Krishnan Sridevi, Krishnan Giri P
Department of Nutrition, University of California Davis, Davis, CA, United States.
School of Medicine, University of California San Diego, La Jolla, CA, United States.
Front Bioinform. 2021 Jun 8;1:667012. doi: 10.3389/fbinf.2021.667012. eCollection 2021.
The N-glycan structure and composition of the spike (S) protein of SARS-CoV-2 are pertinent to vaccine development and efficacy. We reconstructed the glycosylation network based on previously published mass spectrometry data using GNAT, a glycosylation network analysis tool. Our compilation of the network tool had 26 glycosyltransferase and glucosidase enzymes and could infer the pathway of glycosylation machinery based on glycans in the virus spike protein. Once the glycan biosynthesis pathway was generated, we simulated the effect of blocking specific enzymes-swainsonine or deoxynojirimycin for blocking mannosidase-II and indolizidine for blocking alpha-1,6-fucosyltransferase-to see how they would affect the biosynthesis network and the glycans that were synthesized. The N-glycan biosynthesis network of SARS-CoV-2 spike protein shows an elaborate enzymatic pathway with several intermediate glycans, along with the ones identified by mass spectrometric studies. Of the 26 enzymes, the following were involved-Man-Ia, MGAT1, MGAT2, MGAT4, MGAT5, B3GalT, B4GalT, Man-II, SiaT, ST3GalI, ST3GalVI, and FucT8. Blocking specific enzymes resulted in a substantially modified glycan profile of SARS-CoV-2. Variations in the final N-glycan profile of the virus, given its site-specific microheterogeneity, are factors in the host response to the infection, vaccines, and antibodies. Heterogeneity in the N-glycan profile of the spike (S) protein and its potential effect on vaccine efficacy or adverse reactions to the vaccines remain unexplored. Here, we provide all the resources we generated-the glycans in the glycoCT xml format and the biosynthesis network for future work.
严重急性呼吸综合征冠状病毒2(SARS-CoV-2)刺突(S)蛋白的N-聚糖结构和组成与疫苗开发及效力相关。我们使用糖基化网络分析工具GNAT,基于先前发表的质谱数据重建了糖基化网络。我们编制的网络工具包含26种糖基转移酶和糖苷酶,并能根据病毒刺突蛋白中的聚糖推断糖基化机制的途径。一旦生成聚糖生物合成途径,我们就模拟了阻断特定酶——用于阻断甘露糖苷酶-II的苦马豆素或脱氧野尻霉素,以及用于阻断α-1,6-岩藻糖基转移酶的吲哚里西啶——的效果,以观察它们如何影响生物合成网络及合成的聚糖。SARS-CoV-2刺突蛋白的N-聚糖生物合成网络显示出一条复杂的酶促途径,有几种中间聚糖,以及质谱研究鉴定出的那些聚糖。在这26种酶中,涉及的有——甘露糖基转移酶-Ia、N-乙酰葡糖胺转移酶1、N-乙酰葡糖胺转移酶2、N-乙酰葡糖胺转移酶4、N-乙酰葡糖胺转移酶5、β-1,3-半乳糖基转移酶、β-1,4-半乳糖基转移酶、甘露糖苷酶-II、唾液酸转移酶、ST3β-半乳糖苷α-唾液酸基转移酶1、ST3β-半乳糖苷α-唾液酸基转移酶6和岩藻糖基转移酶8。阻断特定酶会导致SARS-CoV-2的聚糖谱发生显著改变。鉴于病毒最终N-聚糖谱的位点特异性微异质性,其变化是宿主对感染、疫苗和抗体反应的因素。刺突(S)蛋白N-聚糖谱的异质性及其对疫苗效力或疫苗不良反应的潜在影响仍未得到探索。在此,我们提供了我们生成的所有资源——糖基转移酶xml格式的聚糖和生物合成网络,以供未来研究使用。