相互信息网络揭示了流感A病毒聚合酶内的进化关系
Sarah Arcos1, Alvin X Han2, Aartjan J W Te Velthuis3
1Department of Microbiology and Immunology, University of Michigan, 1150 West Medical Center Drive, 5641 Medical Science II, Ann Arbor, MI 48109, USA.
Virus evolution
|June 16, 2023
概括
该研究调查了A型流感病毒 (IAV) 聚合酶的演变,该研究引入了加权的相互信息 (wMI) 以揭示残留的共同演变. wMI网络突出显示了关键的聚合酶功能和宿主适应性,提供了对IAV进化驱动因素的见解.
科学领域:
- 病毒学 病毒学
- 进化生物学 进化生物学
- 生物信息学是一种生物信息学.
背景情况:
- 甲型流感病毒 (IAV) 的RNA聚合酶通过突变驱动病毒进化.
- 聚合酶子单元之间的表观相互作用使突变率,复制速度和耐药性的进化分析复杂化.
研究的目的:
- 分析自1968年大流行以来人类季节性H3N2聚合酶的演变.
- 开发和验证一个加权的相互信息 (wMI) 度量来分析病毒序列中的进化关系.
- 构建wMI网络以了解IAV聚合酶内的残留共演,区分功能关系与受血凝素 (HA) 影响的功能关系.
主要方法:
- 在约7000个H3N2聚合酶序列中使用相互信息 (MI) 识别了双对进化关系.
- 开发了一个加权MI (wMI) 度量,以考虑随时间的不同序列采样.
- 构建了 wMI 网络,结合了血质素 (HA),以分析残留的共同进化关系.
主要成果:
- 使用SARS-CoV-2数据验证了wMI与原始MI的优势.
- wMI网络揭示了IAV复制和封装中的残留物之间的共同进化关系.
- 分析区分了聚合酶特定的功能残留物与与HA抗原漂移相关的功能残留物,突出了酶功能和宿主适应性的作用.
结论:
- wMI是一种分析病毒蛋白复杂进化动态的强大方法.
- 同进化网络提供了对流感病毒进化的功能约束和驱动因素的见解.
- 了解这些关系对于预测和控制流感病毒适应至关重要.
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