Differential neutralization efficiency of hemagglutinin epitopes, antibody interference, and the design of influenza vaccines
Differential neutralization efficiency of hemagglutinin epitopes, antibody interference, and the design of influenza vaccines
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DOI：
10.1073/pnas.0903427106
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发表时间：
2009-05-26
影响因子：
11.1
通讯作者：
Levin, Simon A.
中科院分区：
文献类型：
--
作者：
Ndifon, Wilfred;Wingreen, Ned S.;Levin, Simon A.
一般认为，流感病毒的表面蛋白血凝素（HA）的氨基酸突变允许这些病毒在感染期间被诱导的抗体中和。然而，关于流行流感病毒的经验数据表明，某些氨基酸改变为HA实际上增加了针对母病毒产生的抗体对突变病毒的中和效率。在这里，我们认为HA突变后中和效率的惊人增加可能反映了抗体之间的位阻干扰。具体来说，如果具有不同中和效率的抗体与HA结合存在空间竞争，那么减少低中和效率抗体结合的突变可能会增加整体病毒中和。我们使用病毒-抗体相互作用的数学模型来阐明氨基酸突变到HA可能导致病毒中和增加的条件。利用从模型中获得的见解，结合遗传和结构数据，我们预测甲型流感/H3N2病毒HA表位C和E的氨基酸突变可能导致突变病毒的中和作用平均增加。我们提出了支持这一预测的数据，并讨论了设计更有效的流感病毒和其他病原体疫苗的意义。
It is generally assumed that amino acid mutations in the surface protein, hemagglutinin (HA), of influenza viruses allow these viruses to circumvent neutralization by antibodies induced during infection. However, empirical data on circulating influenza viruses show that certain amino acid changes to HA actually increase the efficiency of neutralization of the mutated virus by antibodies raised against the parent virus. Here, we suggest that this surprising increase in neutralization efficiency after HA mutation could reflect steric interference between antibodies. Specifically, if there is a steric competition for binding to HA by antibodies with different neutralization efficiencies, then a mutation that reduces the binding of antibodies with low neutralization efficiencies could increase overall viral neutralization. We use a mathematical model of virus - antibody interaction to elucidate the conditions under which amino acid mutations to HA could lead to an increase in viral neutralization. Using insights gained from the model, together with genetic and structural data, we predict that amino acid mutations to epitopes C and E of the HA of influenza A/H3N2 viruses could lead on average to an increase in the neutralization of the mutated viruses. We present data supporting this prediction and discuss the implications for the design of more effective vaccines against influenza viruses and other pathogens.