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深度学习预测了禽流感H5N1与人类流感病毒的潜在重组

Jun-Qing Wei^1,2, Sen Zhang¹, Ya-Dan Li¹

¹State Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing 100071, China.

National science review

|December 18, 2025

概括

一个新的AI模型,HAIRANGE,预测鸟类H5N1流感A病毒 (IAV) 与人类IAV重组. 该工具识别了潜在的适应性病毒基因重组带来的流行病风险.

科学领域:

病毒学和生物信息学
计算生物学和机器学习
传染病流行病学传染病流行病学

背景情况:

禽流感A型病毒 (IAVs),特别是H5N1,由于可能与人类IAVs重组,造成了重大流行病威胁.
预测病毒适应和重组对于疫情准备和监测至关重要.
基因组背景在病毒宿主适应和血清型确定中起着至关重要的作用.

研究的目的:

开发一个注意力深度学习模型,HAIRANGE,用于预测鸟类H5N1和人类IAV的人类适应性重新分类.
评估IAV RNA聚合酶基因的基因组背景和病毒宿主/血清型之间的关联.
通过体外测试验证模型的预测.

主要方法:

开发了HAIRANGE深度学习模型,其中包含了一个新的Codon2Vec嵌入器.
与ESM2和DNABERT2.2等既有模型对比HAIRANGE的嵌入器进行基准测试.
试验室聚合酶活性测定验证预测的适应性重组.

主要成果:

该Codon2Vec嵌入器展示了竞争性性能,突出显示了基因组背景对IAV RNA聚合酶基因的重要性.
毛色准确地预测了基因适应和适应性重组事件.
关于鸟类H5N1和人类H3N2IAV之间的适应性重组的预测和实验验证.

结论:

通过利用嵌入式基因组背景,HAIRANGE有效地预测了自适应性IAV重组.
该模型为识别禽流感病毒潜在的流行病威胁提供了有价值的工具.
这项研究强调了H5N1 IAV通过与人类流感菌株重新组合的持续流行潜力.

关键词:

这是一种H5N1流感.适应性重新排序方式深度学习是一种深度学习.这是基因组嵌入.聚合酶基因的基因是聚合酶基因.

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