Prevalence of epistasis in the evolution of influenza A surface proteins.
Prevalence of epistasis in the evolution of influenza A surface proteins.
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DOI：
10.1371/journal.pgen.1001301
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发表时间：
2011-02
期刊：
影响因子：
4.5
通讯作者：
Plotkin JB
中科院分区：
文献类型：
--
作者：
Kryazhimskiy S;Dushoff J;Bazykin GA;Plotkin JB
人类甲型流感病毒的表面蛋白经历正选择以逃避人类免疫和最近的抗病毒药物治疗。在细菌和病毒中，免疫逃逸和耐药表型通常通过几种突变的组合出现，这些突变对病原体的适应性具有上位效应。然而，流感病毒蛋白上位性的程度和结构尚未得到系统研究。在这里，我们开发了一种新的统计方法，根据观察到的序列进化的时间模式来检测蛋白质中位点对之间的正上位性。该方法基于一个简单的想法，即如果一个位点是正上位的，则一个位点的替换应该迅速跟随另一个位点的替换。我们将该方法应用于甲型流感病毒 H3N2 和 H1N1 亚型的表面蛋白血凝素和神经氨酸酶。与非上位零分布相比，我们检测到大量的上位并确定了假定的上位位点对的身份。特别是，仅使用序列数据，我们的方法识别了神经氨酸酶特定位点之间的上位相互作用，最近已在体外证明这些位点赋予对药物奥司他韦的耐药性；这些上位相互作用导致了当今流行的 H1N1 病毒中广泛的耐药性。该实验验证证明了我们的方法在识别对病毒适应和公共卫生重要的上位位点方面的预测能力。我们得出的结论是，上位性在塑造流感病毒的分子进化中发挥着重要作用。特别是，具有 的位点（通常不会被识别为正选择）可以通过与其伙伴位点的上位相互作用促进病毒适应。了解流感蛋白位点之间的特定相互作用可以帮助我们预测抗原进化的过程，从而选择更合适的疫苗和药物。上位性描述了遗传位点之间的非加性相互作用：一个位点突变的结果可能取决于其他位点基因组的状态。在极端情况下，如果突变发生在一种遗传背景上，则可能不会产生任何影响，但会对另一种遗传背景产生强烈影响。生活在抗生素治疗或免疫压力等恶劣条件下的病毒和细菌的上位突变通常会使病原体产生耐药性或逃避免疫系统。在本文中，我们开发了一种新的系统发育方法来检测上位性，并将该方法应用于甲型流感病毒的表面蛋白，这是免疫系统和药物治疗的重要靶标。作者鉴定并描述了这些蛋白质中的数百个上位突变。在那些已确定的突变中，我们发现了最近实验证明的特定上位突变，这些突变可赋予达菲药物耐药性。这项研究的结果可能有助于预测流感抗原进化的过程并选择更合适的疫苗和药物。
The surface proteins of human influenza A viruses experience positive selection to escape both human immunity and, more recently, antiviral drug treatments. In bacteria and viruses, immune-escape and drug-resistant phenotypes often appear through a combination of several mutations that have epistatic effects on pathogen fitness. However, the extent and structure of epistasis in influenza viral proteins have not been systematically investigated. Here, we develop a novel statistical method to detect positive epistasis between pairs of sites in a protein, based on the observed temporal patterns of sequence evolution. The method rests on the simple idea that a substitution at one site should rapidly follow a substitution at another site if the sites are positively epistatic. We apply this method to the surface proteins hemagglutinin and neuraminidase of influenza A virus subtypes H3N2 and H1N1. Compared to a non-epistatic null distribution, we detect substantial amounts of epistasis and determine the identities of putatively epistatic pairs of sites. In particular, using sequence data alone, our method identifies epistatic interactions between specific sites in neuraminidase that have recently been demonstrated, in vitro, to confer resistance to the drug oseltamivir; these epistatic interactions are responsible for widespread drug resistance among H1N1 viruses circulating today. This experimental validation demonstrates the predictive power of our method to identify epistatic sites of importance for viral adaptation and public health. We conclude that epistasis plays a large role in shaping the molecular evolution of influenza viruses. In particular, sites with , which would normally not be identified as positively selected, can facilitate viral adaptation through epistatic interactions with their partner sites. The knowledge of specific interactions among sites in influenza proteins may help us to predict the course of antigenic evolution and, consequently, to select more appropriate vaccines and drugs. Epistasis describes non-additive interactions among genetic sites: the consequence of a mutation at one site may depend on the status of the genome at other sites. In an extreme case, a mutation may have no effect if it arises on one genetic background, but a strong effect on another background. Epistatic mutations in viruses and bacteria that live under severe conditions, such as antibiotic treatments or immune pressure, often allow pathogens to develop drug resistance or escape the immune system. In this paper we develop a new phylogenetic method for detecting epistasis, and we apply this method to the surface proteins of the influenza A virus, which are important targets of the immune system and drug treatments. The authors identify and characterize hundreds of epistatic mutations in these proteins. Among those identified, we find the specific epistatic mutations that were recently shown, experimentally, to confer resistance to the drug Tamiflu. The results of this study may help to predict the course of influenza's antigenic evolution and to select more appropriate vaccines and drugs.
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影响因子：
64.8
作者：
通讯作者：
--
影响因子：
4.3
作者：
Baussand J;Carbone A
通讯作者：
Carbone A
影响因子：
5.8
作者：
Dunn, S. D.;Wahl, L. M.;Gloor, G. B.
通讯作者：
Gloor, G. B.
DOI：
10.1073/pnas.0901522106
发表时间：
2009-06-16
影响因子：
11.1
作者：
Bloom, Jesse D.;Arnold, Frances H.
通讯作者：
Arnold, Frances H.
DOI：
10.1126/science.1187816
发表时间：
2010-06-04
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Bloom JD;Gong LI;Baltimore D
通讯作者：
Baltimore D