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

Enrichment methods of N-linked glycopeptides from human serum or plasma: A mini-review

Human diseases often correlate with changes in protein glycosylation, which can be observed in serum or plasma samples. N-glycosylation, the most common form, can provide potential biomarkers for disease prognosis and diagnosis. However, glycoproteins constitute a relatively small proportion of the total proteins in human serum and plasma compared to the non-glycosylated protein albumin, which constitutes the majority. The detection of microheterogeneity and low glycan abundance presents a challenge. Mass spectrometry facilitates glycoproteomics research, yet it faces challenges due to interference from abundant plasma proteins. Therefore, methods have emerged to enrich N-glycans and N-linked glycopeptides using glycan affinity, chemical properties, stationary phase chemical coupling, bioorthogonal techniques, and other alternatives. This review focuses on N-glycans and N-glycopeptides enrichment in human serum or plasma, emphasizing methods and applications. Although not exhaustive, it aims to elucidate principles and showcase the utility and limitations of glycoproteome characterization.

Carbohydrate flow through agricultural ecosystems: Implications for synthesis and microbial conversion of carbohydrates

Carbohydrates are chemically and structurally diverse biomolecules, serving numerous and varied roles in agricultural ecosystems. Crops and horticulture products are inherent sources of carbohydrates that are consumed by humans and non-human animals alike; however carbohydrates are also present in other agricultural materials, such as soil and compost, human and animal tissues, milk and dairy products, and honey. The biosynthesis, modification, and flow of carbohydrates within and between agricultural ecosystems is intimately related with microbial communities that colonize and thrive within these environments. Recent advances in -omics techniques have ushered in a new era for microbial ecology by illuminating the functional potential for carbohydrate metabolism encoded within microbial genomes, while agricultural glycomics is providing fresh perspective on carbohydrate-microbe interactions and how they influence the flow of functionalized carbon. Indeed, carbohydrates and carbohydrate-active enzymes are interventions with unrealized potential for improving carbon sequestration, soil fertility and stability, developing alternatives to antimicrobials, and circular production systems. In this manner, glycomics represents a new frontier for carbohydrate-based biotechnological solutions for agricultural systems facing escalating challenges, such as the changing climate.

Mouse brain glycomics - Insights from exploring the Allen Brain Atlas and the implications for the neuroimmune brain

The Allen Institute Mouse Brain Atlas, with visualisation using the Brain Explorer software, offers a 3-dimensional view of region-specific RNA expression of thousands of mouse genes. In this Viewpoint, we focused on the region-specific expression of genes related to cellular glycosylation, and discuss their relevance towards psychoneuroimmunology. Using specific examples, we show that the Atlas validates existing observations reported by others, identifies previously unknown potential region-specific glycan features, and highlights the need to promote collaborations between glycobiology and psychoneuroimmunology researchers.

Dessert or Poison? The Roles of Glycosylation in Alzheimer's, Parkinson's, Huntington's Disease, and Amyotrophic Lateral Sclerosis

Ministry of Education and Key Laboratory of Neurons and glial cells of the central nervous system (CNS) are modified by glycosylation and rely on glycosylation to achieve normal neural function. Neurodegenerative disease is a common disease of the elderly, affecting their healthy life span and quality of life, and no effective treatment is currently available. Recent research implies that various glycosylation traits are altered during neurodegenerative diseases, suggesting a potential implication of glycosylation in disease pathology. Herein, we summarized the current knowledge about glycosylation associated with Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and Amyotrophic lateral sclerosis (ALS) pathogenesis, focusing on their promising functional avenues. Moreover, we collected research aimed at highlighting the need for such studies to provide a wealth of disease-related glycosylation information that will help us better understand the pathophysiological mechanisms and hopefully specific glycosylation information to provide further diagnostic and therapeutic directions for neurodegenerative diseases.

Innovative Metrics for Reporting and Comparing the Glycan Structural Profile in Biotherapeutics

Glycosylation is a critical quality attribute in biotherapeutics, impacting properties such as protein stability, solubility, clearance rate, efficacy, immunogenicity, and safety. Due to the heterogenic and complex nature of protein glycosylation, comprehensive characterization is demanding. Moreover, the lack of standardized metrics for evaluating and comparing glycosylation profiles hinders comparability studies and the establishment of manufacturing control strategies. To address both challenges, we propose a standardized approach based on novel metrics for a comprehensive glycosylation fingerprint which greatly facilitates the reporting and objective comparison of glycosylation profiles. The analytical workflow is based on a liquid chromatography-mass spectrometry-based multi-attribute method. Based on the analytical data, a matrix of glycosylation-related quality attributes, both at site-specific and whole molecule level, are computed, which provide metrics for a comprehensive product glycosylation fingerprint. Two case studies illustrate the applicability of the proposed indices as a standardized and versatile approach for reporting all dimensions of the glycosylation profile. The proposed approach further facilitates the assessments of risks associated with changes in the glycosylation profile that may affect efficacy, clearance, and immunogenicity.

MS-based glycomics and glycoproteomics methods enabling isomeric characterization

Glycosylation is one of the most significant and abundant posttranslational modifications in mammalian cells. It mediates a wide range of biofunctions, including cell adhesion, cell communication, immune cell trafficking, and protein stability. Also, aberrant glycosylation has been associated with various diseases such as diabetes, Alzheimer's disease, inflammation, immune deficiencies, congenital disorders, and cancers. The alterations in the distributions of glycan and glycopeptide isomers are involved in the development and progression of several human diseases. However, the microheterogeneity of glycosylation brings a great challenge to glycomic and glycoproteomic analysis, including the characterization of isomers. Over several decades, different methods and approaches have been developed to facilitate the characterization of glycan and glycopeptide isomers. Mass spectrometry (MS) has been a powerful tool utilized for glycomic and glycoproteomic isomeric analysis due to its high sensitivity and rich structural information using different fragmentation techniques. However, a comprehensive characterization of glycan and glycopeptide isomers remains a challenge when utilizing MS alone. Therefore, various separation methods, including liquid chromatography, capillary electrophoresis, and ion mobility, were developed to resolve glycan and glycopeptide isomers before MS. These separation techniques were coupled to MS for a better identification and quantitation of glycan and glycopeptide isomers. Additionally, bioinformatic tools are essential for the automated processing of glycan and glycopeptide isomeric data to facilitate isomeric studies in biological cohorts. Here in this review, we discuss commonly employed MS-based techniques, separation hyphenated MS methods, and software, facilitating the separation, identification, and quantitation of glycan and glycopeptide isomers.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2017-2018

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization mass spectrometry (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2018. Also included are papers that describe methods appropriate to glycan and glycoprotein analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. Topics covered in the first part of the review include general aspects such as theory of the MALDI process, new methods, matrices, derivatization, MALDI imaging, fragmentation and the use of arrays. The second part of the review is devoted to applications to various structural types such as oligo- and poly-saccharides, glycoproteins, glycolipids, glycosides, and biopharmaceuticals. Most of the applications are presented in tabular form. The third part of the review covers medical and industrial applications of the technique, studies of enzyme reactions, and applications to chemical synthesis. The reported work shows increasing use of combined new techniques such as ion mobility and highlights the impact that MALDI imaging is having across a range of diciplines. MALDI is still an ideal technique for carbohydrate analysis and advancements in the technique and the range of applications continue steady progress.

Glycosylation and the global virome

The sugars that coat the outsides of viruses and host cells are key to successful disease transmission, but they remain understudied compared to other molecular features. Understanding the comparative zoology of glycosylation - and harnessing it for predictive science - could help close the molecular gap in zoonotic risk assessment.

MS-based glycomics: An analytical tool to assess nervous system diseases

Neurological diseases affect millions of peopleochemistryorldwide and are continuously increasing due to the globe's aging population. Such diseases affect the nervous system and are characterized by a progressive decline in brain function and progressive cognitive impairment, decreasing the quality of life for those with the disease as well as for their families and loved ones. The increased burden of nervous system diseases demands a deeper insight into the biomolecular mechanisms at work during disease development in order to improve clinical diagnosis and drug design. Recently, evidence has related glycosylation to nervous system diseases. Glycosylation is a vital post-translational modification that mediates many biological functions, and aberrant glycosylation has been associated with a variety of diseases. Thus, the investigation of glycosylation in neurological diseases could provide novel biomarkers and information for disease pathology. During the last decades, many techniques have been developed for facilitation of reliable and efficient glycomic analysis. Among these, mass spectrometry (MS) is considered the most powerful tool for glycan analysis due to its high resolution, high sensitivity, and the ability to acquire adequate structural information for glycan identification. Along with MS, a variety of approaches and strategies are employed to enhance the MS-based identification and quantitation of glycans in neurological samples. Here, we review the advanced glycomic tools used in nervous system disease studies, including separation techniques prior to MS, fragmentation techniques in MS, and corresponding strategies. The glycan markers in common clinical nervous system diseases discovered by utilizing such MS-based glycomic tools are also summarized and discussed.

N-Glycan Isomer Differentiation by Zero Flow Capillary Electrophoresis Coupled to Mass Spectrometry

Isomeric N-glycans often vastly differ in their biological activities, hence the need for methods that allow resolving and structurally characterizing them in biological material. Here, we established a zero flow approach using capillary electrophoresis in combination with (tandem) mass spectrometry to allow structural characterization of isomeric N-glycans at high sensitivity. Additionally, diagnostic fragment ion ratios were identified, indicative for the antenna carrying specifically linked sialic acids. In total, 208 N-glycans were characterized in human plasma, with 57 compositions showing multiple isomers.

Mass spectrometry based biomarkers for early detection of HCC using a glycoproteomic approach

Hepatocellular carcinoma (HCC) is the fourth most common cause of cancer-related mortality worldwide and 80%-90% of HCC develops in patients that have underlying cirrhosis. Better methods of surveillance are needed to increase early detection of HCC and the proportion of patients that can be offered curative therapies. Recent work in novel mass spec-based methods for glycomic and glycopeptide analysis for discovery and confirmation of markers for early detection of HCC versus cirrhosis is reviewed in this chapter. Results from recent work in these fields by several groups and the progress made in developing markers of early HCC which can outperform the current serum-based markers are described and discussed. Also, recent developments in isoform analysis of glycans and glycopeptides and in various mass spec fragmentation methods will be described and discussed.

Serum N-glycomic profiling may provide potential signatures for surveillance of COVID-19

Disease development and progression are often associated with aberrant glycosylation, indicating that changes in biological fluid glycome may potentially serve as disease signatures. The corona virus disease-2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) represents a significant threat to global human health. However, the effect of SARS-CoV-2 infection on the overall serum N-glycomic profile has been largely unexplored. Here, we extended our 96-well-plate-based high-throughput, high-sensitivity N-glycan profiling platform further with the aim of elucidating potential COVID-19-associated serum N-glycomic alterations. Use of this platform revealed both similarities and differences between the serum N-glycomic fingerprints of COVID-19 positive and control cohorts. Although there were no specific glycan peaks exclusively present or absent in COVID-19 positive cohort, this cohort showed significantly higher levels of glycans and variability. On the contrary, the overall N-glycomic profiles for healthy controls were well-contained within a narrow range. From the serum glycomic analysis, we were able to deduce changes in different glycan subclasses sharing certain structural features. Of significance was the hyperbranched and hypersialylated glycans and their derived glycan subclass traits. T-distributed stochastic neighbour embedding (tSNE) and hierarchical heatmap clustering analysis were performed to identify 13 serum glycomic variables that potentially distinguished the COVID-19 positive from healthy controls. Such serum N-glycomic changes described herein may indicate or correlate to the changes in serum glycoproteins upon COVID-19 infection. Furthermore, mapping the serum N-glycome following SARS-CoV-2 infection may help us better understand the disease and enable "Long-COVID" surveillance to capture the full spectrum of persistent symptoms.

Construction of InstantPC derivatized glycan GU database: A foundation work for high-throughput and high-sensitivity glycomic analysis

Glycosylation is well-recognized as a critical quality attribute of biotherapeutics being routinely monitored to ensure desired product quality, safety, and efficacy. Additionally, as one of the most prominent and complex post-translational modifications, glycosylation plays a key role in disease manifestation. Changes in glycosylation may serve as a specific and sensitive biomarker for disease diagnostics and prognostics. However, the conventional 2-aminobenzamide based N-glycosylation analysis procedure is time-consuming and insensitive, with poor reproducibility. We have evaluated an innovative streamlined 96-well-plate-based platform utilizing InstantPC label for high-throughput, high-sensitivity glycan profiling, which is user-friendly, robust, and ready for automation. However, the limited availability of InstantPC labelled glycan standards has significantly hampered the applicability and transferability of this platform for expedited glycan structural profiling. To address this challenge, we have constructed a detailed InstantPC labelled glycan glucose unit database through analysis of human serum and a variety of other glycoproteins from various sources. Following preliminary hydrophilic interaction liquid chromatography with fluorescence detection separation and analysis, glycoproteins with complex glycan profiles were subjected to further fractionation by weak anion exchange hydrophilic interaction liquid chromatography and exoglycosidase sequential digestion for cross-validation of the glycan assignment. Hydrophilic interaction ultra-performance liquid chromatography coupled with electrospray ionization mass spectrometry was subsequently utilised for glycan fragmentation and accurate glycan mass confirmation. The constructed InstantPC glycan GU database is accurate and robust. It is believed that this database will enhance the application of the developed platform for high-throughput, high-sensitivity glycan profiling, and eventually advance glycan-based biopharmaceutical production and disease biomarker discovery.

Advances in mass spectrometry-based glycoproteomics: An update covering the period 2017-2021

Protein glycosylation is one of the most common posttranslational modifications, and plays an essential role in a wide range of biological processes such as immune response, intercellular signaling, inflammation, host-pathogen interaction, and protein stability. Glycoproteomics is a proteomics subfield dedicated to identifying and characterizing the glycans and glycoproteins in a given cell or tissue. Aberrant glycosylation has been associated with various diseases such as Alzheimer's disease, viral infections, inflammation, immune deficiencies, congenital disorders, and cancers. However, glycoproteomic analysis remains challenging because of the low abundance, site-specific heterogeneity, and poor ionization efficiency of glycopeptides during LC-MS analyses. Therefore, the development of sensitive and accurate approaches to efficiently characterize protein glycosylation is crucial. Methods such as metabolic labeling, enrichment, and derivatization of glycopeptides, coupled with different mass spectrometry techniques and bioinformatics tools, have been developed to achieve sophisticated levels of quantitative and qualitative analyses of glycoproteins. This review attempts to update the recent developments in the field of glycoproteomics reported between 2017 and 2021.

The Hitchhiker's guide to glycoproteomics

Protein glycosylation is one of the most common post-translational modifications that are essential for cell function across all domains of life. Changes in glycosylation are considered a hallmark of many diseases, thus making glycoproteins important diagnostic and prognostic biomarker candidates and therapeutic targets. Glycoproteomics, the study of glycans and their carrier proteins in a system-wide context, is becoming a powerful tool in glycobiology that enables the functional analysis of protein glycosylation. This 'Hitchhiker's guide to glycoproteomics' is intended as a starting point for anyone who wants to explore the emerging world of glycoproteomics. The review moves from the techniques that have been developed for the characterisation of single glycoproteins to technologies that may be used for a successful complex glycoproteome characterisation. Examples of the variety of approaches, methodologies, and technologies currently used in the field are given. This review introduces the common strategies to capture glycoprotein-specific and system-wide glycoproteome data from tissues, body fluids, or cells, and a perspective on how integration into a multi-omics workflow enables a deep identification and characterisation of glycoproteins - a class of biomolecules essential in regulating cell function.

Peptide Sequence Mapping around Bisecting GlcNAc-Bearing N-Glycans in Mouse Brain

N-glycosylation is essential for many biological processes in mammals. A variety of N-glycan structures exist, of which, the formation of bisecting N-acetylglucosamine (GlcNAc) is catalyzed by N-acetylglucosaminyltransferase-III (GnT-III, encoded by the Mgat3 gene). We previously identified various bisecting GlcNAc-modified proteins involved in Alzheimer's disease and cancer. However, the mechanisms by which GnT-III acts on the target proteins are unknown. Here, we performed comparative glycoproteomic analyses using brain membranes of wild type (WT) and Mgat3-deficient mice. Target glycoproteins of GnT-III were enriched with E4-phytohemagglutinin (PHA) lectin, which recognizes bisecting GlcNAc, and analyzed by liquid chromatograph-mass spectrometry. We identified 32 N-glycosylation sites (Asn-Xaa-Ser/Thr, Xaa ≠ Pro) that were modified with bisecting GlcNAc. Sequence alignment of identified N-glycosylation sites that displayed bisecting GlcNAc suggested that GnT-III does not recognize a specific primary amino acid sequence. The molecular modeling of GluA1 as one of the good cell surface substrates for GnT-III in the brain, indicated that GnT-III acts on N-glycosylation sites located in a highly flexible and mobile loop of GluA1. These results suggest that the action of GnT-III is partially affected by the tertiary structure of target proteins, which can accommodate bisecting GlcNAc that generates a bulky flipped-back conformation of the modified glycans.

A General New Method for Calculating the Molecular Nonpolar Surface for Analysis of LC-MS Data

The accurate determination of the nonpolar surface area of glycans is vital when utilizing liquid chromatograph/mass spectrometry (LC-MS) for structural characterization. A new approach for defining and computing nonpolar surface areas based on continuum solvation models (CS-NPSA) is presented. It is based on the classification of individual surface elements representing the solvent accessible surface used for the description of the polarized charge density elements in the CS models. Each element can be classified as polar or nonpolar according to a threshold value. The summation of the nonpolar elements then results in the NPSA resulting in a very fine resolution of this surface. The further advantage of the CS-NPSA approach is the straightforward connection to standard quantum chemical methods and program packages. The method has been analyzed in terms of the contributions of different atoms to the NPSA. The analysis showed that not only atoms normally classified as nonpolar contributed to the NPSA, but at least partially also atoms next to polar atoms or N atoms. By virtue of the construction of the solvent accessible surface, atoms in the inner regions of a molecule can be automatically identified as not contributing to the NPSA. The method has been applied to a variety of examples such as the phenylbutanehydrazide series, model dextrans consisting of glucose units and biantennary glycans. Linear correlation of the CS-NPSA values with retention times obtained from liquid chromatographic separations measurements in the mentioned cases give excellent results and promise for more extended applications on a larger variety of compounds.

Glycoproteins as diagnostic and prognostic biomarkers for neurodegenerative diseases: A glycoproteomic approach

Neurodegenerative diseases (NDs) are incurable and can develop progressively debilitating disorders, including dementia and ataxias. Alzheimer's disease and Parkinson's disease are the most common NDs that mainly affect the elderly people. There is an urgent need to develop new diagnostic tools so that patients can be accurately stratified at an early stage. As a common post-translational modification, protein glycosylation plays a key role in physiological and pathological processes. The abnormal changes in glycosylation are associated with the altered biological pathways in NDs. The pathogenesis-related proteins, like amyloid-β and microtubule-associated protein tau, have altered glycosylation. Importantly, specific glycosylation changes in cerebrospinal fluid, blood and urine are valuable for revealing neurodegeneration in the early stages. This review describes the emerging biomarkers based on glycoproteomics in NDs, highlighting the potential applications of glycoprotein biomarkers in the early detection of diseases, monitoring of the disease progression, and measurement of the therapeutic responses. The mass spectrometry-based strategies for characterizing glycoprotein biomarkers are also introduced.

Glycoproteogenomics: Setting the Course for Next-generation Cancer Neoantigen Discovery for Cancer Vaccines

Molecular-assisted precision oncology gained tremendous ground with high-throughput next-generation sequencing (NGS), supported by robust bioinformatics. The quest for genomics-based cancer medicine set the foundations for improved patient stratification, while unveiling a wide array of neoantigens for immunotherapy. Upfront pre-clinical and clinical studies have successfully used tumor-specific peptides in vaccines with minimal off-target effects. However, the low mutational burden presented by many lesions challenges the generalization of these solutions, requiring the diversification of neoantigen sources. Oncoproteogenomics utilizing customized databases for protein annotation by mass spectrometry (MS) is a powerful tool toward this end. Expanding the concept toward exploring proteoforms originated from post-translational modifications (PTMs) will be decisive to improve molecular subtyping and provide potentially targetable functional nodes with increased cancer specificity. Walking through the path of systems biology, we highlight that alterations in protein glycosylation at the cell surface not only have functional impact on cancer progression and dissemination but also originate unique molecular fingerprints for targeted therapeutics. Moreover, we discuss the outstanding challenges required to accommodate glycoproteomics in oncoproteogenomics platforms. We envisage that such rationale may flag a rather neglected research field, generating novel paradigms for precision oncology and immunotherapy.

State-of-the-Art Glycomics Technologies in Glycobiotechnology

Glycosylation affects the properties of biologics; thus regulatory bodies classified it as critical quality attribute and force biopharma industry to capture and control it throughout all phases, from R&D till end of product lifetime. The shift from originators to biosimilars further increases importance and extent of glycoanalysis, which thus increases the need for technology platforms enabling reliable high-throughput and in-depth glycan analysis. In this chapter, we will first summarize on established glycoanalytical methods based on liquid chromatography focusing on hydrophilic interaction chromatography, capillary electrophoresis focusing on multiplexed capillary gel electrophoresis, and mass spectrometry focusing on matrix-assisted laser desorption; we will then highlight two emerging technologies based on porous graphitized carbon liquid chromatography and on ion-mobility mass spectrometry as both are highly promising tools to deliver an additional level of information for in-depth glycan analysis; additionally we elaborate on the advantages and challenges of different glycoanalytical technologies and their complementarity; finally, we briefly review applications thereof to biopharmaceutical products. This chapter provides an overview of current state-of-the-art analytical approaches for glycan characterization of biopharmaceuticals that can be employed to capture glycoprotein heterogeneity in a biopharmaceutical context.

Omics Biomarkers in Obesity: Novel Etiological Insights and Targets for Precision Prevention

PURPOSE OF REVIEW

Omics-based technologies were suggested to provide an advanced understanding of obesity etiology and its metabolic consequences. This review highlights the recent developments in "omics"-based research aimed to identify obesity-related biomarkers.

RECENT FINDINGS

Recent advances in obesity and metabolism research increasingly rely on new technologies to identify mechanisms in the development of obesity using various "omics" platforms. Genetic and epigenetic biomarkers that translate into changes in transcriptome, proteome, and metabolome could serve as targets for obesity prevention. Despite a number of promising candidate biomarkers, there is an increased demand for larger prospective cohort studies to validate findings and determine biomarker reproducibility before they can find applications in primary care and public health. "Omics" biomarkers have advanced our knowledge on the etiology of obesity and its links with chronic diseases. They bring substantial promise in identifying effective public health strategies that pave the way towards patient stratification and precision prevention.

Harnessing the potential of artificial neural networks for predicting protein glycosylation

Kinetic models offer incomparable insight on cellular mechanisms controlling protein glycosylation. However, their ability to reproduce site-specific glycoform distributions depends on accurate estimation of a large number of protein-specific kinetic parameters and prior knowledge of enzyme and transport protein levels in the Golgi membrane. Herein we propose an artificial neural network (ANN) for protein glycosylation and apply this to four recombinant glycoproteins produced in Chinese hamster ovary (CHO) cells, two monoclonal antibodies and two fusion proteins. We demonstrate that the ANN model accurately predicts site-specific glycoform distributions of up to eighteen glycan species with an average absolute error of 1.1%, correctly reproducing the effect of metabolic perturbations as part of a hybrid, kinetic/ANN, glycosylation model (HyGlycoM), as well as the impact of manganese supplementation and glycosyltransferase knock out experiments as a stand-alone machine learning algorithm. These results showcase the potential of machine learning and hybrid approaches for rapidly developing performance-driven models of protein glycosylation.

Finding the Keys to the CAR: Identifying Novel Target Antigens for T Cell Redirection Immunotherapies

Oncology immunotherapy has been a significant advancement in cancer treatment and involves harnessing and redirecting a patient’s immune response towards their own tumour. Specific recognition and elimination of tumour cells was first proposed over a century ago with Paul Erlich’s ‘magic bullet’ theory of therapy. In the past decades, targeting cancer antigens by redirecting T cells with antibodies using either bispecific T cell engagers (BiTEs) or chimeric antigen receptor (CAR) T cell therapy has achieved impressive clinical responses. Despite recent successes in haematological cancers, linked to a high and uniformly expressed CD19 antigen, the efficacy of T cell therapies in solid cancers has been disappointing, in part due to antigen escape. Targeting heterogeneous solid tumours with T cell therapies will require the identification of novel tumour specific targets. These targets can be found among a range of cell-surface expressed antigens, including proteins, glycolipids or carbohydrates. In this review, we will introduce the current tumour target antigen classification, outline existing approaches to discover novel tumour target antigens and discuss considerations for future design of antibodies with a focus on their use in CAR T cells.

N-glycome signatures in human plasma: associations with physiology and major diseases

N-glycome analysis in total plasma or serum yields information about the levels and glycosylation patterns of major plasma glycoproteins, including immunoglobulins, acute-phase proteins, and apolipoproteins. Until recently, glycomic studies in disease settings largely suffered from small cohort sizes, poor analytical resolution, and poor comparability of results owing to the diversity of analytical techniques. Here, we report on recent advances in high-throughput mass spectrometry glycomics technology that enabled elucidation of N-glycome signatures in the plasma of patients with type 2 diabetes, inflammatory bowel disease, or colorectal cancer. Use of this technology revealed both commonalities and differences among disease fingerprints. Moreover, we summarize findings on glycomic signatures associated with age, sex, and body mass index. High-throughput, high-resolution glycomics technologies, together with robust data analysis workflows, will advance clinical translation.

Glycans in drug discovery

Glycans are key players in many biological processes. They are essential for protein folding and stability and act as recognition elements in cell-cell and cell-matrix interactions. Thus, being at the heart of medically relevant biological processes, glycans have come onto the scene and are considered hot spots for biomedical intervention. The progress in biophysical techniques allowing access to an increasing molecular and structural understanding of these processes has led to the development of effective therapeutics. Indeed, strategies aimed at designing glycomimetics able to block specific lectin-carbohydrate interactions, carbohydrate-based vaccines mimicking self- and non-self-antigens as well as the exploitation of the therapeutic potential of glycosylated antibodies are being pursued. In this mini-review the most prominent contributions concerning recurrent diseases are highlighted, including bacterial and viral infections, cancer or immune-related pathologies, which certainly show the great promise of carbohydrates in drug discovery.

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

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

Characterization of glycan isomers using magnetic carbon nanoparticles as a MALDI co-matrix

Matrix-assisted laser desorption ionization-in source decay (MALDI-ISD) analysis is a useful technique in the structural analysis of glycans. Our recent publication demonstrated that magnetic carbon nanoparticles (MCNPs), used as a MALDI co-matrix, significantly enhanced ISD efficiency for glycomic analysis by MALDI-TOF. In this study, MCNPs were used for the structural study of isomeric glycans. Results from the standard glycans confirmed easy distinction of positional and linkage isomers without the need for further derivatization of glycan molecules. Extensive glycosidic and cross-ring fragmented ions provided different fragment patterns for various glycan isomers. Core- and branch-fucosylated isomers were distinguished by several unique ions, and pseudo-MS³ data were used to recognize the fucosylated branch. Although no diagnostic fragment ion was observed for 2,3- and 2,6-linked sialic acid isomers, their MALDI-ISD patterns were found to be significantly different (P < 0.05). Furthermore, the method introduced in this study could not only be used for the identification of glycan isomers but has also proved effective for the isomeric structural confirmation of gangliosides. GD1a and GD1b gangliosides were easily distinguished by the diagnostic ion originated from GD1a, produced by Z_4αZ_2β cleavages. Moreover, liquid chromatography coupled with MALDI-TOF was applied to analyze N-glycan isomers derived from a pooled human blood serum sample, providing an alternative method of isomeric glycomic analysis of biological specimens.

Magnetic carbon nanoparticles as a MALDI co-matrix enable isomeric characterization of glycans in biological samples.

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

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

Understanding cellular glycan surfaces in the central nervous system

Glycosylation, the enzymatic process by which glycans are attached to proteins and lipids, is the most abundant and functionally important type of post-translational modification associated with brain development, neurodegenerative disorders, psychopathologies and brain cancers. Glycan structures are diverse and complex; however, they have been detected and targeted in the central nervous system (CNS) by various immunohistochemical detection methods using glycan-binding proteins such as anti-glycan antibodies or lectins and/or characterized with analytical techniques such as chromatography and mass spectrometry. The glycan structures on glycoproteins and glycolipids expressed in neural stem cells play key roles in neural development, biological processes and CNS maintenance, such as cell adhesion, signal transduction, molecular trafficking and differentiation. This brief review will highlight some of the important findings on differential glycan expression across stages of CNS cell differentiation and in pathological disorders and diseases such as Alzheimer's disease, Parkinson's disease, Huntington's disease, multiple sclerosis, amyotrophic lateral sclerosis, schizophrenia and brain cancer.

Clinical application of quantitative glycomics

INTRODUCTION

Aberrant glycosylation has been associated with many diseases. Decades of research activities have reported many reliable glycan biomarkers of different diseases which enable effective disease diagnostics and prognostics. However, none of the glycan markers have been approved for clinical diagnosis. Thus, a review of these studies is needed to guide the successful clinical translation. Area covered: In this review, we describe and discuss advances in analytical methods enabling clinical glycan biomarker discovery, focusing only on studies of released glycans. This review also summarizes the different glycobiomarkers identified for cancers, Alzheimer's disease, diabetes, hepatitis B and C, and other diseases. Expert commentary: Along with the development of techniques in quantitative glycomics, more glycans or glycan patterns have been reported as better potential biomarkers of different diseases and proved to have greater diagnostic/diagnostic sensitivity and specificity than existing markers. However, to successfully apply glycan markers in clinical diagnosis, more studies and verifications on large biological cohorts need to be performed. In addition, faster and more efficient glycomic strategies need to be developed to shorten the turnaround time. Thus, glycan biomarkers have an immense chance to be used in clinical prognosis and diagnosis of many diseases in the near future.