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Glycosylation is considered one of the most complex and structurally diverse post-translational modifications of proteins. Glycans play important roles in many biological processes such as protein folding, regulation of protein stability, solubility and serum half-life. One of the ways to study glycosylation is systematic structural characterizations of protein glycosylation utilizing glycomics methodology based around mass spectrometry (MS). The most prevalent bottleneck stages for glycomic analyses is laborious sample preparation steps. Therefore, in this study, we aim to improve sample preparations by automation. We recently demonstrated the successful application of an automated high-throughput (HT), glycan permethylation protocol based on 96-well microplates, in the analysis of purified glycoproteins. Therefore, we wanted to test if these developed HT methodologies could be applied to more complex biological starting materials. Our automated 96-well-plate based permethylation method showed very comparable results with established glycomic methodology. Very similar glycomic profiles were obtained for complex glycoprotein/protein mixtures derived from heterogeneous mouse tissues. Automated N-glycan release, enrichment and automated permethylation of samples proved to be convenient, robust and reliable. Therefore we conclude that these automated procedures are a step forward towards the development of a fully automated, fast and reliable glycomic profiling system for analysis of complex biological materials.

This review covers advances in analytical technologies for high-throughput (HTP) glycomics. Our focus is on structural studies of glycoprotein glycosylation to support biopharmaceutical realization and the discovery of glycan biomarkers for human disease. For biopharmaceuticals, there is increasing use of glycomics in Quality by Design studies to help optimize glycan profiles of drugs with a view to improving their clinical performance. Glycomics is also used in comparability studies to ensure consistency of glycosylation both throughout product development and between biosimilars and innovator drugs. In clinical studies there is as well an expanding interest in the use of glycomics—for example in Genome Wide Association Studies—to follow changes in glycosylation patterns of biological tissues and fluids with the progress of certain diseases. These include cancers, neurodegenerative disorders and inflammatory conditions. Despite rising activity in this field, there are significant challenges in performing large scale glycomics studies. The requirement is accurate identification and quantitation of individual glycan structures. However, glycoconjugate samples are often very complex and heterogeneous and contain many diverse branched glycan structures. In this article we cover HTP sample preparation and derivatization methods, sample purification, robotization, optimized glycan profiling by UHPLC, MS and multiplexed CE, as well as hyphenated techniques and automated data analysis tools. Throughout, we summarize the advantages and challenges with each of these technologies. The issues considered include reliability of the methods for glycan identification and quantitation, sample throughput, labor intensity, and affordability for large sample numbers.

Background & Aims Biomarkers are needed for early detection of Crohn’s disease (CD) and ulcerative colitis (UC) or to predict patient outcomes. Glycosylation is a common and complex posttranslational modification of proteins that affects their structure and activity. We compared plasma N-glycosylation profiles between patients with CD or UC and healthy individuals (controls). Methods We analyzed the total plasma N-glycomes of 2635 patients with inflammatory bowel diseases and 996 controls by mass spectrometry with a linkage-specific sialic acid derivatization technique. Plasma samples were acquired from 2 hospitals in Italy (discovery cohort, 1989 patients with inflammatory bowel disease [IBD] and 570 controls) and 1 medical center in the United States (validation cohort, 646 cases of IBD and 426 controls). Sixty-three glycoforms met our criteria for relative quantification and were extracted from the raw data with the software MassyTools. Common features shared by the glycan compositions were combined in 78 derived traits, including the number of antennae of complex-type glycans and levels of fucosylation, bisection, galactosylation, and sialylation. Associations of plasma N-glycomes with age, sex, CD, UC, and IBD-related parameters such as disease location, surgery and medication, level of C-reactive protein, and sedimentation rate were tested by linear and logistic regression. Results Plasma samples from patients with IBD had a higher abundance of large-size glycans compared with controls, a decreased relative abundance of hybrid and high-mannose structures, lower fucosylation, lower galactosylation, and higher sialylation (α2,3- and α2,6-linked). We could discriminate plasma from patients with CD from that of patients with UC based on higher bisection, lower galactosylation, and higher sialylation (α2,3-linked). Glycosylation patterns were associated with disease location and progression, the need for a more potent medication, and surgery. These results were replicated in a large independent cohort. Conclusions We performed high-throughput analysis to compare total plasma N-glycomes of individuals with vs without IBD and to identify patterns associated with disease features and the need for treatment. These profiles might be used in diagnosis and for predicting patients’ responses to treatment.

BACKGROUND AND AIMS: Causes of inflammatory bowel diseases are not well understood and the most prominent forms, Crohn's disease (CD) and ulcerative colitis (UC), are sometimes hard to distinguish. Glycosylation of IgG has been associated with CD and UC. IgG Fc-glycosylation affects IgG effector functions. We evaluated changes in IgG Fc- glycosylation associated with UC and CD, as well as with disease characteristics in different patient groups. METHODS: We analyzed 3441 plasma samples obtained from 2 independent cohorts of patients with CD (874 patients from Italy and 391 from the United States) or UC (1056 from Italy and 253 from the US and healthy individuals [controls] ; 427 in Italy and 440 from the United States). IgG Fc-glycosylation (tryptic glycopeptides) was analyzed by liquid chromatography coupled to mass spectrometry. We analyzed associations between disease status (UC vs controls, CD vs controls, and UC vs CD) and glycopeptide traits, and associations between clinical characteristics and glycopeptide traits, using a logistic regression model with age and sex included as covariates. RESULTS: Patients with CD or UC had lower levels of IgG galactosylation than controls. For example, the odds ratio (OR) for IgG1 galactosylation in patients with CD was 0.59 (95% confidence interval [CI], 0.51-0.69) and for patients with UC was 0.81 (95% CI, 0.71-0.92). Fucosylation of IgG was increased in patients with CD vs controls (for IgG1: OR, 1.27 ; 95% CI, 1.12-1.44), but decreased in patients with UC vs controls (for IgG23: OR, 0.72 ; 95% CI, 0.63-0.82). Decreased galactosylation associated with more severe CD or UC, including the need for surgery in patients with UC vs controls (for IgG1: OR, 0.69 ; 95% CI, 0.54-0.89) and in patients with CD vs controls (for IgG23: OR, 0.78 ; 95% CI, 0.66-0.91). CONCLUSIONS: In a retrospective analysis of plasma samples from patients with CD or UC, we associated levels of IgG Fc-glycosylation with disease (compared to controls) and its clinical features. These findings could increase our understanding of mechanisms of CD and UC pathogenesis and be used to develop diagnostics or guide treatment.