Simultaneous Immunoglobulin A and G Glycopeptide Profiling for High-Throughput Applications

Comprehensive Immunoglobulin G, A, and M Glycopeptide Profiling for Large-Scale Biomedical Research

Glycosylation of immunoglobulin G (IgG) is recognized as a key modulator of cellular effector functions. At the same time, an increasing body of evidence underlines the importance of other antibody isotypes, especially IgA and IgM, in pathophysiological conditions. Therefore, methods to efficiently study the complex interplay between isotypes, subclasses, and glycosylation of antibodies during acute and chronic states of inflammation are needed. As a solution, we present an integrated and comprehensive method combining simultaneous affinity enrichment of IgG, IgA, and IgM with a single measurement, glycopeptide-centered LC-MS analysis of all isotypes which provides protein-specific (isotype and subclass), and site-specific N- and O-glycosylation quantitation. A two-protease approach provided individual peptides for each glycosylation site, allowing unambiguous compositional assignment and relative quantitation of glycoforms on the MS1 level as well as structural confirmation and partial isomer assignment on the MS/MS level. We demonstrate that our methodology can be efficiently applied to large clinical studies revealing differences in antibody glycosylation in women during and after pregnancy, as well as between healthy donors and patients with rheumatoid arthritis. In addition, this showcased the advantages of our method in comprehensiveness and resolution of isotypes, subclasses, and glycosylation sites as well as its precision and robustness.

IgA displays site- and subclass-specific glycoform differences despite equal glycoenzyme expression

BACKGROUND

Glycosylation is an important posttranslational modification of proteins and in most cases indispensable for proper protein function. Like most soluble proteins, IgA, the second most prevalent antibody in human serum, contains several N- and O-glycosylation sites. While for IgG the impact of Fc glycosylation on effector functions and inflammatory potential has been studied intensively, only little is known for IgA. In addition, only glimpses exist regarding the regulation of IgA glycosylation. We have previously shown that IgA1 and IgA2 differ functionally and also show differences in their glycosylation pattern. The more pro-inflammatory IgA2 which is linked to autoimmune diseases displays decreased sialylation, galactosylation, fucosylation and bisection as compared to IgA1. In the present study, we aimed to investigate these differences in glycosylation in detail and to explore the mechanisms underlying them.

METHODS

IgA1 and IgA2 was isolated from serum of 12 healthy donors. Site specific glycosylation was analyzed by mass spectrometry. In addition, human bone marrow plasma cells were investigated using single cell mRNA sequencing, flow cytometry and ELISpot.

RESULTS

We found that certain glycoforms greatly differ in their abundance between IgA1 and IgA2 while others are equally abundant. Overall, the IgA2 glycans displayed a more immature phenotype with a higher prevalence of oligomannose and fewer fully processed glycans. Of note, these differences can't be explained by differences in the glycosylation enzyme machinery as mRNA sequencing and flow cytometry analysis showed equal enzyme expression in IgA1 and IgA2 producing plasma cells. ELISpot analysis suggested a slightly increased antibody production rate in IgA2 producing plasma cells which might contribute to its lower glycan processing rates. But this difference was only minor, suggesting that further factors such as steric accessibility determine glycan processing. This is supported by the fact that glycans at different positions on the same IgA chain differ dramatically in fucosylation, sialylation and bisection.

CONCLUSION

In summary, our detailed overview of IgA1 and IgA2 glycosylation shows a class, subclass, and site-specific glycosylation fingerprint, most likely due to structural differences of the protein backbones.

The importance of IgG glycosylation-What did we learn after analyzing over 100,000 individuals

All four subclasses of immunoglobulin G (IgG) antibodies have glycan structures attached to the protein part of the IgG molecules. Glycans linked to the Fc portion of IgG are found in all IgG antibodies, while about one-fifth of IgG antibodies in plasma also have glycans attached to the Fab portion of IgG. The IgG3 subclass is characterized by more complex glycosylation compared to other IgG subclasses. In this review, we discuss the significant influence that glycans exert on the structural and functional properties of IgG. We provide a comprehensive overview of how the composition of these glycans can affect IgG's effector functions by modulating its interactions with Fcγ receptors and other molecules such as the C1q component of complement, which in turn influence various immune responses triggered by IgG, including antibody-dependent cell-mediated cytotoxicity (ADCC) and complement-dependent cytotoxicity (CDC). In addition, the importance of glycans for the efficacy of therapeutics like monoclonal antibodies and intravenous immunoglobulin (IVIg) therapy is discussed. Moreover, we offer insights into IgG glycosylation characteristics and roles derived from general population, disease-specific, and interventional studies. These studies indicate that IgG glycans are important biomarkers and functional effectors in health and disease.

Glycosylation signature of plasma IgA of critically ill COVID-19 patients

Thromboembolic complications are common in severe COVID-19 and are thought to result from excessive neutrophil-extracellular-trap (NET)-driven immunothrombosis. Glycosylation plays a vital role in the efficiency of immunoglobulin A (IgA) effector functions, with significant implications for NET formation in infectious diseases. This study represents the first comprehensive analysis of plasma IgA glycosylation during severe SARS-CoV-2 or Influenza A infection, revealing lower sialylation and higher galactosylation of IgA1 O-glycans in acute respiratory distress syndrome (ARDS), regardless of the underlying cause of the disease. Importantly, N-glycans displayed an infection-specific pattern, with N47 of IgA2 showing diminished sialylation and bisection, and N340/N327 of IgA1/2 demonstrating lower fucosylation and antennarity along with higher non-complex glycans in COVID-19 compared to Influenza. Notably, COVID-19 IgA possessed strong ability to induce NET formation and its glycosylation patterns correlated with extracellular DNA levels in plasma of critically ill COVID-19 patients. Our data underscores the necessity of further research on the role of IgA glycosylation in the modulation of pathogen-specific immune responses in COVID-19 and other infectious diseases.

AutoFocus: a hierarchical framework to explore multi-omic disease associations spanning multiple scales of biomolecular interaction

Recent advances in high-throughput measurement technologies have enabled the analysis of molecular perturbations associated with disease phenotypes at the multi-omic level. Such perturbations can range in scale from fluctuations of individual molecules to entire biological pathways. Data-driven clustering algorithms have long been used to group interactions into interpretable functional modules; however, these modules are typically constrained to a fixed size or statistical cutoff. Furthermore, modules are often analyzed independently of their broader biological context. Consequently, such clustering approaches limit the ability to explore functional module associations with disease phenotypes across multiple scales. Here, we introduce AutoFocus, a data-driven method that hierarchically organizes biomolecules and tests for phenotype enrichment at every level within the hierarchy. As a result, the method allows disease-associated modules to emerge at any scale. We evaluated this approach using two datasets: First, we explored associations of biomolecules from the multi-omic QMDiab dataset (n = 388) with the well-characterized type 2 diabetes phenotype. Secondly, we utilized the ROS/MAP Alzheimer's disease dataset (n = 500), consisting of high-throughput measurements of brain tissue to explore modules associated with multiple Alzheimer's Disease-related phenotypes. Our method identifies modules that are multi-omic, span multiple pathways, and vary in size. We provide an interactive tool to explore this hierarchy at different levels and probe enriched modules, empowering users to examine the full hierarchy, delve into biomolecular drivers of disease phenotype within a module, and incorporate functional annotations.

A unique serum IgG glycosylation signature predicts development of Crohn's disease and is associated with pathogenic antibodies to mannose glycan

Inflammatory bowel disease (IBD) is characterized by chronic inflammation in the gut. There is growing evidence in Crohn's disease (CD) of the existence of a preclinical period characterized by immunological changes preceding symptom onset that starts years before diagnosis. Gaining insight into this preclinical phase will allow disease prediction and prevention. Analysis of preclinical serum samples, up to 6 years before IBD diagnosis (from the PREDICTS cohort), revealed the identification of a unique glycosylation signature on circulating antibodies (IgGs) characterized by lower galactosylation levels of the IgG fragment crystallizable (Fc) domain that remained stable until disease diagnosis. This specific IgG2 Fc glycan trait correlated with increased levels of antimicrobial antibodies, specifically anti-Saccharomyces cerevisiae (ASCA), pinpointing a glycome-ASCA hub detected in serum that predates by years the development of CD. Mechanistically, we demonstrated that this agalactosylated glycoform of ASCA IgG, detected in the preclinical phase, elicits a proinflammatory immune pathway through the activation and reprogramming of innate immune cells, such as dendritic cells and natural killer cells, via an FcγR-dependent mechanism, triggering NF-κB and CARD9 signaling and leading to inflammasome activation. This proinflammatory role of ASCA was demonstrated to be dependent on mannose glycan recognition and galactosylation levels in the IgG Fc domain. The pathogenic properties of (anti-mannose) ASCA IgG were validated in vivo. Adoptive transfer of antibodies to mannan (ASCA) to recipient wild-type mice resulted in increased susceptibility to intestinal inflammation that was recovered in recipient FcγR-deficient mice. Here we identify a glycosylation signature in circulating IgGs that precedes CD onset and pinpoint a specific glycome-ASCA pathway as a central player in the initiation of inflammation many years before CD diagnosis. This pathogenic glyco-hub may constitute a promising new serum biomarker for CD prediction and a potential target for disease prevention.

A roadmap to the molecular human linking multiomics with population traits and diabetes subtypes

In-depth multiomic phenotyping provides molecular insights into complex physiological processes and their pathologies. Here, we report on integrating 18 diverse deep molecular phenotyping (omics-) technologies applied to urine, blood, and saliva samples from 391 participants of the multiethnic diabetes Qatar Metabolomics Study of Diabetes (QMDiab). Using 6,304 quantitative molecular traits with 1,221,345 genetic variants, methylation at 470,837 DNA CpG sites, and gene expression of 57,000 transcripts, we determine (1) within-platform partial correlations, (2) between-platform mutual best correlations, and (3) genome-, epigenome-, transcriptome-, and phenome-wide associations. Combined into a molecular network of > 34,000 statistically significant trait-trait links in biofluids, our study portrays "The Molecular Human". We describe the variances explained by each omics in the phenotypes (age, sex, BMI, and diabetes state), platform complementarity, and the inherent correlation structures of multiomics data. Further, we construct multi-molecular network of diabetes subtypes. Finally, we generated an open-access web interface to "The Molecular Human" ( http://comics.metabolomix.com ), providing interactive data exploration and hypotheses generation possibilities.

The genetics and epidemiology of N- and O-immunoglobulin A glycomics

BACKGROUND

Immunoglobulin (Ig) glycosylation modulates the immune response and plays a critical role in ageing and diseases. Studies have mainly focused on IgG glycosylation, and little is known about the genetics and epidemiology of IgA glycosylation.

METHODS

We generated, using a novel liquid chromatography-mass spectrometry method, the first large-scale IgA glycomics dataset in serum from 2423 twins, encompassing 71 N- and O-glycan species.

RESULTS

We showed that, despite the lack of a direct genetic template, glycosylation is highly heritable, and that glycopeptide structures are sex-specific, and undergo substantial changes with ageing. We observe extensive correlations between the IgA and IgG glycomes, and, exploiting the twin design, show that they are predominantly influenced by shared genetic factors. A genome-wide association study identified eight loci associated with both the IgA and IgG glycomes (ST6GAL1, ELL2, B4GALT1, ABCF2, TMEM121, SLC38A10, SMARCB1, and MGAT3) and two novel loci specifically modulating IgA O-glycosylation (C1GALT1 and ST3GAL1). Validation of our findings in an independent cohort of 320 individuals from Qatar showed that the underlying genetic architecture is conserved across ancestries.

CONCLUSIONS

Our study delineates the genetic landscape of IgA glycosylation and provides novel potential functional links with the aetiology of complex immune diseases, including genetic factors involved in IgA nephropathy risk.

Glycoproteomics: Charting new territory in mass spectrometry and glycobiology

Glycosylation is an incredibly common and diverse post-translational modification that contributes widely to cellular health and disease. Mass spectrometry is the premier technique to study glycoproteins; however, glycoproteomics has lagged behind traditional proteomics due to the challenges associated with studying glycosylation. For instance, glycans dissociate by collision-based fragmentation, thus necessitating electron-based fragmentation for site-localization. The vast glycan heterogeneity leads to lower overall abundance of each glycopeptide, and often, ion suppression is observed. One of the biggest issues facing glycoproteomics is the lack of reliable software for analysis, which necessitates manual validation and serves as a massive bottleneck in data processing. Here, I will discuss each of these challenges and some ways in which the field is attempting to address them, along with perspectives on how I believe we should move forward.

GlYcoLISA: antigen-specific and subclass-specific IgG Fc glycosylation analysis based on an immunosorbent assay with an LC-MS readout

Immunoglobulin G (IgG) fragment crystallizable (Fc) glycosylation modulates effector functions such as antibody-dependent cellular cytotoxicity and complement-dependent cytotoxicity. Consequently, assessing IgG Fc glycosylation is important for understanding the role of antibodies in infectious, alloimmune and autoimmune diseases. GlYcoLISA determines the Fc glycosylation of antigen-specific IgG by an immunosorbent assay with a liquid chromatography-mass spectrometry (LC-MS) readout. Detection of antigen-specific IgG glycosylation in a subclass- and site-specific manner is realized by LC-MS-based glycopeptide analysis after proteolytic cleavage. GlYcoLISA addresses challenges related to the low abundance of specific IgG and the high background of total IgG by using well-established immunosorbent assays for purifying antibodies of the desired specificity using immobilized antigen. Alternative methods with sufficient glycan resolution lack these important specificities. GlYcoLISA is performed in a 96-well plate format, and the analysis of 160 samples takes ~5 d, with 1 d for sample preparation, 2 d of LC-MS measurement and 2 d for partially automated data processing. GlYcoLISA requires expertise in LC-MS operation and data processing.

High-throughput N-glycan analysis in aging and inflammaging: State of the art and future directions

As the global population ages at an unprecedented rate, the prevalence of age-related diseases is increasing, making inflammaging - a phenomenon characterized by a chronic, low-grade inflammatory state that follows aging - a significant concern. Understanding the mechanisms of inflammaging and its impact on health is critical for developing strategies to improve the quality of life and manage health in the aging population. Despite their crucial roles in various biological processes, including immune response modulation, N-glycans, oligosaccharides covalently attached to many proteins, are often overlooked in clinical and research studies. This repeated oversight is largely due to their inherent complexity and the complexity of the analysis methods. High-throughput N-glycan analysis has emerged as a transformative tool in N-glycosylation research, enabling cost- and time-effective, detailed, and large-scale examination of N-glycan profiles. This paper is the first to explore the application of high-throughput N-glycomics techniques to investigate the complex interplay between N-glycosylation and the immune system in aging. Technological advancements have significantly improved Nglycan detection and characterization, providing insights into age-related changes in Nglycosylation. Key findings highlight consistent shifts in immunoglobulin G (IgG) and plasma/serum glycoprotein glycosylation with age, with a pronounced rise in agalactosylated structures bound to IgG that also affect the composition of the total plasma N-glycome. These N-glycan modifications seem to be strongly associated with inflammaging and have been identified as valuable biomarkers for biological age, predictors of disease risk, and proxy biomarkers for monitoring intervention efficacy at the individual level. Despite current challenges related to data complexity and methodological limitations, ongoing technological innovations and interdisciplinary research are expected tofurther advance our knowledge of glycan biology, improve diagnostic and therapeutic strategies, and promote healthier aging. The integration of glycomics with other omics approaches holds promise for a more comprehensive understanding of the aging immune system, paving the way for personalized medicine and targeted interventions to mitigate inflammaging. In conclusion, this paper underscores the transformative impact of high-throughput Nglycan analysis in aging and inflammaging.

Oxonium ion scanning mass spectrometry for large-scale plasma glycoproteomics

Protein glycosylation, a complex and heterogeneous post-translational modification that is frequently dysregulated in disease, has been difficult to analyse at scale. Here we report a data-independent acquisition technique for the large-scale mass-spectrometric quantification of glycopeptides in plasma samples. The technique, which we named 'OxoScan-MS', identifies oxonium ions as glycopeptide fragments and exploits a sliding-quadrupole dimension to generate comprehensive and untargeted oxonium ion maps of precursor masses assigned to fragment ions from non-enriched plasma samples. By applying OxoScan-MS to quantify 1,002 glycopeptide features in the plasma glycoproteomes from patients with COVID-19 and healthy controls, we found that severe COVID-19 induces differential glycosylation in IgA, haptoglobin, transferrin and other disease-relevant plasma glycoproteins. OxoScan-MS may allow for the quantitative mapping of glycoproteomes at the scale of hundreds to thousands of samples.

High-Throughput Glycan Profiling of Human Serum IgG Subclasses Using Parallel Reaction Monitoring Peptide Bond Fragmentation of Glycopeptides and Microflow LC-MS

LC-MS-based N-glycosylation profiling in four human serum IgG subclasses (IgG1, IgG2, IgG3, and IgG4) often requires additional affinity-based enrichment of specific IgG subclasses, owing to the high amino acid sequence similarity of Fc glycopeptides among subclasses. Notably, for IgG4 and the major allotype of IgG3, the glycopeptide precursors share identical retention time and mass and therefore cannot be distinguished based on precursor or glycan fragmentation. Here, we developed a parallel reaction monitoring (PRM)-based method for quantifying Fc glycopeptides through combined transitions generated from both glycosidic and peptide bond fragmentation. The latter enables the subpopulation of IgG3 and IgG4 to be directly distinguished according to mass differences without requiring further enrichment of specific IgG subclasses. In addition, a multinozzle electrospray emitter coupled to a capillary flow liquid chromatograph was used to increase the robustness and detection sensitivity of the method for low-yield peptide backbone fragment ions. The gradient was optimized to decrease the overall run time and make the method compatible with high-throughput analysis. We demonstrated that this method can be used to effectively monitor the relative levels of 13 representative glycoforms, with a good limit of detection for individual IgG subclasses.

Multiplexed Antibody Glycosylation Profiling Using Dual Enzyme Digestion and Liquid Chromatography-Triple Quadrupole Mass Spectrometry Method

Antibody glycosylation plays a crucial role in the humoral immune response by regulating effector functions and influencing the binding affinity to immune cell receptors. Previous studies have focused mainly on the immunoglobulin G (IgG) isotype owing to the analytical challenges associated with other isotypes. Thus, the development of a sensitive and accurate analytical platform is necessary to characterize antibody glycosylation across multiple isotypes. In this study, we have developed an analytical workflow using antibody-light-chain affinity beads to purify IgG, IgA, and IgM from 16 μL of human plasma. Dual enzymes, trypsin and Glu-C, were used during on-bead digestion to obtain enzymatic glycopeptides and protein-specific surrogate peptides. Ultra-high-performance liquid chromatography coupled with triple quadrupole mass spectrometry was used in order to determine the sensitivity and specificity. Our platform targets 95 glycopeptides across the IgG, IgA, and IgM isotypes, as well as eight surrogate peptides representing total IgG, four IgG classes, two IgA classes, and IgM. Four stable isotope-labeled internal standards were added after antibody purification to calibrate the preparation and instrumental bias during analysis. Calibration curves constructed using serially diluted plasma samples showed good curve fitting (R2 > 0.959). The intrabatch and interbatch precision for all the targets had relative standard deviation of less than 29.6%. This method was applied to 19 human plasma samples, and the glycosylation percentages were calculated, which were comparable to those reported in the literature. The developed method is sensitive and accurate for Ig glycosylation profiling. It can be used in clinical investigations, particularly for detailed humoral immune profiling.

Immunoglobulin A Glycosylation Differs between Crohn's Disease and Ulcerative Colitis

Inflammatory bowel diseases (IBD), such as Crohn's disease (CD) and ulcerative colitis (UC), are chronic and relapsing inflammations of the digestive tract with increasing prevalence, yet they have unknown origins or cure. CD and UC have similar symptoms but respond differently to surgery and medication. Current diagnostic tools often involve invasive procedures, while laboratory markers for patient stratification are lacking. Large glycomic studies of immunoglobulin G and total plasma glycosylation have shown biomarker potential in IBD and could help determine disease mechanisms and therapeutic treatment choice. Hitherto, the glycosylation signatures of plasma immunoglobulin A, an important immunoglobulin secreted into the intestinal mucin, have remained undetermined in the context of IBD. Our study investigated the associations of immunoglobulin A1 and A2 glycosylation with IBD in 442 IBD cases (188 CD and 254 UC) and 120 healthy controls by reversed-phase liquid chromatography electrospray-ionization mass spectrometry of tryptic glycopeptides. Differences of IgA O- and N-glycosylation (including galactosylation, bisection, sialylation, and antennarity) between patient groups were associated with the diseases, and these findings led to the construction of a statistical model to predict the disease group of the patients without the need of invasive procedures. This study expands the current knowledge about CD and UC and could help in the development of noninvasive biomarkers and better patient care.

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.

Glycoproteomics in Cerebrospinal Fluid Reveals Brain-Specific Glycosylation Changes

The glycosylation of proteins plays an important role in neurological development and disease. Glycoproteomic studies on cerebrospinal fluid (CSF) are a valuable tool to gain insight into brain glycosylation and its changes in disease. However, it is important to consider that most proteins in CSFs originate from the blood and enter the CSF across the blood-CSF barrier, thus not reflecting the glycosylation status of the brain. Here, we apply a glycoproteomics method to human CSF, focusing on differences between brain- and blood-derived proteins. To facilitate the analysis of the glycan site occupancy, we refrain from glycopeptide enrichment. In healthy individuals, we describe the presence of heterogeneous brain-type N-glycans on prostaglandin H2-D isomerase alongside the dominant plasma-type N-glycans for proteins such as transferrin or haptoglobin, showing the tissue specificity of protein glycosylation. We apply our methodology to patients diagnosed with various genetic glycosylation disorders who have neurological impairments. In patients with severe glycosylation alterations, we observe that heavily truncated glycans and a complete loss of glycans are more pronounced in brain-derived proteins. We speculate that a similar effect can be observed in other neurological diseases where a focus on brain-derived proteins in the CSF could be similarly beneficial to gain insight into disease-related changes.

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

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

Exploration of quantitative site-specific serum O-glycoproteomics with isobaric labeling for the discovery of putative O-glycoprotein biomarkers

PURPOSE

Exploration study of site-specific isobaric-TMT-labeling quantitative serum O-glycoproteomics for the discovery of putative O-glycoprotein cancer biomarkers.

EXPERIMENTAL DESIGN

Sera of 10 breast cancer patients was used as the exploration cohort. More abundant N-glycosylation was first removed with PNGase F. After tryptic digestion of de-N-glycosylated serum proteome, the TMT-labeled O-glycopeptides mixture was prepared and analyzed with RPLC-MS/MS. Site-specific qualitative and quantitative database search of O-glycopeptides was carried out with pGlyco 3.0. The same raw datasets were also searched with intact N-glycopeptide search engine GPSeeker to exclude possible interference of N-glycosylation. The final IDs were checked manually with GlcNAc-containing glycosite-determining fragment ions for confirmation.

RESULTS

With the control of spectrum-level FDR ≤ 1% and manual validation, 299 O-glycopeptides corresponding to 83 O-glycosites and 66 O-glycoproteins were identified, and 13 O-glycopeptides were found differentially expressed. Most interestingly, differential O-glycosylation was observed for IgG1 and IgG3, which is an interesting putative biomarker panel.

CONCLUSION AND CLINICAL RELEVANCE

Isobaric-labeling site-specific quantitative O-glycoproteomics is currently a state-of-the-art instrumental platform for discovery of putative seral cancer biomarkers. Differential seral O-glycosylation was observed in the IgG1 and IgG3.

High-Throughput Glycomic Methods

Glycomics aims to identify the structure and function of the glycome, the complete set of oligosaccharides (glycans), produced in a given cell or organism, as well as to identify genes and other factors that govern glycosylation. This challenging endeavor requires highly robust, sensitive, and potentially automatable analytical technologies for the analysis of hundreds or thousands of glycomes in a timely manner (termed high-throughput glycomics). This review provides a historic overview as well as highlights recent developments and challenges of glycomic profiling by the most prominent high-throughput glycomic approaches, with N-glycosylation analysis as the focal point. It describes the current state-of-the-art regarding levels of characterization and most widely used technologies, selected applications of high-throughput glycomics in deciphering glycosylation process in healthy and disease states, as well as future perspectives.

Site-specific N-glycosylation characterization of micro monoclonal immunoglobulins based on EThcD-sceHCD-MS/MS

Monoclonal immunoglobulin produced by clonal plasma cells is the main cause in multiple myeloma and monoclonal gammopathy of renal significance. Because of the complicated purification method and the low stoichiometry of purified protein and glycans, site-specific N-glycosylation characterization for monoclonal immunoglobulin is still challenging. To profile the site-specific N-glycosylation of monoclonal immunoglobulins is of great interest. Therefore, in this study, we presented an integrated workflow for micro monoclonal IgA and IgG purification from patients with multiple myeloma in the HYDRASYS system, in-agarose-gel digestion, LC-MS/MS analysis without intact N-glycopeptide enrichment, and compared the identification performance of different mass spectrometry dissociation methods (EThcD-sceHCD, sceHCD, EThcD and sceHCD-pd-ETD). The results showed that EThcD-sceHCD was a better choice for site-specific N-glycosylation characterization of micro in-agarose-gel immunoglobulins (~2 μg) because it can cover more unique intact N-glycopeptides (37 and 50 intact N-glycopeptides from IgA1 and IgG2, respectively) and provide more high-quality spectra than sceHCD, EThcD and sceHCD-pd-ETD. We demonstrated the benefits of the alternative strategy in site-specific N-glycosylation characterizing micro monoclonal immunoglobulins obtained from bands separated by electrophoresis. This work could promote the development of clinical N-glycoproteomics and related immunology.

Glycosylation of immunoglobin G in tumors: Function, regulation and clinical implications

Immunoglobulin G (IgG) is the predominant component in humoral immunity and the major effector of neutralizing heterogeneous antigens. Glycosylation, as excessive posttranscriptional modification, can modulate IgG immune function. Glycosylated IgG has been reported to correlate with tumor progression, presenting several characteristic modifications, including the core fucose, galactose, sialic acid, and the bisect N-acetylglucosamine (GlcNAc). Meanwhile, IgG glycosylation regulates tumor immunity involved in tumor progression and is thus a potential target. Herein, we summarized the research progression to provide novel insight into the application of IgG glycosylation in tumor diagnosis and treatment.

Developments and perspectives in high-throughput protein glycomics: enabling the analysis of thousands of samples

Glycans expand the structural complexity of proteins by several orders of magnitude, resulting in a tremendous analytical challenge when including them in biomedical research. Recent glycobiological research is painting a picture in which glycans represent a crucial structural and functional component of the majority of proteins, with alternative glycosylation of proteins and lipids being an important regulatory mechanism in many biological and pathological processes. Since interindividual differences in glycosylation are extensive, large studies are needed to map the structures and to understand the role of glycosylation in human (patho)physiology. Driven by these challenges, methods have emerged, which can tackle the complexity of glycosylation in thousands of samples, also known as high-throughput (HT) glycomics. For facile dissemination and implementation of HT glycomics technology, the sample preparation, analysis, as well as data mining, need to be stable over a long period of time (months/years), amenable to automation, and available to non-specialized laboratories. Current HT glycomics methods mainly focus on protein N-glycosylation and allow to extensively characterize this subset of the human glycome in large numbers of various biological samples. The ultimate goal in HT glycomics is to gain better knowledge and understanding of the complete human glycome using methods that are easy to adapt and implement in (basic) biomedical research. Aiming to promote wider use and development of HT glycomics, here, we present currently available, emerging, and prospective methods and some of their applications, revealing a largely unexplored molecular layer of the complexity of life.

Strategies for Proteome-Wide Quantification of Glycosylation Macro- and Micro-Heterogeneity

Protein glycosylation governs key physiological and pathological processes in human cells. Aberrant glycosylation is thus closely associated with disease progression. Mass spectrometry (MS)-based glycoproteomics has emerged as an indispensable tool for investigating glycosylation changes in biological samples with high sensitivity. Following rapid improvements in methodologies for reliable intact glycopeptide identification, site-specific quantification of glycopeptide macro- and micro-heterogeneity at the proteome scale has become an urgent need for exploring glycosylation regulations. Here, we summarize recent advances in N- and O-linked glycoproteomic quantification strategies and discuss their limitations. We further describe a strategy to propagate MS data for multilayered glycopeptide quantification, enabling a more comprehensive examination of global and site-specific glycosylation changes. Altogether, we show how quantitative glycoproteomics methods explore glycosylation regulation in human diseases and promote the discovery of biomarkers and therapeutic targets.

Bisecting Lewis X in Hybrid-Type N-Glycans of Human Brain Revealed by Deep Structural Glycomics

The importance of protein glycosylation in the biomedical field requires methods that not only quantitate structures by their monosaccharide composition, but also resolve and identify the many isomers expressed by mammalian cells. The art of unambiguous identification of isomeric structures in complex mixtures, however, did not yet catch up with the fast pace of advance of high-throughput glycomics. Here, we present a strategy for deducing structures with the help of a deci-minute accurate retention time library for porous graphitic carbon chromatography with mass spectrometric detection. We implemented the concept for the fundamental N-glycan type consisting of five hexoses, four N-acetylhexosamines and one fucose residue. Nearly all of the 40 biosynthetized isomers occupied unique elution positions. This result demonstrates the unique isomer selectivity of porous graphitic carbon. With the help of a rather tightly spaced grid of isotope-labeled internal N-glycan, standard retention times were transposed to a standard chromatogram. Application of this approach to animal and human brain N-glycans immediately identified the majority of structures as being of the bisected type. Most notably, it exposed hybrid-type glycans with galactosylated and even Lewis X containing bisected N-acetylglucosamine, which have not yet been discovered in a natural source. Thus, the time grid approach implemented herein facilitated discovery of the still missing pieces of the N-glycome in our most noble organ and suggests itself—in conjunction with collision induced dissociation—as a starting point for the overdue development of isomer-specific deep structural glycomics.

Comparison of human IgG glycopeptides separation using mixed-mode hydrophilic interaction/ion-exchange liquid chromatography and reversed-phase mode

Glycoproteomics is a challenging branch of proteomics because of the micro- and macro-heterogeneity of protein glycosylation. Hydrophilic interaction liquid chromatography (HILIC) is an advantageous alternative to reversed-phase chromatography for intact glycopeptide separation prior to their identification by mass spectrometry. Nowadays, several HILIC columns differing in used chemistries are commercially available. However, there is a lack of comparative studies assessing their performance, and thus providing guidance for the selection of an adequate stationary phase for different glycoproteomics applications. Here, we compare three HILIC columns recently developed by Advanced Chromatography Technologies (ACE)- with unfunctionalized (HILIC-A), polyhydroxy functionalized (HILIC-N), and aminopropyl functionalized (HILIC-B) silica- with a C18 reversed-phase column in the separation of human immunoglobulin G glycopeptides. HILIC-A and HILIC-B exhibit mixed-mode separation combining hydrophilic and ion-exchange interactions for analyte retention. Expectably, reversed-phase mode successfully separated clusters of immunoglobulin G1 and immunoglobulin G2 glycopeptides, which differ in amino acid sequence, but was not able to adequately separate different glycoforms of the same peptide. All ACE HILIC columns showed higher separation power for different glycoforms, and we show that each column separates a different group of glycopeptides more effectively than the others. Moreover, HILIC-A and HILIC-N columns separated the isobaric A2G1F1 glycopeptides of immunoglobulin G, and thus showed the potential for the elucidation of the structure of isomeric glycoforms. Furthermore, the possible retention mechanism for the HILIC columns is discussed on the basis of the determined chromatographic parameters.

Revealing the changes of IgG subclass-specific N-glycosylation in colorectal cancer progression by high-throughput assay

PURPOSE

The changes of glycosylation of different IgG subclass in colorectal cancer (CRC) were rarely investigated. The authors aimed to use a simple and high-throughput analytical method to explore the changes of subclass-specific IgG glycosylation in CRC, and to find the specific glyco-biomarkers for early detection of this disease.

EXPERIMENTAL DESIGN

Serum samples from 71 cancer patients and 22 benign patients with 50 age- and sex-matched healthy controls were collected from two independent cohorts. Subclass-specific IgG glycosylation was profiled by MALDI-MS followed by the structural identification through MALDI-MS/MS. The exported MS data was automatically and rapidly processed by the self-developed MATLAB code.

RESULTS

Statistical analysis suggested the significantly decreased galactosylation and remarkably increased agalactosylation of IgG1 or IgG2 in the malignant transformation of CRC, which enables the differentiation between cancer patients and healthy controls. The changes of glycan features were elucidated by the exploration of individual glycopeptides, showing the biantennary fucosylated glycan without galactose (H3N4F1) or with two galactose (H5N4F1) of IgG1 and IgG2 could distinguish cancer group from both benign and control groups.

CONCLUSIONS AND CLINICAL RELEVANCE

Through the simple and high-throughput procedures, this study revealed the important role of IgG glycopeptides in the premature pathology of CRC.

Serum and Plasma Immunoglobulin G Fc N-Glycosylation Is Stable during Storage

Immunoglobulin G (IgG) glycosylation is studied in biological samples to develop clinical markers for precision medicine, for example, in autoimmune diseases and oncology. Inappropriate storage of proteins, lipids, or metabolites can lead to degradation or modification of biomolecular features, which can have a strong negative impact on accuracy and precision of clinical omics studies. Regarding the preservation of IgG glycosylation, the range of appropriate storage conditions and time frame is understudied. Therefore, we investigated the effect of storage on IgG Fc N-glycosylation in the commonly analyzed biofluids, serum and plasma. Short-term storage and accelerated storage stability were tested by incubating samples from three healthy donors under stress conditions of up to 50 °C for 2 weeks using −80 °C for 2 weeks as the reference condition. All tested IgG glycosylation features—sialylation, galactosylation, bisection, and fucosylation—remained unchanged up to room temperature as well as during multiple freeze–thaw cycles and exposure to light. Only when subjected to 37 °C or 50 °C for 2 weeks, galactosylation and sialylation subtly changed. Therefore, clinical IgG glycosylation analysis does not rely as heavily on mild serum and plasma storage conditions and timely analysis as many other omics analyses.

Glycomic-Based Biomarkers for Ovarian Cancer: Advances and Challenges

Ovarian cancer remains one of the most common causes of death among gynecological malignancies afflicting women worldwide. Among the gynecological cancers, cervical and endometrial cancers confer the greatest burden to the developing and the developed world, respectively; however, the overall survival rates for patients with ovarian cancer are worse than the two aforementioned. The majority of patients with ovarian cancer are diagnosed at an advanced stage when cancer has metastasized to different body sites and the cure rates, including the five-year survival, are significantly diminished. The delay in diagnosis is due to the absence of or unspecific symptoms at the initial stages of cancer as well as a lack of effective screening and diagnostic biomarkers that can detect cancer at the early stages. This, therefore, provides an imperative to prospect for new biomarkers that will provide early diagnostic strategies allowing timely mitigative interventions. Glycosylation is a protein post-translational modification that is modified in cancer patients. In the current review, we document the state-of-the-art of blood-based glycomic biomarkers for early diagnosis of ovarian cancer and the technologies currently used in this endeavor.

Quantitative characterization of O-GalNAc glycosylation

O-GalNAc type glycosylation is an abundant and complex protein modification. Recent developments in mass spectrometry resulted in significant success in quantitative analysis of O-GalNAc glycosylation. The analysis of released O-GalNAc type glycans expanded our horizons of understanding the glycome of various biological models. The site-specific analysis of glycosylation micro-heterogeneity of purified proteins opened perspectives for the improved design of glycoprotein therapeutics. Advanced gene editing and chemical technologies applied to O-glycoproteomics enabled to identify O-GalNAc glycosylation at unprecedented depth. Progress in the analysis of intact glycoproteins under native and reduced conditions enabled the monitoring of glycosylation proteoform variants. Despite of the astonishing results in quantitative O-GalNAc glycoproteomics, site-specific mapping of the full O-GalNAc structural repertoire in complex samples is yet a long way off. Here, we summarize the most common quantitative strategies in O-GalNAc glycoproteomics, review recent progress and discuss benefits and limitations of the various approaches in the field.

Bioinformatics in Immunoglobulin Glycosylation Analysis

Analytical methods developed for studying immunoglobulin glycosylation rely heavily on software tailored for this purpose. Many of these tools are now used in high-throughput settings, especially for the glycomic characterization of IgG. A collection of these tools, and the databases they rely on, are presented in this chapter. Specific applications are detailed in examples of immunoglobulin glycomics and glycoproteomics data processing workflows. The results obtained in the glycoproteomics workflow are emphasized with the use of dedicated visualizing tools. These tools enable the user to highlight glycan properties and their differential expression.

Lectin and Liquid Chromatography-Based Methods for Immunoglobulin (G) Glycosylation Analysis

Immunoglobulin (Ig) glycosylation has been shown to dramatically affect its structure and effector functions. Ig glycosylation changes have been associated with different diseases and show a promising biomarker potential for diagnosis and prognosis of disease advancement. On the other hand, therapeutic biomolecules based on structural and functional features of Igs demand stringent quality control during the production process to ensure their safety and efficacy. Liquid chromatography (LC) and lectin-based methods are routinely used in Ig glycosylation analysis complementary to other analytical methods, e.g., mass spectrometry and capillary electrophoresis. This chapter covers analytical approaches based on LC and lectins used in low- and high-throughput N- and O-glycosylation analysis of Igs, with the focus on immunoglobulin G (IgG) applications. General principles and practical examples of the most often used LC methods for Ig purification are described, together with typical workflows for N- and O-glycan analysis on the level of free glycans, glycopeptides, subunits, or intact Igs. Lectin chromatography is a historical approach for the analysis of lectin-carbohydrate interactions and glycoprotein purification but is still being used as a valuable tool in Igs purification and glycan analysis. On the other hand, lectin microarrays have found their application in the rapid screening of glycan profiles on intact proteins.

Automation of Immunoglobulin Glycosylation Analysis

The development of reliable, affordable, high-resolution glycomics technologies that can be used for many samples in a high-throughput manner are essential for both the optimization of glycosylation in the biopharmaceutical industry as well as for the advancement of clinical diagnostics based on glycosylation biomarkers. We will use this chapter to review the sample preparation processes that have been used on liquid-handling robots to obtain high-quality glycomics data for both biopharmaceutical and clinical antibody samples. This will focus on glycoprotein purification, followed by glycan or glycopeptide generation, derivatization and enrichment. The use of liquid-handling robots for glycomics studies on other sample types beyond antibodies will not be discussed here. We will summarize our thoughts on the current status of the field and explore the benefits and challenges associated with developing and using automated platforms for sample preparation. Finally, the future outlook for the automation of glycomics will be discussed along with a projected impact on the field in general.

Semiautomated glycoproteomics data analysis workflow for maximized glycopeptide identification and reliable quantification

Glycoproteomic data are often very complex, reflecting the high structural diversity of peptide and glycan portions. The use of glycopeptide-centered glycoproteomics by mass spectrometry is rapidly evolving in many research areas, leading to a demand in reliable data analysis tools. In recent years, several bioinformatic tools were developed to facilitate and improve both the identification and quantification of glycopeptides. Here, a selection of these tools was combined and evaluated with the aim of establishing a robust glycopeptide detection and quantification workflow targeting enriched glycoproteins. For this purpose, a tryptic digest from affinity-purified immunoglobulins G and A was analyzed on a nano-reversed-phase liquid chromatography-tandem mass spectrometry platform with a high-resolution mass analyzer and higher-energy collisional dissociation fragmentation. Initial glycopeptide identification based on MS/MS data was aided by the Byonic software. Additional MS1-based glycopeptide identification relying on accurate mass and retention time differences using GlycopeptideGraphMS considerably expanded the set of confidently annotated glycopeptides. For glycopeptide quantification, the performance of LaCyTools was compared to Skyline, and GlycopeptideGraphMS. All quantification packages resulted in comparable glycosylation profiles but featured differences in terms of robustness and data quality control. Partial cysteine oxidation was identified as an unexpectedly abundant peptide modification and impaired the automated processing of several IgA glycopeptides. Finally, this study presents a semiautomated workflow for reliable glycoproteomic data analysis by the combination of software packages for MS/MS- and MS1-based glycopeptide identification as well as the integration of analyte quality control and quantification.