Extreme evolutionary conservation of functionally important regions in H1N1 influenza proteome.
Extreme evolutionary conservation of functionally important regions in H1N1 influenza proteome.
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DOI：
10.1371/journal.pone.0081027
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发表时间：
2013
期刊：
影响因子：
3.7
通讯作者：
Korkin D
中科院分区：
文献类型：
--
作者：
Warren S;Wan XF;Conant G;Korkin D
H1N1亚型甲型流感病毒导致了四起有记录的大流行中的两起，并导致季节性疫情暴发，对公共卫生构成持续威胁。共同传播的抗原性不同的流感毒株大大增加了疫苗开发和使用的复杂性。在这里，通过结合关于H1N1蛋白质组的进化、结构、功能和种群信息，我们试图回答两个问题：(1)构成流感蛋白质组的所有蛋白质中，蛋白质表面残基的进化速度是否一致快于蛋白质核心残基的进化速度？以及(2)尽管流感蛋白的表面残基快速进化，但蛋白质表面有没有不进化的蛋白质区域？为了回答这些问题，我们首先建立了表面和内部替换模式的系统发育感知模型。利用这些模型，我们发现了一个单一的一致的模式，在蛋白质表面更快的进化，这是所有流感蛋白质的特征。这种模式与物种间重组事件、80年代初S流感疫苗在全球范围内的引入以及病毒地理来源造成的差异是一致的。接下来，我们开发了一个自动计算管道来全面检测蛋白质表面残基的区域，这些区域在多年和多个寄主物种中是100%保守的。我们确定了分布在所有禽类、猪类和人类毒株的10种流感蛋白表面的保守区；除了一小部分分离的毒株影响三种蛋白的保守性。令人惊讶的是，这些区域也没有受到2009年大流行H1N1病毒种群数据的遗传变异的影响，这些数据是通过深度测序实验获得的。最后，保守区域与病毒内大分子相互作用界面存在内在联系。我们的研究可能为识别流感抗病毒药物的新蛋白质靶点提供进一步的见解。
The H1N1 subtype of influenza A virus has caused two of the four documented pandemics and is responsible for seasonal epidemic outbreaks, presenting a continuous threat to public health. Co-circulating antigenically divergent influenza strains significantly complicates vaccine development and use. Here, by combining evolutionary, structural, functional, and population information about the H1N1 proteome, we seek to answer two questions: (1) do residues on the protein surfaces evolve faster than the protein core residues consistently across all proteins that constitute the influenza proteome? and (2) in spite of the rapid evolution of surface residues in influenza proteins, are there any protein regions on the protein surface that do not evolve? To answer these questions, we first built phylogenetically-aware models of the patterns of surface and interior substitutions. Employing these models, we found a single coherent pattern of faster evolution on the protein surfaces that characterizes all influenza proteins. The pattern is consistent with the events of inter-species reassortment, the worldwide introduction of the flu vaccine in the early 80’s, as well as the differences caused by the geographic origins of the virus. Next, we developed an automated computational pipeline to comprehensively detect regions of the protein surface residues that were 100% conserved over multiple years and in multiple host species. We identified conserved regions on the surface of 10 influenza proteins spread across all avian, swine, and human strains; with the exception of a small group of isolated strains that affected the conservation of three proteins. Surprisingly, these regions were also unaffected by genetic variation in the pandemic 2009 H1N1 viral population data obtained from deep sequencing experiments. Finally, the conserved regions were intrinsically related to the intra-viral macromolecular interaction interfaces. Our study may provide further insights towards the identification of novel protein targets for influenza antivirals.
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