O-Glycosylation Landscapes of SARS-CoV-2 Spike Proteins.

Yong Zhang,Jingqiang Zhu,Hao Yang,Liqiang Hu,Yaohui Chen,Jingqiu Cheng,Shanshan Zheng,Wei Cao,Yonghong Mao,Meng Gong,Wanjun Zhao

doi:10.3389/fchem.2021.689521

Abstract

The densely glycosylated spike (S) proteins that are highly exposed on the surface of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) facilitate viral attachment, entry, and membrane fusion. We have previously reported all the 22 N-glycosites and site-specific N-glycans in the S protein protomer. Herein, we report the O-glycosylation landscapes of SARS-CoV-2 S proteins, which were characterized through high-resolution mass spectrometry. Following digestion with trypsin and trypsin/Glu-C, and de-N-glycosylation using PNGase F, we determined the GalNAc-type O-glycosylation pattern of S proteins, including O-glycosites and the six most common O-glycans occupying them, via Byonic identification and manual validation. Finally, 255 intact O-glycopeptides composed of 50 peptides sequences and 43 O-glycosites were discovered by higher energy collision-induced dissociation (HCD), and three O-glycosites were confidently identified by electron transfer/higher energy collision-induced dissociation (EThcD) in the insect cell-expressed S protein. Most glycosites were modified by non-sialylated O-glycans such as HexNAc(1) and HexNAc(1)Hex (1). In contrast, in the human cell-expressed S protein S1 subunit, 407 intact O-glycopeptides composed of 34 peptides sequences and 30 O-glycosites were discovered by HCD, and 11 O-glycosites were unambiguously assigned by EThcD. However, the measurement of O-glycosylation occupancy hasn’t been made. Most glycosites were modified by sialylated O-glycans such as HexNAc(1)Hex (1)NeuAc (1) and HexNAc(1)Hex (1)NeuAc (2). Our results reveal that the SARS-CoV-2 S protein is an O-glycoprotein; the O-glycosites and O-glycan compositions vary with the host cell type. These comprehensive O-glycosylation landscapes of the S protein are expected to provide novel insights into the viral binding mechanism and present a strategy for the development of vaccines and targeted drugs.

Highlights

The spike (S) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an extensively N-glycosylated protein (Watanabe et al, 2020) that protrudes from the virus surface and binds to the angiotensin-converting enzyme 2 (ACE2) receptor on host cells to mediate cell entry (Wrapp et al, 2020)
Most O-glycosites of the human cell–produced S1 subunit contained HexNAc(1)Hex (1)NeuAc (2), HexNAc(1) Hex (1)NeuAc (1), and HexNAc(1)Hex (1) (Figure 4D). These results implied that the O-glycosite and O-glycan compositions varied with the host cell type, which could be taken into account when using the recombinant proteins for vaccine and drug development
HexNAc(2)Hex (1) and HexNAc(2) were not verified by EThcD in the S expressed in insect cells, which suggested that the two O-glycans might be misidentified by higher energy collision-induced dissociation (HCD) due to fragmentation of glycans. All of these results indicate that with both HCD and EThcD, we can identify a large number of intact O-glycopeptides of spike proteins

Summary

Introduction

The spike (S) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an extensively N-glycosylated protein (Watanabe et al, 2020) that protrudes from the virus surface and binds to the angiotensin-converting enzyme 2 (ACE2) receptor on host cells to mediate cell entry (Wrapp et al, 2020). O-glycosylation of SARS-CoV-2 Spike Proteins high-resolution liquid chromatography–tandem mass spectrometry (LC-MS/MS) (Lenza et al, 2020; Rosenbalm et al, 2020; Walls et al, 2020; Xu et al, 2020; Yan et al, 2020; Zhang et al, 2020; Wang et al, 2021; Zhou et al, 2021) These N-glycosites are preferentially distributed in two functional subunits responsible for receptor binding (S1 subunit) and membrane fusion (S2 subunit) (Zhang et al, 2020). The comprehensive O-glycosylation analysis cannot be performed without appropriate sample preprocessing, analysis methods, and software (King et al, 2017; Qin et al, 2017; Yang et al, 2017; Yang et al, 2018; Ye et al, 2019; Park et al, 2020; Dong et al, 2021)

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