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用熵方法量化病毒的选择和多样性,并应用于 H3N2 流感的血凝素。

Quantifying selection and diversity in viruses by entropy methods, with application to the haemagglutinin of H3N2 influenza.

机构信息

Department of Bioengineering, Rice University, , 6100 Main Street, Houston, TX 77005, USA.

出版信息

J R Soc Interface. 2011 Nov 7;8(64):1644-53. doi: 10.1098/rsif.2011.0105. Epub 2011 May 4.

Abstract

Many viruses evolve rapidly. For example, haemagglutinin (HA) of the H3N2 influenza A virus evolves to escape antibody binding. This evolution of the H3N2 virus means that people who have previously been exposed to an influenza strain may be infected by a newly emerged virus. In this paper, we use Shannon entropy and relative entropy to measure the diversity and selection pressure by an antibody in each amino acid site of H3 HA between the 1992-1993 season and the 2009-2010 season. Shannon entropy and relative entropy are two independent state variables that we use to characterize H3N2 evolution. The entropy method estimates future H3N2 evolution and migration using currently available H3 HA sequences. First, we show that the rate of evolution increases with the virus diversity in the current season. The Shannon entropy of the sequence in the current season predicts relative entropy between sequences in the current season and those in the next season. Second, a global migration pattern of H3N2 is assembled by comparing the relative entropy flows of sequences sampled in China, Japan, the USA and Europe. We verify this entropy method by describing two aspects of historical H3N2 evolution. First, we identify 54 amino acid sites in HA that have evolved in the past to evade the immune system. Second, the entropy method shows that epitopes A and B on the top of HA evolve most vigorously to escape antibody binding. Our work provides a novel entropy-based method to predict and quantify future H3N2 evolution and to describe the evolutionary history of H3N2.

摘要

许多病毒进化迅速。例如,甲型 H3N2 流感病毒的血凝素 (HA) 通过进化来逃避抗体结合。H3N2 病毒的这种进化意味着以前接触过流感株的人可能会被新出现的病毒感染。在本文中,我们使用香农熵和相对熵来衡量 1992-1993 季节和 2009-2010 季节之间 H3HA 每个氨基酸位点的抗体的多样性和选择压力。香农熵和相对熵是我们用来描述 H3N2 进化的两个独立状态变量。熵方法使用当前可用的 H3HA 序列估计未来的 H3N2 进化和迁移。首先,我们表明进化速度随着当前季节病毒多样性的增加而增加。当前季节序列的熵预测当前季节序列与下一个季节序列之间的相对熵。其次,通过比较在中国、日本、美国和欧洲采样的序列的相对熵流,组装了 H3N2 的全球迁移模式。我们通过描述 H3N2 进化的两个方面来验证这个熵方法。首先,我们确定了 54 个在过去进化以逃避免疫系统的 HA 氨基酸位点。其次,熵方法表明,HA 顶部的表位 A 和 B 最活跃地进化以逃避抗体结合。我们的工作提供了一种基于熵的新方法来预测和量化未来 H3N2 的进化,并描述 H3N2 的进化历史。

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