GlycoDigest: a tool for the targeted use of exoglycosidase digestions in glycan structure determination

Machine learning tool as an enabler for rapid quantification of monoclonal antibodies N-glycans using fluorescence detector

Liquid chromatography-mass spectrometry (LC-MS) is widely used for identification and quantification of N-glycans of monoclonal antibodies (mAbs), owing to its high sensitivity and accuracy. However, its resource-intensive nature necessitates the development of rapid and cost-effective orthogonal analysis approaches. This study aims to develop an online method utilizing the Extreme Gradient Boosting (XGBoost) machine learning (ML) algorithm for real time quantification of InstantPC labelled N-glycans by Liquid Chromatography (LC) - fluorescence detector (FLD). The LC-FLD profile is pre-processed for baseline correction and noise reduction prior to fed to the machine learning (ML) algorithm. The algorithm has been successfully tested for commercial and inhouse developed mAbs and validated using LC-MS quantification as reference. The LC-FLD-ML model predicted values were at par with the LC-MS values with root mean square error of <0.5 and R2 of >0.95. The average errors using ML model (1.80 %) was reduced by a minimum of 28 % and 40 % for origin (1.5 %) and manual (1.07 %) based integration, respectively. The approach reduces the data analysis time per sample by ~70 % (from ~5 min to ~1.5 min), thereby offering a time and resource efficient orthogonality with LC-MS for quantification of N-glycans in mAbs.

GlycoStore: A Platform for H/UPLC and Capillary Electrophoresis Glycan Data

GlycoStore ( http://www.glycostore.org ) is an open access chromatographic and electrophoretic retention database of glycans characterized from glycoproteins, glycolipids, and biotherapeutics. It is a continuation of the GlycoBase project (Oxford Glycobiology Institute and National Institute for Bioprocessing Research and Training, Ireland) but addresses many of the technological limitations that impacted the growth of GlycoBase, in particular, improvements to the bioinformatics architecture, enhancing data annotations and coverage, and improving connectivity with external resources. The first release of GlycoStore (October 2017) contains over 850 glycan entries accompanied by 8500+ retention positions including data from: (1) fluorescently labelled released glycans determined using hydrophilic interaction chromatography (HILIC) ultrahigh-performance liquid chromatography (U/HPLC) and reversed phase (RP)-U/HPLC; (2) porous graphitized carbon chromatography (PGC) interfaced with ESI-MS/MS; and (3) capillary electrophoresis with laser induced fluorescence detection (CE-LIF). In this chapter, we outline the objectives of GlycoStore, and describe a selection of step-by-step workflows for navigating and browsing the information available. We also provide a short description of informatics tools available to query the database using Semantic technologies. The information presented in this chapter supplements our documentation knowledge base that describes interface improvements, new features and tools, and content updates ( https://unicarbkb.freshdesk.com/ ).

Single-cell fucosylation breakdown: Switching fucose to europium

Fucosylation and its fucosidic linkage-specific motifs are believed to be essential to understand their distinct roles in cellular behavior, but their quantitative information has not yet been fully disclosed due to the requirements of ultra-sensitivity and selectivity. Herein, we report an approach that converts fucose (Fuc) to stable europium (Eu) isotopic mass signal on hard ionization inductively coupled plasma mass spectrometry (ICP-MS). Metabolically assembled azido-fucose on the cell surface allows us to tag them with an alkyne-customized Eu-crafted bacteriophage MS2 capsid nanoparticle for Eu signal multiplication, resulting in an ever lowest detection limit of 4.2 zmol Fuc. Quantitative breakdown of the linkage-specific fucosylation motifs in situ preserved on single cancerous HepG2 and paracancerous HL7702 cells can thus be realized on a single-cell ICP-MS platform, specifying their roles during the cancering process. This approach was further applied to the discrimination of normal hepatocellular cells and highly, moderately, and poorly differentiated hepatoma cells collected from real hepatocellular carcinoma tissues.

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Switching facile fucose to stable Eu mass signal on a single-cell ICP-MS platform

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Ever lowest LOD of 4.2 zmol FucAz was achieved using a Eu-decorated MS2 nanoparticle

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Single-cell breakdown of fucosidic linkage-specific motifs

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Discrimination of highly, moderately, and poorly differentiated HCC from normal ones

A Pragmatic Guide to Enrichment Strategies for Mass Spectrometry-Based Glycoproteomics

Glycosylation is a prevalent, yet heterogeneous modification with a broad range of implications in molecular biology. This heterogeneity precludes enrichment strategies that can be universally beneficial for all glycan classes. Thus, choice of enrichment strategy has profound implications on experimental outcomes. Here we review common enrichment strategies used in modern mass spectrometry-based glycoproteomic experiments, including lectins and other affinity chromatographies, hydrophilic interaction chromatography and its derivatives, porous graphitic carbon, reversible and irreversible chemical coupling strategies, and chemical biology tools that often leverage bioorthogonal handles. Interest in glycoproteomics continues to surge as mass spectrometry instrumentation and software improve, so this review aims to help equip researchers with the necessary information to choose appropriate enrichment strategies that best complement these efforts.

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.

Databases and Bioinformatic Tools for Glycobiology and Glycoproteomics

Glycosylation plays critical roles in various biological processes and is closely related to diseases. Deciphering the glycocode in diverse cells and tissues offers opportunities to develop new disease biomarkers and more effective recombinant therapeutics. In the past few decades, with the development of glycobiology, glycomics, and glycoproteomics technologies, a large amount of glycoscience data has been generated. Subsequently, a number of glycobiology databases covering glycan structure, the glycosylation sites, the protein scaffolds, and related glycogenes have been developed to store, analyze, and integrate these data. However, these databases and tools are not well known or widely used by the public, including clinicians and other researchers who are not in the field of glycobiology, but are interested in glycoproteins. In this study, the representative databases of glycan structure, glycoprotein, glycan-protein interactions, glycogenes, and the newly developed bioinformatic tools and integrated portal for glycoproteomics are reviewed. We hope this overview could assist readers in searching for information on glycoproteins of interest, and promote further clinical application of glycobiology.

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.

GlycanAnalyzer: software for automated interpretation of N-glycan profiles after exoglycosidase digestions

SUMMARY

Many eukaryotic proteins are modified by N-glycans. Liquid chromatography (ultra-performance -UPLC and high-performance-HPLC) coupled with mass spectrometry (MS) is conventionally used to characterize N-glycan structures. Software can automatically assign glycan structures by matching their observed retention times and masses with standardized values in reference databases. However, more precise confirmation of N-glycan structures can be derived using exoglycosidases, enzymes that remove specific monosaccharides from glycans. Exoglycosidase removal of monosaccharides results in signature peak shifts, in both UPLC and MS1, yielding an effective way to verify N-glycan structure with high detail (down to the position and isomeric linkage of each monosaccharide). Because manual interpretation of exoglycosidase data is complex and time consuming, we developed GlycanAnalyzer, a web application that pattern matches N-glycan peak shifts following exoglycosidase digestion and automates structure assignments. GlycanAnalyzer significantly improves assignment accuracy over other auto-assignment methods on tests with a monoclonal antibody and four glycan standards (100% versus 82% for the next best software). By automating data interpretation, GlycanAnalyzer enables the easier use of exoglycosidases to precisely define N-glycan structure.

AVAILABILITY AND IMPLEMENTATION

http://glycananalyzer.neb.com. Datasets available online.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Early Stage Glycosylation Biomarkers in Alzheimer's Disease

Alzheimer's disease (AD) is of great cause for concern in our ageing population, which currently lacks diagnostic tools to permit accurate and timely diagnosis for affected individuals. The development of such tools could enable therapeutic interventions earlier in the disease course and thus potentially reducing the debilitating effects of AD. Glycosylation is a common, and important, post translational modification of proteins implicated in a host of disease states resulting in a complex array of glycans being incorporated into biomolecules. Recent investigations of glycan profiles, in a wide range of conditions, has been made possible due to technological advances in the field enabling accurate glycoanalyses. Amyloid beta (Aβ) peptides, tau protein, and other important proteins involved in AD pathogenesis, have altered glycosylation profiles. Crucially, these abnormalities present early in the disease state, are present in the peripheral blood, and help to distinguish AD from other dementias. This review describes the aberrant glycome in AD, focusing on proteins implicated in development and progression, and elucidates the potential of glycome aberrations as early stage biomarkers of AD.

Advancing Solutions to the Carbohydrate Sequencing Challenge

Carbohydrates possess a variety of distinct features with stereochemistry playing a particularly important role in distinguishing their structure and function. Monosaccharide building blocks are defined by a high density of chiral centers. Additionally, the anomericity and regiochemistry of the glycosidic linkages carry important biological information. Any carbohydrate-sequencing method needs to be precise in determining all aspects of this stereodiversity. Recently, several advances have been made in developing fast and precise analytical techniques that have the potential to address the stereochemical complexity of carbohydrates. This perspective seeks to provide an overview of some of these emerging techniques, focusing on those that are based on NMR and MS-hybridized technologies including ion mobility spectrometry and IR spectroscopy.

SugarSketcher: Quick and Intuitive Online Glycan Drawing

SugarSketcher is an intuitive and fast JavaScript interface module for online drawing of glycan structures in the popular Symbol Nomenclature for Glycans (SNFG) notation and exporting them to various commonly used formats encoding carbohydrate sequences (e.g., GlycoCT) or quality images (e.g., svg). It does not require a backend server or any specific browser plugins and can be integrated in any web glycoinformatics project. SugarSketcher allows drawing glycans both for glycobiologists and non-expert users. The "quick mode" allows a newcomer to build up a glycan structure having only a limited knowledge in carbohydrate chemistry. The "normal mode" integrates advanced options which enable glycobiologists to tailor complex carbohydrate structures. The source code is freely available on GitHub and glycoinformaticians are encouraged to participate in the development process while users are invited to test a prototype available on the ExPASY web-site and send feedback.

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.

HappyTools: A software for high-throughput HPLC data processing and quantitation

High-performance liquid chromatography (HPLC) is widely used for absolute quantitation. The advent of new columns and HPLC technology has enabled higher sample throughput, and hence, larger scale studies that perform quantitation on different sample types (e.g. healthy controls vs. patients with rheumatoid arthritis) using HPLC are becoming feasible. However, there remains a lack of methods that can analyse the increased number of HPLC samples. To address this in part, the modular toolkit HappyTools has been developed for the high-throughput targeted quantitation of HPLC measurements. HappyTools enables the user to create an automated workflow that includes retention time (t_r) calibration, data extraction and the calculation of several quality criteria for data curation. HappyTools has been tested on a biopharmaceutical standard and previously published clinical samples. The results show comparable accuracy between HappyTools, Waters Empower and ThermoFisher Chromeleon. However, HappyTools offered superior precision and throughput when compared with Waters Empower and ThermoFisher Chromeleon. HappyTools is released under the Apache 2.0 license, both the source code and a Windows binary can be freely downloaded from https://github.com/Tarskin/HappyTools.

Mining High-Complexity Motifs in Glycans: A New Language To Uncover the Fine Specificities of Lectins and Glycosidases

Knowledge of lectin and glycosidase specificities is fundamental to the study of glycobiology. The primary specificities of such molecules can be uncovered using well-established tools, but the complex details of their specificities are difficult to determine and describe. Here we present a language and algorithm for the analysis and description of glycan motifs with high complexity. The language uses human-readable notation and wildcards, modifiers, and logical operators to define motifs of nearly any complexity. By applying the syntax to the analysis of glycan-array data, we found that the lectin AAL had higher binding where fucose groups are displayed on separate branches. The lectin SNA showed gradations in binding based on the length of the extension displaying sialic acid and on characteristics of the opposing branches. A new algorithm to evaluate changes in lectin binding upon treatment with exoglycosidases identified the primary specificities and potential fine specificities of an α1–2-fucosidase and an α2–3,6,8-neuraminidase. The fucosidase had significantly lower action where sialic acid neighbors the fucose, and the neuraminidase showed statistically lower action where α1–2 fucose neighbors the sialic acid or is on the opposing branch. The complex features identified here would have been inaccessible to analysis using previous methods. The new language and algorithms promise to facilitate the precise determination and description of lectin and glycosidase specificities.

Automated N-Glycosylation Sequencing Of Biopharmaceuticals By Capillary Electrophoresis

Comprehensive analysis of the N-linked carbohydrates of glycoproteins is gaining high recent interest in both the biopharmaceutical and biomedical fields. In addition to high resolution glycosylation profiling, sugar residue and linkage specific enzymes are also routinely used for exoglycosidase digestion based carbohydrate sequencing. This latter one, albeit introduced decades ago, still mostly practiced by following tedious and time consuming manual processes. In this paper we introduce an automated carbohydrate sequencing approach using the appropriate exoglycosidase enzymes in conjunction with the utilization of some of the features of a capillary electrophoresis (CE) instrument to speed up the process. The enzymatic reactions were accomplished within the temperature controlled sample storage compartment of a capillary electrophoresis unit and the separation capillary was also utilized for accurate delivery of the exoglycosidase enzymes. CE analysis was conducted after each digestion step obtaining in this way the sequence information of N-glycans in 60 and 128 minutes using the semi- and the fully-automated methods, respectively.

Building a PGC-LC-MS N-glycan retention library and elution mapping resource

Porous graphitised carbon-liquid chromatography (PGC-LC) has been proven to be a powerful technique for the analysis and characterisation of complex mixtures of isomeric and isobaric glycan structures. Here we evaluate the elution behaviour of N-glycans on PGC-LC and thereby provide the potential of using chromatographic separation properties, together with mass spectrometry (MS) fragmentation, to determine glycan structure assignments more easily. We used previously reported N-glycan structures released from the purified glycoproteins Immunoglobulin G (IgG), Immunoglobulin A (IgA), lactoferrin, α1-acid glycoprotein, Ribonuclease B (RNase B), fetuin and ovalbumin to profile their behaviour on capillary PGC-LC-MS. Over 100 glycan structures were determined by MS/MS, and together with targeted exoglycosidase digestions, created a N-glycan PGC retention library covering a full spectrum of biologically significant N-glycans from pauci mannose to sialylated tetra-antennary classes. The resultant PGC retention library ( http://www.glycostore.org/showPgc ) incorporates retention times and supporting fragmentation spectra including exoglycosidase digestion products, and provides detailed knowledge on the elution properties of N-glycans by PGC-LC. Consequently, this platform should serve as a valuable resource for facilitating the detailed analysis of the glycosylation of both purified recombinant, and complex mixtures of, glycoproteins using established workflows.

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).

Relative quantitation of multi-antennary N-glycan classes: combining PGC-LC-ESI-MS with exoglycosidase digestion

In the search for N-glycan disease biomarkers current glycoanalytical methods may not be revealing a complete picture of precious samples, and we may be missing valuable structural information that fall outside analysis windows.