pGlycoQuant with a deep residual network for quantitative glycoproteomics at intact glycopeptide level

In-depth site-specific glycoproteomic analysis reveals ER-resident protein PDI regulating wheat yellow mosaic virus infection

N-glycosylation is crucial in the process of wheat yellow mosaic virus (WYMV) infection, but changes in site-specific N-glycosylation of proteins during WYMV infection have not been well studied. In this study, we employed an intact glycopeptide approach to analyze mock- and WYMV-infected wheat plants. We found that most glycoproteins have N-glycans containing paucimannose or complex/hybrid chains. Notably, the H3N2F1X1 N-glycan was the most prevalent, comprising 40 % of the total glycan abundance. Six glycan types showed an increasing trend of glycosylation in WYMV-infected wheat. Overall, 1202 unique N-glycopeptides corresponding to 53 N-glycans at 562 N-glycosylation sites in 456 N-glycoproteins were identified, and 176 N-glycopeptides from 115 glycoproteins were significantly regulated in WYMV-infected wheat. Bioinformatics analysis of the hyperglycosylated and hypoglycosylated glycoproteins indicated that two N-glycoproteins with significant regulatory differences were specifically related to protein quality control, endoplasmic reticulum stress response, and protein folding. Furthermore, the protein disulfide isomerase TaPDI 1-4 and TaPDI regulate WYMV infection, and their N-glycosylation is involved in the regulatory process. To our knowledge, this is the first study to analyze the differences and roles of protein N-glycosylation in wheat virus infection at the level of intact glycopeptides.

N-glycosylation Modification of CTSD Affects Liver Metastases in Colorectal Cancer

Liver metastasis is the primary factor contributing to unfavorable prognosis in colorectal cancer (CRC). Although N-glycosylation is implicated in metastasis, there is a notable paucity of comprehensive studies addressing the N-glycosylation proteomics associated with liver metastasis in CRC. In this study, N-glycosylated proteins and N-glycosylation sites of differential expression between primary lesions and paired liver metastatic lesions are identified. Cathepsin D (CTSD) is further screened as a potentially pivotal N-glycosylated protein in CRC liver metastasis. Glycosyltransferases complex DDOST and STT3B can regulate N-glycosylation modification at residue 263 of CTSD (a protease), thereby affecting CTSD protease to lyse ACADM. ACADM can regulate ferroptosis-related proteins (ACSL4, SLC7A11, and GPX4) to further influence the invasion and metastasis of CRC cells. This newly discovered mechanism provides potential therapeutic targets for CRC treatment and insights for controlling CRC progression and metastasis.

Tools and techniques for quantitative glycoproteomic analysis

Recent advances in mass spectrometry (MS)-based methods have significantly expanded the capabilities for quantitative glycoproteomics, enabling highly sensitive and accurate quantitation of glycosylation at intact glycopeptide level. These developments have provided valuable insights into the roles of glycoproteins in various biological processes and diseases. In this short review, we summarize pertinent studies on quantitative techniques and tools for site-specific glycoproteomic analysis published over the past decade. We also highlight state-of-the-art MS-based software that facilitate multi-dimension quantification of the glycoproteome, targeted quantification of specific glycopeptides, and the analysis of glycopeptide isomers. Additionally, we discuss the potential applications of these technologies in clinical biomarker discovery and the functional characterization of glycoproteins in health and disease. The review concludes with a discussion of current challenges and future perspectives in the field, emphasizing the need for more precise, high-throughput and efficient methods to further advance quantitative glycoproteomics and its applications.

The Circulating Proteome─Technological Developments, Current Challenges, and Future Trends

Recent improvements in proteomics technologies have fundamentally altered our capacities to characterize human biology. There is an ever-growing interest in using these novel methods for studying the circulating proteome, as blood offers an accessible window into human health. However, every methodological innovation and analytical progress calls for reassessing our existing approaches and routines to ensure that the new data will add value to the greater biomedical research community and avoid previous errors. As representatives of HUPO's Human Plasma Proteome Project (HPPP), we present our 2024 survey of the current progress in our community, including the latest build of the Human Plasma Proteome PeptideAtlas that now comprises 4608 proteins detected in 113 data sets. We then discuss the updates of established proteomics methods, emerging technologies, and investigations of proteoforms, protein networks, extracellualr vesicles, circulating antibodies and microsamples. Finally, we provide a prospective view of using the current and emerging proteomics tools in studies of circulating proteins.

Unique Glycans in Synaptic Glycoproteins in Mouse Brain

The synapse is an essential connection between neuronal cells in which the membrane and secreted glycoproteins regulate neurotransmission. The post-translational modifications of glycoproteins with carbohydrates, although essential for their functions as well as their specific localization, are not well understood. Oddly, whereas galactose addition to glycoproteins is required for neuronal functions, galactosylation is severely restricted for Asn-linked on N-glycans in the brain, and genetic evidence highlights the important roles of galactose in brain functions and development. To explore this novel glycosylation, we exploited an orthogonal technology in which a biotinylated sialic acid derivative (CMP-biotin-Sia) is transferred to terminally galactosylated proteins by a recombinant sialyltransferase (rST6Gal1). This approach allowed us to identify the carrier proteins as well as their localization on brain sections. Immunohistochemical analysis of the biotinylated glycoproteins in brain sections demonstrates that they are largely positioned in the pre- and postsynaptic membranes. Consistent with this positioning, glycoproteomic analyses of the labeled glycoproteins identified a number of them that are involved in synaptic function, cell adhesion, and extracellular matrix interactions. The discovery of these galactosylated N-glycoproteins and their relative confinement to synapses provide novel insights into the unusual and specific nature of protein glycosylation in the brain.

Clinical glycoproteomics: methods and diseases

Glycoproteins, representing a significant proportion of posttranslational products, play pivotal roles in various biological processes, such as signal transduction and immune response. Abnormal glycosylation may lead to structural and functional changes of glycoprotein, which is closely related to the occurrence and development of various diseases. Consequently, exploring protein glycosylation can shed light on the mechanisms behind disease manifestation and pave the way for innovative diagnostic and therapeutic strategies. Nonetheless, the study of clinical glycoproteomics is fraught with challenges due to the low abundance and intricate structures of glycosylation. Recent advancements in mass spectrometry-based clinical glycoproteomics have improved our ability to identify abnormal glycoproteins in clinical samples. In this review, we aim to provide a comprehensive overview of the foundational principles and recent advancements in clinical glycoproteomic methodologies and applications. Furthermore, we discussed the typical characteristics, underlying functions, and mechanisms of glycoproteins in various diseases, such as brain diseases, cardiovascular diseases, cancers, kidney diseases, and metabolic diseases. Additionally, we highlighted potential avenues for future development in clinical glycoproteomics. These insights provided in this review will enhance the comprehension of clinical glycoproteomic methods and diseases and promote the elucidation of pathogenesis and the discovery of novel diagnostic biomarkers and therapeutic targets.

nQuant Enables Precise Quantitative N-Glycomics

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

GP-Marker facilitates the analysis of intact glycopeptide quantitative data at different levels

Protein glycosylation is a highly heterogeneous post-translational modification that has been demonstrated to exhibit significant variations in various diseases. Due to the differential patterns observed in disease and healthy populations, the glycosylated proteins hold promise as early indicators for multiple diseases. With the continuous development of liquid chromatography-mass spectrometry (LC-MS) technology and spectrum analysis software, the sensitivity for the decipher of the tandem mass spectra of the glycopeptides carrying intact glycans, i.e., intact glycopeptides, enzymatic hydrolyzed from glycoproteins has been significantly improved. From quantified intact glycopeptides, the difference of protein glycosylation at multiple levels, e.g., glycoprotein, glycan, glycosite, and site-specific glycans, could be obtained for different samples. However, the manual analysis of the intact glycopeptide quantitative data at multiple levels is tedious and time consuming. In this study, we have developed a software tool named "GP-Marker" to facilitate large-scale data mining of spectra dataset of intact N-glycopeptide at multiple levels. This software provides a user-friendly and interactive interface, offering operational tools for machine learning to researchers without programming backgrounds. It includes a range of visualization plots displaying differential glycosylation and provides the ability to extract multi-level data analysis from intact glycopeptide data quantified by Glyco-Decipher.

Glyco-signatures in patients with advanced lung cancer during anti-PD-1/PD-L1 immunotherapy

Immune checkpoint inhibitors (ICIs) targeting programmed cell death 1/programmed cell death ligand-1 (PD-1/PD-L1) have significantly prolonged the survival of advanced/metastatic patients with lung cancer. However, only a small proportion of patients can benefit from ICIs, and clinical management of the treatment process remains challenging. Glycosylation has added a new dimension to advance our understanding of tumor immunity and immunotherapy. To systematically characterize anti-PD-1/PD-L1 immunotherapy-related changes in serum glycoproteins, a series of serum samples from 12 patients with metastatic lung squamous cell carcinoma (SCC) and lung adenocarcinoma (ADC), collected before and during ICIs treatment, are firstly analyzed with mass-spectrometry-based label-free quantification method. Second, a stratification analysis is performed among anti-PD-1/PD-L1 responders and non-responders, with serum levels of glycopeptides correlated with treatment response. In addition, in an independent validation cohort, a large-scale site-specific profiling strategy based on chemical labeling is employed to confirm the unusual characteristics of IgG N-glycosylation associated with anti-PD-1/PD-L1 treatment. Unbiased label-free quantitative glycoproteomics reveals serum levels' alterations related to anti-PD-1/PD-L1 treatment in 27 out of 337 quantified glycopeptides. The intact glycopeptide EEQFN 177STYR (H3N4) corresponding to IgG4 is significantly increased during anti-PD-1/PD-L1 treatment (FC=2.65, P=0.0083) and has the highest increase in anti-PD-1/PD-L1 responders (FC=5.84, P=0.0190). Quantitative glycoproteomics based on protein purification and chemical labeling confirms this observation. Furthermore, obvious associations between the two intact glycopeptides (EEQFN 177STYR (H3N4) of IgG4, EEQYN 227STFR (H3N4F1) of IgG3) and response to treatment are observed, which may play a guiding role in cancer immunotherapy. Our findings could benefit future clinical disease management.

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.

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.

A Novel Integrated Pipeline for Site-Specific Quantification of N-glycosylation

The site-specific N-glycosylation changes of human plasma immunoglobulin gamma molecules (IgGs) have been shown to modulate the immune response and could serve as potential biomarkers for the accurate diagnosis of various diseases. However, quantifying intact N-glycopeptides accurately in large-scale clinical samples remains a challenge, and the quantitative N-glycosylation of plasma IgGs in patients with chronic kidney diseases (CKDs) has not yet been studied. In this study, we present a novel integrated intact N-glycopeptide quantitative pipeline (termed GlycoQuant), which combines our recently developed mass spectrometry fragmentation method (EThcD-sceHCD) and an intact N-glycopeptide batch quantification software tool (the upgraded PANDA v.1.2.5). We purified and digested human plasma IgGs from 58 healthy controls (HCs), 48 patients with membranous nephropathy (MN), and 35 patients with IgA nephropathy (IgAN) within an hour. Then, we analyzed the digested peptides without enrichment using EThcD-sceHCD-MS/MS, which provided higher spectral quality and greater identified depth. Using upgraded PANDA, we performed site-specific N-glycosylation quantification of IgGs. Several quantified intact N-glycopeptides not only distinguished CKDs from HCs, but also different types of CKD (MN and IgAN) and may serve as accurate diagnostic tools for renal tubular function. In addition, we proved the applicability of this pipeline to complex samples by reanalyzing the intact N-glycopeptides from cell, urine, plasma, and tissue samples that we had previously identified. We believe that this pipeline can be applied to large-scale clinical N-glycoproteomic studies, facilitating the discovery of novel glycosylated biomarkers.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-023-00150-w.

A Fully Automated Online Enrichment and Separation System for Highly Reproducible and In-Depth Analysis of Intact Glycopeptide

A fully automated online enrichment and separation system for intact glycopeptides, named AutoGP, was developed in this study by integrating three different columns in a nano-LC system. Specifically, the peptide mixture from the enzymatic digestion of a complex biological sample was first loaded on a hydrophilic interaction chromatography (HILIC) column. The nonglycopeptides in the sample were washed off the column, and the glycopeptides retained by the HILIC column were eluted to a C18 trap column to achieve an automated glycopeptide enrichment. The enriched glycopeptides were further eluted to a C18 column for separation, and the separated glycopeptides were eventually analyzed by using an orbitrap mass spectrometer (MS). The optimal operating conditions for AutoGP were systemically studied, and the performance of the fully optimized AutoGP was compared with a conventional manual system used for glycopeptide analysis. The experimental evaluation shows that the total number of glycopeptides identified is at least 1.5-fold higher, and the median coefficient of variation for the analyses is at least 50% lower by using AutoGP, as compared to the results acquired by using the manual system. In addition, AutoGP can perform effective analysis even with a 1-μg sample amount, while a 10-μg sample at least will be needed by the manual system, implying an order of magnitude better sensitivity of AutoGP. All the experimental results have consistently proven that AutoGP can be used for much better characterization of intact glycopeptides.

Chemical Proteomic Approach for In-Depth Glycosylation Profiling of Plasma Carcinoembryonic Antigen in Cancer Patients

Carcinoembryonic antigen (CEA) of human plasma is a biomarker of many cancer diseases, and its N-glycosylation accounts for 60% of molecular mass. It is highly desirable to characterize its glycoforms for providing additional dimension of features to increase its performance in prognosis and diagnosis of cancers. However, to systematically characterize its site-specific glycosylation is challenging because of its low abundance. Here, we developed a highly sensitive strategy for in-depth glycosylation profiling of plasma CEA through chemical proteomics combined with multienzymatic digestion. A trifunctional probe was utilized to generate covalent bond of plasma CEA and its antibody upon UV irradiation. As low as 1 ng/ml CEA in plasma could be captured and digested with trypsin and chymotrypsin for intact glycopeptide characterization. Twenty six of 28 potential N-glycosylation sites were well identified, which were the most comprehensive N-glycosylation site characterization of CEA on intact glycopeptide level as far as we known. Importantly, this strategy was applied to the glycosylation analysis of plasma CEA in cancer patients. Differential site-specific glycoforms of plasma CEA were observed in patients with colorectal cancers (CRCs) and lung cancer. The distributions of site-specific glycoforms were different as the progression of CRC, and most site-specific glycoforms were overexpressed in stage II of CRC. Overall, we established a highly sensitive chemical proteomic method to profile site-specific glycosylation of plasma CEA, which should generally applicable to other well-established cancer glycoprotein biomarkers for improving their cancer diagnosis and monitoring performance.

Glycopeptide database search and de novo sequencing with PEAKS GlycanFinder enable highly sensitive glycoproteomics

Here we present GlycanFinder, a database search and de novo sequencing tool for the analysis of intact glycopeptides from mass spectrometry data. GlycanFinder integrates peptide-based and glycan-based search strategies to address the challenge of complex fragmentation of glycopeptides. A deep learning model is designed to capture glycan tree structures and their fragment ions for de novo sequencing of glycans that do not exist in the database. We performed extensive analyses to validate the false discovery rates (FDRs) at both peptide and glycan levels and to evaluate GlycanFinder based on comprehensive benchmarks from previous community-based studies. Our results show that GlycanFinder achieved comparable performance to other leading glycoproteomics softwares in terms of both FDR control and the number of identifications. Moreover, GlycanFinder was also able to identify glycopeptides not found in existing databases. Finally, we conducted a mass spectrometry experiment for antibody N-linked glycosylation profiling that could distinguish isomeric peptides and glycans in four immunoglobulin G subclasses, which had been a challenging problem to previous studies.

Glycoproteomic contributions to hepatocellular carcinoma research: a 2023 update

INTRODUCTION

Hepatocellular carcinoma (HCC) represents a significant burden globally, which ranks sixth among the most frequently diagnosed cancers and stands as the third leading cause of cancer-related mortality. Glycoproteomics, as an important branch of proteomics, has already made significant achievements in the field of HCC research. Aberrant protein glycosylation has shown to promote the malignant transformation of hepatocytes by modulating a wide range of tumor-promoting signaling pathways. The glycoproteome provides valuable information for understanding cancer progression, tumor immunity, and clinical outcome, which could serve as potential diagnostic, prognostic, and therapeutic tools in HCC.

AREAS COVERED

In this review, recent advances of glycoproteomics contribute to clinical applications (diagnosis and prognosis) and molecular mechanisms (hepatocarcinogenesis, progression, stemness and recurrence, and drug resistance) of HCC are summarized.

EXPERT OPINION

Glycoproteomics shows promise in HCC, enhancing early detection, risk stratification, and personalized treatments. Challenges include sample heterogeneity, diverse glycans structures, sensitivity issues, complex workflows, limited databases, and incomplete understanding of immune cell glycosylation. Addressing these limitations requires collaborative efforts, technological advancements, standardization, and validation studies. Future research should focus on targeting abnormal protein glycosylation therapeutically. Advancements in glycobiomarkers and glycosylation-targeted therapies will greatly impact HCC diagnosis, prognosis, and treatment.

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

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

Altered Glycosylation in Progression and Management of Bladder Cancer

Bladder cancer (BC) is the 10th most common malignancy worldwide, with an estimated 573,000 new cases and 213,000 deaths in 2020. Available therapeutic approaches are still unable to reduce the incidence of BC metastasis and the high mortality rates of BC patients. Therefore, there is a need to deepen our understanding of the molecular mechanisms underlying BC progression to develop new diagnostic and therapeutic tools. One such mechanism is protein glycosylation. Numerous studies reported changes in glycan biosynthesis during neoplastic transformation, resulting in the appearance of the so-called tumor-associated carbohydrate antigens (TACAs) on the cell surface. TACAs affect a wide range of key biological processes, including tumor cell survival and proliferation, invasion and metastasis, induction of chronic inflammation, angiogenesis, immune evasion, and insensitivity to apoptosis. The purpose of this review is to summarize the current information on how altered glycosylation of bladder cancer cells promotes disease progression and to present the potential use of glycans for diagnostic and therapeutic purposes.