废物转化为资源:利用机器学习从元基因组的污泥中提取抗菌
Jiaqi Xu1, Xin Xu1, Yunhan Jiang1
1Department of Environmental Engineering, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, China; Zhejiang Provincial Key Laboratory for Water Pollution Control and Environmental Safety, Hangzhou, China.
Environment international
|March 20, 2024
概括
研究人员使用元基因组学和机器学习发现了新型抗微生物 (AMP). 工程环境,比如污泥,显示出寻找新的抗生素替代品来对抗耐药细菌的巨大潜力.
科学领域:
- 微生物学 微生物学
- 生物技术是生物技术.
- 环境科学 环境科学
背景情况:
- 抗生素耐药性是一个关键的全球健康威胁.
- 抗微生物 (AMP) 是天然化合物,具有作为抗生素替代品的潜力.
- 环境资源为新型AMP发现提供了广的,尚未开发的水库.
研究的目的:
- 从环境样本中识别和描述新型抗微生物 (AMP).
- 评估工程环境的潜力,特别是污泥,用于AMP发现.
- 为了验证预测AMP的抗菌活性.
主要方法:
- 用于大规模AMP预测的元基因组测序和机器学习.
- 在污泥中针对性地识别AMP的metaproteomic分析和相关性研究.
- 候选AMP的化学合成和实验验证.
主要成果:
- 预测来自环境元基因组的超过1600万个抗微生物 (AMP).
- 从污泥中确定了27种候选AMP,其中21种对测试的菌株表现出抗菌活性.
- 已证实工程环境,特别是污泥,是新型AMP的可行来源.
结论:
- 工程环境是发现新的抗微生物 (AMP) 的有希望的来源.
- 与机器学习相结合的元基因组和元蛋白组方法对于从污泥等复杂环境中挖掘AMP是有效的.
- 这项研究证实了AMP作为对抗抗生素耐药细菌的未来战略的潜力.
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