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莫比雷斯:通过移动基因组分析进行抗体风险预测的整合管道
Santhiya Kalimuthu1, Ananthasubramanian Muthusamy1
1Centre for Biological Bigdata Analytics, Department of Biotechnology, PSG College of Technology, Coimbatore 641 004, India.
Journal of microbiological methods
|March 12, 2026
概括
抗菌素耐药性 (AMR) 是一个全球性的威胁. 一个新的计算框架,MobiRes,评估移动遗传元素 (MGE) 的风险,如转位子,确定它们是抗生素耐药性基因在不同环境中传播的关键驱动因素.
科学领域:
- 环境微生物学环境微生物学
- 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:
- 抗菌素耐药性 (AMR) 是一个关键的全球卫生问题.
- 环境作为抗生素耐药性基因 (ARG) 的储存库.
- 缺乏推动ARG传播的移动遗传元素 (MGE) 的系统风险评估.
研究的目的:
- 引入MobiRes,这是一个开源的计算框架,用于预测AMR风险.
- 整合移动组和微生物组数据,以进行全面的风险评估.
- 评估MGE在ARG在各种环境中的传播中的作用.
主要方法:
- 开发和评估了使用各种公共元基因组数据集的MobiRes管道.
- 应用统计分析和机器学习 (随机森林,SHAP) 来评估MGE在ARG传播中的作用.
- 分析了与等离子体,菌体,转子体和整合元素相关的ARG的环境变化.
主要成果:
- 转子被确定为占主导地位的MGE类.
- 转子体相关的ARG显示出显著的环境差异化 (ANOVA p=0.0017).
- 随机森林模型实现了0.82AUC,转子子丰富是ARG传播的主要驱动因素.
结论:
- MobiRes提供了一个可扩展的,以One Health为导向的AMR风险评估框架.
- 转子子是ARG在各种环境中传播的关键媒介.
- 整合宿主,移动性和生态数据可以提高抗药性耐药性风险评估.
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