采用基于深度学习的方法进行的大规模基因组调查,揭示了菌株水平的菌体特异性决定因素

采用基于深度学习的方法进行的大规模基因组调查,揭示了菌株水平的菌体特异性决定因素

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Isolation and Genome Analysis of Single Virions using 'Single Virus Genomics'

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Isolation and Genome Analysis of Single Virions using 'Single Virus Genomics'

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Yiyan Yang¹, Keith Dufault-Thompson¹, Wei Yan¹

¹National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.

GigaScience

|April 22, 2024

概括

新的深度学习工具SpikeHunter识别了菌体尾尖蛋白质,这些蛋白质对于向抗生素耐药细菌至关重要. 这可以通过基于细菌多糖体受体预测菌体-宿主特异性来推进菌体治疗.

科学领域:

微生物学微生物学
生物信息学是一种生物信息学.
基因组学就是基因组学.

背景情况:

菌体治疗是对抗抗菌素耐药性的有希望的策略.
由受体结合蛋白决定的菌体特异性是关键的,但由于菌体的多样性,其特征具有挑战性.
缺乏现有的工具来大规模表征受体结合蛋白.

研究的目的:

开发和介绍SpikeHunter,一种用于表征菌体尾尖蛋白的深度学习方法.
分析尾尖蛋白与细菌多糖之间的关联.
为了预测菌体-宿主特异性.

主要方法:

使用ESM-2蛋白语言模型开发SpikeHunter.
分析了787,566个细菌基因组,以识别菌体编码的尾尖蛋白.
与细菌多糖体受体和菌体-宿主特异性相关的尾尖蛋白域.

主要成果:

确定了231,965种不同的菌体尾尖蛋白.
在86.60%的鉴定蛋白质和特定的细菌多糖之间发现了强烈的关联.
证明相同的尾尖蛋白可以感染具有相似受体的不同细菌物种,突出显示C端域在特异性中的作用.
与真实世界的菌素治疗病例相比,经过验证的预测.

结论:

斯派克亨特提供了一种方法和数据库,用于了解菌体特异性决定因素.
提高了对菌体特异性的菌株级理解.
提供了一个指导治疗应用中的菌体选择的框架.

关键词:

这是一种细菌多糖化物.菌体受体结合蛋白是一种菌体受体结合蛋白.菌体疗法是一种菌体疗法.菌体宿主特异性血清型的血清型是什么

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