病原体FAIR:是一组FAIR和适应性 (元基因组学) 工作流程,用于检测和跟踪 (食源) 病原体
Engy Nasr1, Anna Henger2, Björn Grüning1
1Bioinformatics Group, Department of Computer Science, University of Freiburg, 79110 Freiburg im Breisgau, Germany.
GigaScience
|September 26, 2025
概括
病原GFAIR是一种新的工作流程,用于使用元基因组纳米孔测序检测病原体. 它可以准确地识别食品和其他样本中的病原体,有助于疫情调查和公共卫生.
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:
- 食物传播的病原体导致了全球重大健康问题,每年影响数百万人.
- 微生物学分析对于在食品传播疫情调查期间识别病原体至关重要.
- 超基因组方法与纳米孔测序相结合,可以快速检测病原体,但缺乏可访问的管道.
研究的目的:
- 开发和验证PathoGFAIR,一个用户友好的,符合FAIR的病原体识别和跟踪工作流程.
- 解决 (元) 基因组病原体分析中可访问的生物信息管道的需求.
主要方法:
- 开发了PathoGFAIR,这是一个基于银河系的FAIR工作流的集合.
- 利用从元基因组纳米孔序列数据中检测病原体的最先进的工具.
- 在各种实验条件下,对130个不同样本进行了工作流程测试.
主要成果:
- 在130个测试样本中,PathoGFAIR成功检测出该物种的预期病原体,在130个测试样本中排名第129.
- 该工作流在不同的主机和实验条件中显示出有效性.
- 在具有足够病原体负载的样本中发现了更高的分类学等级.
结论:
- 病原GFAIR在物种和亚种层面准确地识别病原体,在样品类型和制备方法中证明强大.
- 工作流程易于使用,适应性强,可用于各种病原体检测场景.
- 病理GFAIR增强了用于公共卫生监测的元基因组纳米孔测序的应用.
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