Zeteo Tech Inc, Sykesville, Maryland, United States of America.
Desmond Tutu HIV Centre, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, Cape Town, South Africa.
Sci Rep. 2020 May 6;10(1):7647. doi: 10.1038/s41598-020-64637-6.
Tuberculosis remains a global health threat killing over 1 million people per year. Current sputum-based diagnostics are specific but lack sensitivity resulting in treatment of many sputum negative cases. In this proof-of-concept study, we used high-resolution mass spectrometry to identify specific lipids in peripheral lung fluid samples of TB patients and controls, captured using a novel non-invasive sampling system. Exhaled respiratory particles were collected in liquid and after concentration and lipid extraction directly infused into a high-resolution mass spectrometer. High-resolution mass spectrometric data collection was conducted in a dual ion mode and chemical compositions were constructed using accurate mass measurement. Over 400 features with high segregating capacity were extracted and optimized using feature selection algorithm and machine learning, from which the accuracy of detection of positive tuberculosis patients was estimated. This current strategy provides sensitivity offered by high-resolution mass spectrometry and can be readily susceptible for developing a novel clinical assay exploring peripheral lung fluid for the detection of active TB cases.
结核病仍然是一个全球性的健康威胁,每年导致超过 100 万人死亡。目前基于痰液的诊断方法具有特异性,但缺乏敏感性,导致许多痰液阴性病例被误诊。在这项概念验证研究中,我们使用高分辨率质谱技术来鉴定结核患者和对照者外周肺液样本中的特定脂质,这些样本是使用一种新的非侵入性采样系统采集的。呼吸颗粒被收集在液体中,经过浓缩和脂质提取后,直接注入高分辨率质谱仪。高分辨率质谱数据的采集采用双离子模式进行,化学组成则通过精确质量测量来构建。从 400 多个具有高分离能力的特征中提取并优化了特征选择算法和机器学习,从而估计了阳性结核患者的检测准确性。该策略结合了高分辨率质谱技术的敏感性,很容易开发出一种新的临床检测方法,通过检测外周肺液来诊断活动性结核病。