Quantitative profiling of N-glycosylation of SARS-CoV-2 spike protein variants.

With the global spread of the corona virus disease-2019 pandemic, new spike variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continuously emerge due to increased possibility of virus adaptive amino acid mutations. However, the N-glycosylation profiles of different spike variants are yet to be explored extensively, although the spike protein is heavily glycosylated and surface glycans are well-established to play key roles in viral infection and immune response. Here, we investigated quantitatively the N-glycosylation profiles of seven major emerging spike variants including Original, Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Kappa (B.1.671.1), Delta (B.1.671.2), and Omicron (B.1.1.529). The aim was to understand the changing pattern of N-glycan profiles in SARS-CoV-2 evolution in addition to the widely studied amino acid mutations. Different spike variants exhibit substantial variations in the relative abundance of different glycan peaks and subclasses, although no specific glycan species are exclusively present in or absent from any specific variant. Cluster analysis shows that the N-glycosylation profiles may hold the potential for SARS-CoV-2 spike variants classification. Alpha and Beta variants exhibit the closest similarity to the Original, and the Delta variant displays substantial similarity to Gamma and Kappa variants, while the Omicron variant is significantly different from its counterparts. We demonstrated that there is a quantifiable difference in N-glycosylation profiles among different spike variants. The current study and observations herein provide a valuable framework for quantitative N-glycosylation profiling of new emerging viral variants and give us a more comprehensive picture of COVID-19 evolution.

Serum N-glycomic profiling may provide potential signatures for surveillance of COVID-19.

Disease development and progression are often associated with aberrant glycosylation, indicating that changes in biological fluid glycome may potentially serve as disease signatures. The corona virus disease-2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) represents a significant threat to global human health. However, the effect of SARS-CoV-2 infection on the overall serum N-glycomic profile has been largely unexplored. Here, we extended our 96-well-plate-based high-throughput, high-sensitivity N-glycan profiling platform further with the aim of elucidating potential COVID-19-associated serum N-glycomic alterations. Use of this platform revealed both similarities and differences between the serum N-glycomic fingerprints of COVID-19 positive and control cohorts. Although there were no specific glycan peaks exclusively present or absent in COVID-19 positive cohort, this cohort showed significantly higher levels of glycans and variability. On the contrary, the overall N-glycomic profiles for healthy controls were well-contained within a narrow range. From the serum glycomic analysis, we were able to deduce changes in different glycan subclasses sharing certain structural features. Of significance was the hyperbranched and hypersialylated glycans and their derived glycan subclass traits. T-distributed stochastic neighbor embedding and hierarchical heatmap clustering analysis were performed to identify 13 serum glycomic variables that potentially distinguished the COVID-19 positive from healthy controls. Such serum N-glycomic changes described herein may indicate or correlate to the changes in serum glycoproteins upon COVID-19 infection. Furthermore, mapping the serum N-glycome following SARS-CoV-2 infection may help us better understand the disease and enable "Long-COVID" surveillance to capture the full spectrum of persistent symptoms.