GlycoBase and autoGU: tools for HPLC-based glycan analysis

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.

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.

Synthesis and application of BODIPY-based fluorescent labeling tag for oligosaccharide and N-linked glycan analysis by high-performance liquid chromatography with fluorescence detection

BACKGROUND

Glycosylation analysis is still challenging, not only because of the extreme structure complexity and conjugation diversity of glycans but also because of instrumental aspects such as the sensitivity limits of analyses. Therefore, glycan analysis by chromatographic methods is very often combined with fluorescence detection in addition to MS. The majority of fluorescent labeling employed before LC separation is based on 2-aminobenzamide, which has several disadvantages such as low labeling yield, poor fluorescence properties, and MS ionization efficiency. Therefore, even after several decades of development of new labels, there is still a need for new labeling tags with improved characteristics.

RESULTS

We present the application of a newly synthesized fluorescent label designed for oligosaccharide and glycan analysis by high-performance liquid chromatography with fluorescence detection (HPLC/FLD). The novel hydrazide derivative of dipyrrometheneboron difluoride (BODIPY) was synthesized from 2,4-dimethylpyrrole, methyl succinyl chloride, and boron trifluoride etherate followed by a reaction with hydrazine. The synthesized label was characterized by several analytical methods including NMR, UV/Vis and fluorescence spectroscopy, and mass spectrometry. The labeling reaction via hydrazone formation chemistry was optimized by labeling of maltooligosaccharide standards. The analysis of maltohexaose labeled by BODIPY-hydrazide followed by HPLC/FLD analysis provided the limit of detection in the low tens of femtomole. The presented method based on fluorescence detection is at least 30 times more sensitive than the standard approach employing labeling by 2-aminobenzamide. In addition, the labeling method by BODIPY-hydrazide was used for N-linked glycan profiling of several glycoproteins (ribonuclease B, immunoglobulin G) by RP-HPLC/FLD as well as HILIC/FLD analysis.

SIGNIFICANCE

This work represents the design, synthesis, and application of a new fluorescent label based on the BODIPY core and hydrazone formation chemistry for oligosaccharide and glycan analysis by HPLC/FLD. The proposed approach significantly improved the oligosaccharide and glycan analysis in comparison to the commonly used procedure employing 2-aminobenzamide.

Human-specific features and developmental dynamics of the brain N-glycome

Comparative "omics" studies have revealed unique aspects of human neurobiology, yet an evolutionary perspective of the brain N-glycome is lacking. We performed multiregional characterization of rat, macaque, chimpanzee, and human brain N-glycomes using chromatography and mass spectrometry and then integrated these data with complementary glycotranscriptomic data. We found that, in primates, the brain N-glycome has diverged more rapidly than the underlying transcriptomic framework, providing a means for rapidly generating additional interspecies diversity. Our data suggest that brain N-glycome evolution in hominids has been characterized by an overall increase in complexity coupled with a shift toward increased usage of α(2-6)-linked N-acetylneuraminic acid. Moreover, interspecies differences in the cell type expression pattern of key glycogenes were identified, including some human-specific differences, which may underpin this evolutionary divergence. Last, by comparing the prenatal and adult human brain N-glycomes, we uncovered region-specific neurodevelopmental pathways that lead to distinct spatial N-glycosylation profiles in the mature brain.

CHOmpact: A reduced metabolic model of Chinese hamster ovary cells with enhanced interpretability

Metabolic modeling has emerged as a key tool for the characterization of biopharmaceutical cell culture processes. Metabolic models have also been instrumental in identifying genetic engineering targets and developing feeding strategies that optimize the growth and productivity of Chinese hamster ovary (CHO) cells. Despite their success, metabolic models of CHO cells still present considerable challenges. Genome-scale metabolic models (GeMs) of CHO cells are very large (>6000 reactions) and are difficult to constrain to yield physiologically consistent flux distributions. The large scale of GeMs also makes the interpretation of their outputs difficult. To address these challenges, we have developed CHOmpact, a reduced metabolic network that encompasses 101 metabolites linked through 144 reactions. Our compact reaction network allows us to deploy robust, nonlinear optimization and ensure that the computed flux distributions are physiologically consistent. Furthermore, our CHOmpact model delivers enhanced interpretability of simulation results and has allowed us to identify the mechanisms governing shifts in the anaplerotic consumption of asparagine and glutamate as well as an important mechanism of ammonia detoxification within mitochondria. CHOmpact, thus, addresses key challenges of large-scale metabolic models and will serve as a platform to develop dynamic metabolic models for the control and optimization of biopharmaceutical cell culture processes.

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.

Protein glycosylation and glycoinformatics for novel biomarker discovery in neurodegenerative diseases

Glycosylation is a common post-translational modification of brain proteins including cell surface adhesion molecules, synaptic proteins, receptors and channels, as well as intracellular proteins, with implications in brain development and functions. Using advanced state-of-the-art glycomics and glycoproteomics technologies in conjunction with glycoinformatics resources, characteristic glycosylation profiles in brain tissues are increasingly reported in the literature and growing evidence shows deregulation of glycosylation in central nervous system disorders, including aging associated neurodegenerative diseases. Glycan signatures characteristic of brain tissue are also frequently described in cerebrospinal fluid due to its enrichment in brain-derived molecules. A detailed structural analysis of brain and cerebrospinal fluid glycans collected in publications in healthy and neurodegenerative conditions was undertaken and data was compiled to create a browsable dedicated set in the GlyConnect database of glycoproteins (https://glyconnect.expasy.org/brain). The shared molecular composition of cerebrospinal fluid with brain enhances the likelihood of novel glycobiomarker discovery for neurodegeneration, which may aid in unveiling disease mechanisms, therefore, providing with novel therapeutic targets as well as diagnostic and progression monitoring tools.

Creation of a milk oligosaccharide database, MilkOligoDB, reveals common structural motifs and extensive diversity across mammals

The carbohydrate fraction of most mammalian milks contains a variety of oligosaccharides that encompass a range of structures and monosaccharide compositions. Human milk oligosaccharides have received considerable attention due to their biological roles in neonatal gut microbiota, immunomodulation, and brain development. However, a major challenge in understanding the biology of milk oligosaccharides across other mammals is that reports span more than 5 decades of publications with varying data reporting methods. In the present study, publications on milk oligosaccharide profiles were identified and harmonized into a standardized format to create a comprehensive, machine-readable database of milk oligosaccharides across mammalian species. The resulting database, MilkOligoDB, includes 3193 entries for 783 unique oligosaccharide structures from the milk of 77 different species harvested from 113 publications. Cross-species and cross-publication comparisons of milk oligosaccharide profiles reveal common structural motifs within mammalian orders. Of the species studied, only chimpanzees, bonobos, and Asian elephants share the specific combination of fucosylation, sialylation, and core structures that are characteristic of human milk oligosaccharides. However, agriculturally important species do produce diverse oligosaccharides that may be valuable for human supplementation. Overall, MilkOligoDB facilitates cross-species and cross-publication comparisons of milk oligosaccharide profiles and the generation of new data-driven hypotheses for future research.

Comprehensive N-Glycan Mapping using Parallel Reaction Monitoring LC-MS/MS

PURPOSE

Glycan composition can impact a biotherapeutic's safety and efficacy. For example, changes in the relative abundance of different glycan attributes like afucosylation, galactosylation or high-mannose content can change the properties or functions of a monoclonal antibody (mAb). While established methods can effectively characterize major glycan species in biotherapeutic drug products, there is still a need for more sensitive and specific methods that can effectively monitor low abundance species which may impact mAb function.

METHODS

Glycans released from two mAbs, adalimumab and trastuzumab, were derivatized with Rapifluor-MS™. Glycans were separated using HILIC and detected using either fluorescence (FLD) or mass spectrometry (MS). A parallel reaction monitoring (PRM) workflow was used for the MS analysis.

RESULTS AND CONCLUSION

FLD analysis identified 18 and 19 glycan peaks in adalimumab and trastuzumab, respectively. Glycan identities were determined using MS-analysis and a high number of FLD peaks containing co-eluting glycan species were observed. PRM analysis quantified 38 and 39 glycan species in adalimumab and trastuzumab, respectively, and the increase in glycans that could be identified was due to superior sensitivity and selectivity compared to FLD. Notably, many low abundance glycans identified by PRM included species that were not reported in other studies. PRM also offered several additional advantages; unique structural features could be identified using the collected MS/MS spectra and de-coupling MS acquisition and data processing simplified the transfer of methods between instruments. The results established PRM as a precise, informative tool for glycan analysis and quantitation.

Chemical conjugation to differentiate monosaccharides by Raman and surface enhanced Raman spectroscopy

Sugars play important roles in numerous biological processes, from providing energy to modifying proteins to alter their function. Glycosylation, the attachment of a sugar residue to a protein, is the most common post translational modification. Identifying the glycans on a protein is a useful tool both for pharmaceutical development as well as probing the proteome and glycome further. Sugars, however, are difficult analytes to probe due to their isomeric nature. In this work, Raman spectroscopy and surface enhanced Raman spectroscopy (SERS) are used to identify different monosaccharide species based on the vibrational modes of these isomeric analytes. The weak scattering of the sugars was overcome through conjugation with phenylboronic acid to provide a larger Raman scattering cross section and induce slight changes in the observed spectra associated with the structure of the monosaccharides. Spontaneous Raman, SERS in flow, and static SERS detection were performed in order to discriminate between arabinose, fructose, galactose, glucose, mannose, and ribose, as well as provide a method for identification and quantification for these sugar conjugates.

Comparative analysis of transferrin and IgG N-glycosylation in two human populations

Human plasma transferrin (Tf) N-glycosylation has been mostly studied as a marker for congenital disorders of glycosylation, alcohol abuse, and hepatocellular carcinoma. However, inter-individual variability of Tf N-glycosylation is not known, mainly due to technical limitations of Tf isolation in large-scale studies. Here, we present a highly specific robust high-throughput approach for Tf purification from human blood plasma and detailed characterization of Tf N-glycosylation on the level of released glycans by ultra-high-performance liquid chromatography based on hydrophilic interactions and fluorescence detection (HILIC-UHPLC-FLD), exoglycosidase sequencing, and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). We perform a large-scale comparative study of Tf and immunoglobulin G (IgG) N-glycosylation analysis in two human populations and demonstrate that Tf N-glycosylation is associated with age and sex, along with multiple biochemical and physiological traits. Observed association patterns differ compared to the IgG N-glycome corroborating tissue-specific N-glycosylation and specific N-glycans' role in their distinct physiological functions.

Human-specific features and developmental dynamics of the brain N-glycome

Comparative "omics" studies have revealed unique aspects of human neurobiology, yet an evolutionary perspective of the brain N-glycome is lacking. Here, we performed multi-regional characterization of rat, macaque, chimpanzee, and human brain N-glycomes using chromatography and mass spectrometry, then integrated these data with complementary glycotranscriptomic data. We found that in primates the brain N-glycome has evolved more rapidly than the underlying transcriptomic framework, providing a mechanism for generating additional diversity. We show that brain N-glycome evolution in hominids has been characterized by an increase in complexity and α(2-6)-linked N-acetylneuraminic acid along with human-specific cell-type expression of key glycogenes. Finally, by comparing the prenatal and adult human brain N-glycome, we identify region-specific neurodevelopmental pathways that lead to distinct spatial N-glycosylation profiles in the mature brain.

One-Sentence Summary

Evolution of the human brain N-glycome has been marked by an increase in complexity and a shift in sialic acid linkage.

Quantitative clinical glycomics strategies: A guide for selecting the best analysis approach

Glycans introduce complexity to the proteins to which they are attached. These modifications vary during the progression of many diseases; thus, they serve as potential biomarkers for disease diagnosis and prognosis. The immense structural diversity of glycans makes glycosylation analysis and quantitation difficult. Fortunately, recent advances in analytical techniques provide the opportunity to quantify even low-abundant glycopeptides and glycans derived from complex biological mixtures, allowing for the identification of glycosylation differences between healthy samples and those derived from disease states. Understanding the strengths and weaknesses of different quantitative glycomics analysis methods is important for selecting the best strategy to analyze glycosylation changes in any given set of clinical samples. To provide guidance towards selecting the proper approach, we discuss four widely used quantitative glycomics analysis platforms, including fluorescence-based analysis of released N-linked glycans and three different varieties of MS-based analysis: liquid chromatography (LC)-mass spectrometry (MS) analysis of glycopeptides, matrix-assisted laser desorption ionization-time of flight MS, and LC-ESI-MS analysis of released N-linked glycans. These methods' strengths and weaknesses are compared, particularly associated with the figures of merit that are important for clinical biomarker studies, including: the initial sample requirements, the methods' throughput, sample preparation time, the number of species identified, the methods' utility for isomer separation and structural characterization, method-related challenges associated with quantitation, repeatability, the expertise required, and the cost for each analysis. This review, therefore, provides unique guidance to researchers who endeavor to undertake a clinical glycomics analysis by offering insights on the available analysis technologies.

High-Throughput Glycomic Methods

Glycomics aims to identify the structure and function of the glycome, the complete set of oligosaccharides (glycans), produced in a given cell or organism, as well as to identify genes and other factors that govern glycosylation. This challenging endeavor requires highly robust, sensitive, and potentially automatable analytical technologies for the analysis of hundreds or thousands of glycomes in a timely manner (termed high-throughput glycomics). This review provides a historic overview as well as highlights recent developments and challenges of glycomic profiling by the most prominent high-throughput glycomic approaches, with N-glycosylation analysis as the focal point. It describes the current state-of-the-art regarding levels of characterization and most widely used technologies, selected applications of high-throughput glycomics in deciphering glycosylation process in healthy and disease states, as well as future perspectives.

Characterization of Mesothelin Glycosylation in Pancreatic Cancer: Decreased Core Fucosylated Glycoforms in Pancreatic Cancer Patients’ Sera

Currently, there are no reliable biomarkers for the diagnosis of pancreatic cancer (PaC). Glycoproteomic approaches that analyze the glycan determinants on specific glycoproteins have proven useful to develop more specific cancer biomarkers than the corresponding protein levels. In PaC, mesothelin (MSLN) is a neo-expressed glycoprotein. MSLN glycosylation has not been described and could be altered in PaC. In this work, we aimed to characterize MSLN glycans from PaC cells and serum samples to assess their potential usefulness as PaC biomarkers. First, we analyzed MSLN glycans from PaC cell lines and then we developed an enzyme-linked lectin assay to measure core fucosylated-MSLN (Cf-MSLN) glycoforms. MSLN glycans from PaC cells were analyzed by glycan sequencing and through Western blotting with lectins. All of the cell lines secreted MSLN, with its three N-glycosylation sites occupied by complex-type N-glycans, which were mainly α2,3-sialylated, core fucosylated and highly branched. The Cf-MSLN glycoforms were quantified on PaC serum samples, and compared with MSLN protein levels. The Cf-MSLN was significantly decreased in PaC patients compared to control sera, while no differences were detected by using MSLN protein levels. In conclusion, Cf-MSLN glycoforms were differently expressed in PaC, which opens the way to further investigate their usefulness as PaC biomarkers.

Acute lyme disease IgG N-linked glycans contrast the canonical inflammatory signature

Lyme disease (LD) infection is caused by Borrelia burgdorferi sensu lato (Bb). Due to the limited presence of this pathogen in the bloodstream in humans, diagnosis of LD relies on seroconversion. Immunoglobulins produced in response to infection are differentially glycosylated to promote or inhibit downstream inflammatory responses by the immune system. Immunoglobulin G (IgG) N-glycan responses to LD have not been characterized. In this study, we analyzed IgG N-glycans from cohorts of healthy controls, acute LD patient serum, and serum collected after acute LD patients completed a 2- to 3-week course of antibiotics and convalesced for 70-90 days. Results indicate that during the acute phase of Bb infection, IgG shifts its glycosylation profile to include structures that are not associated with the classic proinflammatory IgG N-glycan signature. This unexpected result is in direct contrast to what is reported for other inflammatory diseases. Furthermore, IgG N-glycans detected during acute LD infection discriminated between control, acute, and treated cohorts with a sensitivity of 75-100% and specificity of 94.7-100%.

Dextran as internal calibrant for N-glycan analysis by liquid chromatography coupled to ion mobility-mass spectrometry

LC-MS is one of the most important tools for the comprehensive characterization of N-glycans. Despite many efforts to speed up glycan analysis via optimized sample preparation (e.g., faster enzyme digestion in combination with instant or rapid labeling dyes), a major bottleneck remains the rather long measurement times of HILIC chromatography. Further complication arises from the necessity to concomitantly calibrate with an external standard to allow for accurate retention times and the conversion into more robust GU values. Here we demonstrate the use of an internal calibration strategy for HILIC chromatography to speed up glycan analysis. By reducing the number of utilized dextran oligosaccharides, the calibrant can be spiked directly into the sample such that external calibration runs are no longer required. The minimized dextran ladder shows accurate GU calibration with a minor deviation of well below 1% and can be applied without modifications in sample preparation or data processing. We further demonstrate the simultaneous use of the minimized dextran ladder as calibrant for the estimation of CCS values in traveling wave ion mobility spectrometry. In both cases, the minimized dextran ladder enables the measurement of calibrant and sample in a single HPLC run without losing information or accuracy.

Mass Spectrometry-Based Techniques to Elucidate the Sugar Code

Cells encode information in the sequence of biopolymers, such as nucleic acids, proteins, and glycans. Although glycans are essential to all living organisms, surprisingly little is known about the "sugar code" and the biological roles of these molecules. The reason glycobiology lags behind its counterparts dealing with nucleic acids and proteins lies in the complexity of carbohydrate structures, which renders their analysis extremely challenging. Building blocks that may differ only in the configuration of a single stereocenter, combined with the vast possibilities to connect monosaccharide units, lead to an immense variety of isomers, which poses a formidable challenge to conventional mass spectrometry. In recent years, however, a combination of innovative ion activation methods, commercialization of ion mobility-mass spectrometry, progress in gas-phase ion spectroscopy, and advances in computational chemistry have led to a revolution in mass spectrometry-based glycan analysis. The present review focuses on the above techniques that expanded the traditional glycomics toolkit and provided spectacular insight into the structure of these fascinating biomolecules. To emphasize the specific challenges associated with them, major classes of mammalian glycans are discussed in separate sections. By doing so, we aim to put the spotlight on the most important element of glycobiology: the glycans themselves.

Changes in Specific Biomarkers Indicate Cardiac Adaptive and Anti-inflammatory Response of Repeated Recreational SCUBA Diving

Objective

Recreational SCUBA (rSCUBA) diving has become a highly popular and widespread sport. Yet, information on molecular events underlying (patho)physiological events that follow exposure to the specific environmental conditions (hyperbaric conditions, coldness, immersion, and elevated breathing pressure), in which rSCUBA diving is performed, remain largely unknown. Our previous study suggested that repeated rSCUBA diving triggers an adaptive response of cardiovascular and immune system. To elucidate further molecular events underlying cardiac and immune system adaptation and to exclude possible adverse effects we measured blood levels of specific cardiac and inflammation markers.

Methods

This longitudinal intervention study included fourteen recreational divers who performed five dives, one per week, on the depth 20–30 m that lasted 30 min, after the non-dive period of 5 months. Blood samples were taken immediately before and after the first, third, and fifth dives. Copeptin, immunoglobulins A, G and M, complement components C3 and C4, and differential blood count parameters, including neutrophil-to-lymphocyte ratio (NLR) were determined using standard laboratory methods. Cell-free DNA was measured by qPCR analysis and N-glycans released from IgG and total plasma proteins (TPP), were analyzed by hydrophilic interaction ultra-performance liquid chromatography.

Results

Copeptin level increased after the first dive but decreased after the third and fifth dive. Increases in immunoglobulins level after every dive and during whole studied period were observed, but no changes in C3, C4, and cfDNA level were detected. NLR increased only after the first dive. IgG and TPP N-glycosylation alterations toward anti-inflammatory status over whole studied period were manifested as an increase in monogalyctosylated and core-fucosylated IgG N-glycans and decrease in agalactosylated TPP N-glycans.

Conclusion

rSCUBA diving practiced on a regular basis promotes anti-inflammatory status thus contributing cardioprotection and conferring multiple health benefits.

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).

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/ ).

Combining functional metagenomics and glycoanalytics to identify enzymes that facilitate structural characterization of sulfated N-glycans

BACKGROUND

Sulfate modification of N-glycans is important for several biological functions such as clearance of pituitary hormones or immunoregulation. Yet, the prevalence of this N-glycan modification and its functions remain largely unexplored. Characterization of N-glycans bearing sulfate modifications is hampered in part by a lack of enzymes that enable site-specific detection of N-glycan sulfation. In this study, we used functional metagenomic screening to identify enzymes that act upon sulfated N-acetylglucosamine (GlcNAc). Using multiplexed capillary gel electrophoresis with laser-induced fluorescence detection (xCGE-LIF) -based glycoanalysis we proved their ability to act upon GlcNAc-6-SO4 on N-glycans.

RESULTS

Our screen identified a sugar-specific sulfatase that specifically removes sulfate from GlcNAc-6-SO4 when it is in a terminal position on an N-glycan. Additionally, in the absence of calcium, this sulfatase binds to the sulfated glycan but does not remove the sulfate group, suggesting it could be used for selective isolation of sulfated N-glycans. Further, we describe isolation of a sulfate-dependent hexosaminidase that removes intact GlcNAc-6-SO4 (but not asulfated GlcNAc) from a terminal position on N-glycans. Finally, the use of these enzymes to detect the presence of sulfated N-glycans by xCGE-LIF is demonstrated.

CONCLUSION

The present study demonstrates the feasibility of using functional metagenomic screening combined with glycoanalytics to discover enzymes that act upon chemical modifications of glycans. The discovered enzymes represent new specificities that can help resolve the presence of GlcNAc-6-SO4 in N-glycan structural analyses.

GlycanGUI: Automated Glycan Annotation and Quantification Using Glucose Unit Index

The retention time provides critical information for glycan annotation and quantification from the Liquid Chromatography Mass Spectrometry (LC-MS) data. However, the variation of the precise retention time of glycans is highly dependent on the experimental conditions such as the specific separating columns, MS instruments and/or the buffer used. This variation hampers the exploitation of retention time for the glycan annotation from LC-MS data, especially when inter-laboratory data are compared. To incorporate the retention time of glycan across experiments, Glucose Unit Index (GUI) can be computed using the dextrin ladder as internal standard. The retention time of glycans are then calibrated with respect to glucose units derived from dextrin ladders. Despite the successful application of the GUI approach, the manual calibration process is quite tedious and often error prone. In this work, we present a standalone software tool GlycanGUI, with a graphic user interface to automatically carry out the GUI-based glycan annotation/quantification and subsequent data analysis. When tested on experimental data, GlycanGUI reported accurate GUI values compared with manual calibration, and thus is ready to be used for automated glycan annotation and quantification using GUI.

The effect of n-3 polyunsaturated fatty acids enriched hen eggs consumption on IgG and total plasma protein N-glycosylation in healthy individuals and cardiovascular patients

OBJECTIVE

This study determined the effect of n-3 PUFAs enriched hen eggs consumption on IgG and total plasma protein N-glycan profiles and inflammatory biomarkers level in healthy individuals (N = 33) and cardiovascular (CV) patients (N = 21).

MATERIALS AND METHODS

Subjects were divided to Control-Healthy and Control-CV subgroups (consumed three regular hens' eggs/daily (249 mg n-3 PUFAs/day)), and n-3-PUFAs-Healthy and n-3-PUFAs-CV subgroups (consumed three n-3 PUFAs enriched hen eggs/daily (1053 mg n-3 PUFAs/day)) for 3 weeks. Serum free fatty acids profile and high-sensitivity C reactive protein (hsCRP), interleukin 6 and 10 (IL-6, IL-10) and tumor necrosis factor alpha were measured. Total plasma protein and IgG N-glycome have been profiled before and after dietary protocols.

RESULTS

Serum n-3 PUFAs concentration significantly increased following n-3 PUFAs hen eggs consumption in both n-3-PUFAs-Healthy and n-3-PUFAs-CV. IL-10 significantly increased in both Healthy subgroups, while no change occurred in CV subgroups. Derived IgG N-glycan traits: bisecting GlcNAc (B) significantly decreased in n-3-PUFAs-Healthy, while agalactosylation (G0) and core fucosylation (CF) significantly increased in Control-Healthy. Derived total plasma protein N-glycan traits: high branching glycans (HB), trigalactosylation (G3), tetragalactosylation (G4), trisialylation (S3), tetrasialylation (S4) and antennary fucosylation (AF) significantly decreased, while G0, monogalactosylation (G1), neutral glycans (S0), B, CF and oligomannose structures (OM) significantly increased in n-3 PUFAs-CV. Digalactosylation (G2) significantly decreased, and G0, G1, S0, disialylation (S2), B and CF significantly increased in Control-CV.

CONCLUSIONS

n-3 PUFAs consumption alters IgG N-glycan traits and IL-10 in healthy individuals, and total plasma protein N-glycan traits in CV patients, by shifting them toward less inflammatory N-glycosylation profile.

Continuous optical in-line glucose monitoring and control in CHO cultures contributes to enhanced metabolic efficiency while maintaining darbepoetin alfa product quality

Great efforts are directed towards improving productivity, consistency and quality of biopharmaceutical processes and products. One particular area is the development of new sensors for continuous monitoring of critical bioprocess parameters by using online or in-line monitoring systems. Recently, we developed a glucose biosensor applicable in single-use, in-line and long-term glucose monitoring in mammalian cell bioreactors. Now, we integrated this sensor in an automated glucose monitoring and feeding system capable of maintaining stable glucose levels, even at very low concentrations. We compared this fed-batch feedback system at both low (< 1 mM) and high (40 mM) glucose levels with traditional batch culture methods, focusing on glycosylation and glycation of the recombinant protein darbepoetin alfa (DPO) produced by a CHO cell line. We evaluated cell growth, metabolite and product concentration under different glucose feeding strategies and show that continuous feeding, even at low glucose levels, has no harmful effects on DPO quantity and quality. We conclude that our system is capable of tight glucose level control throughout extended bioprocesses and has the potential to improve performance where constant maintenance of glucose levels is critical.

Glycosylation Biomarkers Associated with Age-Related Diseases and Current Methods for Glycan Analysis

Ageing is a complex process which implies the accumulation of molecular, cellular and organ damage, leading to an increased vulnerability to disease. In Western societies, the increase in the elderly population, which is accompanied by ageing-associated pathologies such as cardiovascular and mental diseases, is becoming an increasing economic and social burden for governments. In order to prevent, treat and determine which subjects are more likely to develop these age-related diseases, predictive biomarkers are required. In this sense, some studies suggest that glycans have a potential role as disease biomarkers, as they modify the functions of proteins and take part in intra- and intercellular biological processes. As the glycome reflects the real-time status of these interactions, its characterisation can provide potential diagnostic and prognostic biomarkers for multifactorial diseases. This review gathers the alterations in protein glycosylation profiles that are associated with ageing and age-related diseases, such as cancer, type 2 diabetes mellitus, metabolic syndrome and several chronic inflammatory diseases. Furthermore, the review includes the available techniques for the determination and characterisation of glycans, such as liquid chromatography, electrophoresis, nuclear magnetic resonance and mass spectrometry.

Toward robust N-glycomics of various tissue samples that may contain glycans with unknown or unexpected structures

Glycans in tissues are structurally diverse and usually include a large number of isomers that cannot be easily distinguished by mass spectrometry (MS). To address this issue, we developed a combined method that can efficiently separate and identify glycan isomers. First, we separated 2-aminopyridine (PA)-derivatized N-glycans from chicken colon by reversed-phase liquid chromatography (LC) and directly analyzed them by electrospray ionization (ESI)-MS and MS/MS to obtain an overview of the structural features of tissue glycans. Next, we deduced the structures of isomers based on their elution positions, full MS, and MS/MS data, before or after digestions with several exoglycosidases. In this method, the elution position differed greatly depending on the core structure and branching pattern, allowing multiantennary N-glycan structures to be easily distinguished. To further determine linkages of branch sequences, we modified PA-N-glycans with sialic acid linkage-specific alkylamidation and/or permethylation, and analyzed the products by LC–MS and multistage MS. We determined the relative abundances of core structures, branching patterns, and branch sequences of N-glycans from chicken colon, and confirmed presence of characteristic branch sequences such as Le^x, sialyl Le^x, sulfated LacNAc, LacNAc repeat, and LacdiNAc. The results demonstrated that our method is useful for comparing N-glycomes among various tissue samples.

Released N-Glycan Analysis for Biotherapeutic Development Using Liquid Chromatography and Mass Spectrometry

In this chapter, we describe an LC-fluorescence (FLR)/MS-based method for released N-glycan analysis in the development of biotherapeutic proteins. The method includes enzymatic release and labeling of N-glycans with a signal-enhancing tag, LC-MS data collection, and data interpretation. Using the given protocol, up to 24 glycan samples can be prepared within 1 h, while the LC-FLR/MS data can be collected and analyzed using an established data processing method in a semi-automated manner.

Lectin and Liquid Chromatography-Based Methods for Immunoglobulin (G) Glycosylation Analysis

Immunoglobulin (Ig) glycosylation has been shown to dramatically affect its structure and effector functions. Ig glycosylation changes have been associated with different diseases and show a promising biomarker potential for diagnosis and prognosis of disease advancement. On the other hand, therapeutic biomolecules based on structural and functional features of Igs demand stringent quality control during the production process to ensure their safety and efficacy. Liquid chromatography (LC) and lectin-based methods are routinely used in Ig glycosylation analysis complementary to other analytical methods, e.g., mass spectrometry and capillary electrophoresis. This chapter covers analytical approaches based on LC and lectins used in low- and high-throughput N- and O-glycosylation analysis of Igs, with the focus on immunoglobulin G (IgG) applications. General principles and practical examples of the most often used LC methods for Ig purification are described, together with typical workflows for N- and O-glycan analysis on the level of free glycans, glycopeptides, subunits, or intact Igs. Lectin chromatography is a historical approach for the analysis of lectin-carbohydrate interactions and glycoprotein purification but is still being used as a valuable tool in Igs purification and glycan analysis. On the other hand, lectin microarrays have found their application in the rapid screening of glycan profiles on intact proteins.

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.

Glycosylation in Indolent, Significant and Aggressive Prostate Cancer by Automated High-Throughput N-Glycan Profiling

The diagnosis and treatment of prostate cancer (PCa) is a major health-care concern worldwide. This cancer can manifest itself in many distinct forms and the transition from clinically indolent PCa to the more invasive aggressive form remains poorly understood. It is now universally accepted that glycan expression patterns change with the cellular modifications that accompany the onset of tumorigenesis. The aim of this study was to investigate if differential glycosylation patterns could distinguish between indolent, significant, and aggressive PCa. Whole serum N-glycan profiling was carried out on 117 prostate cancer patients’ serum using our automated, high-throughput analysis platform for glycan-profiling which utilizes ultra-performance liquid chromatography (UPLC) to obtain high resolution separation of N-linked glycans released from the serum glycoproteins. We observed increases in hybrid, oligomannose, and biantennary digalactosylated monosialylated glycans (M5A1G1S1, M8, and A2G2S1), bisecting glycans (A2B, A2(6)BG1) and monoantennary glycans (A1), and decreases in triantennary trigalactosylated trisialylated glycans with and without core fucose (A3G3S3 and FA3G3S3) with PCa progression from indolent through significant and aggressive disease. These changes give us an insight into the disease pathogenesis and identify potential biomarkers for monitoring the PCa progression, however these need further confirmation studies.

Determination of complex type free, non-conjugated oligosaccharide glucose unit values in tomato xylem sap for early detection of nutrient deficiency

Although knowledge on glycan biosynthesis and processing is continuously maturing, there are still a limited number of studies that examine biological functions of N-glycan structures in plants, which remain virtually unknown. Here, the statistical correlation between nutrient (nitrogen) deficiency symptoms of crops and changes in 8-aminopyrene-1,3,6-trisulfonic acid (APTS)-labeled complex type free oligosaccharides is reported. While deficiency symptoms are predicted by multispectral images and Kjeldahl digestion, APTS-labeled complex type free oligosaccharides are identified by their glucose unit (GU) values in tomato xylem sap, using capillary electrophoresis with laser induced fluorescence detection (CE-LIF). Given the limited number of structures obtained from plants, archived in the literature, in the future, it is intended to create an open access database of promising indicators, namely, glycan structures that are presumably responsible for the nutrient deficiency caused stress in plants (http://glycoplants.org).

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

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

Open Database Searching Enables the Identification and Comparison of Bacterial Glycoproteomes without Defining Glycan Compositions Prior to Searching

Mass spectrometry has become an indispensable tool for the characterization of glycosylation across biological systems. Our ability to generate rich fragmentation of glycopeptides has dramatically improved over the last decade yet our informatic approaches still lag behind. Although glycoproteomic informatics approaches using glycan databases have attracted considerable attention, database independent approaches have not. This has significantly limited high throughput studies of unusual or atypical glycosylation events such as those observed in bacteria. As such, computational approaches to examine bacterial glycosylation and identify chemically diverse glycans are desperately needed. Here we describe the use of wide-tolerance (up to 2000 Da) open searching as a means to rapidly examine bacterial glycoproteomes. We benchmarked this approach using N-linked glycopeptides of Campylobacter fetus subsp. fetus as well as O-linked glycopeptides of Acinetobacter baumannii and Burkholderia cenocepacia revealing glycopeptides modified with a range of glycans can be readily identified without defining the glycan masses before database searching. Using this approach, we demonstrate how wide tolerance searching can be used to compare glycan use across bacterial species by examining the glycoproteomes of eight Burkholderia species (B. pseudomallei; B. multivorans; B. dolosa; B. humptydooensis; B. ubonensis, B. anthina; B. diffusa; B. pseudomultivorans). Finally, we demonstrate how open searching enables the identification of low frequency glycoforms based on shared modified peptides sequences. Combined, these results show that open searching is a robust computational approach for the determination of glycan diversity within bacterial proteomes.

Open Database Searching Enables the Identification and Comparison of Bacterial Glycoproteomes without Defining Glycan Compositions Prior to Searching

Mass spectrometry has become an indispensable tool for the characterization of glycosylation across biological systems. Our ability to generate rich fragmentation of glycopeptides has dramatically improved over the last decade yet our informatic approaches still lag behind. Although glycoproteomic informatics approaches using glycan databases have attracted considerable attention, database independent approaches have not. This has significantly limited high throughput studies of unusual or atypical glycosylation events such as those observed in bacteria. As such, computational approaches to examine bacterial glycosylation and identify chemically diverse glycans are desperately needed. Here we describe the use of wide-tolerance (up to 2000 Da) open searching as a means to rapidly examine bacterial glycoproteomes. We benchmarked this approach using N-linked glycopeptides of Campylobacter fetus subsp. fetus as well as O-linked glycopeptides of Acinetobacter baumannii and Burkholderia cenocepacia revealing glycopeptides modified with a range of glycans can be readily identified without defining the glycan masses before database searching. Using this approach, we demonstrate how wide tolerance searching can be used to compare glycan use across bacterial species by examining the glycoproteomes of eight Burkholderia species (B. pseudomallei; B. multivorans; B. dolosa; B. humptydooensis; B. ubonensis, B. anthina; B. diffusa; B. pseudomultivorans). Finally, we demonstrate how open searching enables the identification of low frequency glycoforms based on shared modified peptides sequences. Combined, these results show that open searching is a robust computational approach for the determination of glycan diversity within bacterial proteomes.

New Enzymatic Approach to Distinguish Fucosylation Isomers of N-Linked Glycans in Tissues Using MALDI Imaging Mass Spectrometry

Specific alterations in N-linked glycans, such as core fucosylation, are associated with many cancers and other disease states. Because of the many possible anomeric linkages associated with fucosylated N-glycans, determination of specific anomeric linkages and the site of fucosylation (i.e., core vs outer arm) can be difficult to elucidate. A new MALDI mass spectrometry imaging workflow in formalin-fixed clinical tissues is described using recombinant endoglycosidase F3 (Endo F3), an enzyme with a specific preference for cleaving core-fucosylated N-glycans attached to glycoproteins. In contrast to the broader substrate enzyme peptide-N-glycosidase F (PNGaseF), Endo F3 cleaves between the two core N-acetylglucosamine residues at the protein attachment site. On tissues, this results in a mass shift of 349.137 a.m.u. for core-fucosylated N-glycans when compared to N-glycans released with standard PNGaseF. Endo F3 can be used singly and in combination with PNGaseF digestion of the same tissue sections. Initial results in liver and prostate tissues indicate core-fucosylated glycans associated to specific tissue regions while still demonstrating a diverse mix of core- and outer arm-fucosylated glycans throughout all regions of tissue. By determining these specific linkages while preserving localization, more targeted diagnostic biomarkers for disease states are possible without the need for microdissection or solubilization of the tissue.

Discovery of Highly Active Recombinant PNGase H+ Variants Through the Rational Exploration of Unstudied Acidobacterial Genomes

Peptide-N ⁴-(N-acetyl-β-glucosaminyl) asparagine amidases (PNGases, N-glycanases, EC 3.5.1.52) are indispensable tools in releasing N-glycans from glycoproteins. So far, only a limited number of PNGase candidates are available for the structural analysis of glycoproteins and their glycan moieties. Herein, a panel of 13 novel PNGase H⁺ candidates (the suffix H⁺ refers to the acidic pH optimum of these acidobacterial PNGases) was tested in their recombinant form for their deglycosylation performance. One candidate (originating from the bacterial species Dyella japonica) showed superior properties both in solution-phase and immobilized on amino-, epoxy- and nitrilotriacetate resins when compared to currently acidic available PNGases. The high expression yield compared to a previously described PNGase H⁺, broad substrate specificity, and good storage stability of this novel N-glycanase makes it a valuable tool for the analysis of protein glycosylation.

High-Throughput Analysis of Fluorescently Labeled N-Glycans Derived from Biotherapeutics Using an Automated LC-MS-Based Solution

Protein glycosylation can impact the efficacy and safety of biotherapeutics and therefore needs to be well characterized and monitored throughout the drug product life cycle. Glycosylation is commonly assessed by fluorescent labeling of released glycans, which provides comprehensive information of the glycoprofile but can be resource-intensive regarding sample preparation, data acquisition, and data analysis. In this work, we evaluate a comprehensive solution from sample preparation to data reporting using a liquid chromatography–mass spectrometry (LC-MS)-based analytical platform for increased productivity in released glycan analysis. To minimize user intervention and improve assay robustness, a robotic liquid handling platform was used to automate the release and labeling of N-glycans within 2 h. To further increase the throughput, a 5 min method was developed on a liquid chromatography–fluorescence–mass spectrometry (LC-FLR-MS) system using an integrated glycan library based on retention time and accurate mass. The optimized method was then applied to 48 released glycan samples derived from six batches of infliximab to mimic comparability testing encountered in the development of biopharmaceuticals. Consistent relative abundance of critical species such as high mannose and sialylated glycans was obtained for samples within the same batch (mean percent relative standard deviation [RSD] = 5.3%) with data being acquired, processed, and reported in an automated manner. The data acquisition and analysis of the 48 samples were completed within 6 h, which represents a 90% improvement in throughput compared with conventional LC-FLR-based methods. Together, this workflow facilitates the rapid screening of glycans, which can be deployed at various stages of drug development such as process optimization, bioreactor monitoring, and clone selections, where high-throughput and improved productivity are particularly desired.

Expanding the capillary electrophoresis-based glucose unit database of the GUcal app

GUcal is a standalone application for automatically calculating the glucose unit (GU) values for separated N-glycan components of interest in an electropherogram and suggests their tentative structures by utilizing an internal database. We have expanded the original database of GUcal by integrating all publicly available capillary electrophoresis (CE) data in the GlycoStore collection (https://www.glycostore.org) and with in-house measured GU values. The GUcal app is freely available online (https://www.gucal.hu) and readily facilitates CE-based high throughput GU value determination for first line structural elucidation.

Glycosylation Heterogeneity of Hyperglycosylated Recombinant Human Interferon-β (rhIFN-β)

We previously developed a biobetter version of rhIFN-β (R27T) that possesses an additional glycosylation site compared with rhIFN-β 1a. Herein, we characterized N-glycosylation heterogeneity of R27T, which includes both N-glycan site occupancy heterogeneity (macro-heterogeneity) and complexity of carbohydrate moieties (micro-heterogeneity). N-glycan site occupancy manifested as distinct differences in size and isoelectric point. The analysis of complex carbohydrate moieties of R27T involved the common biopharmaceutical glycosylation critical quality attributes such as core fucosylation, antennary composition, sialylation, N-acetyllactosamine extensions, linkages, and overall glycan profiles using weak anion-exchange and hydrophilic interaction high-performance liquid chromatography with 2-aminobenzoic acid-labeled N-glycans. The double-glycosylated form accounted for approx. 94% R27T, while the single-glycosylated form accounted for 6% R27T. N-glycans consisted of a mixture of bi-, tri-, and tetra-antennary glycans, some with N-acetyllactosamine extensions, but neither outer arm fucose nor α-galactose was detected. Sialic acid major variants, N-acetyl- and N-glycolyl-neuraminic acid, were more abundant in R27T than in Rebif. The major N-glycan, accounting for ∼42% of total N-glycans, had a di-sialylated, core-fucosylated bi-antennary structure.

N-Glycan Analysis by Ultra-Performance Liquid Chromatography and Capillary Gel Electrophoresis with Fluorescent Labeling

Glycans are a class of macromolecules essential for all forms of life. They embellish various proteins and other macromolecules in organisms and are responsible for their proper functioning. Because their complex structure is determined by genetic and environmental factors, analysis of such molecules is rather demanding. Liquid chromatography (high-performance and ultra-performance, HPLC and UPLC, respectively) analysis has been used for the purpose of glycoprofiling for years and it is a well-established method regarding its robustness, reproducibility, and high throughput. Another orthogonal method that is now used in glycoprofiling is capillary gel electrophoresis (CGE) because it offers powerful separation and distinct sensitivity. The purpose of the following protocols is to present all steps required for release and fluorescent labeling of total N-glycans from blood plasma/serum or isolated glycoprotein (for example, IgG) and their subsequent UPLC or CGE analysis. © 2019 by John Wiley & Sons, Inc.

Mass spectrometry hybridized with gas-phase InfraRed spectroscopy for glycan sequencing

Precise structural differentiation of often isomeric glycans is important given their roles in numerous biological processes. Mass spectrometry (MS) (and tandem MS) is one of the analytical techniques at the forefront of glycan analysis given its speed, sensitivity in producing structural information as well as the fact it can be coupled to other orthogonal analytical techniques such as liquid chromatography (LC) and ion mobility spectrometry (IMS). This review describes another family of techniques that are more commonly being hybridized to MS(/MS) namely gas-phase infrared (IR) spectroscopy, whose rise is in part due to the development and improved accessibility of tunable IR lasers. Gas-phase IR can often differentiate fine isomeric differences ubiquitous within carbohydrates that MS may be 'blind' to. There are also examples of cryogenic gas-phase IR spectroscopy with much greater spectral resolution as well as hybridizing with separative methods (LC, IMS). Furthermore, collision-induced dissociation (CID) product ions can also be probed by IR, which may be beneficial to deconvolute spectra, aid analysis and build spectral libraries, thus generating novel opportunities for fragment-based approaches to analyze glycans.

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.

Intense Physical Exercise Induces an Anti-inflammatory Change in IgG N-Glycosylation Profile

Exercise is known to improve many aspects of human health, including modulation of the immune system and inflammatory status. It is generally understood that exercise reduces inflammation, but there are missing links in terms of understanding the mechanisms as well as the differences between exercise modalities. N-glycosylation of immunoglobulin G (IgG) and total plasma proteins was previously shown to reflect changes in inflammatory pathways, which could provide valuable information to further clarify exercise effects. In order to further expand the understanding of the relationship between physical activity and inflammation, we examined the effect of intense exercise, in the form of repeated sprint training (RST), on IgG and total plasma proteins N-glycosylation in combination with traditionally used inflammation markers: C-reactive protein (CRP), interleukin 6 (IL-6), and leukocyte count. Twenty-nine male physical education students were separated into treatment (RST, N = 15) and control (N = 14) groups. The RST group completed a 6-week exercise protocol while the control group was instructed to refrain from organized physical activity for the duration of the study. Three blood samples were taken at different time points: prior to start of the training program, the final week of the exercise intervention (EXC), and at the end of the 4-week recovery period (REC). Following the end of the recovery period IgG N-glycosylation profiles showed anti-inflammatory changes in RST group compared to the control group, which manifested as a decrease in agalactosylated (p = 0.0473) and an increase in digalactosylated (p = 0.0473), and monosialylated (p = 0.0339) N-glycans. Plasma protein N-glycans didn’t change significantly, while traditional inflammatory markers also didn’t show significant change in inflammatory status. Observed results demonstrate the potential of intense physical exercise to reduce levels of systemic basal inflammation as well as the potential for IgG N-glycosylation to serve as a sensitive longitudinal systemic inflammation marker.