Department of Biochemistry, Center for Biomedical Mass Spectrometry, Boston University School of Medicine, Boston, Massachusetts, USA.
Boston University Bioinformatics Program, Boston University, Boston, Massachusetts, USA.
Mol Cell Proteomics. 2020 Sep;19(9):1533-1545. doi: 10.1074/mcp.RA120.002031. Epub 2020 Jun 29.
Influenza A virus (IAV) mutates rapidly, resulting in antigenic drift and poor year-to-year vaccine effectiveness. One challenge in designing effective vaccines is that genetic mutations frequently cause amino acid variations in IAV envelope protein hemagglutinin (HA) that create new -glycosylation sequons; resulting -glycans cause antigenic shielding, allowing viral escape from adaptive immune responses. Vaccine candidate strain selection currently involves correlating antigenicity with HA protein sequence among circulating strains, but quantitative comparison of site-specific glycosylation information may likely improve the ability to design vaccines with broader effectiveness against evolving strains. However, there is poor understanding of the influence of glycosylation on immunodominance, antigenicity, and immunogenicity of HA, and there are no well-tested methods for comparing glycosylation similarity among virus samples. Here, we present a method for statistically rigorous quantification of similarity between two related virus strains that considers the presence and abundance of glycopeptide glycoforms. We demonstrate the strength of our approach by determining that there was a quantifiable difference in glycosylation at the protein level between WT IAV HA from A/Switzerland/9715293/2013 (SWZ13) and a mutant strain of SWZ13, even though no -glycosylation sequons were changed. We determined site-specifically that WT and mutant HA have varying similarity at the glycosylation sites of the head domain, reflecting competing pressures to evade host immune response while retaining viral fitness. To our knowledge, our results are the first to quantify changes in glycosylation state that occur in related proteins of considerable glycan heterogeneity. Our results provide a method for understanding how changes in glycosylation state are correlated with variations in protein sequence, which is necessary for improving IAV vaccine strain selection. Understanding glycosylation will be especially important as we find new expression vectors for vaccine production, as glycosylation state depends greatly on the host species.
甲型流感病毒（IAV）快速突变，导致抗原漂移和年度疫苗效果不佳。设计有效疫苗的一个挑战是，遗传突变经常导致 IAV 包膜蛋白血凝素（HA）中的氨基酸变异，从而产生新的 -糖基化序列；由此产生的 -聚糖导致抗原屏蔽，使病毒逃避适应性免疫反应。目前，疫苗候选株的选择涉及在流行株中比较抗原性与 HA 蛋白序列，但定量比较特定部位糖基化信息可能有助于提高针对不断进化的毒株设计更广泛有效疫苗的能力。然而，人们对糖基化对 HA 的免疫原性、抗原性和免疫原性的影响了解甚少，也没有经过充分测试的方法来比较病毒样本之间的糖基化相似性。在这里，我们提出了一种方法，可以对两种相关病毒株之间的相似性进行统计学上严格的定量，同时考虑糖肽糖型的存在和丰度。我们通过确定在蛋白质水平上，A/Switzerland/9715293/2013（SWZ13）的野生型 IAV HA 与 SWZ13 的突变株之间存在可量化的糖基化差异，证明了我们方法的有效性，尽管没有改变 -糖基化序列。我们还确定了，WT 和突变 HA 在头部结构域的糖基化位点上具有特定的、不同的相似性，这反映了逃避宿主免疫反应的竞争压力，同时保留了病毒的适应性。据我们所知，我们的结果是首次定量地确定了在具有相当糖异质性的相关蛋白中发生的糖基化状态的变化。我们的结果提供了一种方法，可以了解糖基化状态的变化如何与蛋白质序列的变化相关联，这对于改进 IAV 疫苗株的选择是必要的。随着我们发现新的疫苗生产表达载体，了解糖基化将变得尤为重要，因为糖基化状态在很大程度上取决于宿主物种。
