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使用PEP-TORCH型组算法精确识别菌根菌种和亚种

Duran Bao^1,2, Sudipa Maity^1,2, Lingpeng Zhan^1,2

¹Center for Cellular and Molecular Diagnostics, Tulane University School of Medicine, New Orleans, LA, 70112, USA.

EMBO molecular medicine

|March 4, 2025

概括

一种新的基于体的方法,PEP-TORCH,可以准确地识别MGIT培养中的真菌菌种和亚种,大大加快了对这些全球健康威胁的诊断和改善治疗策略.

科学领域:

临床微生物学临床微生物学
蛋白质组学是指蛋白质组学.
传染性疾病传染性疾病

背景情况:

菌根菌感染是全球主要的健康问题.
目前的诊断方法往往是缓慢和不准确的,延迟有效的治疗.
精确识别菌根菌种和亚种对于向治疗至关重要.

研究的目的:

开发一种新的,快速和准确的基于体的方法来识别菌根细菌.
利用质谱和定制算法 (PEP-TORCH) 提高诊断能力.
与传统方法相比,简化识别过程.

主要方法:

开发了PEP-TORCH (PEP-Taxonomy/ORganism CHecking) 算法,该算法使用的方法包括:
使用质谱学分析来自Mycobacterial Growth Indicator Tube (MGIT) 培养物的三性.
使用PEP-TORCH选择的生物标志物的向蛋白质组学方法的验证.

主要成果:

在81个个体中,PEP-TORCH在识别菌根菌种,亚种和共感染方面取得了100%的准确性.
该方法消除了传统的亚固体培养程序的需要.
同时识别物种和亚物种显著加快了病原体的检测.

结论:

PEP-TORCH方法提供了一种更快,更准确的方法来诊断菌根菌感染.
已验证的向蛋白质组学生物标志物可以在临床友好的环境中使用.
这种全面的识别策略有望优化临床治疗策略.

关键词:

算法算法是一种算法.这是LC-MS/MS.没有结核病的菌菌菌菌菌.体体 (Peptidome) 是一种体体 (Peptidome) 的形式.亚种亚种亚种亚种亚种

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