Novel methods in glycomics: a 2019 update

Structural and functional optimization of glycoprotein-enzymes for targeted biocatalysis in oral squamous cell carcinoma

The efficacy of optimized glycoproteinenzymes as a novel therapeutic approach for oral squamous cell carcinoma (OSCC) was tested in this study. The stability and viability of SCC-25 and HN4 operating-system cell lines were characterized. Both lines were confirmed to have a spindle-like morphology for SCC-25, while HN4 cells exhibited cobblestone-like clusters. Viability decreased with time for cell clones SCC-25 was 95 % and 80 % after five days, while HN4 was 94 % and 79 %. Enzyme 1, expression in E. coli and Pichia pastoris to high purity recombinant glycoprotein-enzymes. Activities of these enzymes varied equally among experimental conditions. The enzyme showed an activity of 18 units at Condition D as active max, Enzyme 2 retraced 16 units, and Enzyme 3 reached this point in the same condition. Differences in activity between different conditions were also found in various experimental conditions. In therapeutic assessments, glycoprotein-enzyme treatment lowered OSCC cell viability with IC50 values of 10-15 g/ml. Successful cellular localization could be detected primarily in the cytoplasm and nucleus of live animal tissue following treatment with those therapies. In preclinical xenograft models, treatment resulted in a 40-50 % reduction in tumour volume and growth rates, with treated tumours displaying a 60 % decrease in Ki-67, a 50 % reduction in Bcl-2, and a 70 % increase in cleaved caspase-3. Additionally, the Bax/Bcl-2 ratio increased by 80 %, and CD31 staining revealed a 40 % reduction in microvessel density. These results suggest that optimized glycoprotein enzyme therapy effectively inhibits tumour growth, induces apoptosis and reduces angiogenesis, thus laying a solid foundation for its application in clinical therapy of OSCC.

nQuant Enables Precise Quantitative N-Glycomics

N-glycosylation is a highly heterogeneous post-translational modification that modulates protein function. Defects in N-glycosylation are directly linked to various human diseases. Despite the importance of quantifying N-glycans with high precision, existing glycoinformatics tools are limited. Here, we developed nQuant, a glycoinformatics tool that enables label-free and isotopic labeling quantification of N-glycomics data obtained via LC-MS/MS, ensuring a low false quantitation rate. Using the label-free quantification module, we profiled the N-glycans released from purified glycoproteins and HEK293 cells as well as the dynamic changes of N-glycosylation during mouse corpus callosum development. Through the isotopic labeling quantification module, we revealed the dynamic changes of N-glycans in acute promyelocytic leukemia cells after all-trans retinoic acid treatment. Taken together, we demonstrate that nQuant enables fast and precise quantitative N-glycomics.

Targeting protein glycosylation to regulate inflammation in the respiratory tract: novel diagnostic and therapeutic candidates for chronic respiratory diseases

Protein glycosylation is a widespread posttranslational modification that can impact the function of proteins. Dysregulated protein glycosylation has been linked to several diseases, including chronic respiratory diseases (CRDs). CRDs pose a significant public health threat globally, affecting the airways and other lung structures. Emerging researches suggest that glycosylation plays a significant role in regulating inflammation associated with CRDs. This review offers an overview of the abnormal glycoenzyme activity and corresponding glycosylation changes involved in various CRDs, including chronic obstructive pulmonary disease, asthma, cystic fibrosis, idiopathic pulmonary fibrosis, pulmonary arterial hypertension, non-cystic fibrosis bronchiectasis, and lung cancer. Additionally, this review summarizes recent advances in glycomics and glycoproteomics-based protein glycosylation analysis of CRDs. The potential of glycoenzymes and glycoproteins for clinical use in the diagnosis and treatment of CRDs is also discussed.

Targeting Post-Translational Modifications to Improve Combinatorial Therapies in Breast Cancer: The Role of Fucosylation

Various tumors rely on post-translational modifications (PTMs) to promote invasiveness and angiogenesis and to reprogram cellular energetics to abate anti-cancer immunity. Among PTMs, fucosylation is a particular type of glycosylation that has been linked to different aspects of immune and hormonal physiological functions as well as hijacked by many types of tumors. Multiple tumors, including breast cancer, have been linked to dismal prognoses and increased metastatic potential due to fucosylation of the glycan core, namely core-fucosylation. Pre-clinical studies have examined the molecular mechanisms regulating core-fucosylation in breast cancer models, its negative prognostic value across multiple disease stages, and the activity of in vivo pharmacological inhibition, instructing combinatorial therapies and translation into clinical practice. Throughout this review, we describe the role of fucosylation in solid tumors, with a particular focus on breast cancer, as well as physiologic conditions on the immune system and hormones, providing a view into its potential as a biomarker for predicating or predicting cancer outcomes, as well as a potential clinical actionability as a biomarker.

In-depth characterization of protein N-glycosylation for a COVID-19 variant-design vaccine spike protein

COVID-19 is caused by SARS-CoV-2 infection and remains one of the biggest pandemics around the world since 2019. Vaccination has proved to be an effective way of preventing SARS-CoV-2 infection and alleviating the hospitalization burden. Among different forms of COVID-19 vaccine design, the spike protein of SARS-CoV-2 virus is widely used as a candidate vaccine antigen. As a surface protein on the virus envelop, the spike was reported to be heavily N-glycosylated and glycosylation had a great impact on its immunogenicity and efficacy. Besides, N-glycosylation might vary greatly on different expression systems and sequence variant designs. Therefore, comprehensive analysis of spike N-glycosylation is of great significance for better vaccine understanding and quality control. In this study, full characterization of N-glycosylation was performed for a Chinese Hamster Ovary (CHO) cell expressed variant-designed spike protein. The spike protein featured the latest six-proline substitution design together with the incorporation of a combination of mutation sites. Trypsin and Glu-C digestion coupled with PNGase F strategies were adopted, and effective LC-MS/MS methods were applied to analyze samples. As a result, a total of 19 N-glycosites were identified in the recombinant pike protein at intact N-glycopeptide level. Quantitative analysis of released glycan by LC-MS/MS was also performed, and 31 high-abundance N-glycans were identified. Sequencing analysis of glycan was further provided to assist glycan structure confirmation. Moreover, all of the analyses were performed on three consecutive manufactured batches and the glycosylation results on both glycosite and glycans showed good batch-to-batch consistency. Thus, the reported analytical strategy and N-glycosylation information may well facilitate studies on SARS-CoV-2 spike protein analysis and quality studies.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2019-2020

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2020. Also included are papers that describe methods appropriate to analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. The review is basically divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of arrays. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other areas such as medicine, industrial processes and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. The reported work shows increasing use of incorporation of new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented nearly 40 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show little sign of diminishing.

Glucose metabolism and glycosylation link the gut microbiota to autoimmune diseases

Carbohydrates serve as important energy sources and structural substances for human body as well as for gut microbes. As evidenced by the advances in immunometabolism, glucose metabolism and adenosine triphosphate (ATP) generation are deeply involved in immune cell activation, proliferation, and signaling transduction as well as trafficking and effector functions, thus contributing to immune response programming and assisting in host adaption to microenvironment changes. Increased glucose uptake, aberrant expression of glucose transporter 1 (e.g., GLU1), and abnormal glycosylation patterns have been identified in autoimmunity and are suggested as partially responsible for the dysregulated immune response and the modification of gut microbiome composition in the autoimmune pathogenesis. The interaction between gut microbiota and host carbohydrate metabolism is complex and bidirectional. Their impact on host immune homeostasis and the development of autoimmune diseases remains to be elucidated. This review summarized the current knowledge on the crosstalk of glucose metabolism and glycosylation in the host with intestinal microbiota and discussed their possible role in the development and progression of autoimmune diseases. Potential therapeutic strategies targeting glucose metabolism and glycosylation in modulating gut ecosystem and treating autoimmune diseases were discussed as well.

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.

The barrier and beyond: Roles of intestinal mucus and mucin-type O-glycosylation in resistance and tolerance defense strategies guiding host-microbe symbiosis

Over the past two decades, our appreciation of the gut mucus has moved from a static lubricant to a dynamic and essential component of the gut ecosystem that not only mediates the interface between host tissues and vast microbiota, but regulates how this ecosystem functions to promote mutualistic symbioses and protect from microbe-driven diseases. By delving into the complex chemistry and biology of the mucus, combined with innovative in vivo and ex vivo approaches, recent studies have revealed novel insights into the formation and function of the mucus system, the O-glycans that make up this system, and how they mediate two major host-defense strategies - resistance and tolerance - to reduce damage caused by indigenous microbes and opportunistic pathogens. This current review summarizes these findings by highlighting the emerging roles of mucus and mucin-type O-glycans in influencing host and microbial physiology with an emphasis on host defense strategies against bacteria in the gastrointestinal tract.

MS-Decipher: a user-friendly proteome database search software with an emphasis on deciphering the spectra of O-linked glycopeptides

MOTIVATION

The interpretation of mass spectrometry (MS) data is a crucial step in proteomics analysis, and the identification of post-translational modifications (PTMs) is vital for the understanding of the regulation mechanism of the living system. Among various PTMs, glycosylation is one of the most diverse ones. Though many search engines have been developed to decipher proteomic data, some of them are difficult to operate and have poor performance on glycoproteomic datasets compared to advanced glycoproteomic software.

RESULTS

To simplify the analysis of proteomic datasets, especially O-glycoproteomic datasets, here, we present a user-friendly proteomic database search platform, MS-Decipher, for the identification of peptides from MS data. Two scoring schemes can be chosen for peptide-spectra matching. It was found that MS-Decipher had the same sensitivity and confidence in peptide identification compared to traditional database searching software. In addition, a special search mode, O-Search, is integrated into MS-Decipher to identify O-glycopeptides for O-glycoproteomic analysis. Compared with Mascot, MetaMorpheus and MSFragger, MS-Decipher can obtain about 139.9%, 48.8% and 6.9% more O-glycopeptide-spectrum matches. A useful tool is provided in MS-Decipher for the visualization of O-glycopeptide-spectra matches. MS-Decipher has a user-friendly graphical user interface, making it easier to operate. Several file formats are available in the searching and validation steps. MS-Decipher is implemented with Java, and can be used cross-platform.

AVAILABILITY AND IMPLEMENTATION

MS-Decipher is freely available at https://github.com/DICP-1809/MS-Decipher for academic use. For detailed implementation steps, please see the user guide.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Protein O-mannosylation across kingdoms and related diseases: From glycobiology to glycopathology

The post-translational glycosylation of proteins by O-linked α-mannose is conserved from bacteria to humans. Due to advances in high-throughput mass spectrometry-based approaches, a variety of glycoproteins are identified to be O-mannosylated. Various proteins with O-mannosylation are involved in biological processes, providing essential necessity for proper growth and development. In this review, we summarize the process and regulation of O-mannosylation. The multi-step O-mannosylation procedures are quite dynamic and complex, especially when considering the structural and functional inspection of the involved enzymes. The widely studied O-mannosylated proteins in human include α-Dystroglycan (α-DG), cadherins, protocadherins, and plexin, and their aberrant O-mannosylation are associated with many diseases. In addition, O-mannosylation also contributes to diverse functions in lower eukaryotes and prokaryotes. Finally, we present the relationship between O-mannosylation and gut microbiota (GM), and elucidate that O-mannosylation in microbiome is of great importance in the dynamic balance of GM. Our study provides an overview of the processes of O-mannosylation in mammalian cells and other organisms, and also associated regulated enzymes and biological functions, which could contribute to the understanding of newly discovered O-mannosylated glycoproteins.

Clinical importance of high-mannose, fucosylated and complex N-glycans in breast cancermetastasis

BACKGROUND. Although aberrant glycosylation is recognized as a hallmark of cancer, glycosylation in clinical breast cancer (BC) metastasis has not yet been studied. While preclinical studies show that the glycocalyx coating of cancer cells is involved in adhesion, migration, and metastasis, glycosylation changes from primary tumor (PT) to various metastatic sites remain unknown in patients.

METHODS. We investigated N-glycosylation profiles in 17 metastatic BC patients from our rapid autopsy program. Primary breast tumor, lymph node metastases, multiple systemic metastases, and various normal tissue cores from each patient were arranged on unique single-patient tissue microarrays (TMAs). We performed mass spectrometry imaging (MSI) combined with extensive pathology annotation of these TMAs, and this process enabled spatially differentiated cell-based analysis of N-glycosylation patterns in metastatic BC.

RESULTS. N-glycan abundance increased during metastatic progression independently of BC subtype and treatment regimen, with high-mannose glycans most frequently elevated in BC metastases, followed by fucosylated and complex glycans. Bone metastasis, however, displayed increased core-fucosylation and decreased high-mannose glycans. Consistently, N-glycosylated proteins and N-glycan biosynthesis genes were differentially expressed during metastatic BC progression, with reduced expression of mannose-trimming enzymes and with elevated EpCAM, N-glycan branching, and sialyation enzymes in BC metastases versus PT.

CONCLUSION. We show in patients that N-glycosylation of breast cancer cells undergoing metastasis occurs in a metastatic site–specific manner, supporting the clinical importance of high-mannose, fucosylated, and complex N-glycans as future diagnostic markers and therapeutic targets in metastatic BC.

FUNDING. NIH grants R01CA213428, R01CA213492, R01CA264901, T32CA193145, Dutch Province Limburg “LINK”, European Union ERA-NET TRANSCAN2-643638.

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.

Effective Enrichment Strategy Using Boronic Acid-Functionalized Mesoporous Graphene-Silica Composites for Intact N- and O-Linked Glycopeptide Analysis in Human Serum

The heterogeneity and low abundance of protein glycosylation present challenging barriers to the analysis of intact glycopeptides, which is key to comprehensively understanding the role of glycosylation in an organism. Efficient and specific enrichment of intact glycopeptides could help greatly with this problem. Here, we propose a new enrichment strategy using a boronic acid (BA)-functionalized mesoporous graphene-silica composite (denoted as GO@mSiO₂-GLYMO-APB) for isolating intact glycopeptides from complex biological samples. The merits of this composite, including high surface area and synergistic effect from size exclusion functionality of mesoporous material, hydrophilic interaction of silica, and the reversible covalent binding with BA, enable the effective and specific enrichment of both intact N- and O-glycopeptides. The results from the enrichment performance of the strategy evaluated by standard glycoproteins and the application to global N- and O-glycosylation analyses in human serum indicate the robustness and potential of the strategy for intact glycopeptide analysis.

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.

OGP: A Repository of Experimentally Characterized O-Glycoproteins to Facilitate Studies on O-Glycosylation

Numerous studies on cancers, biopharmaceuticals, and clinical trials have necessitated comprehensive and precise analysis of protein O-glycosylation. However, the lack of updated and convenient databases deters the storage of and reference to emerging O-glycoprotein data. To resolve this issue, an O-glycoprotein repository named OGP was established in this work. It was constructed with a collection of O-glycoprotein data from different sources. OGP contains 9354 O-glycosylation sites and 11,633 site-specific O-glycans mapping to 2133 O-glycoproteins, and it is the largest O-glycoprotein repository thus far. Based on the recorded O-glycosylation sites, an O-glycosylation site prediction tool was developed. Moreover, an OGP-based website is already available (https://www.oglyp.org/). The website comprises four specially designed and user-friendly modules: statistical analysis, database search, site prediction, and data submission. The first version of OGP repository and the website allow users to obtain various O-glycoprotein-related information, such as protein accession Nos., O-glycosylation sites, O-glycopeptide sequences, site-specific O-glycan structures, experimental methods, and potential O-glycosylation sites. O-glycosylation data mining can be performed efficiently on this website, which will greatly facilitate related studies. In addition, the database is accessible from OGP website (https://www.oglyp.org/download.php).

Recent Advances in Software Tools for More Generic and Precise Intact Glycopeptide Analysis

Intact glycopeptide identification has long been known as a key and challenging barrier to the comprehensive and accurate understanding the role of glycosylation in an organism. Intact glycopeptide analysis is a blossoming field that has received increasing attention in recent years. MS-based strategies and relative software tools are major drivers that have greatly facilitated the analysis of intact glycopeptides, particularly intact N-glycopeptides. This article provides a systematic review of the intact glycopeptide-identification process using MS data generated in shotgun proteomic experiments, which typically focus on N-glycopeptide analysis. Particular attention is paid to the software tools that have been recently developed in the last decade for the interpretation and quality control of glycopeptide spectra acquired using different MS strategies. The review also provides information about the characteristics and applications of these software tools, discusses their advantages and disadvantages, and concludes with a discussion of outstanding tools.

LectomeXplore, an update of UniLectin for the discovery of carbohydrate-binding proteins based on a new lectin classification

Lectins are non-covalent glycan-binding proteins mediating cellular interactions but their annotation in newly sequenced organisms is lacking. The limited size of functional domains and the low level of sequence similarity challenge usual bioinformatics tools. The identification of lectin domains in proteomes requires the manual curation of sequence alignments based on structural folds. A new lectin classification is proposed. It is built on three levels: (i) 35 lectin domain folds, (ii) 109 classes of lectins sharing at least 20% sequence similarity and (iii) 350 families of lectins sharing at least 70% sequence similarity. This information is compiled in the UniLectin platform that includes the previously described UniLectin3D database of curated lectin 3D structures. Since its first release, UniLectin3D has been updated with 485 additional 3D structures. The database is now complemented by two additional modules: PropLec containing predicted β-propeller lectins and LectomeXplore including predicted lectins from sequences of the NBCI-nr and UniProt for every curated lectin class. UniLectin is accessible at https://www.unilectin.eu/.

An ultrafast and highly efficient enrichment method for both N-Glycopeptides and N-Glycans by bacterial cellulose

A powerful and fast glycopeptide/glycan enrichment method is critical for the efficiency and throughput of mass spectrometry (MS)-based glycoproteomic and glycomic analyses, especially for large-scale sample analysis. Here, we report an ultrafast and effective method for both intact N-glycopeptide and N-glycan enrichment and apply it to human serum samples. In this method, a natural hydrophilic material, bacterial cellulose (BC), was adopted and fully optimized for enrichment. This method offers the following advantages: (i) The enrichment material has natural hydrophilicity and is low-cost, biocompatible, biodegradable and easily accessible; (ii) the whole enrichment procedure is remarkably simple and fast. It takes only 10 min for intact glycopeptides/glycans to be easily purified from mixtures; (iii) the specificity of this method is over 94% for both glycan and glycopeptide enrichment; and (iv) the outstanding specificity of this technique enables high isolation efficiency for the enrichment of both intact glycopeptides and glycans. A total of 36 N-glycans and 31 N-glycopeptides were identified from human immunoglobulin G (IgG). The glycan and glycopeptide absorption capacity of BC was as high as 333 μg/mg and 250 μg/mg (IgG/BC) respectively. The selectivity for glycan and glycopeptide enrichment reached 1:100 (IgG/bovine serum albumin (BSA), molar ratio) and 1:200 (maltoheptaose (DP7)/BSA, molar ratio), respectively. Furthermore, a total of 159 N-glycans and 523 N-glycopeptides were identified in human serum by using this method. Overall, the BC-based enrichment method we present here provides an ultrafast and highly efficient method for the enrichment of both N-glycopeptides and N-glycans in complex samples and shows great potential in large-scale glycoproteomic and glycomic analyses.

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.

Mass spectrometry for the identification and analysis of highly complex glycosylation of therapeutic or pathogenic proteins

INTRODUCTION

Protein glycosylation influences characteristics such as folding, stability, protein interactions, and solubility. Therefore, glycan moieties of therapeutic proteins and proteins that are likely associated with disease pathogenesis should be analyzed in-depth, including glycan heterogeneity and modification sites. Recent advances in analytical methods and instrumentation have enabled comprehensive characterization of highly complex glycosylated proteins.

AREA COVERED

The following aspects should be considered when analyzing glycosylated proteins: sample preparation, chromatographic separation, mass spectrometry (MS) and fragmentation methods, and bioinformatics, such as software solutions for data analyses. Notably, analysis of glycoproteins with heavily sialylated glycans or multiple glycosylation sites requires special considerations. Here, we discuss recent methodological advances in MS that provide detailed characterization of heterogeneous glycoproteins.

EXPERT OPINION

As characterization of complex glycosylated proteins is still analytically challenging, the function or pathophysiological significance of these proteins is not fully understood. To reproducibly produce desired forms of therapeutic glycoproteins or to fully elucidate disease-specific patterns of protein glycosylation, a highly reproducible and robust analytical platform(s) should be established. In addition to advances in MS instrumentation, optimization of analytical and bioinformatics methods and utilization of glycoprotein/glycopeptide standards is desirable. Ultimately, we envision that an automated high-throughput MS analysis will provide additional power to clinical studies and precision medicine.