CSF N-Glycomics Using High-Throughput UPLC-ESI Techniques in Alzheimer's Disease.

In this chapter, we will present a high-throughput method applied in our laboratory for the structural elucidation of the cerebrospinal fluid (CSF) N-glycome. This methodology is based on a commercial equipment developed by WATERS™ to speed up N-deglycosylation and N-glycan labeling of glycoproteins of pharmaceutical and biological interest such as monoclonal antibodies. This analytical kit is sold under the trade name of RapiFluor-MS (RFMS). We have slightly modified the methodology, increasing the glycosylation time and using a high-resolution mass analyzer for the analysis of CSF N-glycans, thus obtaining a high-throughput method (up to 96 samples simultaneously), mass accuracy better than 5 ppm, and the ability to separate and identify isomers.

CSF N-Glycomics Using MALDI MS Techniques.

In this chapter, we will present the methodology currently applied in our laboratory for the structural elucidation of the cerebrospinal fluid (CSF) N-glycome. N-glycans are released from denatured carboxymethylated glycoproteins by digestion with peptide-N-glycosidase F (PNGase F) and purified using both C18 Sep-Pak® and porous graphitized carbon (PGC) HyperSep™ Hypercarb™ solid phase extraction (SPE) cartridges. The glycan pool is subsequently permethylated to increase mass spectrometry sensitivity. Molecular assignments are performed through matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI TOF MS) analysis considering either the protein N-linked glycosylation pathway or MALDI TOF MS/MS data. Each stage has been optimized to obtain high-quality mass spectra in reflector mode with an optimal signal-to-noise ratio up to m/z 4800. This method has been successfully adopted to associate specific N-glycome profiles to the early and the advanced phases of Alzheimer's disease (AD).

Analysis of Native and Permethylated N-Glycan Isomers Using MGC-LC-MS Techniques.

Glycosylation is an important post-translational modification that affects many critical cellular functions such as adhesion, signaling, protein stability, and function, among others. Abnormal glycosylation has been linked to many diseases. As such, the investigation of glycans and their roles in disease pathway and progression is important. Glycan analysis can be challenging, however, due to such factors as the heterogeneity of glycans and isomers as well as the poor ionization efficiency provided by mass spectrometry analyses. This chapter presents efficient methods that overcome these and other challenges for the analysis of native and permethylated N-glycan isomers in biological samples. Instructions regarding the packing of the MGC column, the N-glycan sample prep, and the LC-MS conditions are also provided.

Targeted Glycoproteomics Analysis Using MRM/PRM Approaches.

MS-target analyses are frequently utilized to analyze and validate structural changes of biomolecules across diverse fields of study such as proteomics, glycoproteomics, glycomics, lipidomics, and metabolomics. Targeted studies are commonly conducted using multiple reaction monitoring (MRM) and parallel reaction monitoring (PRM) techniques. A reliable glycoproteomics analysis in intricate biological matrices is possible with these techniques, which streamline the analytical workflow, lower background interference, and enhance selectivity and specificity.

Integrated analysis of natural glycans using a versatile pyrazolone-type heterobifunctional tag ANPMP.

Glycans mediate various biological processes through carbohydrate-protein interactions, and glycan microarrays have become indispensable tools for understanding these mechanisms. However, advances in functional glycomics are hindered by the absence of convenient and universal methods for obtaining natural glycan libraries with diverse structures from glycoconjugates. To address this challenge, we have developed an integrative approach that enables one-pot release and simultaneously capture, separation, structural characterization, and functional analysis of N/O-glycans. Using this approach, glycoconjugates are incubated with a pyrazolone-type heterobifunctional tag-ANPMP to obtain glycan-2ANPMP conjugates, which are then converted to glycan-AEPMP conjugates. We prepared a tagged glycan library from porcine gastric mucin, soy protein, human milk oligosaccharides, etc. Following derivatization by N-acetylation and permethylation, glycans were subjected to detailed structural characterization by ESI-MSn analysis, which revealed >83 highly pure glycan-AEPMPs containing various natural glycan epitopes. A shotgun microarray is constructed to study the fine details of glycan-bindings by proteins and antisera.

Comprehensive Comparison of Bioactive N-Glycans among Seven Species of Livestock and Poultry Plasma Using a Relative Quantification Strategy.

Glycans have been proven to play special roles in keeping human health as a class of nutritional and bioactive ingredients in many food materials. However, their broad use in the food industry is hindered by the lack of comprehensive analytical methods for high-quality food glycomics studies and large-quantity raw materials for their production. This study focuses on structural identification and quantitative comparison of bioactive N-glycans in seven species of livestock and poultry plasma as potential natural glycan resources by a novel comprehensive relative quantification strategy based on stable isotope labeling with nondeuterated and deuterated 4-methyl-1-(2-hydrazino-2-oxoethyl)-pyridinium bromide (d0/d7-HMP) in combination with linkage-specific derivatization of sialic acid residues. Methodological validation of the method in terms of detection sensitivity, signal resolution, quantification linearity, precision, and accuracy on model neutral and complicated sialylated glycans demonstrated its advantages over the existing methods. Based on this method, a series of bioactive N-glycans were found in seven species of livestock and poultry plasma, and their differences in structure, abundance percentages, and relative contents of N-glycans were revealed, demonstrating their excellent applicability for comprehensive food glycomics analysis and great exploitation potential of these plasma samples as large-quantity raw materials in producing bioactive N-glycans for application in food and pharmaceutical industries.

Decoding glycomics with a suite of methods for differential expression analysis.

Glycomics, the comprehensive profiling of all glycan structures in samples, is rapidly expanding to enable insights into physiology and disease mechanisms. However, glycan structure complexity and glycomics data interpretation present challenges, especially for differential expression analysis. Here, we present a framework for differential glycomics expression analysis. Our methodology encompasses specialized and domain-informed methods for data normalization and imputation, glycan motif extraction and quantification, differential expression analysis, motif enrichment analysis, time series analysis, and meta-analytic capabilities, synthesizing results across multiple studies. All methods are integrated into our open-source glycowork package, facilitating performant workflows and user-friendly access. We demonstrate these methods using dedicated simulations and glycomics datasets of N-, O-, lipid-linked, and free glycans. Differential expression tests here focus on human datasets and cancer vs. healthy tissue comparisons. Our rigorous approach allows for robust, reliable, and comprehensive differential expression analyses in glycomics, contributing to advancing glycomics research and its translation to clinical and diagnostic applications.

6-Plex mdSUGAR Isobaric-Labeling Guide Fingerprint Embedding for Glycomics Analysis.

Glycans are vital biomolecules with diverse functions in biological processes. Mass spectrometry (MS) has become the most widely employed technology for glycomics studies. However, in the traditional data-dependent acquisition mode, only a subset of the abundant ions during MS1 scans are isolated and fragmented in subsequent MS2 events, which reduces reproducibility and prevents the measurement of low-abundance glycan species. Here, we reported a new method termed 6-plex mdSUGAR isobaric-labeling guide fingerprint embedding (MAGNI), to achieve multiplexed, quantitative, and targeted glycan analysis. The glycan peak signature was embedded by a triplicate-labeling strategy with a 6-plex mdSUGAR tag, and using ultrahigh-resolution mass spectrometers, the low-abundance glycans that carry the mass fingerprints can be recognized on the MS1 spectra through an in-house developed software tool, MAGNIFinder. These embedded unique fingerprints can guide the selection and fragmentation of targeted precursor ions and further provide rich information on glycan structures. Quantitative analysis of two standard glycoproteins demonstrated the accuracy and precision of MAGNI. Using this approach, we identified 304 N-glycans in two ovarian cancer cell lines. Among them, 65 unique N-glycans were found differentially expressed, which indicates a distinct glycosylation pattern for each cell line. Remarkably, 31 N-glycans can be quantified in only 1 × 103 cells, demonstrating the high sensitivity of our method. Taken together, our MAGNI method offers a useful tool for low-abundance N-glycan characterization and is capable of determining small quantitative differences in N-glycan profiling. Therefore, it will be beneficial to the field of glycobiology and will expand our understanding of glycosylation.

Glycan/Protein-Stable Isotope Labeling in Cell Culture for Enabling Concurrent Quantitative Glycomics/Proteomics/Glycoproteomics.

The complexity and heterogeneity of protein glycosylation present an analytical challenge to the studies of characterization and quantitation. Various LC-MS-based quantitation strategies have emerged in recent decades. Metabolic stable isotope labeling has been developed to enhance the accurate LC/MS-based quantitation between different cell lines. Stable isotope labeling by amino acids in a cell culture (SILAC) is the most widely used metabolic labeling method in proteomic analysis. However, it can only label the peptide backbone and is thus limited in glycomic studies. Here, we present a metabolic isotope labeling strategy, named GlyProSILC (Glycan Protein Stable Isotope Labeling in Cell Culture), that can label both the glycan motif and peptide backbone from the same batch of cells. It was performed by feeding cells with a heavy medium containing amide-15N-glutamine, 13C6-arginine (Arg6), and 13C6-15N2-lysine (Lys8). No significant change of cell line metabolism after GlyProSILC labeling was observed based on transcriptomic, glycomic, and proteomic data. The labeling conditions, labeling efficiency, and quantitation accuracy were investigated. After quantitation correction, we simultaneously quantified 62 N-glycans, 574 proteins, and 344 glycopeptides using the same batch of mixed 231BR/231 cell lines. So far, GlyProSILC provides an accurate and effective quantitation approach for glycomics, proteomics, and glycoproteomics in a cell culture system.

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.

A Holistic 4D Approach to Optimize Intrinsic and Extrinsic Factors Contributing to Variability in Microarray Biosensing in Glycomics.

Protein-carbohydrate interactions happen to be a crucial facet of biology, discharging a myriad of functions. Microarrays have become a premier choice to discern the selectivity, sensitivity and breadth of these interactions in a high-throughput manner. The precise recognition of target glycan ligands among the plethora of others is central for any glycan-targeting probe being tested by microarray analyses. Ever since the introduction of the microarray as an elemental tool for high-throughput glycoprofiling, numerous distinct array platforms possessing different customizations and assemblies have been developed. Accompanying these customizations are various factors ushering variances across array platforms. In this primer, we investigate the influence of various extrinsic factors, namely printing parameters, incubation procedures, analyses and array storage conditions on the protein-carbohydrate interactions and evaluate these factors for the optimal performance of microarray glycomics analysis. We hereby propose a 4D approach (Design-Dispense-Detect-Deduce) to minimize the effect of these extrinsic factors on glycomics microarray analyses and thereby streamline cross-platform analyses and comparisons. This work will aid in optimizing microarray analyses for glycomics, minimize cross-platform disparities and bolster the further development of this technology.

Characterization of aberrant glycosylation associated with osteoarthritis based on integrated glycomics methods.

BACKGROUND: Osteoarthritis (OA) is the most common form of arthritis, affecting millions of aging people. Investigation of abnormal glycosylation is essential for the understanding of pathological mechanisms of OA. METHODS: The total protein was isolated from OA (n = 13) and control (n = 11) cartilages. Subsequently, glycosylation alterations of glycoproteins in OA cartilage were investigated by lectin microarrays and intact glycopeptides analysis. Finally, the expression of glycosyltransferases involved in the synthesis of altered glycosylation was assessed by qPCR and GEO database. RESULTS: Our findings revealed that several glycopatterns, such as α-1,3/6 fucosylation and high-mannose type of N-glycans were altered in OA cartilages. Notably, over 27% of identified glycopeptides (109 glycopeptides derived from 47 glycoproteins mainly located in the extracellular region) disappeared or decreased in OA cartilages, which is related to the cartilage matrix degradation. Interestingly, the microheterogeneity of N-glycans on fibronectin and aggrecan core protein was observed in OA cartilage. Our results combined with GEO data indicated that the pro-inflammatory cytokines altered the expression of glycosyltransferases (ALG3, ALG5, MGAT4C, and MGAT5) which may contribute to the alterations in glycosylation. CONCLUSION: Our study revealed the abnormal glycopatterns and heterogeneities of site-specific glycosylation associated with OA. To our knowledge, it is the first time that the heterogeneity of site-specific N-glycans was reported in OA cartilage. The results of gene expression analysis suggested that the expression of glycosyltransferases was impacted by pro-inflammatory cytokines, which may facilitate the degradation of protein and accelerate the process of OA. Our findings provide valuable information for the understanding of molecular mechanisms in the pathogenesis of OA.

The Role of Clinical Glyco(proteo)mics in Precision Medicine.

Glycoproteomics reveals site-specific O- and N-glycosylation that may influence protein properties including binding, activity, and half-life. The increasingly mature toolbox with glycomic and glycoproteomic strategies is applied for the development of biopharmaceuticals and the discovery and clinical evaluation of glycobiomarkers in various disease fields. Notwithstanding the contributions of glycoscience in identifying new drug targets, the current report is focused on the biomarker modality that is of interest for diagnostic and monitoring purposes. To this end, it is noted that the identification of biomarkers has received more attention than the corresponding quantification. Most analytical methods are very efficient in detecting large numbers of analytes, but developments to accurately quantify these have so far been limited. In this perspective, a parallel is made with earlier proposed tiers for protein quantification using mass spectrometry. Moreover, the foreseen reporting of multimarker readouts is discussed to describe an individual's health or disease state and their role in clinical decision-making. The potential of longitudinal sampling and monitoring of glycomic features for diagnosis and treatment monitoring is emphasized. Finally, different strategies that address the quantification of a multimarker panel are discussed.

GlycoNote with Iterative Decoy Searching and Open-Search Component Analysis for High-Throughput and Reliable Glycan Spectral Interpretation.

Mass spectrometry-based glycome analysis is a viable strategy for the compositional and functional exploration of glycosylation. However, the lack of generic tools for high-throughput and reliable glycan spectral interpretation largely hampers the broad usability of glycomic research. Here, we developed a generic and reliable glycomic tool, GlycoNote, for comprehensive and precise glycome analysis. GlycoNote supports interpretation of tandem-mass spectrometry glycomic data from any sample source, uses a novel target-decoy method with iterative decoy searching for highly reliable result output, and embeds an open-search component analysis mode for heterogeneity analysis of monosaccharides and modifications. We tested GlycoNote on several different large-scale glycomic datasets, including human milk oligosaccharides, N- and O-glycome from human cell lines, plant polysaccharides, and atypical glycans from Caenorhabditis elegans, demonstrating its high capacity for glycome analysis. An application of GlycoNote to the analysis of labeled and derived glycans further demonstrates its broad usability in glycomic studies. By enabling generic characterization of various glycan types and elucidation of component heterogeneity in glycomic samples, the freely available GlycoNote is a promising tool for facilitating glycomics in glycobiology research.

N-glycomic profiling reveals dysregulated N-glycans of peripheral neuropathy in type 2 diabetes.

Given the increasing morbidity of diabetes mellitus type 2 (T2DM) with peripheral neuropathy (PN), efficient screening for T2DM-PN is of great significance. Altered N-glycosylation is closely associated with T2DM progression, whereas its association with T2DM-PN remains uncharacterized. In this study, N-glycomic profiling was performed to identify the N-glycan features between T2DM patients with (n = 39, T2DM-PN) and without PN (n = 36, T2DM-C). Another independent set of T2DM patients (n = 29 for both T2DM-C and T2DM-PN) were utilized to validate these N-glycomic features. There were 10 N-glycans varied significantly between T2DM-C and T2DM-PN (p < 0.05 and 0.7 < AUC < 0.9), of which T2DM-PN was associated with increased oligomannose and core-fucosylation of sialylated glycans, and decreased bisected mono-sialylated glycan. Notably, these results were validated by an independent set of T2DM-C and T2DM-PN. This is the first profiling for N-glycan features in T2DM-PN patients, which reliably differentiates them from T2DM controls, thus providing a prospective profile of glyco-biomarkers for the screening and diagnosis of T2DM-PN.

Integrated glycomics and genetics analyses reveal a potential role for N-glycosylation of plasma proteins and IgGs, as well as the complement system, in the development of type 1 diabetes.

AIMS/HYPOTHESIS: We previously demonstrated that N-glycosylation of plasma proteins and IgGs is different in children with recent-onset type 1 diabetes compared with their healthy siblings. To search for genetic variants contributing to these changes, we undertook a genetic association study of the plasma protein and IgG N-glycome in type 1 diabetes. METHODS: A total of 1105 recent-onset type 1 diabetes patients from the Danish Registry of Childhood and Adolescent Diabetes were genotyped at 183,546 genetic markers, testing these for genetic association with variable levels of 24 IgG and 39 plasma protein N-glycan traits. In the follow-up study, significant associations were validated in 455 samples. RESULTS: This study confirmed previously known plasma protein and/or IgG N-glycosylation loci (candidate genes MGAT3, MGAT5 and ST6GAL1, encoding beta-1,4-mannosyl-glycoprotein 4-beta-N-acetylglucosaminyltransferase, alpha-1,6-mannosylglycoprotein 6-beta-N-acetylglucosaminyltransferase and ST6 beta-galactoside alpha-2,6-sialyltransferase 1 gene, respectively) and identified novel associations that were not previously reported for the general European population. First, novel genetic associations of IgG-bound glycans were found with SNPs on chromosome 22 residing in two genomic intervals close to candidate gene MGAT3; these include core fucosylated digalactosylated disialylated IgG N-glycan with bisecting N-acetylglucosamine (GlcNAc) (pdiscovery=7.65 × 10-12, preplication=8.33 × 10-6 for the top associated SNP rs5757680) and core fucosylated digalactosylated glycan with bisecting GlcNAc (pdiscovery=2.88 × 10-10, preplication=3.03 × 10-3 for the top associated SNP rs137702). The most significant genetic associations of IgG-bound glycans were those with MGAT3. Second, two SNPs in high linkage disequilibrium (missense rs1047286 and synonymous rs2230203) located on chromosome 19 within the protein coding region of the complement C3 gene (C3) showed association with the oligomannose plasma protein N-glycan (pdiscovery=2.43 × 10-11, preplication=8.66 × 10-4 for the top associated SNP rs1047286). CONCLUSIONS/INTERPRETATION: This study identified novel genetic associations driving the distinct N-glycosylation of plasma proteins and IgGs identified previously at type 1 diabetes onset. Our results highlight the importance of further exploring the potential role of N-glycosylation and its influence on complement activation and type 1 diabetes susceptibility.

The Glycan Structure Dictionary-a dictionary describing commonly used glycan structure terms.

Recent technological advances in glycobiology have resulted in a large influx of data and the publication of many papers describing discoveries in glycoscience. However, the terms used in describing glycan structural features are not standardized, making it difficult to harmonize data across biomolecular databases, hampering the harvesting of information across studies and hindering text mining and curation efforts. To address this shortcoming, the Glycan Structure Dictionary has been developed as a reference dictionary to provide a standardized list of widely used glycan terms that can help in the curation and mapping of glycan structures described in publications. Currently, the dictionary has 190 glycan structure terms with 297 synonyms linked to 3,332 publications. For a term to be included in the dictionary, it must be present in at least 2 peer-reviewed publications. Synonyms, annotations, and cross-references to GlyTouCan, GlycoMotif, and other relevant databases and resources are also provided when available. The purpose of this effort is to facilitate biocuration, assist in the development of text mining tools, improve the harmonization of search, and browse capabilities in glycoinformatics resources and help to map glycan structures to function and disease. It is also expected that authors will use these terms to describe glycan structures in their manuscripts over time. A mechanism is also provided for researchers to submit terms for potential incorporation. The dictionary is available at https://wiki.glygen.org/Glycan_structure_dictionary.

Expanding Glycomic Investigations through Thiol-Derivatized Glycans.

N-(2-thioethyl)-2-aminobenzamide (TEAB), a novel glycan auxiliary, was synthesized and its utility was evaluated. The auxiliary was conjugated to glycans by reductive amination with the water-stable reagent 2-picoline borane complex. Glycan products, which ranged from 1 to 7 linked hexoses, were all isolated in yields ranging from 60% to 90% after purification by reverse-phase chromatography. The novel conjugate introduces a convenient, shelf-stable thiol directly onto the desired free glycans with purification advantages and direct modification with efficient reactions through alkenes, halides, epoxides, disulfides, and carboxylates in yields of 49% to 93%. Subsequently, a thiol-selective modification of the BSA protein was used to generate a neoglycoprotein with a bifunctional PEG-maleimide linker. To further illustrate the utility of a thiol motif, 2-thiopyridine activation of a thiol-containing support facilitated the covalent chromatographic purification of labeled glycans in yields up to 63%. Finally, initial proof of concept of implementation in a light printed microarray was explored and validated through FITC-labeled concanavalin A binding. In conclusion, the thiol-functionalized glycans produced greatly expand the diversity of bioconjugation tools that can be developed with glycans and enable a variety of biological investigations.

Glycomics-Assisted Glycoproteomics Enables Deep and Unbiased N-Glycoproteome Profiling of Complex Biological Specimens.

Mass spectrometry-driven glycomics and glycoproteomics, the system-wide profiling of detached glycans and intact glycopeptides from biological samples, respectively, are powerful approaches to interrogate the heterogenous glycoproteome. Efforts to develop integrated workflows employing both glycomics and glycoproteomics have been invested since the concerted application of these complementary approaches enables a deeper exploration of the glycoproteome. This protocol paper outlines, step-by-step, an integrated -omics technology, the "glycomics-assisted glycoproteomics" method, that first establishes the N-glycan fine structures and their quantitative distribution pattern of protein extracts via porous graphitized carbon-LC-MS/MS. The N-glycome information is then used to augment and guide the challenging reversed-phase LC-MS/MS-based profiling of intact N-glycopeptides from the same protein samples. Experimental details and considerations relating to the sample preparation and the N-glycomics and N-glycoproteomics data collection, analysis, and integration are discussed. Benefits of the glycomics-assisted glycoproteomics method, which can be readily applied to both simple and complex biological specimens such as protein extracts from cells, tissues, and bodily fluids (e.g., serum), include quantitative information of the protein carriers and site(s) of glycosylation, site occupancy, and the site-specific glycan structures directly from biological samples. The glycomics-assisted glycoproteomics method therefore facilitates a comprehensive view of the complexity and dynamics of the heterogenous glycoproteome.