Limited Predictability of Amino Acid Substitutions in Seasonal Influenza Viruses.
Limited Predictability of Amino Acid Substitutions in Seasonal Influenza Viruses.
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DOI：
10.1093/molbev/msab065
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发表时间：
2021-06-25
影响因子：
10.7
通讯作者：
Neher RA
中科院分区：
文献类型：
--
作者：
Barrat-Charlaix P;Huddleston J;Bedford T;Neher RA
季节性流感病毒反复感染人类，部分原因是它们迅速改变其抗原性并逃避宿主免疫反应，需要频繁更新疫苗成分。因此，对未来流行毒株的准确预测可能会改善疫苗匹配。在这里，我们研究了频率动力学和氨基酸取代固定的可预测性。正如中性进化中预期的那样，当前频率是最终注视的最强预测因子。其他性质，如出现在先前表征的表位或高局部分支指数(LBI)几乎没有预测能力。平行进化被发现对注视有适度的预测。尽管LBI几乎没有能力预测频率动态，但它仍然成功地挑选出了代表未来种群的品系。后者是由于LBI倾向于比平均序列更接近未来的共识类序列。相比之下，对适应人口模型的模拟则显示出明显的可预测性信号。这表明，流感HA和NA的进化虽然受到强大的选择压力的驱动而发生变化，但通常的定向选择模型，如旅行适应波，描述得很差。
Seasonal influenza viruses repeatedly infect humans in part because they rapidly change their antigenic properties and evade host immune responses, necessitating frequent updates of the vaccine composition. Accurate predictions of strains circulating in the future could therefore improve the vaccine match. Here, we studied the predictability of frequency dynamics and fixation of amino acid substitutions. Current frequency was the strongest predictor of eventual fixation, as expected in neutral evolution. Other properties, such as occurrence in previously characterized epitopes or high Local Branching Index (LBI) had little predictive power. Parallel evolution was found to be moderately predictive of fixation. Although the LBI had little power to predict frequency dynamics, it was still successful at picking strains representative of future populations. The latter is due to a tendency of the LBI to be high for consensus-like sequences that are closer to the future than the average sequence. Simulations of models of adapting populations, in contrast, show clear signals of predictability. This indicates that the evolution of influenza HA and NA, while driven by strong selection pressure to change, is poorly described by common models of directional selection such as traveling fitness waves.
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DOI：
10.2307/3211856
发表时间：
1964-01-01
期刊：
J. appl. Prob.
影响因子：
--
作者：
Kimura, M.
通讯作者：
Kimura, M.
影响因子：
10.7
作者：
Bhatt, Samir;Holmes, Edward C.;Pybus, Oliver G.
通讯作者：
Pybus, Oliver G.
影响因子：
4.6
作者：
Klingen TR;Reimering S;Loers J;Mooren K;Klawonn F;Krey T;Gabriel G;McHardy AC
通讯作者：
McHardy AC
影响因子：
7.7
作者：
Lee, Juhye M.;Eguia, Rachel;Bloom, Jesse D.
通讯作者：
Bloom, Jesse D.
影响因子：
64.8
作者：
Rambaut, Andrew;Pybus, Oliver G.;Holmes, Edward C.
通讯作者：
Holmes, Edward C.