Glycoproteomics: growing up fast

Maximizing Glycoproteomics Results through an Integrated Parallel Accumulation Serial Fragmentation Workflow

Glycoproteins play important roles in numerous physiological processes and are often implicated in disease. Analysis of site-specific protein glycobiology through glycoproteomics has evolved rapidly in recent years thanks to hardware and software innovations. Particularly, the introduction of parallel accumulation serial fragmentation (PASEF) on hybrid trapped ion mobility time-of-flight mass spectrometry instruments combined deep proteome sequencing with separation of (near-)isobaric precursor ions or converging isotope envelopes through ion mobility separation. However, the reported use of PASEF in integrated glycoproteomics workflows to comprehensively capture the glycoproteome is still limited. To this end, we developed an integrated methodology using timsTOF Pro 2 to enhance N-glycopeptide identifications in complex mixtures. We systematically optimized the ion optics tuning, collision energies, mobility isolation width, and the use of dopant-enriched nitrogen gas (DEN). Thus, we obtained a marked increase in unique glycopeptide identification rates compared to standard proteomics settings, showcasing our results on a large set of glycopeptides. With short liquid chromatography gradients of 30 min, we increased the number of unique N-glycopeptide identifications in human plasma samples from around 100 identifications under standard proteomics conditions to up to 1500 with our optimized glycoproteomics approach, highlighting the need for tailored optimizations to obtain comprehensive data.

Exploring affinity chromatography in proteomics: A comprehensive review

Over the past decades, the proteomics field has undergone rapid growth. Progress in mass spectrometry and bioinformatics, together with separation methods, has brought many innovative approaches to the study of the molecular biology of the cell. The potential of affinity chromatography was recognized immediately after its first application in proteomics, and since that time, it has become one of the cornerstones of many proteomic protocols. Indeed, this chromatographic technique exploiting the specific binding between two molecules has been employed for numerous purposes, from selective removal of interfering (over)abundant proteins or enrichment of scarce biomarkers in complex biological samples to mapping the post-translational modifications and protein interactions with other proteins, nucleic acids or biologically active small molecules. This review presents a comprehensive survey of this versatile analytical tool in current proteomics. To navigate the reader, the haphazard space of affinity separations is classified according to the experiment's aims and the separated molecule's nature. Different types of available ligands and experimental strategies are discussed in further detail for each of the mentioned procedures.

Advancing mass spectrometry-based glycoproteomic software tools for comprehensive site-specific glycoproteome analysis

Glycoproteome analysis at a site-specific level and proteome scale stands out as a highly promising approach for gaining insights into the intricate roles of glycans in biological systems. Recent years have witnessed an upsurge in the development of innovative methodologies tailored for precisely this purpose. Breakthroughs in mass spectrometry-based glycoproteomic techniques, enabling the identification, quantification, and systematic exploration of site-specific glycans, have significantly enhanced our capacity to comprehensively and thoroughly characterize glycoproteins. In this short review, we delve into novel tools in advancing site-specific glycoproteomic analysis and summarize pertinent studies published in the past two years. Lastly, we discuss the ongoing challenges and outline future prospects in the field, considering both the analytical strategies of mass spectrometry and the tools employed for data interpretation.

Towards chemoenzymatic labeling strategies for profiling protein glycosylation

Protein glycosylation is one of the most common and important post-translational modifications of proteins involved in regulating glycoprotein functions. The chemoenzymatic glycan labeling strategy allows rapid, efficient, and selective interrogation of glycoproteins. Glycoproteomics identifies protein glycosylation events at a large scale, providing information such as peptide sequences, glycan structures, and glycosylated sites. This review discusses the recent development of chemoenzymatic labeling strategies for glycoprotein analysis, mainly including glycoprotein and glycosite profiling. Furthermore, we highlight the chemoenzymatic enrichment approaches in mass spectrometry analysis for three classes of glycan modifications, including N-glycosylation, O-GlcNAcylation, and mucin-type O-glycosylation. Finally, we highlight the emerging trends in new tools and cutting-edge technologies available for glycoproteomic research.

Altered microheterogeneity at several N-glycosylation sites in OPSCC in constant protein expression conditions

Protein glycosylation responds sensitively to disease states. It is implicated in every hallmark of cancer and has recently started to be considered as a hallmark itself. Changes in N-glycosylation microheterogeneity are more dramatic than those of protein expression due to the non-template nature of protein glycosylation. This enables their potential use in serum-based diagnostics. Here, we perform glycopeptidomics on serum from patients with oropharyngeal squamous cell carcinoma (OPSCC), compared to controls and comparing between cancers based on etiology (human papilloma virus- positive or negative). Using MS2, we then targeted glycoforms, significantly different between the groups, to identify their glycopeptide compositions. Simultaneously we investigate the same serum proteins, comparing whether N-glycosylation changes reflect protein-level changes. Significant glycoforms were identified from proteins such as alpha-1-antitrypsin (SERPINA1), haptoglobin, and different immunoglobulins. SERPINA1 had glycovariance at 2 N-glycosylation sites, that were up to 35 times more abundant in even early-stage OPSCCs, despite minimal differences between SERPINA1 protein levels between groups. Some identified glycoforms' fold changes (FCs) were in line with serum protein level FCs, others were less abundant in early-stage cancers but with great variance in higher-stage cancers, such as on immunoglobulin heavy constant gamma 2, despite no change in protein levels. Such findings indicate that glycovariant analysis might be more beneficial than proteomic analysis, which is yet to be fruitful in the search for biomarkers. Highly sensitive glycopeptide changes could potentially be used in the future for cancer screening. Additionally, characterizing the glycopeptide changes in OPSCC is valuable in the search for potential therapeutic targets.

Protein post-translational modifications: A key factor in colorectal cancer resistance mechanisms

Colorectal cancer (CRC) is one of the leading causes of cancer-related death. Despite advances in treatment, drug resistance remains a critical impediment. Post-translational modifications (PTMs) regulate protein stability, localization, and activity, impacting vital cellular processes. Recent research has highlighted the essential role of PTMs in the development of CRC resistance. This review summarizes recent advancements in understanding PTMs' roles in CRC resistance, focusing on the latest discoveries. We discuss the functional impact of PTMs on signaling pathways and molecules involved in CRC resistance, progress in drug development, and potential therapeutic targets. We also summarize the primary enrichment methods for PTMs. Finally, we discuss current challenges and future directions, including the need for more comprehensive PTM analysis methods and PTM-targeted therapies. This review identifies potential therapeutic interventions for addressing medication resistance in CRC, proposes prospective therapeutic options, and gives an overview of the function of PTMs in CRC resistance.

An identification method to distinguish monomeric sugar isomers on glycopeptides

A one-step protocol for the automated flow synthesis of protected glycosylated amino acids is described using pumps with open-source controls in overall yields of 21-50%. The resulting glycosylated amino acids could be used directly in solid-phase peptide synthesis (SPPS) protocols to quickly produce glycopeptide standards. Access to a variety of stereoisomers of the sugar enabled the development of an LC-MS/MS protocol that can distinguish between peptides modified with carbohydrates having the same exact mass. This method could definitively identify fucose in an O-glycosylation site on the transmembrane protein, Notch1.

The Value of Microbes in Cancer Neoantigen Immunotherapy

Tumor neoantigens are widely used in cancer immunotherapy, and a growing body of research suggests that microbes play an important role in these neoantigen-based immunotherapeutic processes. The human body and its surrounding environment are filled with a large number of microbes that are in long-term interaction with the organism. The microbiota can modulate our immune system, help activate neoantigen-reactive T cells, and play a great role in the process of targeting tumor neoantigens for therapy. Recent studies have revealed the interconnection between microbes and neoantigens, which can cross-react with each other through molecular mimicry, providing theoretical guidance for more relevant studies. The current applications of microbes in immunotherapy against tumor neoantigens are mainly focused on cancer vaccine development and immunotherapy with immune checkpoint inhibitors. This article summarizes the related fields and suggests the importance of microbes in immunotherapy against neoantigens.

Plasma glycoproteomic biomarkers identify metastatic melanoma patients with reduced clinical benefit from immune checkpoint inhibitor therapy

The clinical success of immune-checkpoint inhibitors (ICI) in both resected and metastatic melanoma has confirmed the validity of therapeutic strategies that boost the immune system to counteract cancer. However, half of patients with metastatic disease treated with even the most aggressive regimen do not derive durable clinical benefit. Thus, there is a critical need for predictive biomarkers that can identify individuals who are unlikely to benefit with high accuracy so that these patients may be spared the toxicity of treatment without the likely benefit of response. Ideally, such an assay would have a fast turnaround time and minimal invasiveness. Here, we utilize a novel platform that combines mass spectrometry with an artificial intelligence-based data processing engine to interrogate the blood glycoproteome in melanoma patients before receiving ICI therapy. We identify 143 biomarkers that demonstrate a difference in expression between the patients who died within six months of starting ICI treatment and those who remained progression-free for three years. We then develop a glycoproteomic classifier that predicts benefit of immunotherapy (HR=2.7; p=0.026) and achieves a significant separation of patients in an independent cohort (HR=5.6; p=0.027). To understand how circulating glycoproteins may affect efficacy of treatment, we analyze the differences in glycosylation structure and discover a fucosylation signature in patients with shorter overall survival (OS). We then develop a fucosylation-based model that effectively stratifies patients (HR=3.5; p=0.0066). Together, our data demonstrate the utility of plasma glycoproteomics for biomarker discovery and prediction of ICI benefit in patients with metastatic melanoma and suggest that protein fucosylation may be a determinant of anti-tumor immunity.

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.

Recent advances in computational algorithms and software for large-scale glycoproteomics

Glycoproteomics, or characterizing glycosylation events at a proteome scale, has seen rapid advances in methods for analyzing glycopeptides by tandem mass spectrometry in recent years. These advances have enabled acquisition of far more comprehensive and large-scale datasets, precipitating an urgent need for improved informatics methods to analyze the resulting data. A new generation of glycoproteomics search methods has recently emerged, using glycan fragmentation to split the identification of a glycopeptide into peptide and glycan components and solve each component separately. In this review, we discuss these new methods and their implications for large-scale glycoproteomics, as well as several outstanding challenges in glycoproteomics data analysis, including validation of glycan assignments and quantitation. Finally, we provide an outlook on the future of glycoproteomics from an informatics perspective, noting the key challenges to achieving widespread and reproducible glycopeptide annotation and quantitation.

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

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

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.

High sensitivity glycomics in biomedicine

Many analytical challenges in biomedicine arise from the generally high heterogeneity and complexity of glycan- and glycoconjugate-containing samples, which are often only available in minute amounts. Therefore, highly sensitive workflows and detection methods are required. In this review mass spectrometric workflows and detection methods are evaluated for glycans and glycoproteins. Furthermore, glycomic methodologies and innovations that are tailored for enzymatic treatments, chemical derivatization, purification, separation, and detection at high sensitivity are highlighted. The discussion is focused on the analysis of mammalian N-linked and GalNAc-type O-linked glycans.

Measuring the multifaceted roles of mucin-domain glycoproteins in cancer

Mucin-domain glycoproteins are highly O-glycosylated cell surface and secreted proteins that serve as both biochemical and biophysical modulators. Aberrant expression and glycosylation of mucins are known hallmarks in numerous malignancies, yet mucin-domain glycoproteins remain enigmatic in the broad landscape of cancer glycobiology. Here we review the multifaceted roles of mucins in cancer through the lens of the analytical and biochemical methods used to study them. We also describe a collection of emerging tools that are specifically equipped to characterize mucin-domain glycoproteins in complex biological backgrounds. These approaches are poised to further elucidate how mucin biology can be understood and subsequently targeted for the next generation of cancer therapeutics.

Targeting glycans for CAR therapy: The advent of sweet CARs

Chimeric antigen receptor (CAR) T cell therapy has created a paradigm shift in the treatment of hematologic malignancies but has not been as effective toward solid tumors. For such tumors, the primary obstacles facing CAR T cells are scarcity of tumor-specific antigens and the hostile and complex tumor microenvironment. Glycosylation, the process by which sugars are post-translationally added to proteins or lipids, is profoundly dysregulated in cancer. Abnormally glycosylated glycoproteins expressed on cancer cells offer unique targets for CAR T therapy as they are specific to tumor cells. Tumor stromal cells also express abnormal glycoproteins and thus also have the potential to be targeted by glycan-binding CAR T cells. This review will discuss the state of CAR T cells in the therapy of solid tumors, the cancer glycoproteome and its potential for use as a therapeutic target, and the landscape and future of glycan-binding CAR T cell therapy.

Recent advances and future perspectives on carbohydrate-based cancer vaccines and therapeutics

Carbohydrates are abundantly expressed on the surface of both eukaryotic and prokaryotic cells, often as post translational modifications of proteins. Glycoproteins are recognized by the immune system and can trigger both innate and humoral responses. This feature has been harnessed to generate vaccines against polysaccharide-encapsulated bacteria such as Streptococcus pneumoniae, Hemophilus influenzae type b and Neisseria meningitidis. In cancer, glycosylation plays a pivotal role in malignancy development and progression. Since glycans are specifically expressed on the surface of tumor cells, they have been targeted for the discovery of anticancer preventive and therapeutic treatments, such as vaccines and monoclonal antibodies. Despite the various efforts made over the last years, resulting in a series of clinical studies, attempts of vaccination with carbohydrate-based candidates have proven unsuccessful, primarily due to the immune tolerance often associated with these glycans. New strategies are thus deployed to enhance carbohydrate-based cancer vaccines. Moreover, lessons learned from glycan immunobiology paved the way to the development of new monoclonal antibodies specifically designed to recognize cancer-bound carbohydrates and induce tumor cell killing. Herein we provide an overview of the immunological principles behind the immune response towards glycans and glycoconjugates and the approaches exploited at both preclinical and clinical level to target cancer-associated glycans for the development of vaccines and therapeutic monoclonal antibodies. We also discuss gaps and opportunities to successfully advance glycan-directed cancer therapies, which could provide patients with innovative and effective treatments.

Excavating proteoglycan structure-function relationships: Modern approaches to capture the interactions of ancient biomolecules

Proteoglycans are now well regarded as key facilitators of cell biology. While a majority of their interactions and functions are attributed to the decorating glycosaminoglycan chains, there is a growing appreciation for the roles of the proteoglycan core protein and for considering proteoglycans as replete protein-glycan conjugates. This appreciation, seeded by early work in proteoglycan biology, is now being advanced and exalted by modern approaches in chemical glycobiology. In this review, we discuss up-and-coming methods to unearth the fine-scale architecture of proteoglycans that modulate their functions and interactions. Crucial to these efforts is the production of chemically defined materials, including semi-synthetic proteoglycans and the in situ capture of interacting proteins. Together, the integration of chemical biology approaches promises to expedite the dissection of the structural heterogeneity of proteoglycans and deliver refined insight into their functions.

Revealing the human mucinome

Mucin domains are densely O-glycosylated modular protein domains found in various extracellular and transmembrane proteins. Mucin-domain glycoproteins play important roles in many human diseases, such as cancer and cystic fibrosis, but the scope of the mucinome remains poorly defined. Recently, we characterized a bacterial O-glycoprotease, StcE, and demonstrated that an inactive point mutant retains binding selectivity for mucin-domain glycoproteins. In this work, we leverage inactive StcE to selectively enrich and identify mucin-domain glycoproteins from complex samples like cell lysate and crude ovarian cancer patient ascites fluid. Our enrichment strategy is further aided by an algorithm to assign confidence to mucin-domain glycoprotein identifications. This mucinomics platform facilitates detection of hundreds of glycopeptides from mucin domains and highly overlapping populations of mucin-domain glycoproteins from ovarian cancer patients. Ultimately, we demonstrate our mucinomics approach can reveal key molecular signatures of cancer from in vitro and ex vivo sources.

Mucin-domain glycoproteins are densely O-glycosylated proteins with unique secondary structure that imparts a large influence on cellular environments. Here, the authors develop a technique to selectively enrich and characterize mucin-domain glycoproteins from cell lysate and patient biofluids.

Identification of proteins and N-glycosylation sites of knee cartilage in Kashin-Beck disease compared with osteoarthritis

The aim of this study was to identify crucial proteins and N-glycosylated sites in the pathological mechanism of Kashin-Beck disease (KBD) compared with osteoarthritis (OA). Nine KBD knee subjects and nine OA knee subjects were selected for the study. Quantitative proteomics and N-glycoproteomics data of KBD and OA were obtained by protein and N-glycoprotein enrichment and LC-MS/MS analysis. Differentially expressed proteins or N-glycosylation sites were examined with a comparative analysis between KBD and OA. Total 2205 proteins were identified in proteomic analysis, of which 375 were significantly different. Among these, 121 proteins were up-regulated and 254 were down-regulated. In N-glycoproteomic analysis, 278 different N-glycosylated sites that were related to 187 N-glycoproteins were identified. Proteins and their N-glycosylated sites are associated with KBD pathological process including ITGB1, LRP1, ANO6, COL1A1, MXRA5, DPP4, and CSPG4. CRLF1 and GLG1 are proposed to associate with both KBD and OA pathological processes. Key pathways in KBD vs. OA proteomic and N-glycoproteomic analysis contained extracellular matrix receptor interaction, focal adhesion, phagosome, protein digestion, and absorption. N-glycosylation may influence the pathological process by affecting the integrity of chondrocytes or cartilage. It regulated the intercellular signal transduction pathway, which contributes to cartilage destruction in KBD.

Proteomics of post-translational modifications in colorectal cancer: Discovery of new biomarkers

Colorectal cancer (CRC) is one of the costliest health problems and ranks second in cancer-related mortality in developed countries. With the aid of proteomics, many protein biomarkers for the diagnosis, prognosis, and precise management of CRC have been identified. Furthermore, some protein biomarkers exhibit structural diversity after modifications. Post-translational modifications (PTMs), most of which are catalyzed by a variety of enzymes, extensively increase protein diversity and are involved in many complex and dynamic cellular processes through the regulation of protein function. Accumulating evidence suggests that abnormal PTM events are associated with a variety of human diseases, such as CRC, thus highlighting the need for studying PTMs to discover both the molecular mechanisms and therapeutic targets of CRC. In this review, we begin with a brief overview of the importance of protein PTMs, discuss the general strategies for proteomic profiling of several key PTMs (including phosphorylation, acetylation, glycosylation, ubiquitination, methylation, and citrullination), shift the emphasis to describing the specific methods used for delineating the global landscapes of each of these PTMs, and summarize the recent applications of these methods to explore the potential roles of the PTMs in CRC. Finally, we discuss the current status of PTM research on CRC and provide future perspectives on how PTM regulation can play an essential role in translational medicine for early diagnosis, prognosis stratification, and therapeutic intervention in CRC.

Comparison of Fucose-Specific Lectins to Improve Quantitative AFP-L3 Assay for Diagnosing Hepatocellular Carcinoma Using Mass Spectrometry

Glycoproteins have many important biological functions. In particular, aberrant glycosylation has been observed in various cancers, such as liver cancer. A well-known glycoprotein biomarker is α-fetoprotein (AFP), a surveillance biomarker for hepatocellular carcinoma (HCC) that contains a glycosylation site at asparagine 251. The low diagnostic sensitivity of AFP led researchers to focus on AFP-L3, which has the same sequence as conventional AFP but contains a fucosylated glycan. AFP-L3 has high affinity for Lens culinaris agglutinin (LCA) lectin, prompting many groups to use it for detecting AFP-L3. However, a few studies have identified more effective lectins for fractionating AFP-L3. In this study, we compared the amounts of enriched AFP-L3 with five fucose-specific lectins─LCA, Lotus tetragonolobus lectin (LTL), Ulex europaeus agglutinin I (UEA I), Aleuria aurantia lectin (AAL), and Aspergillus oryzae lectin (AOL)─to identify better lectins and improve HCC diagnostic assays using mass spectrometry (MS). Our results indicate that LTL was the most effective lectin for capturing AFP-L3 species, yielding approximately 3-fold more AFP-L3 than LCA from the same pool of HCC serum samples. Thus, we recommend the use of LTL for AFP-L3 assays, given its potential to improve the diagnostic sensitivity in patients having limited results by conventional LCA assay. The MS data have been deposited to the PeptideAtlas (PASS01752).

Simultaneously Identifying and Distinguishing Glycoproteins with O-GlcNAc and O-GalNAc (the Tn Antigen) in Human Cancer Cells

Glycoproteins with diverse glycans are essential to human cells, and subtle differences in glycan structures may result in entirely different functions. One typical example is proteins modified with O-linked β-N-acetylglucosamine (O-GlcNAc) and O-linked α-N-acetylgalactosamine (O-GalNAc) (the Tn antigen), in which the two glycans have very similar structures and identical chemical compositions, making them extraordinarily challenging to be distinguished. Here, we developed an effective method benefiting from selective enrichment and the enzymatic specificity to simultaneously identify and distinguish glycoproteins with O-GlcNAc and O-GalNAc. Metabolic labeling was combined with bioorthogonal chemistry for enriching glycoproteins modified with O-GlcNAc and O-GalNAc. Then, the enzymatic reaction with galactose oxidase was utilized to specifically oxidize O-GalNAc, but not O-GlcNAc, generating the different tags between glycopeptides with O-GlcNAc and O-GalNAc that can be easily distinguishable by mass spectrometry (MS). Among O-GlcNAcylated proteins commonly identified in three types of human cells, those related to transcription and RNA binding are highly enriched. Cell-specific features are also revealed. Among glycoproteins exclusively in Jurkat cells, those involved in human T-lymphotropic virus type 1 (HTLV-1) infection are overrepresented, which is consistent with the cell line source and suggests that protein O-GlcNAcylation participated in the response to the virus infection. Furthermore, glycoproteins with the Tn antigen have different subcellular distributions in different cells, which may be attributed to the distinct mechanisms for the formation of protein O-GalNAcylation.

Computational Prediction of N- and O-Linked Glycosylation Sites for Human and Mouse Proteins

Protein glycosylation is one of the most complex posttranslational modifications (PTM) that play a fundamental role in protein function. Identification and annotation of these sites using experimental approaches are challenging and time consuming. Hence, there is a demand to build fast and efficient computational methods to address this problem. Here, we present the SPRINT-Gly framework containing the largest dataset and a prediction model of glycosylation sites for a given protein sequence. In this framework, we construct a large dataset containing N- and O-linked glycosylation sites of human and mouse proteins, collected from different sources. We then introduce the SPRINT-Gly method to predict putative N- and O-linked sites. SPRINT-Gly is a machine learning-based approach consisting of a number of trained predictive models for glycosylation sites in both human and mouse proteins, separately. The method is built by incorporating sequence-based, predicted structural, and physicochemical information of the neighboring residues of each N- and O-linked glycosylation site and by training deep learning neural network and support vector machine as classifiers. SPRINT-Gly outperformed other existing methods by achieving 18% and 50% higher Matthew's correlation coefficient for N- and O-linked glycosylation site prediction, respectively. SPRINT-Gly is publicly available as an online and stand-alone predictor at https://sparks-lab.org/server/sprint-gly/ .

Glycopeptide-Centric Approaches for the Characterization of Microbial Glycoproteomes

Protein glycosylation is increasingly recognized as a common class of modifications within microbial species that can shape protein functions and the proteome at large. Due to this, there is an increasing need for robust analytical methods, which allow for the identification and characterization of microbial glycopeptides from proteome samples in a high-throughput manner. Using affinity-based enrichment (either hydrophilicity or antibody-based approaches) glycopeptides can easily be separated from non-glycosylated peptides and analyzed using mass spectrometry. By utilizing multiple mass spectrometry fragmentation approaches and open searching-based bioinformatic techniques, novel glycopeptides can be identified and characterized without prior knowledge of the glycans used for glycosylation. Using these approaches, glycopeptides within samples can rapidly be identified as well as quantified to understand how glycosylation changes in response to stimuli or how changes in glycosylation systems impact the glycoproteome. This chapter outlines a set of robust protocols for the initial preparation, enrichment, and analysis of microbial glycopeptides for both qualitative and quantitative glycoproteomic studies. Using these approaches, glycosylation events can be easily identified by researchers without the need for extensive manual analysis of proteomic datasets.

N-glycosylation profiles of the SARS-CoV-2 spike D614G mutant and its ancestral protein characterized by advanced mass spectrometry

N-glycosylation plays an important role in the structure and function of membrane and secreted proteins. The spike protein on the surface of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes COVID-19, is heavily glycosylated and the major target for developing vaccines, therapeutic drugs and diagnostic tests. The first major SARS-CoV-2 variant carries a D614G substitution in the spike (S-D614G) that has been associated with altered conformation, enhanced ACE2 binding, and increased infectivity and transmission. In this report, we used mass spectrometry techniques to characterize and compare the N-glycosylation of the wild type (S-614D) or variant (S-614G) SARS-CoV-2 spike glycoproteins prepared under identical conditions. The data showed that half of the N-glycosylation sequons changed their distribution of glycans in the S-614G variant. The S-614G variant showed a decrease in the relative abundance of complex-type glycans (up to 45%) and an increase in oligomannose glycans (up to 33%) on all altered sequons. These changes led to a reduction in the overall complexity of the total N-glycosylation profile. All the glycosylation sites with altered patterns were in the spike head while the glycosylation of three sites in the stalk remained unchanged between S-614G and S-614D proteins.

Mucinomics as the Next Frontier of Mass Spectrometry

Mucin-domain glycoproteins comprise a class of proteins whose densely O-glycosylated mucin domains adopt a secondary structure with unique biophysical and biochemical properties. The canonical family of mucins is well-known to be involved in various diseases, especially cancer. Despite this, very little is known about the site-specific molecular structures and biological activities of mucins, in part because they are extremely challenging to study by mass spectrometry (MS). Here, we summarize recent advancements toward this goal, with a particular focus on mucin-domain glycoproteins as opposed to general O-glycoproteins. We summarize proteolytic digestion techniques, enrichment strategies, MS fragmentation, and intact analysis, as well as new bioinformatic platforms. In particular, we highlight mucin directed technologies such as mucin-selective proteases, tunable mucin platforms, and a mucinomics strategy to enrich mucin-domain glycoproteins from complex samples. Finally, we provide examples of targeted mucin-domain glycoproteomics that combine these techniques in comprehensive site-specific analyses of proteins. Overall, this Review summarizes the methods, challenges, and new opportunities associated with studying enigmatic mucin domains.

Recent Advances in Mass Spectrometry-Based Glycomic and Glycoproteomic Studies of Pancreatic Diseases

Modification of proteins by glycans plays a crucial role in mediating biological functions in both healthy and diseased states. Mass spectrometry (MS) has emerged as the most powerful tool for glycomic and glycoproteomic analyses advancing knowledge of many diseases. Such diseases include those of the pancreas which affect millions of people each year. In this review, recent advances in pancreatic disease research facilitated by MS-based glycomic and glycoproteomic studies will be examined with a focus on diabetes and pancreatic cancer. The last decade, and especially the last five years, has witnessed developments in both discovering new glycan or glycoprotein biomarkers and analyzing the links between glycans and disease pathology through MS-based studies. The strength of MS lies in the specificity and sensitivity of liquid chromatography-electrospray ionization MS for measuring a wide range of biomolecules from limited sample amounts from many sample types, greatly enhancing and accelerating the biomarker discovery process. Furthermore, imaging MS of glycans enabled by matrix-assisted laser desorption/ionization has proven useful in complementing histology and immunohistochemistry to monitor pancreatic disease progression. Advances in biological understanding and analytical techniques, as well as challenges and future directions for the field, will be discussed.

Posttranslational Modifications: Emerging Prospects for Cardiac Regeneration Therapy

Heart failure (HF) following ischemic heart disease (IHD) remains a hard nut to crack and a leading cause of death worldwide. Cardiac regeneration aims to promote cardiomyocyte (CM) proliferation by transitioning the cell cycle state of CMs from arrest to re-entry. Protein posttranslational modifications (PTMs) have recently attracted extensive attention in the field of cardiac regeneration due to their reversibility and effects on the stability, activity, and subcellular localization of target proteins. The balance of PTMs is disrupted when neonatal CMs withdraw from the cell cycle, resulting in significant dysfunction of downstream substrate protein localization, expression, and activity, ultimately limiting the maintenance of cardiac regeneration ability. In this review, we summarize recent research concerning the role of PTMs in cardiac regeneration, while focusing on phosphorylation, acetylation, ubiquitination, glycosylation, methylation, and neddylation, and the effects of these modifications on CM proliferation, which may provide potential targets for future treatments for IHD.