Healthy human serum N-glycan profiling reveals the influence of ethnic variation on the identified cancer-relevant glycan biomarkers

Regulators of placental antibody transfer through a modeling lens

Infants are vulnerable to infections owing to a limited ability to mount a humoral immune response and their tolerogenic immune phenotype, which has impeded the success of newborn vaccination. Transplacental transfer of IgG from mother to fetus provides crucial protection in the first weeks of life, and maternal immunization has recently been implemented as a public health strategy to protect newborns against serious infections. Despite their early success, current maternal vaccines do not provide comparable protection across pregnancies with varying gestational lengths and placental and maternal immune features, and they do not account for the dynamic interplay between the maternal immune response and placental transfer. Moreover, progress toward the rational design of maternal vaccines has been hindered by inadequacies of existing experimental models and safety challenges of investigating longitudinal dynamics of IgG transfer in pregnant humans. Alternatively, in silico mechanistic models are a logical framework to disentangle the processes regulating placental antibody transfer. This Review synthesizes current literature through a mechanistic modeling lens to identify placental and maternal regulators of antibody transfer, their clinical covariates, and knowledge gaps to guide future research. We also describe opportunities to use integrated modeling and experimental approaches toward the rational design of vaccines against existing and emerging neonatal pathogen threats.

GlycoSS: A DNA Glycosignal Sieve for Deciphering Spatially Resolved EpCAM-Specific Glycoforms

Malignant transformation of cancer is often accompanied by aberrant glycopatterns. Epithelial-mesenchymal transition (EMT) is a crucial biological process in cancer migration and invasion, accelerating cancer deterioration. High-precision analysis of protein-glycan spatial profiling in the EMT process is essential for elucidating glycosylation functions and cancer progression. However, the diversity of glycans in composition and conformation complicates their spatial analysis. Here, we develop a DNA glycosignal sieve (GlycoSS) visualization platform for screening glycoform expression with a protein spatial dimension. GlycoSS utilizes protein-anchored DNA nanoscanners of distinct lengths to control glycosignal readout, enabling protein-glycan distance modulations, and simultaneously orthogonally amplify glycoform output through signal amplification by an exchange reaction. Using GlycoSS, we screened EpCAM-specific hypoglycosylated glycoform signals in different breast cancer cell subtypes, especially characterizing the spatial distribution of glycans on the MCF-7 cell surface. Considering that the EpCAM-specific N-glycan dysregulation in EMT is pivotal, GlycoSS revealed dynamic glycan fluctuations during IGF-1-induced EMT, revealing that the N-glycans were positively associated with tumor malignancy and metastasis. GlycoSS is anticipated to accelerate the identification of aberrant N-glycosylation in tumor progression, advancing systemic glycobiology insights. Notably, GlycoSS is capable of analyzing diverse glycoprotein profiles, offering additional dimensions into the role of glycoprotein nanoenvironments in regulating membrane protein function.

Medical Relevance, State-of-the-Art and Perspectives of "Sweet Metacode" in Liquid Biopsy Approaches

This review briefly introduces readers to an area where glycomics meets modern oncodiagnostics with a focus on the analysis of sialic acid (Neu5Ac)-terminated structures. We present the biochemical perspective of aberrant sialylation during tumourigenesis and its significance, as well as an analytical perspective on the detection of these structures using different approaches for diagnostic and therapeutic purposes. We also provide a comparison to other established liquid biopsy approaches, and we mathematically define an early-stage cancer based on the overall prognosis and effect of these approaches on the patient's quality of life. Finally, some barriers including regulations and quality of clinical validations data are discussed, and a perspective and major challenges in this area are summarised.

Many Roles of Carbohydrates: A Computational Spotlight on the Coronavirus S Protein Binding

Glycosylation is one of the post-translational modifications with more than 50% of human proteins being glycosylated. The exact nature and chemical composition of glycans are inaccessible to X-ray or cryo-electron microscopy imaging techniques. Therefore, computational modeling studies and molecular dynamics must be used as a "computational microscope". The spike (S) protein of SARS-CoV-2 is heavily glycosylated, and a few glycans play a more functional role "beyond shielding". In this mini-review, we discuss computational investigations of the roles of specific S-protein and ACE2 glycans in the overall ACE2-S protein binding. We highlight different functions of specific glycans demonstrated in myriad computational models and simulations in the context of the SARS-CoV-2 virus binding to the receptor. We also discuss interactions between glycocalyx and the S protein, which may be utilized to design prophylactic polysaccharide-based therapeutics targeting the S protein. In addition, we underline the recent emergence of coronavirus variants and their impact on the S protein and its glycans.

N-glycan profiling of tissue samples to aid breast cancer subtyping

Breast cancer is a highly heterogeneous disease. Its intrinsic subtype classification for diagnosis and choice of therapy traditionally relies on the presence of characteristic receptors. Unfortunately, this classification is often not sufficient for precise prediction of disease prognosis and treatment efficacy. The N-glycan profiles of 145 tumors and 10 healthy breast tissues were determined using Matrix-Assisted Laser Desorption-Ionization Time-of-Flight Mass Spectrometry. The tumor samples were classified into Mucinous, Lobular, No-Special-Type, Human Epidermal Growth Factor 2 + , and Triple-Negative Breast Cancer subtypes. Statistical analysis was conducted using the reproducibility-optimized test statistic software package in R, and the Wilcoxon rank sum test with continuity correction. In total, 92 N-glycans were detected and quantified, with 59 consistently observed in over half of the samples. Significant variations in N-glycan signals were found among subtypes. Mucinous tumor samples exhibited the most distinct changes, with 28 significantly altered N-glycan signals. Increased levels of tri- and tetra-antennary N-glycans were notably present in this subtype. Triple-Negative Breast Cancer showed more N-glycans with additional mannose units, a factor associated with cancer progression. Individual N-glycans differentiated Human Epidermal Growth Factor 2 + , No-Special-Type, and Lobular cancers, whereas lower fucosylation and branching levels were found in N-glycans significantly increased in Luminal subtypes (Lobular and No-Special-Type tumors). Clinically normal breast tissues featured a higher abundance of signals corresponding to N-glycans with bisecting moiety. This research confirms that histologically distinct breast cancer subtypes have a quantitatively unique set of N-glycans linked to clinical parameters like tumor size, proliferative rate, lymphovascular invasion, and metastases to lymph nodes. The presented results provide novel information that N-glycan profiling could accurately classify human breast cancer samples, offer stratification of patients, and ongoing disease monitoring.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2017-2018

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization mass spectrometry (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2018. Also included are papers that describe methods appropriate to glycan and glycoprotein analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. Topics covered in the first part of the review include general aspects such as theory of the MALDI process, new methods, matrices, derivatization, MALDI imaging, fragmentation and the use of arrays. The second part of the review is devoted to applications to various structural types such as oligo- and poly-saccharides, glycoproteins, glycolipids, glycosides, and biopharmaceuticals. Most of the applications are presented in tabular form. The third part of the review covers medical and industrial applications of the technique, studies of enzyme reactions, and applications to chemical synthesis. The reported work shows increasing use of combined new techniques such as ion mobility and highlights the impact that MALDI imaging is having across a range of diciplines. MALDI is still an ideal technique for carbohydrate analysis and advancements in the technique and the range of applications continue steady progress.

Immunoglobulin G N-glycan, inflammation and type 2 diabetes in East Asian and European populations: a Mendelian randomization study

Background

Immunoglobulin G (IgG) N-glycans have been shown to be associated with the risk of type 2 diabetes (T2D) and its risk factors. However, whether these associations reflect causal effects remain unclear. Furthermore, the associations of IgG N-glycans and inflammation are not fully understood.

Methods

We examined the causal associations of IgG N-glycans with inflammation (C-reactive protein (CRP) and fibrinogen) and T2D using two-sample Mendelian randomization (MR) analysis in East Asian and European populations. Genetic variants from IgG N-glycan quantitative trait loci (QTL) data were used as instrumental variables. Two-sample MR was conducted for IgG N-glycans with inflammation (75,391 and 18,348 participants of CRP and fibrinogen in the East Asian population, 204,402 participants of CRP in the European population) and T2D risk (77,418 cases and 356,122 controls of East Asian ancestry, 81,412 cases and 370,832 controls of European ancestry).

Results

After correcting for multiple testing, in the East Asian population, genetically determined IgG N-glycans were associated with a higher risk of T2D, the odds ratios (ORs) were 1.009 for T2D per 1- standard deviation (SD) higher GP5, 95% CI = 1.003–1.015; P = 0.0019; and 1.013 for T2D per 1-SD higher GP13, 95% CI = 1.006–1.021; P = 0.0005. In the European population, genetically determined decreased GP9 was associated with T2D (OR = 0.899 per 1-SD lower GP9, 95% CI: 0.845–0.957). In addition, there was suggestive evidence that genetically determined IgG N-glycans were associated with CRP in both East Asian and European populations after correcting for multiple testing, but no associations were found between IgG N-glycans and fibrinogen. There was limited evidence of heterogeneity and pleiotropy bias.

Conclusions

Our results provided novel genetic evidence that IgG N-glycans are causally associated with T2D.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10020-022-00543-z.

Artificial intelligence in the analysis of glycosylation data

Glycans are complex, yet ubiquitous across biological systems. They are involved in diverse essential organismal functions. Aberrant glycosylation may lead to disease development, such as cancer, autoimmune diseases, and inflammatory diseases. Glycans, both normal and aberrant, are synthesized using extensive glycosylation machinery, and understanding this machinery can provide invaluable insights for diagnosis, prognosis, and treatment of various diseases. Increasing amounts of glycomics data are being generated thanks to advances in glycoanalytics technologies, but to maximize the value of such data, innovations are needed for analyzing and interpreting large-scale glycomics data. Artificial intelligence (AI) provides a powerful analysis toolbox in many scientific fields, and here we review state-of-the-art AI approaches on glycosylation analysis. We further discuss how models can be analyzed to gain mechanistic insights into glycosylation machinery and how the machinery shapes glycans under different scenarios. Finally, we propose how to leverage the gained knowledge for developing predictive AI-based models of glycosylation. Thus, guiding future research of AI-based glycosylation model development will provide valuable insights into glycosylation and glycan machinery.

BOA/DHB/Na: An Efficient UV-MALDI Matrix for High-Sensitivity and Auto-Tagging Glycomics

Matrix selection is a critical factor for success in glycomics studies using matrix-assisted laser desorption/ionization–mass spectrometry (MALDI–MS). In this study, we evaluated and optimized a new solid ionic matrix—O-benzylhydroxylamine (BOA)/2,5-dihydroxybenzoic acid (DHB)/Na—containing BOA and a small amount of sodium as the counter salt of DHB. The concentration of a mixture of BOA/DHB/Na and glycans on a MALDI target plate led to O-benzyloxy tagging of the reducing ends of the glycans. The BOA/DHB/Na matrix showed excellent aggregation performance and the ability to form a homogeneous solid salt on the MALDI target plate with a water-repellent surface. In addition, the BOA/DHB/Na matrix showed a simple peak pattern with suppressed in-source and post-source decay of the reducing ends of the glycans, as well as improved ionization efficiency of glycans. Utilizing the characteristics of the BOA/DHB/Na matrix, O-glycan analysis of porcine stomach mucin showed excellent detection sensitivity and reproducibility of the peak patterns. This BOA/DHB/Na matrix can accelerate glycomics studies using MALDI–MS and, in combination with other organic salt-type matrices that we have developed, constitutes a valuable tool for glycomics studies.

Alteration of rhesus macaque serum N-glycome during infection with the human parasitic filarial nematode Brugia malayi

Serum N-glycan profiling studies during the past decades have shown robust associations between N-glycan changes and various biological conditions, including infections, in humans. Similar studies are scarcer for other mammals, despite the tremendous potential of serum N-glycans as biomarkers for infectious diseases in animal models of human disease and in the veterinary context. To expand the knowledge of serum N-glycan profiles in important mammalian model systems, in this study, we combined MALDI-TOF-MS analysis and HILIC-UPLC profiling of released N-glycans together with glycosidase treatments to characterize the glycan structures present in rhesus macaque serum. We used this baseline to monitor changes in serum N-glycans during infection with Brugia malayi, a parasitic nematode of humans responsible for lymphatic filariasis, in a longitudinal cohort of infected rhesus macaques. Alterations of the HILIC-UPLC profile, notably of abundant structures, became evident as early as 5 weeks post-infection. Given its prominent role in the immune response, contribution of immunoglobulin G to serum N-glycans was investigated. Finally, comparison with similar N-glycan profiling performed during infection with the dog heartworm Dirofilaria immitis suggests that many changes observed in rhesus macaque serum N-glycans are specific for lymphatic filariasis.

Comprehensive role of SARS-CoV-2 spike glycoprotein in regulating host signaling pathway

Since the outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, global public health and the economy have suffered unprecedented damage. Based on the increasing related literature, the characteristics and pathogenic mechanisms of the virus, and epidemiological and clinical features of the disease are being rapidly discovered. The spike glycoprotein (S protein), as a key antigen of SARS-CoV-2 for developing vaccines, antibodies, and drug targets, has been shown to play an important role in viral entry, tissue tropism, and pathogenesis. In this review, we summarize the molecular mechanisms of interaction between S protein and host factors, especially receptor-mediated viral modulation of host signaling pathways, and highlight the progression of potential therapeutic targets, prophylactic and therapeutic agents for prevention and treatment of SARS-CoV-2 infection.

Site-specific glycosylation of SARS-CoV-2: Big challenges in mass spectrometry analysis

Glycosylation of viral proteins is required for the progeny formation and infectivity of virtually all viruses. It is increasingly clear that distinct glycans also play pivotal roles in the virus's ability to shield and evade the host's immune system. Recently, there has been a great advancement in structural identification and quantitation of viral glycosylation, especially spike proteins. Given the ongoing pandemic and the high demand for structure analysis of SARS-CoV-2 densely glycosylated spike protein, mass spectrometry methodologies have been employed to accurately determine glycosylation patterns. There are still many challenges in the determination of site-specific glycosylation of SARS-CoV-2 viral spike protein. This is compounded by some conflicting results regarding glycan site occupancy and glycan structural characterization. These are probably due to differences in the expression systems, form of expressed spike glycoprotein, MS methodologies, and analysis software. In this review, we recap the glycosylation of spike protein and compare among various studies. Also, we describe the most recent advancements in glycosylation analysis in greater detail and we explain some misinterpretation of previously observed data in recent publications. Our study provides a comprehensive view of the spike protein glycosylation and highlights the importance of consistent glycosylation determination.

Recent advances and trends in sample preparation and chemical modification for glycan analysis

Growing significance of glycosylation in protein functions has accelerated the development of methodologies for detection, identification, and characterization of protein glycosylation. In the past decade, glycobiology research has been advanced by innovative techniques with further progression in the post-genome era. Although significant technical progress has been made in terms of analytical throughput, comprehensiveness, and sensitivity, most methods for glycosylation analysis still require laborious and time-consuming sample preparation tasks. Additionally, sample preparation methods that are focused on specific glycan(s) require an in-depth understanding of various issues in glycobiology. In this review, modern sample preparation and chemical modification methods for the structural and quantitative glycan analyses together with the challenges and advantages of recent sample preparation methods are summarized. The techniques presented herein can facilitate the exploration of biomarkers, understanding of unknown glycan functions, and development of biopharmaceuticals.

Cell Free Remodeling of Glycosylation of Antibodies

The N-glycosylation profile of a monoclonal antibody (mAb) is a critical quality attribute in relation to its therapeutic application. The control of this profile during biomanufacture is difficult because of the multiple parameters that affect the glycosylation metabolism within the cell and the environment in which the cell is grown. One of the approaches that can be used to produce a preferred glycan profile or a single glycoform is through chemoenzymatic remodeling during the isolation of a mAb. Here we describe protocols that can be utilized to produce preferred glycoforms that include galactosylated, agalactosylated, or sialylated glycoforms following isolation of a mAb. Methods for analysis and assignment of structures of the samples following glycoengineering are also described. Chemoenzymatic modeling of mAb glycans has the potential for scale-up and to be introduced into biomanufacturing of mAbs with higher specific therapeutic activities.

N-glycan profiles of acute myocardial infarction patients reveal potential biomarkers for diagnosis, severity assessment, and treatment monitoring

Acute myocardial infarction (AMI) is a leading cause of mortality and morbidity worldwide. Diagnostic challenges remain in this highly time-sensitive condition. Using capillary electrophoresis-laser-induced fluorescence, we analyzed the blood plasma N-glycan profile in a cohort study comprising 103 patients with AMI and 69 controls. Subsequently, the data generated was subjected to classification modeling to identify potential AMI biomarkers. An area under the Receiving Operating Characteristic curve (AUCROC) of 0.81 was obtained when discriminating AMI versus non-MI patients. We postulate that the glycan profile involves a switch from a pro- to an anti-inflammatory state in the AMI pathophysiology. This was supported by significantly decreased levels in galactosylation, alongside increased levels in sialylation, afucosylation, and GlcNAc bisection levels in the blood plasma of AMI patients. By substantiating the glycomics analysis with immunoglobulin G (IgG) protein measurements, robustness of the glycan-based classifiers was demonstrated. Changes in AMI-related IgG activities were also confirmed to be associated with alterations at the glycosylation level. Additionally, a glycan-biomarker panel (GBP) derived from glycan features and current clinical biomarkers performed remarkably (AUCROC = 0.90, sensitivity = 0.579 at 5 percent false positive rate) when discriminating between patients with ST-segment elevation MI (n = 84) and non-ST-segment elevation MI (n = 19). Moreover, by applying the model trained using glycomics information, AMI and controls can still be discriminated at one and six months after baseline. Thus, glycomics biomarkers could potentially serve as a valuable complementary test to current diagnostic biomarkers. Additional research on their utility and associated biomechanisms via a large-scale study is recommended.

2-Dimensional ultra-high performance liquid chromatography and DMT-MM derivatization paired with tandem mass spectrometry for comprehensive serum N-glycome characterization

Glycosylation is a prominent co- and post-translational modification which contributes to a variety of important biological functions. Protein glycosylation characteristics, particularly N-glycosylation, are influenced by changes in one's pathological state, such as through the presence of disease, and as such, there is great interest in N-glycans as potential disease biomarkers. Human serum is an attractive source for N-glycan based biomarker studies as circulatory proteins are representative of one's physiology, with many serum proteins containing N-glycosylation. The difficulty in comprehensively characterizing the serum N-glycome arises from the absence of a biosynthetic template resulting in great structural heterogeneity and complexity. To help overcome these challenges we developed a 2-dimensional liquid chromatography platform which utilizes offline weak anion exchange (WAX) chromatography in the first dimension and hydrophilic interaction liquid chromatography (HILIC) in the second dimension to separate N-glycans by charge, corresponding to degree of sialylation, and size, respectively. Performing these separations offline enables subsequent derivatization with 4-(4,6-Dimethoxy-1,3,5-triazin-2-yl)-4-methylmorpholinium chloride (DMT-MM) for sialic acid linkage determination and the identification of sialic acid linkage isomers. Subsequent tandem mass spectrometry analysis revealed the identification of 212 complete and partial N-glycan structures including low abundant N-glycans containing acetyl and sulphate modifications. The identifications obtained through this platform were then applied to N-glycans released from a set of stage 3 gastric cancer serum samples obtained from patients before (pre-op) and after (post-op) tumour resection to investigate how the serum N-glycome can facilitate differentiation between the two pathological states.

In-depth characterization of non-human sialic acid (Neu5Gc) in human serum using label-free ZIC-HILIC/MRM-MS

Sialic acid Neu5Gc, a non-human glycan, is recognized as a new harmful substance that can cause vascular disease and cancer. Humans are unable to synthesize Neu5Gc due to a genetic defect that converts Neu5Ac to Neu5Gc, but Neu5Gc is often observed in human biological samples. Therefore, the demand for accurately measuring the amount of Neu5Gc present in human blood or tissues is rapidly increasing, but there is still no method to reliably quantify trace amounts of a non-human sugar. In particular, selective isolation and detection of Neu5Gc from human serum is analytically challenging due to the presence of excess sialic acid Neu5Ac, which has physicochemical properties very similar to Neu5Gc. Herein, we developed the label-free approach based on ZIC-HILIC/MRM-MS that can enrich sialic acids released from human serum and simultaneously monitor Neu5Ac and Neu5Gc. The combination of complete separation of Neu5Gc from abundant Neu5Ac by hydrophilic and electrostatic interactions with selective monitoring of structure-specific cross-ring cleavage ions generated by negative CID-MS/MS was remarkably effective for quantification of Neu5Ac and Neu5Gc at the femtomole level. Indeed, we were able to successfully determine the absolute quantitation of Neu5Gc from 30 healthy donors in the range of 3.336 ± 1.252 pg/μL (mean ± SD), 10,000 times lower than Neu5Ac. In particular, analysis of sialic acids in protein-free serum revealed that both Neu5Ac and Neu5G are mostly bound to proteins and/or lipids, but not in free form. In addition, the correlation between expression level of Neu5Gc and biological factors such as BMI, age, and sex was investigated. This method can be widely used in studies requiring sialic acid-related measurements such as disease diagnosis or prediction of immunogenicity in biopharmaceuticals as it is both fast and highly sensitive.

ACE2 glycans preferentially interact with SARS-CoV-2 over SARS-CoV

We report a distinct difference in the interactions of the glycans of the host-cell receptor, ACE2, with SARS-CoV-2 and SARS-CoV S-protein receptor-binding domains (RBDs). Our analysis demonstrates that the ACE2 glycan at N322 enhances interactions with the SARS-CoV-2 RBD while the ACE2 glycan at N90 may offer protection against infections of both coronaviruses depending on its composition. The interactions of the ACE2 glycan at N322 with SARS-CoV RBD are blocked by the presence of the RBD glycan at N357 of the SARS-CoV RBD. The absence of this glycosylation site on SARS-CoV-2 RBD may enhance its binding with ACE2.

A new method for purifying N-Glycans released from milk glycoprotein

Human milk is the first source of nutrition for infants, which delivers an array of unique bioactive components to offspring. Modern bovine-milk-based infant formulas are good substitutes when mother's milk is not available. As the third most abundant component in human milk, human free oligosaccharides (HMOs) may interference the analysis of total N-glycans on the glycoproteins in human milk. Herein, we combined acetone precipitation protein with the filter aided sample preparation method (FASP) to thoroughly remove HMOs and purify N-glycans. Furthermore, we also compared both N-glycosylation and glycoproteins between human and bovine milk, which may provide new ideas for the composition adjustment of infant formula in the food industry. SIGNIFICANCE: We described a new method, which can successfully remove HMOs, further extract and purify the N-glycans on glycoproteins from pooled human milk for MALDI-TOF MS analysis by applying acetone precipitation and FASP together. We applied the new method to purify the N-glycans from whey proteins in pooled bovine milk and compared the N-glycosylation differences between pooled human and bovine milk by MALDI-TOF MS. We first reported the difference of N-glycan pattern of glycoproteins between pooled bovine and human milk by lectin blotting, and found significant differences in types and abundance of glycoproteins between the two sourced milk.

Integrated Structural Analysis of N-Glycans and Free Oligosaccharides Allows for a Quantitative Evaluation of ER Stress

Endoplasmic reticulum (ER) stress has been reported in a variety of diseases. Although ER stress can be detected using specific markers, it is still difficult to quantitatively evaluate the degree of stress and to identify the cause of the stress. The ER is the primary site for folding of secretory or transmembrane proteins as well as the site where glycosylation is initiated. This study therefore postulates that tracing the biosynthetic pathway of asparagine-linked glycans (N-glycans) would be a reporter for reflecting the state of the ER and serve as a quantitative descriptor of ER stress. Glycoblotting-assisted mass spectrometric analysis of the HeLa cell line enabled quantitative determination of the changes in the structures of N-glycans and degraded free oligosaccharides (fOSs) in response to tunicamycin- or thapsigargin-induced ER stress. The integrated analysis of neutral and sialylated N-glycans and fOSs showed the potential to elucidate the cause of ER stress, which cannot be readily done by protein markers alone. Changes in the total amount of glycans, increase in the ratio of high-mannose type N-glycans, increase in fOSs, and changes in the ratio of sialylated N-glycans in response to ER stress were shown to be potential descriptors of ER stress. Additionally, drastic clearance of accumulated N-glycans was observed in thapsigargin-treated cells, which may suggest the observation of ER stress-mediated autophagy or ER-phagy in terms of glycomics. Quantitative analysis of N-glycoforms composed of N-glycans and fOSs provides the dynamic indicators reflecting the ER status and the promising strategies for quantitative evaluation of ER stress.

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.

Virus-Receptor Interactions of Glycosylated SARS-CoV-2 Spike and Human ACE2 Receptor

The SARS-CoV-2 betacoronavirus uses its highly glycosylated trimeric Spike protein to bind to the cell surface receptor angiotensin converting enzyme 2 (ACE2) glycoprotein and facilitate host cell entry. We utilized glycomics-informed glycoproteomics to characterize site-specific microheterogeneity of glycosylation for a recombinant trimer Spike mimetic immunogen and for a soluble version of human ACE2. We combined this information with bioinformatics analyses of natural variants and with existing 3D structures of both glycoproteins to generate molecular dynamics simulations of each glycoprotein both alone and interacting with one another. Our results highlight roles for glycans in sterically masking polypeptide epitopes and directly modulating Spike-ACE2 interactions. Furthermore, our results illustrate the impact of viral evolution and divergence on Spike glycosylation, as well as the influence of natural variants on ACE2 receptor glycosylation. Taken together, these data can facilitate immunogen design to achieve antibody neutralization and inform therapeutic strategies to inhibit viral infection.

Analysis of the SARS-CoV-2 spike protein glycan shield reveals implications for immune recognition

Here we have generated 3D structures of glycoforms of the spike (S) glycoprotein from SARS-CoV-2, based on reported 3D structures and glycomics data for the protein produced in HEK293 cells. We also analyze structures for glycoforms representing those present in the nascent glycoproteins (prior to enzymatic modifications in the Golgi), as well as those that are commonly observed on antigens present in other viruses. These models were subjected to molecular dynamics (MD) simulation to determine the extent to which glycan microheterogeneity impacts the antigenicity of the S glycoprotein. Lastly, we have identified peptides in the S glycoprotein that are likely to be presented in human leukocyte antigen (HLA) complexes, and discuss the role of S protein glycosylation in potentially modulating the innate and adaptive immune response to the SARS-CoV-2 virus or to a related vaccine. The 3D structures show that the protein surface is extensively shielded from antibody recognition by glycans, with the notable exception of the ACE2 receptor binding domain, and also that the degree of shielding is largely insensitive to the specific glycoform. Despite the relatively modest contribution of the glycans to the total molecular weight of the S trimer (17% for the HEK293 glycoform) they shield approximately 40% of the protein surface.

Virus-Receptor Interactions of Glycosylated SARS-CoV-2 Spike and Human ACE2 Receptor

The current COVID-19 pandemic is caused by the SARS-CoV-2 betacoronavirus, which utilizes its highly glycosylated trimeric Spike protein to bind to the cell surface receptor ACE2 glycoprotein and facilitate host cell entry. We utilized glycomics-informed glycoproteomics to characterize site-specific microheterogeneity of glycosylation for a recombinant trimer Spike mimetic immunogen and for a soluble version of human ACE2. We combined this information with bioinformatic analyses of natural variants and with existing 3D-structures of both glycoproteins to generate molecular dynamics simulations of each glycoprotein alone and interacting with one another. Our results highlight roles for glycans in sterically masking polypeptide epitopes and directly modulating Spike-ACE2 interactions. Furthermore, our results illustrate the impact of viral evolution and divergence on Spike glycosylation, as well as the influence of natural variants on ACE2 receptor glycosylation that, taken together, can facilitate immunogen design to achieve antibody neutralization and inform therapeutic strategies to inhibit viral infection.

Metformin and statin use associate with plasma protein N-glycosylation in people with type 2 diabetes

INTRODUCTION

Recent studies revealed N-glycosylation signatures of type 2 diabetes, inflammation and cardiovascular risk factors. Most people with diabetes use medication to reduce cardiovascular risk. The association of these medications with the plasma N-glycome is largely unknown. We investigated the associations of metformin, statin, ACE inhibitor/angiotensin II receptor blocker (ARB), sulfonylurea (SU) derivatives and insulin use with the total plasma N-glycome in type 2 diabetes.

RESEARCH DESIGN AND METHODS

After enzymatic release from glycoproteins, N-glycans were measured by matrix-assisted laser desorption/ionization mass spectrometry in the DiaGene (n=1815) and Hoorn Diabetes Care System (n=1518) cohorts. Multiple linear regression was used to investigate associations with medication, adjusted for clinical characteristics. Results were meta-analyzed and corrected for multiple comparisons.

RESULTS

Metformin and statins were associated with decreased fucosylation and increased galactosylation and sialylation in glycans unrelated to immunoglobulin G. Bisection was increased within diantennary fucosylated non-sialylated glycans, but decreased within diantennary fucosylated sialylated glycans. Only few glycans were associated with ACE inhibitor/ARBs, while none associated with insulin and SU derivative use.

CONCLUSIONS

We conclude that metformin and statins associate with a total plasma N-glycome signature in type 2 diabetes. Further studies are needed to determine the causality of these relations, and future N-glycomic research should consider medication a potential confounder.

Simplifying Glycan Profiling through a High-Throughput Micropermethylation Strategy

Glycoproteins play key roles in various molecular and cellular functions and are among the most difficult to analyze biomolecules on account of their microheterogeneity, non-template-driven synthesis, and low abundances. The stability, serum half-life, immunogenicity, and biological activity of therapeutic glycoproteins, including antibodies, vaccines, and biomarkers, are regulated by their glycosylation profile. Thus, there is increasing demand for the qualitative and quantitative characterization and validation of glycosylation on glycoproteins. One of the most important derivatization processes for the structural characterization of released glycans by mass spectrometry (MS) is permethylation. We have recently developed a permethylation strategy in microscale that allows facile permethylation of glycans and permits the processing of large sample sets in nanogram amounts through high-throughput sample handling. Here, we are reporting the wide potential of micropermethylation-based high-throughput structural analysis of glycans from various sources, including human plasma, mammalian cells, and purified glycoproteins, through an automated tandem electrospray ionization-mass spectrometry (ESI-MSn) platform. The glycans released from the plasma, cells, and glycoproteins are permethylated in microscale in a 96-well plate or microcentrifuge tube and isolated by a C18 tip-based cleanup through a shorter and simple process. We have developed a workflow to accomplish an in-depth automated structural characterization MS program for permethylated N/O-glycans through an automated high-throughput multistage tandem MS acquisition. We have demonstrated the utility of this workflow using the examples of sialic acid linkages and bisecting GlcNAc (N-acetylglucosamine) on the glycans. This approach can automate the high-throughput screening of glycosylation on large sample sets of glycoproteins, including clinical glycan biomarkers and glycoprotein therapeutics.

Analysis of the SARS-CoV-2 spike protein glycan shield: implications for immune recognition

Here we have generated 3D structures of glycoforms of the spike (S) glycoprotein from SARS-CoV-2, based on reported 3D structures and glycomics data for the protein produced in HEK293 cells. We also analyze structures for glycoforms representing those present in the nascent glycoproteins (prior to enzymatic modifications in the Golgi), as well as those that are commonly observed on antigens present in other viruses. These models were subjected to molecular dynamics (MD) simulation to determine the extent to which glycan microheterogeneity impacts the antigenicity of the S glycoprotein. Lastly, we have identified peptides in the S glycoprotein that are likely to be presented in human leukocyte antigen (HLA) complexes, and discuss the role of S protein glycosylation in potentially modulating the adaptive immune response to the SARS-CoV-2 virus or to a related vaccine. The 3D structures show that the protein surface is extensively shielded from antibody recognition by glycans, with the exception of the ACE2 receptor binding domain, and also that the degree of shielding is largely insensitive to the specific glycoform. Despite the relatively modest contribution of the glycans to the total molecular weight (17% for the HEK293 glycoform) the level of surface shielding is disproportionately high at 42%.

Sialylated N-glycan profile during acute and chronic infections with Toxoplasma gondii in mice

Toxoplasma gondii is associated with physiological and psychiatric perturbations. The immune response is interrelated to the progress of anhedonia and despair symptoms of T. gondii-infected subjects. We recently reported that serum N-glycans were altered in mice displayed depressive-like behaviors. However, a novel biomarker that correlated to T. gondii infection and associated behaviors is demanded. Glycomics has been used to find affected glycoproteins during depression. The objective of this study is to investigate serum N-glycomics changes during infection with T. gondii in BALB/c mice, immunocompetent, or in severe combined immunodeficient mice, and after treatment with an immunostimulant; 1-methyl tryptophan. Glycans were examined through glycoblotting-protocol then investigated by MALDI-TOF/MS. Both depressive and sickness-related behaviors were significantly abundant (P ≤ 0.001 each), during acute T. gondii in immunocompetent mice, compared to controls. Only sickness symptoms were evident in immunodeficient mice infected with T. gondii, as associated with high expression level (P ≤ 0.001) of Peak # 15 (2 × Neu5Gc) compared to controls. The alteration of sialylated N-glycan expressions is important to detect the immune status of animals/humans against T. gondii. Moreover, 1-methyl tryptophan reduced depressive-like behavior (P ≤ 0.001) compared to controls. Therefore, sialylated N-glycan (Neu5Ac/Neu5Gc-terminal) is targeted to be used as a novel biomarker of sickness/depressive-like behaviors.

N-glycomic Profile in Combat Related Post-Traumatic Stress Disorder

Post-traumatic stress disorder (PTSD) develops in a portion of individuals exposed to extreme trauma. Glycosylation is a post-translational modification that affects protein functions and is altered in various pathophysiological states and aging. There are still no validated biomarkers of PTSD. The aim of this study was to evaluate the N-glycomic profile in 543 male Caucasian individuals (299 veterans with PTSD and 244 control subjects). The study included discovery (N = 233) and replication (N = 310) cohort. Hydrophilic interaction HPLC and ultra-performance liquid chromatography were used to separate and detect 39 plasma and 24 IgG N-glycan species, respectively. All results were corrected for the effects of age and multiple testing. Significant results included only significantly altered N-glycans in cases/controls in both cohorts, in the same direction. Results showed that six plasma N-glycans (four increased and two decreased) were altered in PTSD vs. controls in both cohorts, but IgG N-glycans were similar between groups. The severity of PTSD was not associated with different plasma N-glycans. This is the first study detecting alterations in plasma N-glycans in PTSD. These N-glycans are also associated with other neuropsychiatric disorders and inflammation, suggesting possible shared glycosylation mechanisms.

Mass spectrometry-based qualitative and quantitative N-glycomics: An update of 2017-2018

N-glycosylation is one of the most frequently occurring protein post-translational modifications (PTMs) with broad cellular, physiological and pathological relevance. Mass spectrometry-based N-glycomics has become the state-of-the-art instrumental analytical pipeline for sensitive, high-throughput and comprehensive characterization of N-glycans and N-glycomes. Improvement and new development of methods in N-glycan release, enrichment, derivatization, isotopic labeling, separation, ionization, MS, tandem MS and informatics accompany side-by-side wider and deeper application. This review provides a comprehensive update of mass spectrometry-based qualitative and quantitative N-glycomics in the years of 2017-2018.

Glycoanalysis of the placental membrane glycoproteins throughout placental development

Structural changes of glycans are observed in different (patho)physiological conditions. Human placental membrane (glyco)proteins were isolated from the first and third trimester placentas of mothers at different ages. By using lectin microarray, we demonstrated that the placental membrane N-glycome contains several N-glycan groups: high mannose, asialylated and sialylated biantennary moieties, bisected, core fucosylated, fucosylated at other positions (bearing terminal and/or antennary Fuc), α2-6 and α2-3 sialylated structures. Employing MALDI-TOF MS enabled identification of over sixty different N-glycan structures in all samples, with 17 moieties exceeding the relative abundance of 2%. The major MS peaks originated from: 1) biantennary complex type N-glycan with a bisecting GlcNAc residue and 2) a core Fuc paucimannosidic and high mannose type structures M3-M9. Age of mothers and the stage of placental development affected N-glycome. The work presented in this article is the first comprehensive mass spectrometric study of the N-glycome of human placental membrane proteins. Our results may be seen as the baseline which can serve for future MALDI MS profiling of the placental membrane N-glycome in different pathophysiological conditions.

Identification of bifucosylated glycoforms using low-energy CID spectra

We have used tandem mass spectrometry (MS/MS)-based analysis of glycopeptides in order to identify the composition and structure of rare glycoforms. The results illustrate utility of low-energy MS/MS for structure identification. We have shown the presence of bifucosylated and trifucosylated glycoforms in human α-1-acid glycoprotein (AGP), a major plasma glycoprotein. Fucosylation in the case of AGP always occurs on the antennae; core fucosylation was not observed.

Identification of serum N-glycoproteins as a biological correlate underlying chronic stress response in mice

Glycosylation is a post-translational protein modification in eukaryotes and plays an important role in controlling several diseases. N-glycan structure is emerging as a new paradigm for biomarker discovery of neuropsychiatric disorders. However, the relationship between N-glycosylation pattern and depression is not well elucidated to date. This study aimed to explore whether serum N-glycan structures are altered in depressive-like behavior using a stress based mouse model. We used two groups of BALB/c mice; (i) treated group exposed to chronic unpredictable mild stress (CUMS) as a model of depression, and (ii) control group. Behavioral tests in mice (e.g., sucrose preference test, forced swimming test, and fear conditioning test) were used to evaluate the threshold level to which mice displayed a depressive-like phenotype. Serum N-glycans were analyzed carefully using glycoblotting followed by Matrix-assisted laser desorption ionization-time of flight/mass spectrometry (MALDI-TOF/MS) to exhibit N-glycan expression levels and to illustrate the changes in the N-glycome profile. N-glycan expression levels were commonly altered in the depressive-like model and correlated well with the behavioral data. Our results indicated that sialylated N-glycan was identified as a biomarker associated with depressive symptoms, which may have utility as a candidate biomarker for the clinical diagnosis and monitoring of depression.