一个新的框架,用于通过主机特异性意识图形自编码器预测菌体-主机相互作用
IEEE journal of biomedical and health informatics
|March 3, 2025
概括
抗生素耐药性需要菌体治疗,但识别菌体与宿主相互作用是具有挑战性的. 通过利用基因组数据和宿主特异性,PHISGAE有效地预测这些相互作用,优于现有的方法.
科学领域:
- 微生物学和生物信息学
- 计算生物学 计算生物学
- 基因组学就是基因组学.
背景情况:
- 抗生素耐药性是一个日益增长的全球健康威胁,推动了对菌体治疗等替代治疗的需求.
- 准确识别菌体与宿主相互作用对于有效的菌体治疗至关重要,但仍然是一个重大挑战.
- 现有的计算方法往往无法充分利用菌体基因组信息或明确纳入宿主特异性.
研究的目的:
- 开发一种有效的计算方法来预测菌体与宿主之间的相互作用.
- 通过整合全面的基因组数据和宿主特异性来解决现有方法的局限性.
- 提高治疗目的的菌体与宿主相互作用预测的准确性和适用性.
主要方法:
- 开发了PHISGAE (使用特异性感知图形自编码器预测Phage-Host交互).
- 最初的菌体-菌体连接是使用菌体基因组和蛋白质序列建立的.
- 使用K-最近邻近策略构建了一个精致的异质网络.
- 使用宿主特异感知图形自编码器来学习菌体和细菌的表征,以预测相互作用.
主要成果:
- 与最先进的方法相比,PHISGAE在预测菌体与宿主相互作用方面表现出卓越的表现.
- 在物种层面达到94.73%,在属层面达到96.32%的高AUC值.
- 在案例研究中,从元基因组数据中成功识别了以前未见的菌体的潜在宿主.
结论:
- PHISGAE提供了一种高效准确的计算方法,用于预测菌体与宿主相互作用.
- 该方法明确使用宿主特异性,提高了预测准确度.
- PHISGAE对于在现实世界的元基因应用中识别新型菌体-宿主对和推进菌体治疗具有实际意义.
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