Integration of systems glycobiology with bioinformatics toolboxes, glycoinformatics resources, and glycoproteomics data

Cell and tissue-specific glycosylation pathways informed by single-cell transcriptomics

While single cell studies have made significant impacts in various subfields of biology, they lag in the Glycosciences. To address this gap, we analyzed single-cell glycogene expressions in the Tabula Sapiens dataset of human tissues and cell types using a recent glycosylation-specific gene ontology (GlycoEnzOnto). At the median sequencing (count) depth, ~40-50 out of 400 glycogenes were detected in individual cells. Upon increasing the sequencing depth, the number of detectable glycogenes saturates at ~200 glycogenes, suggesting that the average human cell expresses about half of the glycogene repertoire. Hierarchies in glycogene and glycopathway expressions emerged from our analysis: nucleotide-sugar synthesis and transport exhibited the highest gene expressions, followed by genes for core enzymes, glycan modification and extensions, and finally terminal modifications. Interestingly, the same cell types showed variable glycopathway expressions based on their organ or tissue origin, suggesting nuanced cell- and tissue-specific glycosylation patterns. Probing deeper into the transcription factors (TFs) of glycogenes, we identified distinct groupings of TFs controlling different aspects of glycosylation: core biosynthesis, terminal modifications, etc. We present webtools to explore the interconnections across glycogenes, glycopathways, and TFs regulating glycosylation in human cell/tissue types. Overall, the study presents an overview of glycosylation across multiple human organ systems.

Forward Genetic Screens of Human Glycosylation Pathways Using the GlycoGene CRISPR Library

CRISPR-Cas9-based forward genetic screens represent a powerful discovery platform to uncover genes regulating specific biological processes. This article describes a method for utilizing a freely available GlycoGene CRISPR library to knock out any gene participating in human glycosylation in arbitrary cell types. The end product is a stable GlycoGene CRISPR knockout cell library, where each cell contains one or more sgRNA and lacks corresponding function. The cell library can be screened using various lectin/antibody reagents. It can also be applied in functional assays to establish glycan structure-glycogene-glycopathway relationships. This is a powerful systems glycobiology strategy for dissecting glycosylation pathways and processes. © 2022 Wiley Periodicals LLC. Basic Protocol 1: Scale-up and NGS validation of the GlycoGene CRISPR plasmid library Basic Protocol 2: Preparation of a GlycoGene CRISPR lentivirus pool and an isogenic cell line stably expressing Cas9 nuclease Basic Protocol 3: Preparation of a GlycoGene CRISPR cell library, self-inactivation of Cas9, and library validation by NGS Basic Protocol 4: Enrichment of lectin-binding or non-binding cells and related multiplex NGS data acquisition Basic Protocol 5: Bioinformatics pathway analysis.

Altered Glycosylation of Human Alpha-1-Acid Glycoprotein as a Biomarker for Malignant Melanoma

A high-resolution HILIC-MS/MS method was developed to analyze anthranilic acid derivatives of N-glycans released from human serum alpha-1-acid glycoprotein (AGP). The method was applied to samples obtained from 18 patients suffering from high-risk malignant melanoma as well as 19 healthy individuals. It enabled the identification of 102 glycan isomers separating isomers that differ only in sialic acid linkage (α-2,3, α-2,6) or in fucose positions (core, antenna). Comparative assessment of the samples revealed that upregulation of certain fucosylated glycans and downregulation of their nonfucosylated counterparts occurred in cancer patients. An increased ratio of isomers with more α-2,6-linked sialic acids was also observed. Linear discriminant analysis (LDA) combining 10 variables with the highest discriminatory power was employed to categorize the samples based on their glycosylation pattern. The performance of the method was tested by cross-validation, resulting in an overall classification success rate of 96.7%. The approach presented here is significantly superior to serological marker S100B protein in terms of sensitivity and negative predictive power in the population studied. Therefore, it may effectively support the diagnosis of malignant melanoma as a biomarker.

ANALYSIS OF CARBOHYDRATES AND GLYCOCONJUGATES BY MATRIX-ASSISTED LASER DESORPTION/IONIZATION MASS SPECTROMETRY: AN UPDATE FOR 2015-2016

This review is the ninth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2016. Also included are papers that describe methods appropriate to analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. Topics covered in the first part of the review include general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation and arrays. The second part of the review is devoted to applications to various structural types such as oligo- and poly-saccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals. Much of this material is presented in tabular form. The third part of the review covers medical and industrial applications of the technique, studies of enzyme reactions and applications to chemical synthesis. The reported work shows increasing use of combined new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented over 30 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show no sign of deminishing. © 2020 Wiley Periodicals, Inc.

N-Glycosylation Network Construction and Analysis to Modify Glycans on the Spike (S) Glycoprotein of SARS-CoV-2

Background: The N-glycan structure and composition of the spike (S) protein of SARS-CoV-2 are pertinent to vaccine development and efficacy.

Methods: We reconstructed the glycosylation network based on previously published mass spectrometry data using GNAT, a glycosylation network analysis tool. Our compilation of the network tool had 26 glycosyltransferase and glucosidase enzymes and could infer the pathway of glycosylation machinery based on glycans in the virus spike protein. Once the glycan biosynthesis pathway was generated, we simulated the effect of blocking specific enzymes—swainsonine or deoxynojirimycin for blocking mannosidase-II and indolizidine for blocking alpha-1,6-fucosyltransferase—to see how they would affect the biosynthesis network and the glycans that were synthesized.

Results: The N-glycan biosynthesis network of SARS-CoV-2 spike protein shows an elaborate enzymatic pathway with several intermediate glycans, along with the ones identified by mass spectrometric studies. Of the 26 enzymes, the following were involved—Man-Ia, MGAT1, MGAT2, MGAT4, MGAT5, B3GalT, B4GalT, Man-II, SiaT, ST3GalI, ST3GalVI, and FucT8. Blocking specific enzymes resulted in a substantially modified glycan profile of SARS-CoV-2.

Conclusion: Variations in the final N-glycan profile of the virus, given its site-specific microheterogeneity, are factors in the host response to the infection, vaccines, and antibodies. Heterogeneity in the N-glycan profile of the spike (S) protein and its potential effect on vaccine efficacy or adverse reactions to the vaccines remain unexplored. Here, we provide all the resources we generated—the glycans in the glycoCT xml format and the biosynthesis network for future work.

FGDB: Database of follicle stimulating hormone glycans

Glycomics, the study of the entire complement of sugars of an organism has received significant attention in the recent past due to the advances made in high throughput mass spectrometry technologies. These analytical advancements have facilitated the characterization of glycans associated with the follicle-stimulating hormones (FSH), which play a central role in the human reproductive system both in males and females utilizing regulating gonadal (testicular and ovarian) functions. The irregularities in FSH activity are also directly linked with osteoporosis. The glycoanalytical studies have been tremendously helpful in understanding the biological roles of FSH. Subsequently, the increasing number of characterized FSH glycan structures and related glycoform data has thrown a challenge to the glycoinformatics community in terms of data organization, storage and access. Also, a user-friendly platform is needed for providing easy access to the database and performing integrated analysis using a high volume of experimental data to accelerate FSH-focused research. FSH Glycans DataBase (FGDB) serves as a comprehensive and unique repository of structures, features, and related information of glycans associated with FSH. Apart from providing multiple search options, the database also facilitates an integrated user-friendly interface to perform the glycan abundance and comparative analyses using experimental data. The automated integrated pipelines present the possible structures of glycans and variants of FSH based on the input data, and allow the user to perform various analyses. The potential application of FGDB will significantly help both glycoinformaticians as well as wet-lab researchers to stimulate the research in this area. FGDB web access: https://fgdb.unmc.edu/.

Systems Glycobiology: Past, Present, and Future

Glycobiology is a glycan-based field of study that focuses on the structure, function, and biology of carbohydrates, and glycomics is a sub-study of the field of glycobiology that aims to define structure/function of glycans in living organisms. With the popularity of the glycobiology and glycomics, application of computational modeling expanded in the scientific area of glycobiology over the last decades. The recent availability of progressive Wet-Lab methods in the field of glycobiology and glycomics is promising for the impact of systems biology on the research area of the glycome, an emerging field that is termed “systems glycobiology.” This chapter will summarize the up-to-date leading edge in the use of bioinformatics tools in the field of glycobiology. The chapter provides basic knowledge both for glycobiologists interested in the application of bioinformatics tools and scientists of computational biology interested in studying the glycome.

A consensus-based and readable extension of Linear Code for Reaction Rules (LiCoRR)

Systems glycobiology aims to provide models and analysis tools that account for the biosynthesis, regulation, and interactions with glycoconjugates. To facilitate these methods, there is a need for a clear glycan representation accessible to both computers and humans. Linear Code, a linearized and readily parsable glycan structure representation, is such a language. For this reason, Linear Code was adapted to represent reaction rules, but the syntax has drifted from its original description to accommodate new and originally unforeseen challenges. Here, we delineate the consensuses and inconsistencies that have arisen through this adaptation. We recommend options for a consensus-based extension of Linear Code that can be used for reaction rule specification going forward. Through this extension and specification of Linear Code to reaction rules, we aim to minimize inconsistent symbology thereby making glycan database queries easier. With a clear guide for generating reaction rule descriptions, glycan synthesis models will be more interoperable and reproducible thereby moving glycoinformatics closer to compliance with FAIR standards. Here, we present Linear Code for Reaction Rules (LiCoRR), version 1.0, an unambiguous representation for describing glycosylation reactions in both literature and code.

Human T cell glycosylation and implications on immune therapy for cancer

Glycosylation is an important post-translational modification, giving rise to a diverse and abundant repertoire of glycans on the cell surface, collectively known as the glycome. When focusing on immunity, glycans are indispensable in virtually all signaling and cell-cell interactions. More specifically, glycans have been shown to regulate key pathophysiological steps within T cell biology such as T cell development, thymocyte selection, T cell activity and signaling as well as T cell differentiation and proliferation. They are of major importance in determining the interaction of human T cells with tumor cells. In this review, we will describe the role of glycosylation of human T cells in more depth, elaborate on the importance of glycosylation in the interaction of human T cells with tumor cells and discuss the potential of cancer immunotherapies that are based on manipulating the glycome functions at the tumor immune interface.^1,2

glypy: An Open Source Glycoinformatics Library

Glycoinformatics is a critical resource for the study of glycobiology, and glycobiology is a necessary component for understanding the complex interface between intra- and extracellular spaces. Despite this, there is limited software available to scientists studying these topics, requiring each to create fundamental data structures and representations anew for each of their applications. This leads to poor uptake of standardization and loss of focus on the real problems. We present glypy, a library written in Python for reading, writing, manipulating, and transforming glycans at several levels of precision. In addition to understanding several common formats for textual representation of glycans, the library also provides application programming interfaces (APIs) for major community databases, including GlyTouCan and UnicarbKB. The library is freely available under the Apache 2 common license with source code available at https://github.com/mobiusklein/ and documentation at https://glypy.readthedocs.io/ .

A Comprehensive, Open-source Platform for Mass Spectrometry-based Glycoproteomics Data Analysis

Glycosylation is among the most abundant and diverse protein post-translational modifications (PTMs) identified to date. The structural analysis of this PTM is challenging because of the diverse monosaccharides which are not conserved among organisms, the branched nature of glycans, their isomeric structures, and heterogeneity in the glycan distribution at a given site. Glycoproteomics experiments have adopted the traditional high-throughput LC-MSⁿ proteomics workflow to analyze site-specific glycosylation. However, comprehensive computational platforms for data analyses are scarce. To address this limitation, we present a comprehensive, open-source, modular software for glycoproteomics data analysis called GlycoPAT (GlycoProteomics Analysis Toolbox; freely available from www.VirtualGlycome.org/glycopat). The program includes three major advances: (1) "SmallGlyPep," a minimal linear representation of glycopeptides for MSⁿ data analysis. This format allows facile serial fragmentation of both the peptide backbone and PTM at one or more locations. (2) A novel scoring scheme based on calculation of the "Ensemble Score (ES)," a measure that scores and rank-orders MS/MS spectrum for N- and O-linked glycopeptides using cross-correlation and probability based analyses. (3) A false discovery rate (FDR) calculation scheme where decoy glycopeptides are created by simultaneously scrambling the amino acid sequence and by introducing artificial monosaccharides by perturbing the original sugar mass. Parallel computing facilities and user-friendly GUIs (Graphical User Interfaces) are also provided. GlycoPAT is used to catalogue site-specific glycosylation on simple glycoproteins, standard protein mixtures and human plasma cryoprecipitate samples in three common MS/MS fragmentation modes: CID, HCD and ETD. It is also used to identify 960 unique glycopeptides in cell lysates from prostate cancer cells. The results show that the simultaneous consideration of peptide and glycan fragmentation is necessary for high quality MSⁿ spectrum annotation in CID and HCD fragmentation modes. Additionally, they confirm the suitability of GlycoPAT to analyze shotgun glycoproteomics data.

Microbial glycoproteomics

Mass spectrometry-based "-omics" technologies are important tools for global and detailed mapping of post-translational modifications. Protein glycosylation is an abundant and important post translational modification widespread throughout all domains of life. Characterization of glycoproteins, including identification of glycan structure and components, their attachment sites and protein carriers, remains challenging. However, recent advances in glycoproteomics, a subbranch that studies and categorizes protein glycosylations, have greatly expanded the known protein glycosylation space and research in this area is rapidly accelerating. Here, we review recent developments in glycoproteomic technologies with a special focus on microbial protein glycosylation.

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.

Multi-level regulation of cellular glycosylation: from genes to transcript to enzyme to structure

Glycosylation is a ubiquitous mammalian post-translational modification that both decorates a majority of expressed proteins and regulates their function. Cellular glycan biosynthesis is facilitated by a few hundred enzymes that are collectively termed 'glycoenzymes'. The expression and activity of these enzymes is controlled at the transcription, translation and post-translation levels. New wet-lab advances are providing analytical methods to collect large-scale data at these multiple levels, relational databases are starting to collate these results, and computer models are beginning to integrate this information across scales in order to gain new knowledge. These activities are likely to enable the qualitative and quantitative mapping of pathways regulating glycan production and function in proteins, cells and tissue.

gFinder: A Web-Based Bioinformatics Tool for the Analysis of N-Glycopeptides

Glycoproteins influence numerous indispensable biological functions, and changes in protein glycosylation have been observed in various diseases. The identification and characterization of glycoprotein and glycosylation sites by mass spectrometry (MS) remain challenging tasks, and great efforts have been devoted to the development of proteome informatics tools that facilitate the MS analysis of glycans and glycopeptides. Here we report on the development of gFinder, a web-based bioinformatics tool that analyzes mixtures of native N-glycopeptides that have been profiled by tandem MS. gFinder not only enables the simultaneous integration of collision-induced dissociation (CID) and high-energy collisional dissociation (HCD) fragmentation but also merges the spectra for high-throughput analysis. These merged spectra expedite the identification of both glycans and N-glycopeptide backbones in tandem MS data using the glycan database and a proteomic search tool (e.g., Mascot). These data can be used to simultaneously characterize peptide backbone sequences and possible N-glycan structures using assigned scores. gFinder also provides many convenient functions that make it easy to perform manual calculations while viewing the spectrum on-screen. We used gFinder to detect an additional protein (Q8N9B8) that was missed from the previously published data set containing N-linked glycosylation. For N-glycan analysis, we used the GlycomeDB glycan structure database, which integrates the structural and taxonomic data from all of the major carbohydrate databases available in the public domain. Thus, gFinder is a convenient, high-throughput analytical tool for interpreting the tandem mass spectra of N-glycopeptides, which can then be used for identification of potential missing proteins having glycans. gFinder is available publicly at http://gFinder.proteomix.org/ .

Maturing Glycoproteomics Technologies Provide Unique Structural Insights into the N-glycoproteome and Its Regulation in Health and Disease

The glycoproteome remains severely understudied because of significant analytical challenges associated with glycoproteomics, the system-wide analysis of intact glycopeptides. This review introduces important structural aspects of protein N-glycosylation and summarizes the latest technological developments and applications in LC-MS/MS-based qualitative and quantitative N-glycoproteomics. These maturing technologies provide unique structural insights into the N-glycoproteome and its synthesis and regulation by complementing existing methods in glycoscience. Modern glycoproteomics is now sufficiently mature to initiate efforts to capture the molecular complexity displayed by the N-glycoproteome, opening exciting opportunities to increase our understanding of the functional roles of protein N-glycosylation in human health and disease.

Glycosphingolipids on Human Myeloid Cells Stabilize E-Selectin-Dependent Rolling in the Multistep Leukocyte Adhesion Cascade

OBJECTIVE

Recent studies suggest that the E-selectin ligands expressed on human leukocytes may differ from those in other species, particularly mice. To elaborate on this, we evaluated the impact of glycosphingolipids expressed on human myeloid cells in regulating E-selectin-mediated cell adhesion.

APPROACH AND RESULTS

A series of modified human cell lines and primary neutrophils were created by targeting UDP-Glucose Ceramide Glucosyltransferase using either lentivirus-delivered shRNA or CRISPR-Cas9-based genome editing. Enzymology and mass spectrometry confirm that the modified cells had reduced or abolished glucosylceramide biosynthesis. Glycomics profiling showed that UDP-Glucose Ceramide Glucosyltransferase disruption also increased prevalence of bisecting N-glycans and reduced overall sialoglycan expression on leukocyte N- and O-glycans. Microfluidics-based flow chamber studies demonstrated that both the UDP-Glucose Ceramide Glucosyltransferase knockouts and knockdowns display ≈60% reduction in leukocyte rolling and firm adhesion on E-selectin bearing stimulated endothelial cells, without altering cell adhesion to P-selectin. Consistent with the concept that the glycosphingolipids support slow rolling and the transition to firm arrest, inhibiting UDP-Glucose Ceramide Glucosyltransferase activity resulted in frequent leukocyte detachment events, skipping motion, and reduced diapedesis across the endothelium. Cells bearing truncated O- and N-glycans also sustained cell rolling on E-selectin, although their ability to be recruited from free fluid flow was diminished.

CONCLUSIONS

Glycosphingolipids likely contribute to human myeloid cell adhesion to E-selectin under fluid shear, particularly the transition of rolling cells to firm arrest.