N-GlycositeAtlas: a database resource for mass spectrometry-based human N-linked glycoprotein and glycosylation site mapping

Regulation of intracellular activity of N-glycan branching enzymes in mammals

Most proteins in the secretory pathway are glycosylated, and N-glycans are estimated to be attached to over 7000 proteins in humans. As structural variation of N-glycans critically regulates the functions of a particular glycoprotein, it is pivotal to understand how structural diversity of N-glycans is generated in cells. One of the major factors conferring structural variation of N-glycans is the variable number of N-acetylglucosamine branches. These branch structures are biosynthesized by dedicated glycosyltransferases, including GnT-III (MGAT3), GnT-IVa (MGAT4A), GnT-IVb (MGAT4B), GnT-V (MGAT5), and GnT-IX (GnT-Vb, MGAT5B). In addition, the presence or absence of core modification of N-glycans, namely, core fucose (included as an N-glycan branch in this manuscript), synthesized by FUT8, also confers large structural variation on N-glycans, thereby crucially regulating many protein-protein interactions. Numerous biochemical and medical studies have revealed that these branch structures are involved in a wide range of physiological and pathological processes. However, the mechanisms regulating the activity of the biosynthetic glycosyltransferases are yet to be fully elucidated. In this review, we summarize the previous findings and recent updates regarding regulation of the activity of these N-glycan branching enzymes. We hope that such information will help readers to develop a comprehensive overview of the complex system regulating mammalian N-glycan maturation.

MS-PyCloud: A Cloud Computing-Based Pipeline for Proteomic and Glycoproteomic Data Analyses

Rapid development and wide adoption of mass spectrometry-based glycoproteomic technologies have empowered scientists to study proteins and protein glycosylation in complex samples on a large scale. This progress has also created unprecedented challenges for individual laboratories to store, manage, and analyze proteomic and glycoproteomic data, both in the cost for proprietary software and high-performance computing and in the long processing time that discourages on-the-fly changes of data processing settings required in explorative and discovery analysis. We developed an open-source, cloud computing-based pipeline, MS-PyCloud, with graphical user interface (GUI), for proteomic and glycoproteomic data analysis. The major components of this pipeline include data file integrity validation, MS/MS database search for spectral assignments to peptide sequences, false discovery rate estimation, protein inference, quantitation of global protein levels, and specific glycan-modified glycopeptides as well as other modification-specific peptides such as phosphorylation, acetylation, and ubiquitination. To ensure the transparency and reproducibility of data analysis, MS-PyCloud includes open-source software tools with comprehensive testing and versioning for spectrum assignments. Leveraging public cloud computing infrastructure via Amazon Web Services (AWS), MS-PyCloud scales seamlessly based on analysis demand to achieve fast and efficient performance. Application of the pipeline to the analysis of large-scale LC-MS/MS data sets demonstrated the effectiveness and high performance of MS-PyCloud. The software can be downloaded at https://github.com/huizhanglab-jhu/ms-pycloud.

Systematic Investigation of the Trafficking of Glycoproteins on the Cell Surface

Glycoproteins located on the cell surface play a pivotal role in nearly every extracellular activity. N-glycosylation is one of the most common and important protein modifications in eukaryotic cells, and it often regulates protein folding and trafficking. Glycosylation of cell-surface proteins undergoes meticulous regulation by various enzymes in the endoplasmic reticulum (ER) and the Golgi, ensuring their proper folding and trafficking to the cell surface. However, the impacts of protein N-glycosylation, N-glycan maturity, and protein folding status on the trafficking of cell-surface glycoproteins remain to be explored. In this work, we comprehensively and site-specifically studied the trafficking of cell-surface glycoproteins in human cells. Integrating metabolic labeling, bioorthogonal chemistry, and multiplexed proteomics, we investigated 706 N-glycosylation sites on 396 cell-surface glycoproteins in monocytes, either by inhibiting protein N-glycosylation, disturbing N-glycan maturation, or perturbing protein folding in the ER. The current results reveal their distinct impacts on the trafficking of surface glycoproteins. The inhibition of protein N-glycosylation dramatically suppresses the trafficking of many cell-surface glycoproteins. The N-glycan immaturity has more substantial effects on proteins with high N-glycosylation site densities, while the perturbation of protein folding in the ER exerts a more pronounced impact on surface glycoproteins with larger sizes. Furthermore, for N-glycosylated proteins, their trafficking to the cell surface is related to the secondary structures and adjacent amino acid residues of glycosylation sites. Systematic analysis of surface glycoprotein trafficking advances our understanding of the mechanisms underlying protein secretion and surface presentation.

The Immunometabolic Gene N-Acetylglucosamine Kinase Is Uniquely Involved in the Heritability of Multiple Sclerosis Severity

The clinical severity of multiple sclerosis (MS), an autoimmune disorder of the central nervous system, is thought to be determined by environmental and genetic factors that have not yet been identified. In a recent genome-wide association study (GWAS), a single nucleotide polymorphism (SNP), rs10191329, has been associated with MS severity in two large independent cohorts of patients. Different approaches were followed by the authors to prioritize the genes that are transcriptionally regulated by such an SNP. It was concluded that the identified SNP regulates a group of proximal genes involved in brain resilience and cognitive abilities rather than immunity. Here, by conducting an alternative strategy for gene prioritization, we reached the opposite conclusion. According to our re-analysis, the main target of rs10191329 is N-Acetylglucosamine Kinase (NAGK), a metabolic gene recently shown to exert major immune functions via the regulation of the nucleotide-binding oligomerization domain-containing protein 2 (NOD2) pathway. To gain more insights into the immunometabolic functions of NAGK, we analyzed the currently known list of NAGK protein partners. We observed that NAGK integrates a dense network of human proteins that are involved in glucose metabolism and are highly expressed by classical monocytes. Our findings hold potentially major implications for the understanding of MS pathophysiology.

Recent Advancements in Subcellular Proteomics: Growing Impact of Organellar Protein Niches on the Understanding of Cell Biology

The mammalian cell is a complex entity, with membrane-bound and membrane-less organelles playing vital roles in regulating cellular homeostasis. Organellar protein niches drive discrete biological processes and cell functions, thus maintaining cell equilibrium. Cellular processes such as signaling, growth, proliferation, motility, and programmed cell death require dynamic protein movements between cell compartments. Aberrant protein localization is associated with a wide range of diseases. Therefore, analyzing the subcellular proteome of the cell can provide a comprehensive overview of cellular biology. With recent advancements in mass spectrometry, imaging technology, computational tools, and deep machine learning algorithms, studies pertaining to subcellular protein localization and their dynamic distributions are gaining momentum. These studies reveal changing interaction networks because of "moonlighting proteins" and serve as a discovery tool for disease network mechanisms. Consequently, this review aims to provide a comprehensive repository for recent advancements in subcellular proteomics subcontexting methods, challenges, and future perspectives for method developers. In summary, subcellular proteomics is crucial to the understanding of the fundamental cellular mechanisms and the associated diseases.

N-Glycosylation as a Modulator of Protein Conformation and Assembly in Disease

Glycosylation, a prevalent post-translational modification, plays a pivotal role in regulating intricate cellular processes by covalently attaching glycans to macromolecules. Dysregulated glycosylation is linked to a spectrum of diseases, encompassing cancer, neurodegenerative disorders, congenital disorders, infections, and inflammation. This review delves into the intricate interplay between glycosylation and protein conformation, with a specific focus on the profound impact of N-glycans on the selection of distinct protein conformations characterized by distinct interactomes-namely, protein assemblies-under normal and pathological conditions across various diseases. We begin by examining the spike protein of the SARS virus, illustrating how N-glycans regulate the infectivity of pathogenic agents. Subsequently, we utilize the prion protein and the chaperone glucose-regulated protein 94 as examples, exploring instances where N-glycosylation transforms physiological protein structures into disease-associated forms. Unraveling these connections provides valuable insights into potential therapeutic avenues and a deeper comprehension of the molecular intricacies that underlie disease conditions. This exploration of glycosylation's influence on protein conformation effectively bridges the gap between the glycome and disease, offering a comprehensive perspective on the therapeutic implications of targeting conformational mutants and their pathologic assemblies in various diseases. The goal is to unravel the nuances of these post-translational modifications, shedding light on how they contribute to the intricate interplay between protein conformation, assembly, and disease.

Identification and characterization of intact glycopeptides in human urine

Glycoproteins in urine have the potential to provide a rich class of informative molecules for studying human health and disease. Despite this promise, the urine glycoproteome has been largely uncharacterized. Here, we present the analysis of glycoproteins in human urine using LC-MS/MS-based intact glycopeptide analysis, providing both the identification of protein glycosites and characterization of the glycan composition at specific glycosites. Gene enrichment analysis reveals differences in biological processes, cellular components, and molecular functions in the urine glycoproteome versus the urine proteome, as well as differences based on the major glycan class observed on proteins. Meta-heterogeneity of glycosylation is examined on proteins to determine the variation in glycosylation across multiple sites of a given protein with specific examples of individual sites differing from the glycosylation trends in the overall protein. Taken together, this dataset represents a potentially valuable resource as a baseline characterization of glycoproteins in human urine for future urine glycoproteomics studies.

Hydrophilic Peptide and Glycopeptide as Immobilized Sorbents for Glycosylation Analysis

Hydrophilic interaction liquid chromatography (HILIC) is widely used for glycopeptide enrichment in shot-gun glycoproteomics to enhance the glycopeptide signal and minimize the ionization competition of peptides. In this work, we have developed a novel hydrophilic material (glycoHILIC) based on glycopeptides and peptides to provide hydrophilic properties. GlycoHILIC was synthesized by oxidizing cotton and then reacting the resulting aldehyde with the N-terminus of the glycopeptide or peptide by reductive amination. Due to the large amount of hydrophilic carbohydrates and hydrophilic amino acids contained in glycopeptides, glycoHILIC showed significantly better enrichment of glycopeptides than cotton itself. Our results demonstrate that glycoHILIC has high selectivity, a low detection limit, and good stability. Over 257 unique N-linked glycosylation sites in 1477 intact N-glycopeptides from 146 glycoproteins were identified from 1 μL of human serum using glycoHILIC. Serum analysis of pancreatic cancer patients found that 38 N-glycopeptides among 21 glycoproteins changed significantly, of which 7 N-glycopeptides increased and 31 N-glycopeptides decreased. These results demonstrate that glycoHILIC can be used for glycopeptide enrichment and analysis.

EMNGly: predicting N-linked glycosylation sites using the language models for feature extraction

MOTIVATION

N-linked glycosylation is a frequently occurring post-translational protein modification that serves critical functions in protein folding, stability, trafficking, and recognition. Its involvement spans across multiple biological processes and alterations to this process can result in various diseases. Therefore, identifying N-linked glycosylation sites is imperative for comprehending the mechanisms and systems underlying glycosylation. Due to the inherent experimental complexities, machine learning and deep learning have become indispensable tools for predicting these sites.

RESULTS

In this context, a new approach called EMNGly has been proposed. The EMNGly approach utilizes pretrained protein language model (Evolutionary Scale Modeling) and pretrained protein structure model (Inverse Folding Model) for features extraction and support vector machine for classification. Ten-fold cross-validation and independent tests show that this approach has outperformed existing techniques. And it achieves Matthews Correlation Coefficient, sensitivity, specificity, and accuracy of 0.8282, 0.9343, 0.8934, and 0.9143, respectively on a benchmark independent test set.

Molecular basis for bacterial N-glycosylation by a soluble HMW1C-like N-glycosyltransferase

Soluble HMW1C-like N-glycosyltransferases (NGTs) catalyze the glycosylation of Asn residues in proteins, a process fundamental for bacterial autoaggregation, adhesion and pathogenicity. However, our understanding of their molecular mechanisms is hindered by the lack of structures of enzymatic complexes. Here, we report structures of binary and ternary NGT complexes of Aggregatibacter aphrophilus NGT (AaNGT), revealing an essential dyad of basic/acidic residues located in the N-terminal all α-domain (AAD) that intimately recognizes the Thr residue within the conserved motif Asn0-X+1-Ser/Thr+2. Poor substrates and inhibitors such as UDP-galactose and UDP-glucose mimetics adopt non-productive conformations, decreasing or impeding catalysis. QM/MM simulations rationalize these results, showing that AaNGT follows a SN2 reaction mechanism in which the acceptor asparagine uses its imidic form for catalysis and the UDP-glucose phosphate group acts as a general base. These findings provide key insights into the mechanism of NGTs and will facilitate the design of structure-based inhibitors to treat diseases caused by non-typeable H. influenzae or other Gram-negative bacteria.

Whole proteome copy number dataset in primary mouse cortical neurons

The functional diversity of neurons is specified through their proteome resulting in elaborate and tightly regulated protein interaction networks and signalling that regulates neuronal processes. Dysregulation of these dynamic networks in development or in adulthood lead to neurodevelopmental or neurological disorders respectively. Over the past few decades, mass spectrometry has become a powerful tool for quantifying and resolving any proteome, including complex tissues such as the brain proteome, with technological advances leading to higher levels of resolution and throughput than traditional biochemical techniques. In this article, we provide a proteomic reference dataset that has been generated to identify proteins and quantify their level of expression in primary mouse cortical neurons. It represents a summary analysis of previously published data in (Antico et al., 2021). Mouse cortical neurons were isolated from E16.5 C57Bl/6J mice and cultured for 21 days in vitro (DIV). We employed the mitochondrial uncouplers AntimycinA/Oligomycin (AO) to induce mitochondrial depolarisation that is a well-established paradigm to assess mitophagic signalling. Total lysates from mouse primary cortical neurons were subjected to label-free quantitative proteomic analysis using both data dependent acquisition (DDA) and data independent acquisition (DIA) modes. DDA proteomic analysis identified a total dataset of 9367 proteins in mouse cortical neurons and absolute abundance of proteins was calculated as copy numbers per cell. DDA dataset was also processed to generate a reference spectral library to fit in and quantify MS spectra generated in DIA mode. Quantitative DIA analysis identified more than 6000 protein groups and statistical comparison of the two analysed groups (untreated and AO-treated) revealed that the neuronal proteome was largely unchanged post mitochondrial depolarisation for 5 hours. To our knowledge, these files represent the most comprehensive DDA and DIA reference datasets of fully functional maturated mouse primary cortical neurons and serve as a valuable resource for further investigating the role of specific proteins involved in neurobiology and neurological disorders such as Alzheimer's disease (AD), Parkinson's disease (PD) and Autism Spectrum Disorders (ASD).

Integrated glycoproteomic characterization of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC), a common form of RCC, is responsible for the high mortality rate of kidney cancer. Dysregulations of glycoproteins have been shown to associate with ccRCC. However, the molecular mechanism has not been well characterized. Here, a comprehensive glycoproteomic analysis is conducted using 103 tumors and 80 paired normal adjacent tissues. Altered glycosylation enzymes and corresponding protein glycosylation are observed, while two of the major ccRCC mutations, BAP1 and PBRM1, show distinct glycosylation profiles. Additionally, inter-tumor heterogeneity and cross-correlation between glycosylation and phosphorylation are observed. The relation of glycoproteomic features to genomic, transcriptomic, proteomic, and phosphoproteomic changes shows the role of glycosylation in ccRCC development with potential for therapeutic interventions. This study reports a large-scale tandem mass tag (TMT)-based quantitative glycoproteomic analysis of ccRCC that can serve as a valuable resource for the community.

Critical considerations in N-glycoproteomics

N-Glycoproteomics, the system-wide study of glycans asparagine-linked to protein carriers, holds a unique and still largely untapped potential to provide deep insights into the complexity and dynamics of the heterogeneous N-glycoproteome. Despite the advent of innovative analytical and informatics tools aiding the analysis, N-glycoproteomics remains challenging and consequently largely restricted to specialised laboratories. Aiming to stimulate discussions of method harmonisation, data standardisation and reporting guidelines to make N-glycoproteomics more reproducible and accessible to the community, we here discuss critical considerations related to the design and execution of N-glycoproteomics experiments and highlight good practices in N-glycopeptide data collection, analysis, interpretation and sharing. Giving the rapid maturation and, expectedly, a wide-spread implementation of N-glycoproteomics capabilities across the community in future years, this piece aims to point out common pitfalls, to encourage good data sharing and documentation practices, and to highlight practical solutions and strategies to enhance the insight into the N-glycoproteome.

N-glycosylation of serum proteins in adult type 1 diabetes mellitus exposes further changes compared to children at the disease onset

OBJECTIVE

Previously we have shown that plasma protein N-glycosylation is changed in children at the onset of type 1 diabetes. In this study, we aim to identify N-glycan changes in adults with T1DM, compare them to those in children, and investigate their associations with disease duration, complications, glycaemic status, and smoking.

METHODS

Serum protein N-glycans from 200 adults with type 1 diabetes and 298 healthy controls were analysed using ultra-high performance liquid chromatography and divided into 39 directly measured glycan groups from which 16 derived traits were calculated.

RESULTS

Compared to healthy controls, subjects with type 1 diabetes showed differences in 19 glycan groups and a decrease in monogalactosylated, an increase in digalactosylated, monosialylated, and antennary fucosylated derived traits, from which changes in monogalactosylation and seven directly measured traits overlapped with previously reported in children. Changes in four directly measured and two derived traits previously seen in children were not detected in adults. HbA1c was positively associated with sialylated and highly branched structures, whereas N-glycome was not influenced by disease duration or diabetic complications.

CONCLUSIONS

Our results suggest potential N-glycome involvement in different stages of type 1 diabetes, including processes underlying its development, the disease itself, as well as those occurring after disease establishment.

Post-translational proteomics platform identifies neurite outgrowth impairments in Parkinson's disease GBA-N370S dopamine neurons

Variants at the GBA locus, encoding glucocerebrosidase, are the strongest common genetic risk factor for Parkinson's disease (PD). To understand GBA-related disease mechanisms, we use a multi-part-enrichment proteomics and post-translational modification (PTM) workflow, identifying large numbers of dysregulated proteins and PTMs in heterozygous GBA-N370S PD patient induced pluripotent stem cell (iPSC) dopamine neurons. Alterations in glycosylation status show disturbances in the autophagy-lysosomal pathway, which concur with upstream perturbations in mammalian target of rapamycin (mTOR) activation in GBA-PD neurons. Several native and modified proteins encoded by PD-associated genes are dysregulated in GBA-PD neurons. Integrated pathway analysis reveals impaired neuritogenesis in GBA-PD neurons and identify tau as a key pathway mediator. Functional assays confirm neurite outgrowth deficits and identify impaired mitochondrial movement in GBA-PD neurons. Furthermore, pharmacological rescue of glucocerebrosidase activity in GBA-PD neurons improves the neurite outgrowth deficit. Overall, this study demonstrates the potential of PTMomics to elucidate neurodegeneration-associated pathways and potential drug targets in complex disease models.

Protein glycosylation in urine as a biomarker of diseases

Human body fluids have become an indispensable resource for clinical research, diagnosis and prognosis. Urine is widely used to discover disease-specific glycoprotein biomarkers because of its recurrently non-invasive collection and disease-indicating properties. While urine is an unstable fluid in that its composition changes with ingested nutrients and further as it is excreted through micturition, urinary proteins are more stable and their abnormal glycosylation is associated with diseases. It is known that aberrant glycosylation can define tumor malignancy and indicate disease initiation and progression. However, a thorough and translational survey of urinary glycosylation in diseases has not been performed. In this article, we evaluate the clinical applications of urine, introduce methods for urine glycosylation analysis, and discuss urine glycoprotein biomarkers. We emphasize the importance of mining urinary glycoproteins and searching for disease-specific glycosylation in various diseases (including cancer, neurodegenerative diseases, diabetes, and viral infections). With advances in mass spectrometry-based glycomics/glycoproteomics/glycopeptidomics, characterization of disease-specific glycosylation will optimistically lead to the discovery of disease-related urinary biomarkers with better sensitivity and specificity in the near future.

Systematic characterization of extracellular glycoproteins using mass spectrometry

Surface and secreted glycoproteins are essential to cells and regulate many extracellular events. Because of the diversity of glycans, the low abundance of many glycoproteins, and the complexity of biological samples, a system-wide investigation of extracellular glycoproteins is a daunting task. With the development of modern mass spectrometry (MS)-based proteomics, comprehensive analysis of different protein modifications including glycosylation has advanced dramatically. This review focuses on the investigation of extracellular glycoproteins using MS-based proteomics. We first discuss the methods for selectively enriching surface glycoproteins and investigating protein interactions on the cell surface, followed by the application of MS-based proteomics for surface glycoprotein dynamics analysis and biomarker discovery. We then summarize the methods to comprehensively study secreted glycoproteins by integrating various enrichment approaches with MS-based proteomics and their applications for global analysis of secreted glycoproteins in different biological samples. Collectively, MS significantly expands our knowledge of extracellular glycoproteins and enables us to identify extracellular glycoproteins as potential biomarkers for disease detection and drug targets for disease treatment.

GlycoSLASH: Concurrent Glycopeptide Identification from Multiple Related LC-MS/MS Data Sets by Using Spectral Clustering and Library Searching

Liquid chromatography coupled with tandem mass spectrometry is commonly adopted in large-scale glycoproteomic studies involving hundreds of disease and control samples. The software for glycopeptide identification in such data (e.g., the commercial software Byonic) analyzes the individual data set and does not exploit the redundant spectra of glycopeptides presented in the related data sets. Herein, we present a novel concurrent approach for glycopeptide identification in multiple related glycoproteomic data sets by using spectral clustering and spectral library searching. The evaluation on two large-scale glycoproteomic data sets showed that the concurrent approach can identify 105%-224% more spectra as glycopeptides compared to the glycopeptide identification on individual data sets using Byonic alone. The improvement of glycopeptide identification also enabled the discovery of several potential biomarkers of protein glycosylations in hepatocellular carcinoma patients.

Quantitative analysis of fucosylated glycoproteins by immobilized lectin-affinity fluorescent labeling

Human biofluids are often used to discover disease-specific glycosylation, since abnormal changes in protein glycosylation can discern physiopathological states. Highly glycosylated proteins in biofluids make it possible to identify disease signatures. Glycoproteomic studies on saliva glycoproteins showed that fucosylation was significantly increased during tumorigenesis and that glycoproteins became hyperfucosylated in lung metastases, and tumor stage is associated with fucosylation. Quantification of salivary fucosylation can be achieved by mass spectrometric analysis of fucosylated glycoproteins or fucosylated glycans; however, the use of mass spectrometry is non-trivial for clinical practice. Here, we developed a high-throughput quantitative method, lectin-affinity fluorescent labeling quantification (LAFLQ), to quantify fucosylated glycoproteins without relying on mass spectrometry. Lectins with a specific affinity for fucoses are immobilized on the resin and effectively capture fluorescently labeled fucosylated glycoproteins, which are further quantitatively characterized by fluorescence detection in a 96-well plate. Our results demonstrated that serum IgG can be accurately quantified by lectin and fluorescence detection. Quantification in saliva showed significantly higher fucosylation in lung cancer patients compared to healthy controls or other non-cancer diseases, suggesting that this method has the potential to quantify stage-related fucosylation in lung cancer saliva.

Lectin-Based Affinity Enrichment and Characterization of N-Glycoproteins from Human Tear Film by Mass Spectrometry

The glycosylation of proteins is one of the most common post-translational modifications (PTMs) and plays important regulatory functions in diverse biological processes such as protein stability or cell signaling. Accordingly, glycoproteins are also a consistent part of the human tear film proteome, maintaining the proper function of the ocular surface and forming the first defense barrier of the ocular immune system. Irregularities in the glycoproteomic composition of tear film might promote the development of chronic eye diseases, indicating glycoproteins as a valuable source for biomarker discovery or drug target identification. Therefore, the present study aimed to develop a lectin-based affinity method for the enrichment and concentration of tear glycoproteins/glycopeptides and to characterize their specific N-glycosylation sites by high-resolution mass spectrometry (MS). For method development and evaluation, we first accumulated native glycoproteins from human tear sample pools and assessed the enrichment efficiency of different lectin column systems by 1D gel electrophoresis and specific protein stainings (Coomassie and glycoproteins). The best-performing multi-lectin column system (comprising the four lectins ConA, JAC, WGA, and UEA I, termed 4L) was applied to glycopeptide enrichment from human tear sample digests, followed by MS-based detection and localization of their specific N-glycosylation sites. As the main result, our study identified a total of 26 N glycosylation sites of 11 N-glycoproteins in the tear sample pools of healthy individuals (n = 3 biological sample pools). Amongst others, we identified tear film proteins lactotransferrin (N497 and N642, LTF), Ig heavy chain constant α-1 (N144 and 340, IGHA1), prolactin-inducible protein (N105, PIP), and extracellular lacritin (N105, LACRT) as highly reliable and significant N glycoproteins, already associated with the pathogenesis of various chronic eye diseases such as dry eye syndrome (DES). In conclusion, the results of the present study will serve as an important tear film N-glycoprotein catalog for future studies focusing on human tear film and ocular surface-related inflammatory diseases.

Deciphering O-glycoprotease substrate preferences with O-Pair Search

O-Glycoproteases are an emerging class of enzymes that selectively digest glycoproteins at positions decorated with specific O-linked glycans. O-Glycoprotease substrates range from any O-glycoprotein (albeit with specific O-glycan modifications) to only glycoproteins harboring specific O-glycosylated sequence motifs, such as those found in mucin domains. Their utility for multiple glycoproteomic applications is driving the search to both discover new O-glycoproteases and to understand how structural features of characterized O-glycoproteases influence their substrate specificities. One challenge of defining O-glycoprotease specificity restraints is the need to characterize O-glycopeptides with site-specific analysis of O-glycosites. Here, we demonstrate how O-Pair Search, a recently developed O-glycopeptide-centric identification platform that enables rapid searches and confident O-glycosite localization, can be used to determine substrate specificities of various O-glycoproteases de novo from LC-MS/MS data of O-glycopeptides. Using secreted protease of C1 esterase inhibitor (StcE) from enterohemorrhagic Escherichia coli and O-endoprotease OgpA from Akkermansia mucinophila, we explore numerous settings that effect O-glycopeptide identification and show how non-specific and semi-tryptic searches of O-glycopeptide data can produce candidate cleavage motifs. These putative motifs can be further used to define new protease cleavage settings that lower search times and improve O-glycopeptide identifications. We use this platform to generate a consensus motif for the recently characterized immunomodulating metalloprotease (IMPa) from Pseudomonas aeruginosa and show that IMPa is a favorable O-glycoprotease for characterizing densely O-glycosylated mucin-domain glycoproteins.

Glycoinformatics in the Artificial Intelligence Era

Artificial intelligence (AI) methods have been and are now being increasingly integrated in prediction software implemented in bioinformatics and its glycoscience branch known as glycoinformatics. AI techniques have evolved in the past decades, and their applications in glycoscience are not yet widespread. This limited use is partly explained by the peculiarities of glyco-data that are notoriously hard to produce and analyze. Nonetheless, as time goes, the accumulation of glycomics, glycoproteomics, and glycan-binding data has reached a point where even the most recent deep learning methods can provide predictors with good performance. We discuss the historical development of the application of various AI methods in the broader field of glycoinformatics. A particular focus is placed on shining a light on challenges in glyco-data handling, contextualized by lessons learnt from related disciplines. Ending on the discussion of state-of-the-art deep learning approaches in glycoinformatics, we also envision the future of glycoinformatics, including development that need to occur in order to truly unleash the capabilities of glycoscience in the systems biology era.

qPTM: an updated database for PTM dynamics in human, mouse, rat and yeast

Post-translational modifications (PTMs) are critical molecular mechanisms that regulate protein functions temporally and spatially in various organisms. Since most PTMs are dynamically regulated, quantifying PTM events under different states is crucial for understanding biological processes and diseases. With the rapid development of high-throughput proteomics technologies, massive quantitative PTM proteome datasets have been generated. Thus, a comprehensive one-stop data resource for surfing big data will benefit the community. Here, we updated our previous phosphorylation dynamics database qPhos to the qPTM (http://qptm.omicsbio.info). In qPTM, 11 482 553 quantification events among six types of PTMs, including phosphorylation, acetylation, glycosylation, methylation, SUMOylation and ubiquitylation in four different organisms were collected and integrated, and the matched proteome datasets were included if available. The raw mass spectrometry based false discovery rate control and the recurrences of identifications among datasets were integrated into a scoring system to assess the reliability of the PTM sites. Browse and search functions were improved to facilitate users in swiftly and accurately acquiring specific information. The results page was revised with more abundant annotations, and time-course dynamics data were visualized in trend lines. We expected the qPTM database to be a much more powerful and comprehensive data repository for the PTM research community.

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.

Mass spectrometry-based N-glycosylation analysis in kidney disease

Kidney disease is a global health concern with an enormous expense. It is estimated that more than 10% of the population worldwide is affected by kidney disease and millions of patients would progress to death prematurely and unnecessarily. Although creatinine detection and renal biopsy are well-established tools for kidney disease diagnosis, they are limited by several inevitable defects. Therefore, diagnostic tools need to be upgraded, especially for the early stage of the disease and possible progression. As one of the most common post-translational modifications of proteins, N-glycosylation plays a vital role in renal structure and function. Deepening research on N-glycosylation in kidney disease provides new insights into the pathophysiology and paves the way for clinical application. In this study, we reviewed recent N-glycosylation studies on several kidney diseases. We also summarized the development of mass spectrometric methods in the field of N-glycoproteomics and N-glycomics.

TNFα-induced metabolic reprogramming drives an intrinsic anti-viral state

Cytokines induce an anti-viral state, yet many of the functional determinants responsible for limiting viral infection are poorly understood. Here, we find that TNFα induces significant metabolic remodeling that is critical for its anti-viral activity. Our data demonstrate that TNFα activates glycolysis through the induction of hexokinase 2 (HK2), the isoform predominantly expressed in muscle. Further, we show that glycolysis is broadly important for TNFα-mediated anti-viral defense, as its inhibition attenuates TNFα’s ability to limit the replication of evolutionarily divergent viruses. TNFα was also found to modulate the metabolism of UDP-sugars, which are essential precursor substrates for glycosylation. Our data indicate that TNFα increases the concentration of UDP-glucose, as well as the glucose-derived labeling of UDP-glucose and UDP-N-acetyl-glucosamine in a glycolytically-dependent manner. Glycolysis was also necessary for the TNFα-mediated accumulation of several glycosylated anti-viral proteins. Consistent with the importance of glucose-driven glycosylation, glycosyl-transferase inhibition attenuated TNFα’s ability to promote the anti-viral cell state. Collectively, our data indicate that cytokine-mediated metabolic remodeling is an essential component of the anti-viral response.

Viral infection often activates a host cell’s intrinsic immune response resulting in the cellular secretion of cytokines, important host-defense molecules. These cytokines act on neighboring cells to make them less permissive to viral infection. Many of the mechanisms through which cytokines promote a less permissive cell state remain unclear. Our data indicate that treatment with the anti-viral cytokine TNFα induces substantial changes to cellular metabolic activity, including activating glucose metabolism. We find that these TNFα-induced metabolic changes are critical for TNFα to limit the replication of diverse viruses including Human Cytomegalovirus and two Coronaviruses, OC43 and SARS-CoV-2. Inhibition of glucose metabolism during TNFα treatment prevented the expression of a variety of known cellular anti-viral proteins. Collectively, our data indicate that cytokine-induced metabolic remodeling is an important component of TNFα’s ability to promote a less permissive cell state and raises further questions about the mechanisms through which specific cytokine-induced metabolic activities contribute to various aspects of anti-viral defense.

Mass Spectrometry-Based Analysis of Serum N-Glycosylation Changes in Patients with Parkinson's Disease

It is urgently needed to find reliable biofluid biomarkers for early diagnosis of Parkinson's disease in order to achieve better treatment. Promising biomarkers can be found in Parkinson's disease-related glycoproteins as aberrant protein glycosylation plays an important role in disease progression. However, current information on serum N-glycoproteomic changes in Parkinson's disease is still limited. Here, we used glycoproteomics methods, which combine the solid-phase chemoenzymatic method, lectin affinity chromatography, and hydrophilic interaction chromatography with high-resolution mass spectrometry, to analyze the glycans, glycosites, and intact glycopeptides of serum. Increased abundance of glycans containing core fucose, sialic acid, and bisecting N-acetyl glucosamine was detected at the overall glycan level and also at specific glycosites of glycopeptides. Five Parkinson's disease-associated proteins with this type of N-glycosylation changes were also identified. We propose that the revealed site-specific N-glycosylation changes in serum can be potential biomarkers for Parkinson's disease.

Cell-type-specific labeling and profiling of glycans in living mice

Metabolic labeling of glycans with clickable unnatural sugars has enabled glycan analysis in multicellular systems. However, cell-type-specific labeling of glycans in vivo remains challenging. Here we develop genetically encoded metabolic glycan labeling (GeMGL), a cell-type-specific strategy based on a bump-and-hole pair of an unnatural sugar and its matching engineered enzyme. N-pentynylacetylglucosamine (GlcNAl) serves as a bumped analog of N-acetylglucosamine (GlcNAc) that is specifically incorporated into glycans of cells expressing a UDP-GlcNAc pyrophosphorylase mutant, AGX2^F383G. GeMGL with the 1,3-di-O-propionylated GlcNAl (1,3-Pr₂GlcNAl) and AGX2^F383G pair was demonstrated in cell cocultures, and used for specific labeling of glycans in mouse xenograft tumors. By generating a transgenic mouse line with AGX2^F383G expressed under a cardiomyocyte-specific promoter, we performed specific imaging of cardiomyocyte glycans in the heart and identified 582 cardiomyocyte O-GlcNAcylated proteins with no interference from other cardiac cell types. GeMGL will facilitate cell-type-specific glycan imaging and glycoproteomics in various tissues and disease models.

Recent advancements in glycoproteomic studies: Glycopeptide enrichment and derivatization, characterization of glycosylation in SARS CoV2, and interacting glycoproteins

Proteomics studies allow for the determination of the identity, amount, and interactions of proteins under specific conditions that allow the biological state of an organism to ultimately change. These conditions can be either beneficial or detrimental. Diseases are due to detrimental changes caused by either protein overexpression or underexpression caused by as a result of a mutation or posttranslational modifications (PTM), among other factors. Identification of disease biomarkers through proteomics can be potentially used as clinical information for diagnostics. Common biomarkers to look for include PTM. For example, aberrant glycosylation of proteins is a common marker and will be a focus of interest in this review. A common way to analyze glycoproteins is by glycoproteomics involving mass spectrometry. Due to factors such as micro- and macroheterogeneity which result in a lower abundance of each version of a glycoprotein, it is difficult to obtain meaningful results unless rigorous sample preparation procedures are in place. Microheterogeneity represents the diversity of glycans at a single site, whereas macroheterogeneity depicts glycosylation levels at each site of a protein. Enrichment and derivatization of glycopeptides help to overcome these limitations. Over the time range of 2016 to 2020, several methods have been proposed in the literature and have contributed to drastically improve the outcome of glycosylation analysis, as presented in the sampling surveyed in this review. As a current topic in 2020, glycoproteins carried by pathogens can also cause disease and this is seen with SARS CoV2, causing the COVID-19 pandemic. This review will discuss glycoproteomic studies of the spike glycoprotein and interacting proteins such as the ACE2 receptor.

Precision glycoproteomics reveals distinctive N-glycosylation in human spermatozoa

Spermatozoon represents a very special cell type in human body, and glycosylation plays essential roles in its whole life including spermatogenesis, maturation, capacitation, sperm–egg recognition, and fertilization. In this study, by mapping the most comprehensive N-glycoproteome of human spermatozoa using our recently developed site-specific glycoproteomic approaches, we show that spermatozoa contain a number of distinctive glycoproteins, which are mainly involved in spermatogenesis, acrosome reaction and sperm:oocyte membrane binding, and fertilization. Heavy fucosylation is observed on 14 glycoproteins mostly located at extracellular and cell surface regions in spermatozoa but not in other tissues. Sialylation and Lewis epitopes are enriched in the biological process of immune response in spermatozoa, while bisected core structures and LacdiNAc structures are highly expressed in acrosome. These data deepen our knowledge about glycosylation in spermatozoa and lay the foundation for functional study of glycosylation and glycan structures in male infertility.

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A precision site-specific glycoproteome is documented in human spermatozoa.

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Distinctive glycoproteins and heavy fucosylation are detected in spermatozoa.

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Sialylation and Lewis epitopes are related to immune response of spermatozoa.

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Bisected core structures and LacdiNAc are enriched on acrosome of spermatozoa.

O-GlcNAcylation regulates β1,4-GlcNAc-branched N-glycan biosynthesis via the OGT/SLC35A3/GnT-IV axis

N-Linked glycosylation and O-linked N-acetylglucosamine (O-GlcNAc) are important protein post-translational modifications that are orchestrated by a diverse set of gene products. Thus far, the relationship between these two types of glycosylation has remained elusive, and it is unclear whether one influences the other via UDP-GlcNAc, which is a common donor substrate. Theoretically, a decrease in O-GlcNAcylation may increase the products of GlcNAc-branched N-glycans. In this study, via examination by lectin blotting, HPLC, and mass spectrometry analysis, however, we found that the amounts of GlcNAc-branched tri-antennary N-glycans catalyzed by N-acetylglucosaminyltransferase IV (GnT-IV) and tetra-antennary N-glycans were significantly decreased in O-GlcNAc transferase knockdown cells (OGT-KD) compared with those in wild type cells. We examined this specific alteration by focusing on SLC35A3, which is the main UDP-GlcNAc transporter in mammals that is believed to modulate GnT-IV activation. It is interesting that a deficiency of SLC35A3 specifically leads to a decrease in the amounts of GlcNAc-branched tri- and tetra-antennary N-glycans. Furthermore, co-immunoprecipitation experiments have shown that SLC35A3 interacts with GnT-IV, but not with N-acetylglucosaminyltransferase V. Western blot and chemoenzymatic labeling assay have confirmed that OGT modifies SLC35A3 and that O-GlcNAcylation contributes to its stability. Furthermore, we found that SLC35A3-KO enhances cell spreading and suppresses both cell migration and cell proliferation, which is similar to the phenomena observed in the OGT-KD cells. Taken together, these data are the first to demonstrate that O-GlcNAcylation specifically governs the biosynthesis of tri- and tetra-antennary N-glycans via the OGT-SLC35A3-GnT-IV axis.

OmicsOne: associate omics data with phenotypes in one-click

BACKGROUND

The rapid advancements of high throughput "omics" technologies have brought a massive amount of data to process during and after experiments. Multi-omic analysis facilitates a deeper interrogation of a dataset and the discovery of interesting genes, proteins, lipids, glycans, metabolites, or pathways related to the corresponding phenotypes in a study. Many individual software tools have been developed for data analysis and visualization. However, it still lacks an efficient way to investigate the phenotypes with multiple omics data. Here, we present OmicsOne as an interactive web-based framework for rapid phenotype association analysis of multi-omic data by integrating quality control, statistical analysis, and interactive data visualization on 'one-click'.

MATERIALS AND METHODS

OmicsOne was applied on the previously published proteomic and glycoproteomic data sets of high-grade serous ovarian carcinoma (HGSOC) and the published proteome data set of lung squamous cell carcinoma (LSCC) to confirm its performance. The data was analyzed through six main functional modules implemented in OmicsOne: (1) phenotype profiling, (2) data preprocessing and quality control, (3) knowledge annotation, (4) phenotype associated features discovery, (5) correlation and regression model analysis for phenotype association analysis on individual features, and (6) enrichment analysis for phenotype association analysis on interested feature sets.

RESULTS

We developed an integrated software solution, OmicsOne, for the phenotype association analysis on multi-omics data sets. The application of OmicsOne on the public data set of ovarian cancer data showed that the software could confirm the previous observations consistently and discover new evidence for HNRNPU and a glycopeptide of HYOU1 as potential biomarkers for HGSOC data sets. The performance of OmicsOne was further demonstrated in the Tumor and NAT comparison study on the proteome data set of LSCC.

CONCLUSIONS

OmicsOne can effectively simplify data analysis and reveal the significant associations between phenotypes and potential biomarkers, including genes, proteins, and glycopeptides, in minutes to assist users to understand aberrant biological processes.

DeepNGlyPred: A Deep Neural Network-Based Approach for Human N-Linked Glycosylation Site Prediction

Protein N-linked glycosylation is a post-translational modification that plays an important role in a myriad of biological processes. Computational prediction approaches serve as complementary methods for the characterization of glycosylation sites. Most of the existing predictors for N-linked glycosylation utilize the information that the glycosylation site occurs at the N-X-[S/T] sequon, where X is any amino acid except proline. Not all N-X-[S/T] sequons are glycosylated, thus the N-X-[S/T] sequon is a necessary but not sufficient determinant for protein glycosylation. In that regard, computational prediction of N-linked glycosylation sites confined to N-X-[S/T] sequons is an important problem. Here, we report DeepNGlyPred a deep learning-based approach that encodes the positive and negative sequences in the human proteome dataset (extracted from N-GlycositeAtlas) using sequence-based features (gapped-dipeptide), predicted structural features, and evolutionary information. DeepNGlyPred produces SN, SP, MCC, and ACC of 88.62%, 73.92%, 0.60, and 79.41%, respectively on N-GlyDE independent test set, which is better than the compared approaches. These results demonstrate that DeepNGlyPred is a robust computational technique to predict N-Linked glycosylation sites confined to N-X-[S/T] sequon. DeepNGlyPred will be a useful resource for the glycobiology community.

Proteogenomic characterization of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with poor patient survival. Toward understanding the underlying molecular alterations that drive PDAC oncogenesis, we conducted comprehensive proteogenomic analysis of 140 pancreatic cancers, 67 normal adjacent tissues, and 9 normal pancreatic ductal tissues. Proteomic, phosphoproteomic, and glycoproteomic analyses were used to characterize proteins and their modifications. In addition, whole-genome sequencing, whole-exome sequencing, methylation, RNA sequencing (RNA-seq), and microRNA sequencing (miRNA-seq) were performed on the same tissues to facilitate an integrated proteogenomic analysis and determine the impact of genomic alterations on protein expression, signaling pathways, and post-translational modifications. To ensure robust downstream analyses, tumor neoplastic cellularity was assessed via multiple orthogonal strategies using molecular features and verified via pathological estimation of tumor cellularity based on histological review. This integrated proteogenomic characterization of PDAC will serve as a valuable resource for the community, paving the way for early detection and identification of novel therapeutic targets.

The structure of an archaeal oligosaccharyltransferase provides insight into the strict exclusion of proline from the N-glycosylation sequon

Oligosaccharyltransferase (OST) catalyzes oligosaccharide transfer to the Asn residue in the N-glycosylation sequon, Asn-X-Ser/Thr, where Pro is strictly excluded at position X. Considering the unique structural properties of proline, this exclusion may not be surprising, but the structural basis for the rejection of Pro residues should be explained explicitly. Here we determined the crystal structure of an archaeal OST in a complex with a sequon-containing peptide and dolichol-phosphate to a 2.7 Å resolution. The sequon part in the peptide forms two inter-chain hydrogen bonds with a conserved amino acid motif, TIXE. We confirmed the essential role of the TIXE motif and the adjacent regions by extensive alanine-scanning of the external loop 5. A Ramachandran plot revealed that the ring structure of the Pro side chain is incompatible with the ϕ backbone dihedral angle around -150° in the rigid sequon-TIXE structure. The present structure clearly provides the structural basis for the exclusion of Pro residues from the N-glycosylation sequon.

Affinity proteomics and deglycoproteomics uncover novel EDEM2 endogenous substrates and an integrative ERAD network

Various pathologies result from disruptions to or stress of endoplasmic reticulum (ER) homeostasis, such as Parkinson's disease and most neurodegenerative illnesses, diabetes, pulmonary fibrosis, viral infections and cancers. A critical process in maintaining ER homeostasis is the selection of misfolded proteins by the ER quality-control system (ERQC) for destruction via ER-associated degradation (ERAD). One key protein proposed to act during the first steps of misfolded glycoprotein degradation is the ER degradation-enhancing α-mannosidase-like protein 2 (EDEM2). Therefore, characterization of the EDEM2 associated proteome is of great interest. We took advantage of using melanoma cells overexpressing EDEM2 as a cancer model system, to start documenting at the deglycoproteome level (N-glycosites identification) the emerging link between ER homeostasis and cancer progression. The dataset created for identifying the EDEM2 glyco-clients carrying high mannose/hybrid N-glycans provides a comprehensive N-glycosites analysis mapping over 1000 N-glycosites on more than 600 melanoma glycoproteins. To identify EDEM2-associated proteins we used affinity-proteomics and proteome-wide analysis of sucrose density fractionation in an integrative workflow. Using intensity and spectral count-based quantification, we identify seven new EDEM2 partners, all of which are involved in ERQC and ERAD. Moreover, we defined novel endogenous candidates for EDEM2-dependent ERAD by combining deglycoproteomics, SILAC-based proteomics, and biochemical methods. These included tumor antigens and several ER-transiting endogenous melanoma proteins, including ITGA1 and PCDH2, the expression of which was negatively correlated with that of EDEM2. Tumor antigens are key in the antigen presentation process, whilst ITGA1 and PCDH2 are involved in melanoma metastasis and invasion. EDEM2 could therefore have a regulatory role in melanoma through the modulation of these glycoproteins degradation and trafficking. The data presented herein suggest that EDEM2 is involved in ER homeostasis to a greater extent than previously suggested.

Differential Glycosite Profiling-A Versatile Method to Compare Membrane Glycoproteomes

Glycosylation is the most prevalent and varied form of post-translational protein modifications. Protein glycosylation regulates multiple cellular functions, including protein folding, cell adhesion, molecular trafficking and clearance, receptor activation, signal transduction, and endocytosis. In particular, membrane proteins are frequently highly glycosylated, which is both linked to physiological processes and of high relevance in various disease mechanisms. The cellular glycome is increasingly considered to be a therapeutic target. Here we describe a new strategy to compare membrane glycoproteomes, thereby identifying proteins with altered glycan structures and the respective glycosites. The workflow started with an optimized procedure for the digestion of membrane proteins followed by the lectin-based isolation of glycopeptides. Since alterations in the glycan part of a glycopeptide cause mass alterations, analytical size exclusion chromatography was applied to detect these mass shifts. N-glycosidase treatment combined with nanoUPLC-coupled mass spectrometry identified the altered glycoproteins and respective glycosites. The methodology was established using the colon cancer cell line CX1, which was treated with 2-deoxy-glucose-a modulator of N-glycosylation. The described methodology is not restricted to cell culture, as it can also be adapted to tissue samples or body fluids. Altogether, it is a useful module in various experimental settings that target glycan functions.

An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility

BACKGROUND

While genome-wide associations studies (GWAS) have successfully elucidated the genetic architecture of complex human traits and diseases, understanding mechanisms that lead from genetic variation to pathophysiology remains an important challenge. Methods are needed to systematically bridge this crucial gap to facilitate experimental testing of hypotheses and translation to clinical utility.

RESULTS

Here, we leveraged cross-phenotype associations to identify traits with shared genetic architecture, using linkage disequilibrium (LD) information to accurately capture shared SNPs by proxy, and calculate significance of enrichment. This shared genetic architecture was examined across differing biological scales through incorporating data from catalogs of clinical, cellular, and molecular GWAS. We have created an interactive web database (interactive Cross-Phenotype Analysis of GWAS database (iCPAGdb)) to facilitate exploration and allow rapid analysis of user-uploaded GWAS summary statistics. This database revealed well-known relationships among phenotypes, as well as the generation of novel hypotheses to explain the pathophysiology of common diseases. Application of iCPAGdb to a recent GWAS of severe COVID-19 demonstrated unexpected overlap of GWAS signals between COVID-19 and human diseases, including with idiopathic pulmonary fibrosis driven by the DPP9 locus. Transcriptomics from peripheral blood of COVID-19 patients demonstrated that DPP9 was induced in SARS-CoV-2 compared to healthy controls or those with bacterial infection. Further investigation of cross-phenotype SNPs associated with both severe COVID-19 and other human traits demonstrated colocalization of the GWAS signal at the ABO locus with plasma protein levels of a reported receptor of SARS-CoV-2, CD209 (DC-SIGN). This finding points to a possible mechanism whereby glycosylation of CD209 by ABO may regulate COVID-19 disease severity.

CONCLUSIONS

Thus, connecting genetically related traits across phenotypic scales links human diseases to molecular and cellular measurements that can reveal mechanisms and lead to novel biomarkers and therapeutic approaches. The iCPAGdb web portal is accessible at http://cpag.oit.duke.edu and the software code at https://github.com/tbalmat/iCPAGdb .

Mapping Physiological ADP-Ribosylation Using Activated Ion Electron Transfer Dissociation

ADP-ribosylation (ADPr) is a post-translational modification that plays pivotal roles in a wide range of cellular processes. Mass spectrometry (MS)-based analysis of ADPr under physiological conditions, without relying on genetic or chemical perturbation, has been hindered by technical limitations. Here, we describe the applicability of activated ion electron transfer dissociation (AI-ETD) for MS-based proteomics analysis of physiological ADPr using our unbiased Af1521 enrichment strategy. To benchmark AI-ETD, we profile 9,000 ADPr peptides mapping to >5,000 unique ADPr sites from a limited number of cells exposed to oxidative stress and identify 120% and 28% more ADPr peptides compared to contemporary strategies using ETD and electron-transfer higher-energy collisional dissociation (EThcD), respectively. Under physiological conditions, AI-ETD identifies 450 ADPr sites on low-abundant proteins, including in vivo cysteine modifications on poly(ADP-ribosyl)polymerase (PARP) 8 and tyrosine modifications on PARP14, hinting at specialist enzymatic functions for these enzymes. Collectively, our data provide insights into the physiological regulation of ADPr.

In-depth Site-specific Analysis of N-glycoproteome in Human Cerebrospinal Fluid and Glycosylation Landscape Changes in Alzheimer's Disease

As the body fluid that directly interchanges with the extracellular fluid of the central nervous system (CNS), cerebrospinal fluid (CSF) serves as a rich source for CNS-related disease biomarker discovery. Extensive proteome profiling has been conducted for CSF, but studies aimed at unraveling site-specific CSF N-glycoproteome are lacking. Initial efforts into site-specific N-glycoproteomics study in CSF yield limited coverage, hindering further experimental design of glycosylation-based disease biomarker discovery in CSF. In the present study, we have developed an N-glycoproteomic approach that combines enhanced N-glycopeptide sequential enrichment by hydrophilic interaction chromatography (HILIC) and boronic acid enrichment with electron transfer and higher-energy collision dissociation (EThcD) for large-scale intact N-glycopeptide analysis. The application of the developed approach to the analyses of human CSF samples enabled identifications of a total of 2893 intact N-glycopeptides from 511 N-glycosites and 285 N-glycoproteins. To our knowledge, this is the largest site-specific N-glycoproteome dataset reported for CSF to date. Such dataset provides molecular basis for a better understanding of the structure-function relationships of glycoproteins and their roles in CNS-related physiological and pathological processes. As accumulating evidence suggests that defects in glycosylation are involved in Alzheimer's disease (AD) pathogenesis, in the present study, a comparative in-depth N-glycoproteomic analysis was conducted for CSF samples from healthy control and AD patients, which yielded a comparable N-glycoproteome coverage but a distinct expression pattern for different categories of glycoforms, such as decreased fucosylation in AD CSF samples. Altered glycosylation patterns were detected for a number of N-glycoproteins including alpha-1-antichymotrypsin, ephrin-A3 and carnosinase CN1 etc., which serve as potentially interesting targets for further glycosylation-based AD study and may eventually lead to molecular elucidation of the role of glycosylation in AD progression.

Clinically Viable Assay for Monitoring Uromodulin Glycosylation

Uromodulin, also known as the Tamm-Horsfall protein or THP, is the most abundant protein excreted in human urine. It is associated with the progression of kidney diseases; therefore, changes in the glycosylation profile of this protein could serve as a potential biomarker for kidney health. The typical glycomics analysis approaches used to quantify uromodulin glycosylation involve time-consuming and tedious glycoprotein isolation and labeling steps, which limit their utility in clinical glycomics assays, where sample throughput is important. Herein, we introduce a radically simplified sample preparation workflow, with direct ESI-MS analysis, enabling the quantification of N-linked glycans that originate from uromodulin. The method omits any glycan labeling steps but includes steps to reduce the salt content of the samples, thereby minimizing ion suppression. The method is effective for quantifying subtle glycosylation differences of uromodulin samples derived from different biological states. As a proof of concept, glycosylation from samples that differ by pregnancy status were shown to be differentiable.

O-GlcNAcAtlas: A database of experimentally identified O-GlcNAc sites and proteins

O-linked β-N-acetylglucosamine (O-GlcNAc) is a post-translational modification (i.e., O-GlcNAcylation) on the serine/threonine residues of proteins. As a unique intracellular monosaccharide modification, protein O-GlcNAcylation plays important roles in almost all biochemical processes examined. Aberrant O-GlcNAcylation underlies the etiologies of a number of chronic diseases. With the tremendous improvement of techniques, thousands of proteins along with their O-GlcNAc sites have been reported. However, until now, there are few databases dedicated to accommodate the rapid accumulation of such information. Thus, O-GlcNAcAtlas is created to integrate all experimentally identified O-GlcNAc sites and proteins. O-GlcNAcAtlas consists of two datasets (Dataset-I and Dataset-II, for unambiguously identified sites and ambiguously identified sites, respectively), representing a total number of 4571 O-GlcNAc modified proteins from all species studied from 1984 to 31 Dec 2019. For each protein, comprehensive information (including species, sample type, gene symbol, modified peptides and/or modification sites, site mapping methods and literature references) is provided. To solve the heterogeneity among the data collected from different sources, the sequence identity of these reported O-GlcNAc peptides are mapped to the UniProtKB protein entries. To our knowledge, O-GlcNAcAtlas is a highly comprehensive and rigorously curated database encapsulating all O-GlcNAc sites and proteins identified in the past 35 years. We expect that O-GlcNAcAtlas will be a useful resource to facilitate O-GlcNAc studies and computational analyses of protein O-GlcNAcylation. The public version of the web interface to the O-GlcNAcAtlas can be found at http://oglcnac.org/.

N-Glycosylation

N-glycosylation is a highly conserved glycan modification, and more than 7000 proteins are N-glycosylated in humans. N-glycosylation has many biological functions such as protein folding, trafficking, and signal transduction. Thus, glycan modification to proteins is profoundly involved in numerous physiological and pathological processes. The N-glycan precursor is biosynthesized in the endoplasmic reticulum (ER) from dolichol phosphate by sequential enzymatic reactions to generate the dolichol-linked oligosaccharide composed of 14 sugar residues, Glc₃Man₉GlcNAc₂. The oligosaccharide is then en bloc transferred to the consensus sequence N-X-S/T (X represents any amino acid except proline) of nascent proteins. Subsequently, the N-glycosylated nascent proteins enter the folding step, in which N-glycans contribute largely to attaining the correct protein fold by recruiting the lectin-like chaperones, calnexin, and calreticulin. Despite the N-glycan-dependent folding process, some glycoproteins do not fold correctly, and these misfolded glycoproteins are destined to degradation by proteasomes in the cytosol. Properly folded proteins are transported to the Golgi, and N-glycans undergo maturation by the sequential reactions of glycosidases and glycosyltransferases, generating complex-type N-glycans. N-Acetylglucosaminyltransferases (GnT-III, GnT-IV, and GnT-V) produce branched N-glycan structures, affording a higher complexity to N-glycans. In this chapter, we provide an overview of the biosynthetic pathway of N-glycans in the ER and Golgi.

A Pragmatic Guide to Enrichment Strategies for Mass Spectrometry-Based Glycoproteomics

Glycosylation is a prevalent, yet heterogeneous modification with a broad range of implications in molecular biology. This heterogeneity precludes enrichment strategies that can be universally beneficial for all glycan classes. Thus, choice of enrichment strategy has profound implications on experimental outcomes. Here we review common enrichment strategies used in modern mass spectrometry-based glycoproteomic experiments, including lectins and other affinity chromatographies, hydrophilic interaction chromatography and its derivatives, porous graphitic carbon, reversible and irreversible chemical coupling strategies, and chemical biology tools that often leverage bioorthogonal handles. Interest in glycoproteomics continues to surge as mass spectrometry instrumentation and software improve, so this review aims to help equip researchers with the necessary information to choose appropriate enrichment strategies that best complement these efforts.

Glycoproteomics-based signatures for tumor subtyping and clinical outcome prediction of high-grade serous ovarian cancer

Inter-tumor heterogeneity is a result of genomic, transcriptional, translational, and post-translational molecular features. To investigate the roles of protein glycosylation in the heterogeneity of high-grade serous ovarian carcinoma (HGSC), we perform mass spectrometry-based glycoproteomic characterization of 119 TCGA HGSC tissues. Cluster analysis of intact glycoproteomic profiles delineates 3 major tumor clusters and 5 groups of intact glycopeptides. It also shows a strong relationship between N-glycan structures and tumor molecular subtypes, one example of which being the association of fucosylation with mesenchymal subtype. Further survival analysis reveals that intact glycopeptide signatures of mesenchymal subtype are associated with a poor clinical outcome of HGSC. In addition, we study the expression of mRNAs, proteins, glycosites, and intact glycopeptides, as well as the expression levels of glycosylation enzymes involved in glycoprotein biosynthesis pathways in each tumor. The results show that glycoprotein levels are mainly controlled by the expression of their individual proteins, and, furthermore, that the glycoprotein-modifying glycans correspond to the protein levels of glycosylation enzymes. The variation in glycan types further shows coordination to the tumor heterogeneity. Deeper understanding of the glycosylation process and glycosylation production in different subtypes of HGSC may provide important clues for precision medicine and tumor-targeted therapy.

Altered protein glycosylation is increasingly recognized as a hallmark of cancer. Here, the authors profile the glycoproteome of 119 high-grade serous ovarian carcinoma tissues, showing that glycosylation patterns correlate with tumor molecular subtypes and clinical outcomes.

Comparison of Three Glycoproteomic Methods for the Analysis of the Secretome of CHO Cells Treated with 1,3,4-O-Bu3ManNAc

Comprehensive analysis of the glycoproteome is critical due to the importance of glycosylation to many aspects of protein function. The tremendous complexity of this post-translational modification, however, makes it difficult to adequately characterize the glycoproteome using any single method. To overcome this pitfall, in this report we compared three glycoproteomic analysis methods; first the recently developed N-linked glycans and glycosite-containing peptides (NGAG) chemoenzymatic method, second, solid-phase extraction of N-linked glycoproteins (SPEG), and third, hydrophilic interaction liquid chromatography (HILIC) by characterizing N-linked glycosites in the secretome of Chinese hamster ovary (CHO) cells. Interestingly, the glycosites identified by SPEG and HILIC overlapped considerably whereas NGAG identified many glycosites not observed in the other two methods. Further, utilizing enhanced intact glycopeptide identification afforded by the NGAG workflow, we found that the sugar analog 1,3,4-O-Bu₃ManNAc, a "high flux" metabolic precursor for sialic acid biosynthesis, increased sialylation of secreted proteins including recombinant human erythropoietin (rhEPO).

Databases and Bioinformatic Tools for Glycobiology and Glycoproteomics

Glycosylation plays critical roles in various biological processes and is closely related to diseases. Deciphering the glycocode in diverse cells and tissues offers opportunities to develop new disease biomarkers and more effective recombinant therapeutics. In the past few decades, with the development of glycobiology, glycomics, and glycoproteomics technologies, a large amount of glycoscience data has been generated. Subsequently, a number of glycobiology databases covering glycan structure, the glycosylation sites, the protein scaffolds, and related glycogenes have been developed to store, analyze, and integrate these data. However, these databases and tools are not well known or widely used by the public, including clinicians and other researchers who are not in the field of glycobiology, but are interested in glycoproteins. In this study, the representative databases of glycan structure, glycoprotein, glycan-protein interactions, glycogenes, and the newly developed bioinformatic tools and integrated portal for glycoproteomics are reviewed. We hope this overview could assist readers in searching for information on glycoproteins of interest, and promote further clinical application of glycobiology.