三倍菌体的基因组分析,以ML为基础的宿主受体预测和其评估来限制MDR E. coli及其评估
Vineetha K Unnikrishnan1,2, Niranjana Sri Sundaramoorthy1,3, Veena G Nair1,2
1Center for Research On Infectious Diseases (CRID), School of Chemical and Biotechnology, SASTRA Deemed University, Thanjavur, Tamil Nadu, 613401, India.
Scientific reports
|December 28, 2023
概括
菌体疗法为对抗多药耐药细菌的抗生素提供了一个有希望的替代方案. 两种菌体的尾酒有效地降低了斑马鱼的抗卡巴因耐药大肠杆菌,证明了菌体疗法.
科学领域:
- 微生物学 微生物学
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
背景情况:
- 耐多药性 (MDR) 细菌感染构成了严重的全球健康威胁.
- 使用感染细菌的病毒进行菌体治疗,是传统抗生素的一个有希望的替代方案.
- 针对不同受体的菌体尾酒可能会增强对MDR细菌的疗效.
研究的目的:
- 隔离和表征对抗抗卡巴因耐药大肠杆菌*U1007.7.有效的菌体.
- 采用机器学习来预测菌体与宿主受体相互作用.
- 评估菌体尾酒对*大肠杆菌*U1007.7的体内疗效.
主要方法:
- 从环境来源中分离和表征三种菌体 (U1G,CR,M).
- 传输电子显微镜 (TEM) 用于体形态学和基因组测序.
- 机器学习模型 (随机森林,物流回归,决策树) 用于受体预测.
- 在斑马鱼感染模型中的体内疗效研究.
主要成果:
- 孤立的菌体U1G (Podoviridae),CR (Myoviridae) 和M (Siphoviridae) 的基因组缺乏耐药性或毒性基因.
- 机器学习准确地预测了每个菌体的潜在宿主受体.
- 通过生理实验验证了OmpC作为U1G菌体的受体.
- 一种双相尾酒 (U1G+M) 结合胆固醇可显著降低体内*大肠杆菌*U1007细胞数量.
结论:
- 机器学习是预测菌体与宿主受体相互作用的宝贵工具.
- 菌体尾酒显示出对抗多药耐药性大肠杆菌感染的巨大潜力.
- 这项研究支持菌体治疗的发展,作为对抗生素耐药细菌的可行策略.
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