对于2023年在两个欧盟国家参考实验室进行结核耐药性查的基因型和表型的相对定位
Richard Anthony1, Ramona Groenheit2, Mikael Mansjö2
1National Tuberculosis Reference Laboratory, Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), 3721BA Bilthoven, The Netherlands.
Microorganisms
|July 29, 2023
概括
全基因组测序 (WGS) 准确地预测了Mycobacterium结核病的药物易感性,减少了广泛的表型测试的需要. 这种方法通过将表型药物敏感性测试 (pDST) 专注于由WGS识别的耐药病例来优化资源使用.
科学领域:
- 微生物学 微生物学
- 基因组学就是基因组学.
- 流行病学 流行病学
背景情况:
- 全基因组测序 (WGS) 越来越多地用于Mycobacterium结核病 (Mtb) 类型化.
- 广泛的知识库将Mtb突变与药物耐药性联系起来.
- 从单独的数据中,WGS可以预测药物敏感性概况.
研究的目的:
- 评估WGS在Mtb.中预测一线药物敏感性的实用性.
- 与WGS一起评估常规表型药物敏感性测试 (pDST) 的效率.
- 为Mtb耐药性监测提出一个优化的战略.
主要方法:
- 全基因组测序 (WGS) 在Mtb分离物上进行.
- 基于WGS的敏感性预测与表型药物敏感性测试 (pDST) 进行了比较.
- 评估了WGS的准确性和阻力水平预测能力.
主要成果:
- WGS准确地预测了Mtb分离物的第一线药物敏感性,与pDST相比.
- 大约80%的分离物被预测完全易受WGS.
- 常规的pDST对WGS敏感的隔离物提供了最小的额外信息.
结论:
- 常规的WGS可以可靠地预测Mtb对一线药物的敏感性.
- 一个优化的策略包括针对WGS识别的耐药分离物进行有针对性的pDST.
- 这种方法提高了Mtb耐药性监测的效率和资源配置.
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