Quantitative Glycomics Research Articles

12-Plex Isobaric Multiplex Labeling Reagents for Carbonyl-Containing Compound (SUGAR) Tag-Enabled High-Throughput Quantitative Glycomics.

Glycans, which are ubiquitously distributed on most proteins and cell surfaces, are a class of important biomolecules playing crucial roles in various biological processes such as molecular recognition and cellular communication. Modern mass spectrometry (MS) coupled with novel chemical probe labeling strategies has greatly advanced analysis of glycans. However, the requirement of high-throughput and robust quantitative analysis still calls for the development of more advanced tools. Recently, we devised isobaric multiplex reagents for carbonyl-containing compound (SUGAR) tags for 4-plex N-glycan analysis. To further improve the throughput, we utilized the mass-defect strategy and expanded the multiplexing capacity to 12 channels without changing the chemical structure of the SUGAR tag, achieving a threefold enhancement in throughput compared with the original design and managing to perform high-throughput N-glycan analysis in a single LC-MS/MS injection. Herein, we present detailed methods for the synthesis of 12-plex SUGAR isobaric tags, the procedure to release and label the N-glycans from proteins, and the analysis by high-resolution LC-MS/MS, as well as data processing to achieve multiplexed quantitative glycomics.

Comprehensive Glycoprofiling of Oral Tumors Associates N-Glycosylation With Lymph Node Metastasis and Patient Survival

While altered protein glycosylation is regarded a trait of oral squamous cell carcinoma (OSCC), the heterogeneous and dynamic glycoproteome of tumor tissues from OSCC patients remain unmapped. To this end, we here employ an integrated multi-omics approach comprising unbiased and quantitative glycomics and glycoproteomics applied to a cohort of resected primary tumor tissues from OSCC patients with (n = 19) and without (n = 12) lymph node metastasis. While all tumor tissues displayed relatively uniform N-glycome profiles suggesting overall stable global N-glycosylation during disease progression, altered expression of six sialylated N-glycans was found to correlate with lymph node metastasis. Notably, glycoproteomics and advanced statistical analyses uncovered altered site-specific N-glycosylation revealing previously unknown associations with several clinicopathological features. Importantly, the glycomics and glycoproteomics data unveiled that comparatively high abundance of two core-fucosylated and sialylated N-glycans (Glycan 40a and Glycan 46a) and one N-glycopeptide from fibronectin were associated with low patient survival, while a relatively low abundance of N-glycopeptides from both afamin and CD59 were also associated with poor survival. This study provides insight into the complex OSCC tissue N-glycoproteome, thereby forming an important resource to further explore the underpinning disease mechanisms and uncover new prognostic glycomarkers for OSCC.

High-Throughput Quantitative Glycomics Enabled by 12-plex Isobaric Multiplex Labeling Reagents for Carbonyl-Containing Compound (SUGAR) Tags.

Glycans, which are widely distributed on most proteins and cell surfaces, are a class of important biomolecules playing crucial roles in various biological processes such as immune response and cellular communication. Modern mass spectrometry (MS) coupled with novel chemical probes greatly facilitates routine analysis of glycans. However, the requirement of high-throughput analysis still calls for advanced tools to be developed. Recently, we devised isobaric multiplex reagents for carbonyl-containing compound (SUGAR) tags for 4-plex N-glycan analysis. To further improve the throughput, we utilized the subtle mass differences among different isotopologues and expanded the multiplexing capacity to 12 channels, a 3-fold throughput improvement for the original SUGAR tag design and achieved high-throughput N-glycan analysis in a single LC-MS/MS injection. We then applied 12-plex SUGAR tags to profile the N-glycans in four subtypes of human Immunoglobulin G (IgG) and to investigate the N-glycan changes in the endometrial cancer cells (ECC1) treated with Atovaquone, a quinone antimicrobial medication, and a dihydroorotate dehydrogenase (DHODH) inhibitor. Data are available via ProteomeXchange with the identifier PXD038501.

Mouse tissue glycome atlas 2022 highlights inter-organ variation in major N-glycan profiles

This study presents “mouse tissue glycome atlas” representing the profiles of major N-glycans of mouse glycoproteins that may define their essential functions in the surface glycocalyx of mouse organs/tissues and serum-derived extracellular vesicles (exosomes). Cell surface glycocalyx composed of a variety of N-glycans attached covalently to the membrane proteins, notably characteristic “N-glycosylation patterns” of the glycocalyx, plays a critical role for the regulation of cell differentiation, cell adhesion, homeostatic immune response, and biodistribution of secreted exosomes. Given that the integrity of cell surface glycocalyx correlates significantly with maintenance of the cellular morphology and homeostatic immune functions, dynamic alterations of N-glycosylation patterns in the normal glycocalyx caused by cellular abnormalities may serve as highly sensitive and promising biomarkers. Although it is believed that inter-organs variations in N-glycosylation patterns exist, information of the glycan diversity in mouse organs/tissues remains to be elusive. Here we communicate for the first-time N-glycosylation patterns of 16 mouse organs/tissues, serum, and serum-derived exosomes of Slc:ddY mice using an established solid-phase glycoblotting platform for the rapid, easy, and high throughput MALDI-TOFMS-based quantitative glycomics. The present results elicited occurrence of the organ/tissue-characteristic N-glycosylation patterns that can be discriminated to each other. Basic machine learning analysis using this N-glycome dataset enabled classification between 16 mouse organs/tissues with the highest F1 score (69.7–100%) when neural network algorithm was used. A preliminary examination demonstrated that machine learning analysis of mouse lung N-glycome dataset by random forest algorithm allows for the discrimination of lungs among the different mouse strains such as the outbred mouse Slc:ddY, inbred mouse DBA/2Crslc, and systemic lupus erythematosus model mouse MRL-lpr/lpr with the highest F1 score (74.5–83.8%). Our results strongly implicate importance of “human organ/tissue glycome atlas” for understanding the crucial and diversified roles of glycocalyx determined by the organ/tissue-characteristic N-glycosylation patterns and the discovery research for N-glycome-based disease-specific biomarkers and therapeutic targets.

Quantitative Analysis and Structural Elucidation of Fatty Acids by Isobaric Multiplex Labeling Reagents for Carbonyl-Containing Compound (SUGAR) Tags and m-CPBA Epoxidation.

In this study, a novel analytical method was developed to investigate fatty acids (FAs) for relative quantification, carbon-carbon double-bond localization, and cis-/trans-geometry differentiation by isobaric multiplex labeling reagents for carbonyl-containing compound (SUGAR) tag conjugation and meta-chloroperoxybenzoic acid (m-CPBA) epoxidation. FAs are essential components of cells and have diverse functions in energy storage and as complex lipid constituents. It has been reported that FAs play different roles in various biological processes such as the functional development of the brain. The comprehensive characterization and quantification of FAs are crucial to further elucidate their biological roles. However, it is challenging to perform relative quantification and structural elucidation of FAs using integrated mass spectrometry (MS)-based methods. Recently, our group developed isobaric multiplex SUGAR tags for quantitative glycomics. Besides aldehyde/ketone groups on glycans, hydrazide groups also possess reactivity toward carboxylic acids on FAs. In this study, we extended SUGAR tag labeling with FAs for the quantitative analysis by liquid chromatography (LC)-MS/MS in the positive ion mode and applied this strategy for the comparative analysis of FAs hydrolyzed from oil samples. In addition, to comprehensively elucidate the structures of unsaturated FAs, epoxidation by m-CPBA was performed before SUGAR tag labeling to enable carbon-carbon double-bond localization. Moreover, the cis- and trans-geometries of carbon-carbon double bonds in multiple pairs of monounsaturated FAs could also be differentiated in higher-energy collisional dissociation (HCD)-MS/MS. This study developed a high-throughput comprehensive FA analysis platform, which could be widely applied and utilized in biological and clinical studies.

N-acetyl-β-D-hexosaminidases mediate the generation of paucimannosidic proteins via a putative noncanonical truncation pathway in human neutrophils.

We recently discovered that human neutrophils express immunomodulatory glycoproteins carrying unusual and highly truncated paucimannosidic N-glycans (Man1-3GlcNAc2Fuc0-1), but their biosynthesis remains elusive. Guided by the well-characterized truncation pathway in invertebrates and plants in which the N-acetyl-β-D-hexosaminidase (Hex) isoenzymes catalyze paucimannosidic protein (PMP) formation, we here set out to test if the homologous human Hex α and β subunits encoded by HEXA and HEXB drive a similar truncation pathway in human neutrophils. To this end, we performed quantitative glycomics and glycoproteomics of several CRISPR-Cas9-edited Hex-disrupted neutrophil-like HL-60 mutants (HEXA-KO and HEXB-KO) and matching unedited cell lines. Hex disruption was validated using next-generation sequencing, enzyme-linked immunosorbent assay (ELISA), quantitative proteomics and Hex activity assays. Excitingly, all Hex-disrupted mutants displayed significantly reduced levels of paucimannosylation, particularly Man2-3GlcNAc2Fuc1, relative to unedited HL-60 suggesting that both HEXA and HEXB contribute to PMP formation via a hitherto unexplored truncation pathway in neutrophils. Quantitative N-glycomics indeed demonstrated reduced utilization of a putative noncanonical truncation pathway in favor of the canonical elongation pathway in all Hex-disrupted mutants relative to unedited controls. Quantitative glycoproteomics recapitulated the truncation-to-elongation switch in all Hex-disrupted mutants and showed a greater switch for N-glycoproteins cotrafficking with Hex to the azurophilic granules of neutrophils such as myeloperoxidase. Finally, we supported the Hex-PMP relationship by documenting that primary neutrophils isolated from an early-onset Sandhoff disease patient (HEXB-/-) displayed dramatically reduced paucimannosylation relative to neutrophils from an age-matched unaffected donor. We conclude that both human Hex α and β mediate PMP formation via a putative noncanonical truncation pathway in neutrophils.

Trends in oligomannosylation and α1,2-mannosidase expression in human cancers.

Aberrant protein glycosylation is a prominent cancer feature. While many tumour-associated glycoepitopes have been reported, advances in glycoanalytics continue to uncover new associations between glycosylation and cancer. Guided by a comprehensive literature survey suggesting that oligomannosylation (Man5–9 GlcNAc2) is a widespread and often regulated glycosignature in human cancers, we here revisit a valuable compilation of nearly 500 porous graphitized carbon LC-MS/MS N-glycomics datasets acquired across 11 human cancer types to systematically test for oligomannose-cancer associations. Firstly, the quantitative glycomics data obtained across 34 cancerous cell lines demonstrated that oligomannosylation is a pan-cancer feature spanning in a wide abundance range. In keeping with literature, our quantitative glycomics data of tumour and matching control tissues and new MALDI-MS imaging data of tissue microarrays showed a strong cancer-associated elevation of oligomannosylation in both basal cell (p = 1.78 × 10–12) and squamous cell (p = 1.23 × 10–11) skin cancer and colorectal cancer (p = 8.0 × 10–4). The glycomics data also indicated that some cancer types including gastric and liver cancer exhibit unchanged or reduced oligomannose levels, observations also supported by literature and MALDI-MS imaging data. Finally, expression data from public cancer repositories indicated that several α1,2-mannosidases are regulated in tumour tissues suggesting that these glycan-processing enzymes may contribute to the cancer-associated modulation of oligomannosylation. This omics-centric study has compiled robust glycomics and enzyme expression data revealing interesting molecular trends that open avenues to better understand the role of oligomannosylation in human cancers.

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).

GQuant, an Automated Tool for Quantitative Glycomic Data Analysis.

MALDI-MS-based glycan isotope labeling methods have been effectively and widely used for quantitative glycomics. However, interpretation of the data produced by MALDI-MS is inaccurate and tedious because the bioinformatic tools are inadequate. In this work, we present gQuant, an automated tool for MALDI-MS-based glycan isotope labeling data processing. gQuant was designed with a set of dedicated algorithms to improve the efficiency, accuracy and convenience of quantitation data processing. When tested on the reference data set, gQuant showed a fast processing speed, as it was able to search the glycan data of model glycoproteins in a few minutes and reported more results than the manual analysis did. The reported quantitation ratios matched well with the experimental glycan mixture ratios ranging from 1:10 to 10:1. In addition, gQuant is fully open-source and is coded in Python, which is supported by most operating systems, and it has a user-friendly interface. gQuant can be easily adapted by users for specific experimental designs, such as specific glycan databases, different derivatization types and relative quantitation designs and can thus facilitate fast glycomic quantitation for clinical sample analysis using MALDI-MS-based stable isotope labeling.

Isotope labeling strategies of glycans for mass spectrometry-based quantitative glycomics

Robust mass spectrometry-based methods for quantitative glycomics are almost invariable based on stable isotope labeling. These approaches represent a mature and yet evolving array of techniques that enable high-accuracy, high-speed, high-sensitivity, and high-throughput analysis of glycans from diverse biological matrices. The introduction of stable isotopes into biomolecules can be accomplished by three major ways, namely by metabolic, enzymatic, and chemical labeling of samples. Together, these approaches cover a wide variety of potential sample types, including purified glycans, cell and tissue samples, as well as clinical specimens. In this review, various aspects of isotope labeling strategies in comparative glycomics are discussed.

Metabolic labeling of glycans with isotopic glucose for quantitative glycomics in yeast

Changes in glycan levels could directly affect the biochemical properties of glycoproteins and thus influence their physiological functions. In order to decode the correlation of glycan prevalence with their physiological contribution, many mass spectrometry (MS) and stable isotope labeling-based methods have been developed for the relative quantification of glycans. In this study, we expand the quantitative glycomic toolbox with the addition of optimized Metabolic Isotope Labeling of Polysaccharides with Isotopic Glucose (MILPIG) approach in baker's yeast (Saccharomyces cerevisiae). We demonstrate that culturing baker's yeast in the presence of carbon-13 labeled glucose (1–13C1) leads to effective incorporation of carbon-13 to both N-linked and O-linked glycans. We established that metabolic incorporation of isotope-labeled glucose at a concentration of 5 mg/mL for three days is required for an accurate quantitative analysis with optimal isotopic cluster distribution of glycans. To validate the robustness of the method, we performed the analysis by 1:1 mixing of normal and isotope-labeled glycans, and obtained excellent linear calibration curves from various analytes. Finally, we quantitated the inhibitory effect of tunicamycin, a N-linked glycosylation inhibitor, to glycan expression profile in yeast.

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.

The Complexity and Dynamics of the Tissue Glycoproteome Associated With Prostate Cancer Progression

The complexity and dynamics of the immensely heterogeneous glycoproteome of the prostate cancer (PCa) tumor microenvironment remain incompletely mapped, a knowledge gap that impedes our molecular-level understanding of the disease. To this end, we have used sensitive glycomics and glycoproteomics to map the protein-, cell-, and tumor grade–specific N- and O-glycosylation in surgically removed PCa tissues spanning five histological grades (n = 10/grade) and tissues from patients with benign prostatic hyperplasia (n = 5). Quantitative glycomics revealed PCa grade–specific alterations of the oligomannosidic-, paucimannosidic-, and branched sialylated complex-type N-glycans, and dynamic remodeling of the sialylated core 1- and core 2-type O-glycome. Deep quantitative glycoproteomics identified ∼7400 unique N-glycopeptides from 500 N-glycoproteins and ∼500 unique O-glycopeptides from nearly 200 O-glycoproteins. With reference to a recent Tissue and Blood Atlas, our data indicate that paucimannosidic glycans of the PCa tissues arise mainly from immune cell–derived glycoproteins. Furthermore, the grade-specific PCa glycosylation arises primarily from dynamics in the cellular makeup of the PCa tumor microenvironment across grades involving increased oligomannosylation of prostate-derived glycoproteins and decreased bisecting GlcNAcylation of N-glycans carried by the extracellular matrix proteins. Furthermore, elevated expression of several oligosaccharyltransferase subunits and enhanced N-glycoprotein site occupancy were observed associated with PCa progression. Finally, correlations between the protein-specific glycosylation and PCa progression were observed including increased site-specific core 2-type O-glycosylation of collagen VI. In conclusion, integrated glycomics and glycoproteomics have enabled new insight into the complexity and dynamics of the tissue glycoproteome associated with PCa progression generating an important resource to explore the underpinning disease mechanisms.

Isotope Labeling of N‐linked Glycans by Transglycosylation of Endo‐M and Isotopic Glucose for Quantitative Glycomics

To understand the biological relevance of glycans, many mass spectrometry (MS)‐based methods have been developed for the relative quantification of N‐linked glycans using stable isotopic labeling. The increasing demand for the simultaneous comparative quantification of N‐linked glycans for samples of various biological conditions is a new challenge for MS. We proposed a novel relative quantitative glycomics that enzymatically incorporates isotope‐labeled glucose into N‐linked glycans through transglycosylation of endo‐β‐N‐acetylglucosaminidase M (Endo‐M) and isotope‐labeled glucose. Newly incorporated normal (light) and isotope‐labeled (heavy) N‐linked glycans were synthesized using the same known concentration of sialyglycopeptide, and their relative quantitative properties were realized from the duplex mass spectrum. In addition, the dynamic range and accuracy of the relative quantification were shown with light and heavy N‐linked glycans for sialyglycopeptide at a constant concentration ratio.

Multiplex Quantitative Glycomics Enabled by Periodate Oxidation and Triplex Mass Defect Isobaric Multiplex Reagents for Carbonyl-Containing Compound Tags.

Glycosylation is one of the most important post-translational modifications (PTMs) with essential physiological functions, including protein folding, cell signaling, and immune response. Thus, various qualitative and quantitative glycomics analysis strategies have been developed. Recently, the isobaric multiplex reagents for carbonyl-containing compound (SUGAR) tag was developed for quantitative glycomics with multiplexing capacity and increased reporter ion yield. To further improve quantification efficiency and enable quantifying low-abundance species, the mass defect based triplex SUGAR (mdSUGAR) tag has been designed. In addition, we also introduce additional reaction sites for mdSUGAR at the terminal sialic acid by periodate oxidation of the polyhydroxy chain to extend the mass difference and lower the requirement for resolving power. As a result, mdSUGAR tags show complete labeling efficiency, improved fragmentation pattern, and accurate quantification. Moreover, the quantitative performance of the mdSUGAR tags in a complex system has been systematically evaluated and demonstrated reliable results.

Isobaric Multiplex Labeling Reagents for Carbonyl-Containing Compound (SUGAR) Tags: A Probe for Quantitative Glycomic Analysis.

Glycans are highly complex entities with multiple building units and different degrees of branched polymerization. Intensive research efforts have been directed to mass spectrometry (MS)-based qualitative and quantitative glycomic analysis due to the important functions of glycans. Among various strategies, isobaric labeling has become popular because of its higher multiplexing capacity. Over the past few years, several isobaric chemical tags have been developed for quantitative glycomics. However, caveats also exist for these tags, such as relatively low reporter ion yield for aminoxyTMT-labeled complex glycans. To overcome the limitations of existing isobaric chemical tags, we designed a class of novel isobaric multiplex reagents for carbonyl-containing compound (SUGAR) tags that can be used to label glycans for quantitative glycomic analysis. The quantitative performance including labeling efficiency, quantification accuracy, and dynamic range of these SUGAR tags has been evaluated, showing promising results. Finally, the 4-plex SUGAR tags have been utilized to investigate N-glycan changes of B-cell acute lymphoblastic leukemia (ALL) pediatric patients before and after chemotherapy.

Advances in mass spectrometry-based glycomics.

The diversification of the chemical properties and biological functions of proteins is attained through posttranslational modifications, such as glycosylation. Glycans, which are covalently attached to proteins, play a vital role in cell activities. The microheterogeneity and complexity of glycan structures associated with proteins make comprehensive glycomic analysis challenging. However, recent advancements in mass spectrometry (MS), separation techniques, and sample preparation methods have primarily facilitated structural elucidation and quantitation of glycans. This review focuses on describing recent advances in MS-based techniques used for glycomic analysis (2012-2018), including ionization, tandem MS, and separation techniques coupled with MS. Progress in glycomics workflow involving glycan release, purification, derivatization, and separation will also be highlighted here. Additionally, the recent development of quantitative glycomics through comparative and multiplex approaches will also be described.

A novel, simplified strategy of relative quantification N-glycan: Quantitative glycomics using electrospray ionization mass spectrometry through the stable isotopic labeling by transglycosylation reaction of mutant enzyme Endo-M-N175Q

The lack of a highly sensitive and simple method for the quantitative analysis of glycan has impeded the exploration of protein glycosylation patterns (glycomics), evaluation of antibody drug stability, and screening of disease glycan biomarkers. In this study, we describe a novel and simplified quantitative glycomics strategy. Quantitation by mutant enzyme reaction stable isotope labeling (QMERSIL) to label the N-glycans with either a nondeuterated (d0-) or deuterated (d8-) 4-(2,4-Dinitro-5-piperazin-1-yl-phenyl)-1,1-dimethyl-piperazin-1-ium (MPDPZ)-Boc-asparaginyl-N-acetyl-d-glucosamine (Boc-Asn-GlcNAc) acceptor of a positive charge structure through the glycosynthase (Endo-M-N175Q) transglycosylation reaction with mass spectrometry facilitates comparative glycomics. The sialylglycopeptide (SGP) of the complex type was used to demonstrate that QMERSIL facilitates the relative quantitation over a linear dynamic range (up to d0/d8=0.02:20) of 3 orders of magnitude. The area ratios of the N-glycan peaks from the QMERSIL method showed a good linearity (d0/d8, R2=0.9999; d8/d0, R2=0.9978). The reproducibility and accuracy assay precisions were all less than 6.12%, and the mean recoveries (%) of SGP spiked in the human plasma were 97.34%. Moreover, the QMERSIL using LC–MS/MS was evaluated with various molar ratios (1:1, 1:5, 5:1) of d0(d8)- MPDPZ-Boc-Asn-GlcNAc-labeled glycans from ribonuclease B, bovine fetuin, and ovalbumin. The ratios of the relative intensity between the isotopically MPDPZ-Boc-Asn-GlcNAc labeled N-glycans were almost equal a close to the theoretical values (1:1, 1:5, 5:1). Finally, this method was used for the relative quantitative comparison of the N-Linked oligosaccharides in human plasma.

Quantitative glycomics using liquid phase separations coupled to mass spectrometry.

Post-translational modification of proteins by the attachment of glycans is governed by a variety of highly specific enzymes and is associated with fundamental impacts on the parent protein's physical, chemical and biological properties. The inherent connection between cellular physiology and specific glycosylation patterns has been shown to offer potential for diagnostic and prognostic monitoring of altered glycosylation in the disease state. Conversely, glycoprotein based biopharmaceuticals have emerged as dominant therapeutic strategies in the treatment of intricate diseases. Glycosylation present on these biopharmaceuticals represents a major critical quality attribute with impacts on both pharmacokinetics and pharmacodynamics. The structural variety of glycans, based upon their non-template driven assembly, poses a significant analytical challenge for both qualitative and quantitative analysis. Labile monosaccharide constituents, isomeric species and often low sample availability from biological sources necessitates meticulous sample handling, ultra-high-resolution analytical separation and sensitive detection techniques, respectively. In this article a critical review of analytical quantitation approaches using liquid phase separations coupled to mass spectrometry for released glycans of biopharmaceutical and biomedical significance is presented. Considerations associated with sample derivatisation strategies, ionisation, relative quantitation through isotopic as well as isobaric labelling, metabolic/enzymatic incorporation and targeted analysis are all thoroughly discussed.

Quantitative Glycomics: A Combined Analytical and Bioinformatics Approach.

Glycosylation is one of the most common and essential protein modifications. Glycans conjugated to biomolecules modulate the function of such molecules through both direct recognition of glycan structures and indirect mechanisms that involve the control of protein turnover rates, stability, and conformation. The biological attributes of glycans in numerous biological processes and implications in a number of diseases highlight the necessity for comprehensive characterization of protein glycosylation. This chapter reviews cutting-edge methods and tools developed to facilitate quantitative glycomics. This chapter highlights the different methods employed for the release and purification of glycans from biological samples. The most effective labeling methods developed for sensitive quantitative glycomics are also described and discussed. The chromatographic approaches that have been used effectively in glycomics are also highlighted.