Using sequence data to infer the antigenicity of influenza virus.
Using sequence data to infer the antigenicity of influenza virus.
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DOI：
10.1128/mbio.00230-13
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发表时间：
2013-07-02
期刊：
影响因子：
6.4
通讯作者：
Wan XF
中科院分区：
文献类型：
--
作者：
Sun H;Yang J;Zhang T;Long LP;Jia K;Yang G;Webby RJ;Wan XF
当前流感疫苗的效力需要在流行毒株和疫苗毒株之间的抗原密切匹配。因此，及时识别新出现的流感病毒抗原变体对流感疫苗接种计划的成功至关重要。确定流感病毒抗原性的经验方法耗时且产量中等，并且需要活病毒。在这里，我们提出了一种新的，实验验证，计算方法确定流感病毒抗原性的血凝素（HA）序列的基础上。该方法将自举脊回归与抗原定位相结合，利用流感病毒HA1序列定量测定抗原距离。我们的方法应用于H3N2季节性流感病毒，鉴定了13个先前识别的H3N2抗原簇和2009年导致H3N2疫苗株变化的抗原漂移事件。本报告提供了一种新的方法来定量抗原距离和鉴定抗原变异单独使用序列。该方法将有助于流感疫苗株的选择，大大减少了血清学表征的人力劳动，并将增加正确选择流感疫苗候选株的可能性。
The efficacy of current influenza vaccines requires a close antigenic match between circulating and vaccine strains. As such, timely identification of emerging influenza virus antigenic variants is central to the success of influenza vaccination programs. Empirical methods to determine influenza virus antigenic properties are time-consuming and mid-throughput and require live viruses. Here, we present a novel, experimentally validated, computational method for determining influenza virus antigenicity on the basis of hemagglutinin (HA) sequence. This method integrates a bootstrapped ridge regression with antigenic mapping to quantify antigenic distances by using influenza HA1 sequences. Our method was applied to H3N2 seasonal influenza viruses and identified the 13 previously recognized H3N2 antigenic clusters and the antigenic drift event of 2009 that led to a change of the H3N2 vaccine strain. This report supplies a novel method for quantifying antigenic distance and identifying antigenic variants using sequences alone. This method will be useful in influenza vaccine strain selection by significantly reducing the human labor efforts for serological characterization and will increase the likelihood of correct influenza vaccine candidate selection.