Deciphering Protein Glycosylation by Computational Integration of On-chip Profiling, Glycan-array Data, and Mass Spectrometry

Metabolomics and 13C labelled glucose tracing to identify carbon incorporation into aberrant cell membrane glycans in cancer

Cell membrane glycans contribute to immune recognition, signaling, and cellular adhesion and migration, and altered membrane glycosylation is a feature of cancer cells that contributes to cancer progression. The uptake and metabolism of glucose and other nutrients essential for glycan synthesis could underlie altered membrane glycosylation, but the relationship between shifts in nutrient metabolism and the effects on glycans have not been directly examined. We developed a method that combines stable isotope tracing with metabolomics to enable direct observations of glucose allocation to nucleotide sugars and cell-membrane glycans. We compared the glucose allocation to membrane glycans of two pancreatic cancer cell lines that are genetically identical but have differing energy requirements. The 8988-S cells had higher glucose allocation to membrane glycans and intracellular pathways relating to glycan synthesis, but the 8988-T cells had higher glucose uptake and commitment of glucose to non-glycosylation pathways. The cell lines differed in the requirements of glucose for energy production, resulting in differences in glucose bioavailability for glycan synthesis. The workflow demonstrated here enables studies on the effects of metabolic shifts on the commitment of nutrients to cell-membrane glycans. The results suggest that cell-membrane glycans are remodeled through shifts in glucose commitment to non-glycosylation pathways.

Mass Spectrometry-Based Glycoproteomic Workflows for Cancer Biomarker Discovery

Glycosylation has a clear role in cancer initiation and progression, with numerous studies identifying distinct glycan features or specific glycoproteoforms associated with cancer. Common findings include that aggressive cancers tend to have higher expression levels of enzymes that regulate glycosylation as well as glycoproteins with greater levels of complexity, increased branching, and enhanced chain length1. Research in cancer glycoproteomics over the last 50-plus years has mainly focused on technology development used to observe global changes in glycosylation. Efforts have also been made to connect glycans to their protein carriers as well as to delineate the role of these modifications in intracellular signaling and subsequent cell function. This review discusses currently available techniques utilizing mass spectrometry-based technologies used to study glycosylation and highlights areas for future advancement.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2019-2020

This review is the tenth 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 2020. 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. The review is basically divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of arrays. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other areas such as medicine, industrial processes and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. The reported work shows increasing use of incorporation of new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented nearly 40 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show little sign of diminishing.

Simple and practical sialoglycan encoding system reveals vast diversity in nature and identifies a universal sialoglycan-recognizing probe derived from AB5 toxin B subunits

Vertebrate sialic acids (Sias) display much diversity in modifications, linkages, and underlying glycans. Slide microarrays allow high-throughput explorations of sialoglycan-protein interactions. A microarray presenting ~150 structurally defined sialyltrisaccharides with various Sias linkages and modifications still poses challenges in planning, data sorting, visualization, and analysis. To address these issues, we devised a simple 9-digit code for sialyltrisaccharides with terminal Sias and underlying two monosaccharides assigned from the nonreducing end, with 3 digits assigning a monosaccharide, its modifications, and linkage. Calculations based on the encoding system reveal >113,000 likely linear sialyltrisaccharides in nature. Notably, a biantennary N-glycan with 2 terminal sialyltrisaccharides could thus have >1010 potential combinations and a triantennary N-glycan with 3 terminal sequences, >1015 potential combinations. While all possibilities likely do not exist in nature, sialoglycans encode enormous diversity. While glycomic approaches are used to probe such diverse sialomes, naturally occurring bacterial AB5 toxin B subunits are simpler tools to track the dynamic sialome in biological systems. Sialoglycan microarray was utilized to compare sialoglycan-recognizing bacterial toxin B subunits. Unlike the poor correlation between B subunits and species phylogeny, there is stronger correlation with Sia-epitope preferences. Further supporting this pattern, we report a B subunit (YenB) from Yersinia enterocolitica (broad host range) recognizing almost all sialoglycans in the microarray, including 4-O-acetylated-Sias not recognized by a Yersinia pestis orthologue (YpeB). Differential Sia-binding patterns were also observed with phylogenetically related B subunits from Escherichia coli (SubB), Salmonella Typhi (PltB), Salmonella Typhimurium (ArtB), extra-intestinal E.coli (EcPltB), Vibrio cholera (CtxB), and cholera family homologue of E. coli (EcxB).

Artificial intelligence in the analysis of glycosylation data

Glycans are complex, yet ubiquitous across biological systems. They are involved in diverse essential organismal functions. Aberrant glycosylation may lead to disease development, such as cancer, autoimmune diseases, and inflammatory diseases. Glycans, both normal and aberrant, are synthesized using extensive glycosylation machinery, and understanding this machinery can provide invaluable insights for diagnosis, prognosis, and treatment of various diseases. Increasing amounts of glycomics data are being generated thanks to advances in glycoanalytics technologies, but to maximize the value of such data, innovations are needed for analyzing and interpreting large-scale glycomics data. Artificial intelligence (AI) provides a powerful analysis toolbox in many scientific fields, and here we review state-of-the-art AI approaches on glycosylation analysis. We further discuss how models can be analyzed to gain mechanistic insights into glycosylation machinery and how the machinery shapes glycans under different scenarios. Finally, we propose how to leverage the gained knowledge for developing predictive AI-based models of glycosylation. Thus, guiding future research of AI-based glycosylation model development will provide valuable insights into glycosylation and glycan machinery.

Unusual β1-4-galactosidase activity of an α1-6-mannosidase from Xanthomonas manihotis in the processing of branched hybrid and complex glycans

Mannosidases are a diverse group of glycoside hydrolases that play crucial roles in mannose trimming of oligomannose glycans, glycoconjugates, and glycoproteins involved in numerous cellular processes, such as glycan biosynthesis and metabolism, structure regulation, cellular recognition, and cell–pathogen interactions. Exomannosidases and endomannosidases cleave specific glycosidic bonds of mannoside linkages in glycans and can be used in enzyme-based methods for sequencing of isomeric glycan structures. α1-6-mannosidase from Xanthomonas manihotis is known as a highly specific exoglycosidase that removes unbranched α1-6 linked mannose residues from oligosaccharides. However, we discovered that this α1-6-mannosidase also possesses an unexpected β1-4-galactosidase activity in the processing of branched hybrid and complex glycans through our use of enzymatic reactions, high performance anion-exchange chromatography, and liquid chromatography mass spectrometric sequencing. Our docking simulation of the α1-6-mannosidase with glycan substrates reveals potential interacting residues in a relatively shallow pocket slightly differing from its homologous enzymes in the glycoside hydrolase 125 family, which may be responsible for the observed higher promiscuity in substrate binding and subsequent terminal glycan hydrolysis. This observation of novel β1-4-galactosidase activity of the α1-6-mannosidase provides unique insights into its bifunctional activity on the substrate structure-dependent processing of terminal α1-6-mannose of unbranched glycans and terminal β1-4-galactose of hybrid and complex glycans. The finding thus suggests the dual glycosidase specificity of this α1-6-mannosidase and the need for careful consideration when used for the structural elucidation of glycan isomers.

Utilizing liquid chromatography, ion mobility spectrometry, and mass spectrometry to assess INLIGHT™ derivatized N-linked glycans in biological samples

Glycosylation is a ubiquitous co- and post-translational modification involved in the sorting, folding, and trafficking of proteins in biological systems; in humans, >50% of gene products are glycosylated with the cellular machinery of glycosylation compromising ~2% of the genome. Perturbations in glycosylation have been implicated in a variety of diseases including neurodegenerative diseases and certain types of cancer. However, understanding the relationship between a glycan and its biological role is often difficult due to the numerous glycan isomers that exist. To address this challenge, nanoflow liquid chromatography, ion mobility spectrometry, and mass spectrometry (nLC-IMS-MS) were combined with the Individuality Normalization when Labeling with the Isotopic Glycan Hydrazide Tags (INLIGHT™) strategy to study a series of glycan standards and those enzymatically released from the glycoproteins horseradish peroxidase, fetuin, and pooled human plasma. The combination of IMS and the natural (NAT) and stable-isotope label (SIL) in the INLIGHT™ strategy provided additional confidence for each glycan identification due to the mobility aligned NAT- and SIL-labeled glycans and further capabilities for isomer examinations. Additionally, molecular trend lines based on the IMS and MS dimensions were investigated for the INLIGHT™ derivatized glycans, facilitating rapid identification of putative glycans in complex biological samples.

Customized peptidoglycan surfaces to investigate innate immune recognition via surface plasmon resonance

Glycan-protein interactions facilitate some of the most important biomolecular processes in and between cells. They are involved in different cellular pathways, cell-cell interactions and associated with many diseases, making these interactions of great interest. However, their structural and functional diversity poses great challenges in studying them at the molecular level. Surface plasmon resonance (SPR) technology presents great advantages to study glycan-protein interactions due to its superior sensitivity, ability to monitor real-time interactions, relatively simple data interpretation, and most importantly, direct measurement of binding without a need for fluorescent labeling. Here, another dimensionality of SPR in studying glycan-protein interactions is demonstrated via examples of binding between human innate immune receptors and their bacterial peptidoglycan ligands. In order to best resemble interactions in solution, a novel strategy of tethering the carbohydrate at different positions to the biosensor surface is applied to represent the potential displays of the carbohydrate ligand to the receptor. Subsequent kinetic analysis provides insights into the optimized configuration of peptidoglycan fragments for binding with its receptors. The manuscript contains a "how-to guide" to help with the implementation of these methods in other glycan-protein binding systems.

Combined Analysis of Multiple Glycan-Array Datasets: New Explorations of Protein-Glycan Interactions

Glycan arrays are indispensable for learning about the specificities of glycan-binding proteins. Despite the abundance of available data, the current analysis methods do not have the ability to interpret and use the variety of data types and to integrate information across datasets. Here, we evaluated whether a novel, automated algorithm for glycan-array analysis could meet that need. We developed a regression-tree algorithm with simultaneous motif optimization and packaged it in software called MotifFinder. We applied the software to analyze data from eight different glycan-array platforms with widely divergent characteristics and observed an accurate analysis of each dataset. We then evaluated the feasibility and value of the combined analyses of multiple datasets. In an integrated analysis of datasets covering multiple lectin concentrations, the software determined approximate binding constants for distinct motifs and identified major differences between the motifs that were not apparent from single-concentration analyses. Furthermore, an integrated analysis of data sources with complementary sets of glycans produced broader views of lectin specificity than produced by the analysis of just one data source. MotifFinder, therefore, enables the optimal use of the expanding resource of the glycan-array data and promises to advance the studies of protein-glycan interactions.

Big-Data Glycomics: Tools to Connect Glycan Biosynthesis to Extracellular Communication

Characteristically, cells must sense and respond to environmental cues. Despite the importance of cell-cell communication, our understanding remains limited and often lacks glycans. Glycans decorate proteins and cell membranes at the cell-environment interface, and modulate intercellular communication, from development to pathogenesis. Providing further challenges, glycan biosynthesis and cellular behavior are co-regulating systems. Here, we discuss how glycosylation contributes to extracellular responses and signaling. We further organize approaches for disentangling the roles of glycans in multicellular interactions using newly available datasets and tools, including glycan biosynthesis models, omics datasets, and systems-level analyses. Thus, emerging tools in big data analytics and systems biology are facilitating novel insights on glycans and their relationship with multicellular behavior.

Phospho-regulation of mitotic spindle assembly

The assembly of the bipolar mitotic spindle requires the careful orchestration of a myriad of enzyme activities like protein posttranslational modifications. Among these, phosphorylation has arisen as the principle mode for spatially and temporally activating the proteins involved in early mitotic spindle assembly processes. Here, we review key kinases, phosphatases, and phosphorylation events that regulate critical aspects of these processes. We highlight key phosphorylation substrates that are important for ensuring the fidelity of centriole duplication, centrosome maturation, and the establishment of the bipolar spindle. We also highlight techniques used to understand kinase-substrate relationships and to study phosphorylation events. We conclude with perspectives on the field of posttranslational modifications in early mitotic spindle assembly.

Advances in Tools to Determine the Glycan-Binding Specificities of Lectins and Antibodies

Proteins that bind carbohydrate structures can serve as tools to quantify or localize specific glycans in biological specimens. Such proteins, including lectins and glycan-binding antibodies, are particularly valuable if accurate information is available about the glycans that a protein binds. Glycan arrays have been transformational for uncovering rich information about the nuances and complexities of glycan-binding specificity. A challenge, however, has been the analysis of the data. Because protein-glycan interactions are so complex, simplistic modes of analyzing the data and describing glycan-binding specificities have proven inadequate in many cases. This review surveys the methods for handling high-content data on protein-glycan interactions. We contrast the approaches that have been demonstrated and provide an overview of the resources that are available. We also give an outlook on the promising experimental technologies for generating new insights into protein-glycan interactions, as well as a perspective on the limitations that currently face the field.

A Novel Mass Spectrometry Platform for Multiplexed N-Glycoprotein Biomarker Discovery from Patient Biofluids by Antibody Panel Based N-Glycan Imaging

A new platform for N-glycoprotein analysis from serum that combines matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) workflows with antibody slide arrays is described. Antibody panel based (APB) N-glycan imaging allows for the specific capture of N-glycoproteins by antibodies on glass slides and N-glycan analysis in a protein-specific and multiplexed manner. Development of this technique has focused on characterizing two abundant and well-studied human serum glycoproteins, alpha-1-antitrypsin and immunoglobulin G. Using purified standard solutions and 1 μL samples of human serum, both glycoproteins can be immunocaptured and followed by enzymatic release of N-glycans. N-Glycans are detected with a MALDI FT-ICR mass spectrometer in a concentration-dependent manner while maintaining specificity of capture. Importantly, the N-glycans detected via slide-based antibody capture were identical to that of direct analysis of the spotted standards. As a proof of concept, this workflow was applied to patient serum samples from individuals with liver cirrhosis to accurately detect a characteristic increase in an IgG N-glycan. This novel approach to protein-specific N-glycan analysis from an antibody panel can be further expanded to include any glycoprotein for which a validated antibody exists. Additionally, this platform can be adapted for analysis of any biofluid or biological sample that can be analyzed by antibody arrays.