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A multiple-method comparative study using GC–MS, AMDIS and in-house-built software for the detection and identification of “unknown” volatile organic compounds in breath
Journal of Mass Spectrometry ( IF 2.3 ) Pub Date : 2021-08-16 , DOI: 10.1002/jms.4782
Dana Marder 1 , Nitzan Tzanani 1 , Adva Baratz 1 , Eyal Drug 1 , Hagit Prihed 1 , Shay Weiss 2 , Eli Ben-Chetrit 3 , Roni Eichel 4 , Shai Dagan 1 , Lilach Yishai Aviram 1
Affiliation  

The human respiratory system is a highly complex matrix that exhales many volatile organic compounds (VOCs). Breath-exhaled VOCs are often “unknowns” and possess low concentrations, which make their analysis, peak digging and data processing challenging. We report a new methodology, applied in a proof-of-concept experiment, for the detection of VOCs in breath. For this purpose, we developed and compared four complementary analysis methods based on solid-phase microextraction and thermal desorption (TD) tubes with two GC–mass spectrometer (MS) methods. Using eight model compounds, we obtained an LOD range of 0.02–20 ng/ml. We found that in breath analysis, sampling the exhausted air from Tedlar bags is better when TD tubes are used, not only because of the preconcentration but also due to the stability of analytes in the TD tubes. Data processing (peak picking) was based on two data retrieval approaches with an in-house script written for comparison and differentiation between two populations: sick and healthy. We found it best to use “raw” AMDIS deconvolution data (.ELU) rather than its NIST (.FIN) identification data for comparison between samples. A successful demonstration of this method was conducted in a pilot study (n = 21) that took place in a closed hospital ward (Covid-19 ward) with the discovery of four potential markers. These preliminary findings, at the molecular level, demonstrate the capabilities of our method and can be applied in larger and more comprehensive experiments in the omics world.

中文翻译:

使用 GC-MS、AMDIS 和内置软件检测和鉴定呼吸中“未知”挥发性有机化合物的多方法比较研究

人体呼吸系统是一个高度复杂的基质,会呼出许多挥发性有机化合物 (VOC)。呼出的 VOC 通常是“未知的”并且浓度很低,这使得它们的分析、峰值挖掘和数据处理具有挑战性。我们报告了一种应用于概念验证实验的新方法,用于检测呼吸中的 VOC。为此,我们开发并比较了四种基于固相微萃取和热解吸 (TD) 管的互补分析方法与两种 GC-质谱仪 (MS) 方法。使用八种模型化合物,我们获得了 0.02–20 ng/ml 的 LOD 范围。我们发现,在呼气分析中,当使用 TD 管时,从 Tedlar 袋中抽取废气的采样效果更好,这不仅是因为预浓缩,还因为 TD 管中分析物的稳定性。数据处理(峰值挑选)基于两种数据检索方法,内部脚本编写用于比较和区分两个人群:生病和健康。我们发现最好使用“原始”AMDIS 解卷积数据 (.ELU) 而不是其 NIST (.FIN) 识别数据来比较样本。在一项试点研究中成功地演示了这种方法(n  = 21) 发生在封闭的医院病房(Covid-19 病房)中,发现了四个潜在的标志物。这些在分子水平上的初步发现证明了我们方法的能力,并且可以应用于组学世界中更大、更全面的实验。
更新日期:2021-09-15
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