整合基因组流行病学和深度突变扫描数据,以预测SARS-CoV-2 Omicron系的流行率
Zhong-Yi Lei1,2, Xiao-Min Zhang2, Jia-Lu Han3,4
1College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, China.
PloS one
|November 3, 2025
概括
预测严重急性呼吸道综合征冠状病毒2 (SARS-CoV-2) Omicron血统流行率至关重要. 一个新的模型,CoVPF,将基因组数据与功能突变洞察力相结合,以实现更准确的预测.
科学领域:
- 病毒学 病毒学
- 基因组学就是基因组学.
- 流行病学 流行病学
背景情况:
- 严重急性呼吸道综合征冠状病毒2 (SARS-CoV-2) 持续演变,Omicron变种产生了众多的血统.
- 准确预测新出现的SARS-CoV-2血统对于公共卫生至关重要.
- 以前的预测模型往往忽视了突变在血统层面的功能影响.
研究的目的:
- 开发一种新的模型,CoVPF,用于预测SARS-CoV-2 Omicron血统的流行率.
- 将基因组流行病学与深度突变扫描数据相结合,以提高预测准确度.
- 评估突变之间的表观相互作用在谱系流行率预测中的重要性.
主要方法:
- 拟议的CoVPF模型整合了基因组流行病学和深度突变扫描 (DMS) 数据.
- 专注于SARS-CoV-2尖端蛋白的受体结合域 (RBD).
- 对特定的Omicron血统 (例如,EG.5.1,XBB.1.5) 的回顾性验证和案例研究.
主要成果:
- 与以前的方法相比,CoVPF在追溯验证中显示了20.7%的更高准确性.
- 考虑到epistasis显著提高了预测准确性,当忽视时,准确性下降了43%.
- CoVPF提供了更准确和更及时的预测,对血统扩张和曲折.
结论:
- CoVPF提供了一个强大的框架,通过结合基因组和功能数据来预测SARS-CoV-2血统流行率.
- 该模型强调了表皮病在病毒进化和预测中的关键作用.
- 这种方法通过提高预测病毒传播和演变的能力来支持公共卫生倡议.
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