skin. Fish subjected to both chronic and acute stress had an increased proportion of large O-glycan structures. Overall, four of the O-glycan changes have potential as indicators of stress, especially for the combined chronic and acute stress. Stress thus impairs skin barrier function and induces glycosylation changes, which have potential to both affect interactions with pathogens and serve as stress indicators.

Bioinformatics in Immunoglobulin Glycosylation Analysis

Analytical methods developed for studying immunoglobulin glycosylation rely heavily on software tailored for this purpose. Many of these tools are now used in high-throughput settings, especially for the glycomic characterization of IgG. A collection of these tools, and the databases they rely on, are presented in this chapter. Specific applications are detailed in examples of immunoglobulin glycomics and glycoproteomics data processing workflows. The results obtained in the glycoproteomics workflow are emphasized with the use of dedicated visualizing tools. These tools enable the user to highlight glycan properties and their differential expression.

Insights into Bioinformatic Applications for Glycosylation: Instigating an Awakening towards Applying Glycoinformatic Resources for Cancer Diagnosis and Therapy

Glycosylation plays a crucial role in various diseases and their etiology. This has led to a clear understanding on the functions of carbohydrates in cell communication, which eventually will result in novel therapeutic approaches for treatment of various disease. Glycomics has now become one among the top ten technologies that will change the future. The direct implication of glycosylation as a hallmark of cancer and for cancer therapy is well established. As in proteomics, where bioinformatics tools have led to revolutionary achievements, bioinformatics resources for glycosylation have improved its practical implication. Bioinformatics tools, algorithms and databases are a mandatory requirement to manage and successfully analyze large amount of glycobiological data generated from glycosylation studies. This review consolidates all the available tools and their applications in glycosylation research. The achievements made through the use of bioinformatics into glycosylation studies are also presented. The importance of glycosylation in cancer diagnosis and therapy is discussed and the gap in the application of widely available glyco-informatic tools for cancer research is highlighted. This review is expected to bring an awakening amongst glyco-informaticians as well as cancer biologists to bridge this gap, to exploit the available glyco-informatic tools for cancer.

Gill Mucus and Gill Mucin O-glycosylation in Healthy and Amebic Gill Disease-Affected Atlantic Salmon

Amoebic gill disease (AGD) causes poor performance and death in salmonids. Mucins are mainly comprised by carbohydrates and are main components of the mucus covering the gill. Since glycans regulate pathogen binding and growth, glycosylation changes may affect susceptibility to primary and secondary infections. We investigated gill mucin O-glycosylation from Atlantic salmon with and without AGD using liquid chromatography–mass spectrometry. Gill mucin glycans were larger and more complex, diverse and fucosylated than skin mucins. Confocal microscopy revealed that fucosylated mucus coated sialylated mucus strands in ex vivo gill mucus. Terminal HexNAcs were more abundant among O-glycans from AGD-affected Atlantic salmon, whereas core 1 structures and structures with acidic moieties such as N-acetylneuraminic acid (NeuAc) and sulfate groups were less abundant compared to non-infected fish. The fucosylated and NeuAc-containing O-glycans were inversely proportional, with infected fish on the lower scale of NeuAc abundance and high on fucosylated structures. The fucosylated epitopes were of three types: Fuc-HexNAc-R, Gal-[Fuc-]HexNAc-R and HexNAc-[Fuc-]HexNAc-R. These blood group-like structures could be an avenue to diversify the glycan repertoire to limit infection in the exposed gills. Furthermore, care must be taken when using skin mucus as proxy for gill mucus, as gill mucins are distinctly different from skin mucins.

Leveraging glycomics data in glycoprotein 3D structure validation with Privateer

The heterogeneity, mobility and complexity of glycans in glycoproteins have been, and currently remain, significant challenges in structural biology. These aspects present unique problems to the two most prolific techniques: X-ray crystallography and cryo-electron microscopy. At the same time, advances in mass spectrometry have made it possible to get deeper insights on precisely the information that is most difficult to recover by structure solution methods: the full-length glycan composition, including linkage details for the glycosidic bonds. The developments have given rise to glycomics. Thankfully, several large scale glycomics initiatives have stored results in publicly available databases, some of which can be accessed through API interfaces. In the present work, we will describe how the Privateer carbohydrate structure validation software has been extended to harness results from glycomics projects, and its use to greatly improve the validation of 3D glycoprotein structures.

Decrease of core 2 O-glycans on synovial lubricin in osteoarthritis reduces galectin-3 mediated crosslinking

The synovial fluid glycoprotein lubricin (also known as proteoglycan 4) is a mucin-type O-linked glycosylated biological lubricant implicated to be involved in osteoarthritis (OA) development. Lubricin's ability to reduce friction is related to its glycosylation consisting of sialylated and unsialylated Tn-antigens and core 1 and core 2 structures. The glycans on lubricin have also been suggested to be involved in crosslinking and stabilization of the lubricating superficial layer of cartilage by mediating interaction between lubricin and galectin-3. However, with the spectrum of glycans being found on lubricin, the glycan candidates involved in this interaction were unknown. Here, we confirm that the core 2 O-linked glycans mediate this lubricin-galectin-3 interaction, shown by surface plasmon resonance data indicating that recombinant lubricin (rhPRG4) devoid of core 2 structures did not bind to recombinant galectin-3. Conversely, transfection of Chinese hamster ovary cells with the core 2 GlcNAc transferase acting on a mucin-type O-glycoprotein displayed increased galectin-3 binding. Both the level of galectin-3 and the galectin-3 interactions with synovial lubricin were found to be decreased in late-stage OA patients, coinciding with an increase in unsialylated core 1 O-glycans (T-antigens) and Tn-antigens. These data suggest a defect in crosslinking of surface-active molecules in OA and provide novel insights into OA molecular pathology.

ProGlycProt V2.0, a repository of experimentally validated glycoproteins and protein glycosyltransferases of prokaryotes

Knowledge of glycosylation status and glycan-pattern of proteins are of considerable medical, academic and application interest. ProGlycProt V2.0 (www.proglycprot.org) therefore, is conceived and maintained as an exclusive web-resource providing comprehensive information on experimentally validated glycoproteins and protein glycosyltransferases (GTs) of prokaryotic origin. The second release of ProGlycProt features a major update with a 191% increase in the total number of entries, manually collected and curated from 607 peer-reviewed publications, on the subject. Protein GTs from prokaryotes that catalyze a varied range of glycan linkages are amenable glycoengineering tools. Therefore, the second release presents content that is greatly expanded and reorganized in two sub-databases: ProGPdb and ProGTdb. While ProGPdb provides information about validated glycoproteins (222 entries), ProGTdb catalogs enzymes/proteins that are instrumental in protein glycosylation, directly (122) or as accessory proteins (182). ProGlycProt V2.0 remains highly cross-referenced yet exclusive and complementary in content to other related databases. The second release further features enhanced search capability, a "compare" entries option and an innovative geoanalytical tool (MapView) facilitating location-assisted search-cum filtering of the entries using geo-positioning information of researchers/groups cited in the ProGlycProt V2.0 databases. Thus, ProGlycProt V2.0 continues to serve as a useful one-point web-resource on various evidence-based information on protein glycosylation in prokaryotes.

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.

Recent advances in glycoinformatic platforms for glycomics and glycoproteomics

Protein glycosylation is the most complex and prevalent post-translation modification in terms of the number of proteins modified and the diversity generated. To understand the functional roles of glycoproteins it is important to gain an insight into the repertoire of oligosaccharides present. The comparison and relative quantitation of glycoforms combined with site-specific identification and occupancy are necessary steps in this direction. Computational platforms have continued to mature assisting researchers with the interpretation of such glycomics and glycoproteomics data sets, but frequently support dedicated workflows and users rely on the manual interpretation of data to gain insights into the glycoproteome. The growth of site-specific knowledge has also led to the implementation of machine-learning algorithms to predict glycosylation which is now being integrated into glycoproteomics pipelines. This short review describes commercial and open-access databases and software with an emphasis on those that are actively maintained and designed to support current analytical workflows.

REStLESS: automated translation of glycan sequences from residue-based notation to SMILES and atomic coordinates

Motivation

Glycans and glycoconjugates are usually recorded in dedicated databases in residue-based notations. Only a few of them can be converted into chemical (atom-based) formats highly demanded in conformational and biochemical studies. In this work, we present a tool for translation from a residue-based glycan notation to SMILES.

Results

The REStLESS algorithm for translation from the CSDB Linear notation to SMILES was developed. REStLESS stands for ResiduEs as Smiles and LinkagEs as SmartS, where SMARTS reaction expressions are used to merge pre-encoded residues into a molecule. The implementation supports virtually all structural features reported in natural carbohydrates and glycoconjugates. The translator is equipped with a mechanism for conversion of SMILES strings into optimized atomic coordinates which can be used as starting geometries for various computational tasks.

Availability and implementation

REStLESS is integrated in the Carbohydrate Structure Database (CSDB) and is freely available on the web (http://csdb.glycoscience.ru/csdb2atoms.html).

Supplementary information

Supplementary data are available at Bioinformatics online.

Towards a standardized bioinformatics infrastructure for N- and O-glycomics

The mass spectrometry (MS)-based analysis of free polysaccharides and glycans released from proteins, lipids and proteoglycans increasingly relies on databases and software. Here, we review progress in the bioinformatics analysis of protein-released N- and O-linked glycans (N- and O-glycomics) and propose an e-infrastructure to overcome current deficits in data and experimental transparency. This workflow enables the standardized submission of MS-based glycomics information into the public repository UniCarb-DR. It implements the MIRAGE (Minimum Requirement for A Glycomics Experiment) reporting guidelines, storage of unprocessed MS data in the GlycoPOST repository and glycan structure registration using the GlyTouCan registry, thereby supporting the development and extension of a glycan structure knowledgebase.

Deciphering Isomers with a Multiple Reaction Monitoring Method for the Complete Detectable O-Glycan Repertoire of the Candidate Therapeutic, Lubricin

Glycosylation is a fundamental post-translational modification, occurring on half of all proteins. Despite its significance, our understanding is limited, in part due to the inherent difficulty in studying these branched, multi-isomer structures. Accessible, detailed, and quantifiable methods for studying glycans, particularly O-glycans, are needed. Here we take a multiple reaction monitoring (MRM) approach to differentiate and relatively quantify all detectable glycans, including isomers, on the heavily O-glycosylated protein lubricin. Lubricin (proteoglycan 4) is essential for lubrication of the joint and eye. Given the therapeutic potential of lubricin, it is essential to understand its O-glycan repertoire in biological and recombinantly produced samples. O-Glycans were released by reductive β-elimination and defined, showing a range of 26 neutral, sulfated, sialylated, and both sulfated and sialylated core 1 (Galβ1-3GalNAcα1-) and core 2 (Galβ1-3(GlcNAcβ1-6)GalNAcα1-) structures. Isomer-specific MRM transitions allowed effective differentiation of neutral glycan isomers as well as sulfated isomeric structures, where the sulfate was retained on the fragment ions. This strategy was not as effective with labile sialylated structures; instead, it was observed that the optimal collision energy for the m/z 290.1 sialic acid B-fragment differed consistently between sialic acid isomers, allowing differentiation between isomers when fragmentation spectra were insufficient. This approach was also effective for purchased Neu5Acα2-3Galβ1-4Glc and Neu5Acα2-6Galβ1-4Glc and for Neu5Acα2-3Galβ1-4GlcNAc and Neu5Acα2-6Galβ1-4GlcNAc linkage isomers with the Neu5Acα2-6 consistently requiring more energy for optimal generation of the m/z 290.1 fragment. Overall, this method provides an effective and easily accessible approach for the quantification and annotation of complex released O-glycan samples.

Effects of Size and Geographical Origin on Atlantic salmon, Salmo salar, Mucin O-Glycan Repertoire

Diseases cause ethical concerns and economic losses in the Salmonid industry. The mucus layer comprised of highly O-glycosylated mucins is the first contact between pathogens and fish. Mucin glycans govern pathogen adhesion, growth and virulence. The Atlantic salmon O-glycome from a single location has been characterized and the interindividual variation was low. Because interindividual variation is considered a population-based defense, hindering the entire population from being wiped out by a single infection, low interindividual variation among Atlantic salmon may be a concern. Here, we analyzed the O-glycome of 25 Atlantic salmon from six cohorts grown under various conditions from Sweden, Norway and Australia (Tasmania) using mass spectrometry. This expanded the known Atlantic salmon O-glycome by 60% to 169 identified structures. The mucin O-glycosylation was relatively stable over time within a geographical region, but the size of the fish affected skin mucin glycosylation. The skin mucin glycan repertoires from Swedish and Norwegian Atlantic salmon populations were closely related compared with Tasmanian ones, regardless of size and salinity, with differences in glycan size and composition. The internal mucin glycan repertoire also clustered based on geographical origin and into pyloric cecal and distal intestinal groups, regardless of cohort and fish size. Fucosylated structures were more abundant in Tasmanian pyloric caeca and distal intestine mucins compared with Swedish ones. Overall, Tasmanian Atlantic salmon mucins have more O-glycan structures in skin but less in the gastrointestinal tract compared with Swedish fish. Low interindividual variation was confirmed within each cohort. The results can serve as a library for identifying structures of importance for host-pathogen interactions, understanding population differences of salmon mucin glycosylation in resistance to diseases and during breeding and selection of strains. The results could make it possible to predict potential vulnerabilities to diseases and suggest that inter-region breeding may increase the glycan diversity.

Standardization of PGC-LC-MS-based glycomics for sample specific glycotyping

Porous graphitized carbon (PGC) based chromatography achieves high-resolution separation of glycan structures released from glycoproteins. This approach is especially valuable when resolving structurally similar isomers and for discovery of novel and/or sample-specific glycan structures. However, the implementation of PGC-based separations in glycomics studies has been limited because system-independent retention values have not been established to normalize technical variation. To address this limitation, this study combined the use of hydrolyzed dextran as an internal standard and Skyline software for post-acquisition normalization to reduce retention time and peak area technical variation in PGC-based glycan analyses. This approach allowed assignment of system-independent retention values that are applicable to typical PGC-based glycan separations and supported the construction of a library containing >300 PGC-separated glycan structures with normalized glucose unit (GU) retention values. To enable the automation of this normalization method, a spectral MS/MS library was developed of the dextran ladder, achieving confident discrimination against isomeric glycans. The utility of this approach is demonstrated in two ways. First, to inform the search space for bioinformatically predicted but unobserved glycan structures, predictive models for two structural modifications, core-fucosylation and bisecting GlcNAc, were developed based on the GU library. Second, the applicability of this method for the analysis of complex biological samples is evidenced by the ability to discriminate between cell culture and tissue sample types by the normalized intensity of N-glycan structures alone. Overall, the methods and data described here are expected to support the future development of more automated approaches to glycan identification and quantitation.

Mapping human N-linked glycoproteins and glycosylation sites using mass spectrometry

N-linked glycoprotein is a highly interesting class of proteins for clinical and biological research. Over the last decade, large-scale profiling of N-linked glycoproteins and glycosylation sites from biological and clinical samples has been achieved through mass spectrometry-based glycoproteomic approaches. In this paper, we reviewed the human glycoproteomic profiles that have been reported in more than 80 individual studies, and mainly focused on the N-glycoproteins and glycosylation sites identified through their deglycosylated forms of glycosite-containing peptides. According to our analyses, more than 30,000 glycosite-containing peptides and 7,000 human glycoproteins have been identified from five different body fluids, twelve human tissues (or related cell lines), and four special cell types. As the glycoproteomic data is still missing for many organs and tissues, a systematical glycoproteomic analysis of various human tissues and body fluids using a uniform platform is still needed for an integrated map of human N-glycoproteomes.

Glycomics@ExPASy: Bridging the Gap

Glycomics@ExPASy (https://www.expasy.org/glycomics) is the glycomics tab of ExPASy, the server of SIB Swiss Institute of Bioinformatics. It was created in 2016 to centralize web-based glycoinformatics resources developed within an international network of glycoscientists. The hosted collection currently includes mainly databases and tools created and maintained at SIB but also links to a range of reference resources popular in the glycomics community. The philosophy of our toolbox is that it should be {glycoscientist AND protein scientist}-friendly with the aim of (1) popularizing the use of bioinformatics in glycobiology and (2) emphasizing the relationship between glycobiology and protein-oriented bioinformatics resources. The scarcity of data bridging these two disciplines led us to design tools as interactive as possible based on database connectivity to facilitate data exploration and support hypothesis building. Glycomics@ExPASy was designed, and is developed, with a long-term vision in close collaboration with glycoscientists to meet as closely as possible the growing needs of the community for glycoinformatics.

Cracking the Sugar Code by Mass Spectrometry : An Invited Perspective in Honor of Dr. Catherine E. Costello, Recipient of the 2017 ASMS Distinguished Contribution Award

The structural study of glycans and glycoconjugates is essential to assign their roles in homeostasis, health, and disease. Once dominated by nuclear magnetic resonance spectroscopy, mass spectrometric methods have become the preferred toolbox for the determination of glycan structures at high sensitivity. The patterns of such structures in different cellular states now allow us to interpret the sugar codes in health and disease, based on structure-function relationships. Dr. Catherine E. Costello was the 2017 recipient of the American Society for Mass Spectrometry's Distinguished Contribution Award. In this Perspective article, we describe her seminal work in a historical and geographical context and review the impact of her research accomplishments in the field.8 ᅟ Graphical abstract.

Human disease glycomics: technology advances enabling protein glycosylation analysis - part 1

INTRODUCTION

Protein glycosylation is recognized as an important post-translational modification, with specific substructures having significant effects on protein folding, conformation, distribution, stability and activity. However, due to the structural complexity of glycans, elucidating glycan structure-function relationships is demanding. The fine detail of glycan structures attached to proteins (including sequence, branching, linkage and anomericity) is still best analysed after the glycans are released from the purified or mixture of glycoproteins (glycomics). The technologies currently available for glycomics are becoming streamlined and standardized and many features of protein glycosylation can now be determined using instruments available in most protein analytical laboratories. Areas covered: This review focuses on the current glycomics technologies being commonly used for the analysis of the microheterogeneity of monosaccharide composition, sequence, branching and linkage of released N- and O-linked glycans that enable the determination of precise glycan structural determinants presented on secreted proteins and on the surface of all cells. Expert commentary: Several emerging advances in these technologies enabling glycomics analysis are discussed. The technological and bioinformatics requirements to be able to accurately assign these precise glycan features at biological levels in a disease context are assessed.

Sample handling of gastric tissue and O-glycan alterations in paired gastric cancer and non-tumorigenic tissues

Sample collection, handling and storage are the most critical steps for ensuring the highest preservation of specimens. Pre-analytical variability can influence the results as protein signatures alter rapidly after tissue excision or during long-term storage. Hence, we evaluated current state-of-the-art biobank preservation methods from a glycomics perspective and analyzed O-glycan alterations occurring in the gastric cancer tissues. Paired tumor and adjacent normal tissue samples were obtained from six patients undergoing gastric cancer surgery. Collected samples (n = 24) were either snap-frozen or heat stabilized and then homogenized. Glycans were released from extracted glycoproteins and analyzed by LC-MS/MS. In total, the relative abundance of 83 O-glycans and 17 derived structural features were used for comparison. There was no statistically significant difference found in variables between snap frozen and heat-stabilized samples, which indicated the two preservation methods were comparable. The data also showed significant changes between normal and cancerous tissue. In addition to a shift from high sialylation in the cancer area towards blood group ABO in the normal area, we also detected that the LacdiNAc epitope (N,N'-diacetyllactosamine) was significantly decreased in cancer samples. The O-glycan alterations that are presented here may provide predictive power for the detection and prognosis of gastric cancer.

Deprotonated carbohydrate anion fragmentation chemistry: structural evidence from tandem mass spectrometry, infra-red spectroscopy, and theory

We investigate the gas-phase structures and fragmentation chemistry of deprotonated carbohydrate anions using combined tandem mass spectrometry, infrared spectroscopy, regioselective labelling, and theory.

GlyTouCan: an accessible glycan structure repository

Rapid and continued growth in the generation of glycomic data has revealed the need for enhanced development of basic infrastructure for presenting and interpreting these datasets in a manner that engages the broader biomedical research community. Early in their growth, the genomic and proteomic fields implemented mechanisms for assigning unique gene and protein identifiers that were essential for organizing data presentation and for enhancing bioinformatic approaches to extracting knowledge. Similar unique identifiers are currently absent from glycomic data. In order to facilitate continued growth and expanded accessibility of glycomic data, the authors strongly encourage the glycomics community to coordinate the submission of their glycan structures to the GlyTouCan Repository and to make use of GlyTouCan identifiers in their communications and publications. The authors also deeply encourage journals to recommend a submission workflow in which submitted publications utilize GlyTouCan identifiers as a standard reference for explicitly describing glycan structures cited in manuscripts.

Tissue glycomics distinguish tumour sites in women with advanced serous adenocarcinoma

In the era of precision medicine, the tailoring of cancer treatment is increasingly important as we transition from organ‐based diagnosis towards a more comprehensive and patient‐centric molecular diagnosis. This is particularly the case for high‐grade serous adenocarcinomas of the ovary and peritoneum, which are commonly diagnosed at an advanced stage, and collectively treated and managed similarly. We characterized the N‐ and O‐glycome of serous ovarian (OC) and peritoneal cancer (PC) tissues using PGC‐LC‐ESI‐IT‐MS/MS profiling and validated the discriminatory glycans and their corresponding glyco‐gene expression levels using cell lines and transcriptomic data from 232 patients. Overall, the N‐ and O‐glycan repertoires of both cancer types were found to comprise mostly of α2,6‐sialylated glycan structures, with the majority of N‐glycans displaying the biantennary mono‐ and disialylation as well as bisecting‐type biantennary glycans. The MS profiling by PGC‐LC also revealed several glycan structural isomers that corresponded to LacdiNAc‐type (GalNAcβ1‐4GlcNAc) motifs that were unique to the serous ovarian cancers and that correlated with elevated gene expression of B4GALNT3 and B4GALNT4 in patients with serous cancer. Statistical evaluation of the discriminatory glycans also revealed 13 N‐ and 3 O‐glycans (P < 0.05) that significantly discriminated tumour‐sampling sites, with LacdiNAc‐type N‐glycans (m/z 1205.0²⁻ and m/z 1059.4²⁻) being associated with ovarian‐derived cancer tissue and bisecting GlcNAc‐type (m/z 994.9²⁻) and branched N‐glycans (m/z 1294.0²⁻ and m/z 1148.4²⁻) upregulated at the metastatic sites. Hence, we demonstrate for the first time that OC and PC display distinct molecular signatures at both their glycomic and transcriptomic levels. These signatures may have potential utility for the development of accurate diagnosis and personalized treatments.

Glycoforest 1.0

Tandem mass spectrometry, when combined with liquid chromatography and applied to complex mixtures, produces large amounts of raw data, which needs to be analyzed to identify molecular structures. This technique is widely used, particularly in glycomics. Due to a lack of high throughput glycan sequencing software, glycan spectra are predominantly sequenced manually. A challenge for writing glycan-sequencing software is that there is no direct template that can be used to infer structures detectable in an organism. To help alleviate this bottleneck, we present Glycoforest 1.0, a partial de novo algorithm for sequencing glycan structures based on MS/MS spectra. Glycoforest was tested on two data sets (human gastric and salmon mucosa O-linked glycomes) for which MS/MS spectra were annotated manually. Glycoforest generated the human validated structure for 92% of test cases. The correct structure was found as the best scoring match for 70% and among the top 3 matches for 83% of test cases. In addition, the Glycoforest algorithm detected glycan structures from MS/MS spectra missing a manual annotation. In total 1532 MS/MS previously unannotated spectra were annotated by Glycoforest. A portion containing 521 spectra was manually checked confirming that Glycoforest annotated an additional 50 MS/MS spectra overlooked during manual annotation.

Influence of Glycosylation on Interfacial Properties of Recombinant Mucins: Adsorption, Surface Forces, and Friction

Interfacial properties of two brush-with-anchor mucins, C-P55 and C-PSLex, have been investigated at the aqueous solution/poly(methyl methacrylate) (PMMA) interface. Both are recombinant mucin-type fusion proteins, produced by fusing the glycosylated mucin part of P-selectin glycoprotein ligand-1 (PSLG-1) to the Fc part of a mouse immunoglobulin in two different cells. They are mainly expressed as dimers upon production. Analysis of the O-glycans shows that the C-PSLex mucin has the longer and more branched side chains, but C-P55 has slightly higher sialic acid content. The adsorption of the mucins to PMMA surfaces was studied by quartz crystal microbalance with dissipation. The sensed mass, including the adsorbed mucin and water trapped in the layer, was found to be similar for these two mucin layers. Atomic force microscopy with colloidal probe was employed to study surface and friction forces between mucin-coated PMMA surfaces. Purely repulsive forces of steric origin were observed between mucin layers on compression, whereas a small adhesion was detected between both mucin layers on decompression. This was attributed to chain entanglement. The friction force between C-PSLex-coated PMMA is lower than that between C-P55-coated PMMA at low loads, but vice versa at high loads. We discuss our results in terms of the differences in the glycosylation composition of these two mucins.

Structural Diversity of Human Gastric Mucin Glycans

The mucin O-glycosylation of 10 individuals with and without gastric disease was examined in depth in order to generate a structural map of human gastric glycosylation. In the stomach, these mucins and their O-glycosylation protect the epithelial surface from the acidic gastric juice and provide the first point of interaction for pathogens such as Helicobacter pylori, reported to cause gastritis, gastric and duodenal ulcers and gastric cancer. The rational of the present study was to map the O-glycosylation that the pathogen may come in contact with. An enormous diversity in glycosylation was found, which varied both between individuals and within mucins from a single individual: mucin glycan chain length ranged from 2-13 residues, each individual carried 34-103 O-glycan structures and in total over 258 structures were identified. The majority of gastric O-glycans were neutral and fucosylated. Blood group I antigens, as well as terminal α1,4-GlcNAc-like and GalNAcβ1-4GlcNAc-like (LacdiNAc-like), were common modifications of human gastric O-glycans. Furthemore, each individual carried 1-14 glycan structures that were unique for that individual. The diversity and alterations in gastric O-glycosylation broaden our understanding of the human gastric O-glycome and its implications for gastric cancer research and emphasize that the high individual variation makes it difficult to identify gastric cancer specific structures. However, despite the low number of individuals, we could verify a higher level of sialylation and sulfation on gastric O-glycans from cancerous tissue than from healthy stomachs.

Structural diversity of human gastric mucin glycans

The mucin O-glycosylation of 10 individuals with and without gastric disease was examined in depth in order to generate a structural map of human gastric glycosylation. In the stomach, these mucins and their O-glycosylation protect the epithelial surface from the acidic gastric juice and provide the first point of interaction for pathogens such as Helicobacter pylori, reported to cause gastritis, gastric and duodenal ulcers and gastric cancer. The rational of the present study was to map the O-glycosylation that the pathogen may come in contact with. An enormous diversity in glycosylation was found, which varied both between individuals and within mucins from a single individual: mucin glycan chain length ranged from 2-13 residues, each individual carried 34-103 O-glycan structures and in total over 258 structures were identified. The majority of gastric O-glycans were neutral and fucosylated. Blood group I antigens, as well as terminal α1,4-GlcNAc-like and GalNAcβ1-4GlcNAc-like (LacdiNAc-like), were common modifications of human gastric O-glycans. Furthemore, each individual carried 1-14 glycan structures that were unique for that individual. The diversity and alterations in gastric O-glycosylation broaden our understanding of the human gastric O-glycome and its implications for gastric cancer research and emphasize that the high individual variation makes it difficult to identify gastric cancer specific structures. However, despite the low number of individuals, we could verify a higher level of sialylation and sulfation on gastric O-glycans from cancerous tissue than from healthy stomachs.

Navigating the Glycome Space and Connecting the Glycoproteome

UniCarbKB ( http://unicarbkb.org ) is a comprehensive resource for mammalian glycoprotein and annotation data. In particular, the database provides information on the oligosaccharides characterized from a glycoprotein at either the global or site-specific level. This evidence is accumulated from a peer-reviewed and manually curated collection of information on oligosaccharides derived from membrane and secreted glycoproteins purified from biological fluids and/or tissues. This information is further supplemented with experimental method descriptions that summarize important sample preparation and analytical strategies. A new release of UniCarbKB is published every three months, each includes a collection of curated data and improvements to database functionality. In this Chapter, we outline the objectives of UniCarbKB, and describe a selection of step-by-step workflows for navigating the information available. We also provide a short description of web services available and future plans for improving data access. The information presented in this Chapter supplements content available in our knowledgebase including regular updates on interface improvements, new features, and revisions to the database content ( http://confluence.unicarbkb.org ).

Databases and Associated Tools for Glycomics and Glycoproteomics

The access to biodatabases for glycomics and glycoproteomics has proven to be essential for current glycobiological research. This chapter presents available databases that are devoted to different aspects of glycobioinformatics. This includes oligosaccharide sequence databases, experimental databases, 3D structure databases (of both glycans and glycorelated proteins) and association of glycans with tissue, disease, and proteins. Specific search protocols are also provided using tools associated with experimental databases for converting primary glycoanalytical data to glycan structural information. In particular, researchers using glycoanalysis methods by U/HPLC (GlycoBase), MS (GlycoWorkbench, UniCarb-DB, GlycoDigest), and NMR (CASPER) will benefit from this chapter. In addition we also include information on how to utilize glycan structural information to query databases that associate glycans with proteins (UniCarbKB) and with interactions with pathogens (SugarBind).

Identifying N-Glycan Biomarkers in Colorectal Cancer by Mass Spectrometry

Colorectal cancer (CRC) is one of the most prevalent cancers worldwide. Delineating biological markers (biomarkers) for early detection, when treatment is most effective, is key to prevention and long-term survival of patients. Development of reliable biomarkers requires an increased understanding of the CRC biology and the underlying molecular and cellular mechanisms of the disease. With recent advances in new technologies and approaches, tremendous efforts have been put in proteomics and genomics fields to deliver detailed analysis of the two major biomolecules, genes and proteins, to gain a more complete understanding of cellular systems at both genomic and proteomic levels, allowing a mechanistic understanding of the human diseases, including cancer, and opening avenues for identification of novel gene and protein based prognostic and therapeutic markers. Although the importance of glycosylation in modulating protein function has long been appreciated, glycan analysis has been complicated by the diversity of the glycan structures and the large number of potential glycosylation combinations. Driven by recent technological advances, LC-MS/MS based glycomics is gaining momentum in cancer research and holds considerable potential to deliver new glycan-based markers. In our laboratory, we investigated alterations in N-glycosylation associated with CRC malignancy in a panel of CRC cell lines and CRC patient tissues. In an initial study, LC-MS/MS-based N-glycomics were utilized to map the N-glycome landscape associated with a panel of CRC cell lines (LIM1215, LIM1899, and LIM2405). These studies were subsequently extended to paired tumor and nontumorigenic CRC tissues to validate the findings in the cell line. Our studies in both CRC cell lines and tissues identified a strong representation of high mannose and α2,6-linked sialylated complex N-glycans, which corroborate findings from previous studies in CRC and other cancers. In addition, certain unique glycan determinants such as bisecting β1,4-GlcNAcylation and α2,3-sialylation, identified in the metastatic (LIM1215) and aggressive (LIM2405) CRC cell lines, respectively, were shown to be associated with epidermal growth factor receptor (EGFR) expression status. In this Account, we will describe the mass spectrometry based N-glycomics approach utilized in our laboratory to accurately profile the cell- and tissue-specific N-glycomes associated with CRC. We will highlight altered N-glycosylation observed by our studies, consistent with findings from other cancer studies, and discuss how the observed alterations can provide insights into CRC pathogenesis, opening new avenues to identify novel disease-associated glycan markers.

Quantitative profiling of glycans and glycopeptides: an informatics' perspective

Experimental techniques to identify and quantify glycan structures in a given sample are continuously improving. However, as they advance data analysis and annotation seems to become more complex. To address this issue, much progress has been made in developing software for interpretation of quantitative glycan profiles. Here, we focus on these informatics tools for high/ultra performance liquid chromatography (H/UPLC), mass spectrometry (MS), tandem mass spectrometry (MSⁿ) and combinations thereof. Software for biomarker discovery, pathway, genomic and disease analysis and a final note on some future prospects for glycoinformatics are also mentioned.