通过气道微生物组概况识别识别Mycobacterium结核病感染状态的协议
Geoffrey Olweny1, Moses Levi Ntayi1, Edward Kyalo1
1Department of Immunology and Molecular Biology, Makerere University College of Health Sciences, Kampala 256, Uganda; Lung Institute, Makerere University College of Health Sciences, Kampala 256, Uganda.
STAR protocols
|January 18, 2025
概括
本协议详细说明了如何分析气道微生物组数据以确定Mycobacterium结核病感染. 它概述了数据处理,多样性分析和生物标志物发现的方法,以改善结核病诊断.
科学领域:
- 微生物学 微生物学
- 传染性疾病 传染性疾病
- 生物信息学是一种生物信息学.
背景情况:
- 结核病仍然是一个全球性卫生挑战,需要改进诊断方法.
- 呼吸道微生物组作为呼吸道感染的非侵入性生物标志物具有潜力.
- 准确识别Mycobacterium结核病感染状态对于有效的治疗和控制至关重要.
研究的目的:
- 为分析气道微生物群数据提供标准化协议.
- 为了建立一个微生物群签名来识别Mycobacterium结核病感染.
- 为了指导对结核病诊断的潜在生物标志物的识别.
主要方法:
- 处理原始微生物组测序数据的标准化程序.
- 计算α和β多样性指标以评估微生物社区结构.
- 应用迪里克莱特多项混合模型用于微生物组概况.
- 对分类学相对和差异丰度的分析.
- 确定与M.结核病感染相关的特定微生物种群或模式.
主要成果:
- 该协议可以生成气道微生物群签名.
- 签名可以区分M.结核病感染状态.
- 确定了与感染状况相关的潜在微生物生物标志物.
结论:
- 呼吸道微生物组分析是检测M.结核病的一种可行的方法.
- 该协议促进了呼吸道微生物组诊断的可重复性研究.
- 进一步验证可能会导致结核病的新型诊断工具.
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