Graphical abstract The severe acute respiratory syndrome-related coronavirus-2 (SARS-CoV-2) infection displays a wide array of clinical manifestations. Although some risk factors for coronavirus disease 2019 (COVID-19) severity and outcomes have been identified the underlying biologic mechanisms are still not well understood. The surface SARS-CoV-2 proteins are heavily glycosylated enabling host cell interaction and viral entry. Angiotensin-converting enzyme 2 (ACE2) has been identified to be the main host cell receptor enabling SARS-CoV-2 cell entry after interaction with its S glycoprotein. However, recent studies report SARS-CoV-2 S glycoprotein interaction with other cell receptors, mainly C-type lectins which recognize specific glycan epitopes facilitating SARS-CoV-2 entry to susceptible cells. Here, we are summarizing the main findings on SARS-CoV-2 interactions with ACE2 and other cell membrane surface receptors and soluble lectins involved in the viral cell entry modulating its infectivity and potentially playing a role in subsequent clinical manifestations of COVID-19.

A large variation in the severity of disease symptoms is one of the key open questions in COVID-19 pandemics. The fact that only a small subset of people infected with SARS-CoV-2 develop severe disease suggests that there have to be some predisposing factors, but biomarkers that reliably predict disease severity have not been found so far. Since overactivation of the immune system is implicated in a severe form of COVID-19 and the IgG glycosylation is known to be involved in the regulation of different immune processes, we evaluated the association of inter-individual variation in IgG N-glycome composition with the severity of COVID-19. The analysis of 166 severe and 167 mild cases from hospitals in Spain, Italy and Portugal revealed statistically significant differences in the composition of the IgG N-glycome. The most notable difference was the decrease in bisecting N-acetylglucosamine (GlcNAc) in severe patients from all three cohorts. IgG galactosylation was also lower in severe cases in all cohorts, but the difference in galactosylation was not statistically significant after correction for multiple testing. To our knowledge, this is the first study exploring IgG N-glycome variability in COVID-19 severity.

Post-translational modifications diversify protein functions and dynamically coordinate their signalling networks, influencing most aspects of cell physiology. Nevertheless, their genetic regulation or influence on complex traits is not fully understood. Here, we compare the genetic regulation of the same PTM of two proteins – glycosylation of transferrin and immunoglobulin G (IgG). By performing genome-wide association analysis of transferrin glycosylation, we identify 10 significantly associated loci, 9 of which were not reported previously. Comparing these with IgG glycosylation-associated genes, we note protein-specific associations with genes encoding glycosylation enzymes (transferrin - MGAT5, ST3GAL4, B3GAT1; IgG - MGAT3, ST6GAL1), as well as shared associations (FUT6, FUT8). Colocalisation analyses of the latter suggest that different causal variants in the FUT genes regulate fucosylation of the two proteins. Glycosylation of these proteins is thus genetically regulated by both shared and protein-specific mechanisms.

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.

The nature of the immune responses associated with COVID‐19 pathogenesis and disease severity, as well as the breadth of vaccine coverage and duration of immunity, is still unclear. Given the unpredictability for developing a severe/complicated disease, there is an urgent need in the field for predictive biomarkers of COVID‐19. We have analyzed IgG Fc N ‐glycan traits of 82 SARS‐CoV‐2+ unvaccinated patients, at diagnosis, by nano‐LC‐ESI‐MS. We determined the impact of IgG Fc glyco‐variations in the induction of NK cells activation, further evaluating the association between IgG Fc N ‐glycans and disease severity/prognosis. We found that SARS‐CoV‐2+ individuals display, at diagnosis, variations in the glycans composition of circulating IgGs. Importantly, levels of galactose and sialic acid structures on IgGs are able to predict the development of a poor COVID‐19 disease. Mechanistically, we demonstrated that a deficiency on galactose structures on IgG Fc in COVID‐19 patients appears to induce NK cells activation associated with increased release of IFN‐γ and TNF‐α, which indicates the presence of pro‐inflammatory immunoglobulins and higher immune activation, associated with a poor disease course. This study brings to light a novel blood biomarker based on IgG Fc glycome composition with capacity to stratify patients at diagnosis.

Protein glycosylation is the attachment of a carbohydrate moiety to a protein backbone affecting both structure and function of the protein. Abnormal glycosylation is associated with various diseases, and some of the changes in glycosylation are detectable even before symptom development. As such, glycans have emerged as compelling new biomarker candidates. A wide range of analytical methods exist for small-scale glycan analyses. However, there is a growing need for highly robust and reproducible high-throughput techniques that allow for large-scale glycoprofiling. Here we describe the evaluation of robustness and repeatability of immunoglobulin G (IgG) N-glycan analysis using the GlycoWorks RapiFluor-MS N-Glycan Kit followed by hydrophilic interaction ultra-high-performance liquid chromatography (HILIC-UHPLC) from 335 technical replicates of human plasma randomly distributed across 67 96-well plates. The data was collected over a five-month period using multiple UHPLC systems and chromatographic columns. Following relative IgG N-glycan quantification in acquired chromatograms, data analysis showed that the most abundant peaks that together made up for three fourths of the detected IgG N-glycome all had coefficients of variation (CVs) lower than 2 percent. The highest CVs ranging from 16 to 29 percent accompanied low abundance glycan peaks with the individual relative peak area below 1 percent that together made up for less than 2 percent of the detected IgG N-glycome. These results show that the tested method is very robust and repeatable, making it suitable for the IgG N-glycan analysis of a large number of samples in a high-throughput manner over a longer period of time.

A large variation in the severity of disease symptoms is one of the key open questions in COVID-19 pandemics. The fact that only a small subset of people infected with SARS-CoV-2 develop severe disease suggests that there have to be some predisposing factors, but biomarkers that reliably predict disease severity have not been found so far. Since overactivation of the immune system is implicated in a severe form of COVID-19 and the IgG glycosylation is known to be involved in the regulation of different immune processes, we evaluated the association of inter-individual variation in IgG N-glycome composition with the severity of COVID-19. The analysis of 166 severe and 167 mild cases from hospitals in Spain, Italy and Portugal revealed statistically significant differences in the composition of the IgG N-glycome. The most notable difference was the decrease in bisecting N -acetylglucosamine (GlcNAc) in severe patients from all three cohorts. IgG galactosylation was also lower in severe cases in all cohorts, but the difference in galactosylation was not statistically significant after correction for multiple testing.

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