Department of Chemistry, Faculty of Science, University of British Columbia, Vancouver Campus, 2036 Main Mall, Vancouver V6T 1Z1, BC, Canada.
Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Key Laboratory of Speed Capability Research, Jinan University, Guangzhou 510632, China.
J Am Soc Mass Spectrom. 2024 Aug 7;35(8):1818-1825. doi: 10.1021/jasms.4c00152. Epub 2024 Jul 25.
Nontargeted breath analysis in real time using high-resolution mass spectrometry (HRMS) is a promising approach for high coverage profiling of metabolites in human exhaled breath. However, the information-rich and unique non-Gaussian metabolic signal shapes of real-time HRMS-based data pose a significant challenge for efficient data processing. This work takes a typical real-time HRMS technique as an example, i.e. secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS), and presents BreathXplorer, an open-source Python package designed for the processing of real-time exhaled breath data comprising multiple exhalations. BreathXplorer is composed of four main modules. The first module applies either a topological algorithm or a Gaussian mixture model (GMM) to determine the start and end points of each exhalation. Next, density-based spatial clustering of applications with noise (DBSCAN) is employed to cluster / values belonging to the same metabolic feature, followed by applying an intensity relative standard deviation (RSD) filter to extract real breath metabolic features. BreathXplorer also offers functions of (1) feature alignment across the samples and (2) associating MS/MS spectra with their corresponding metabolic features for downstream compound annotation. Manual inspection of the metabolic features extracted from SESI-HRMS breath data suggests that BreathXplorer can achieve 100% accuracy in identifying the start and end points of each exhalation and acquire accurate quantitative measurements of each breath feature. In a proof-of-concept study on exercise breathomics using SESI-HRMS, BreathXplorer successfully reveals the significantly changed metabolites that are pertinent to exercise. BreathXplorer is publicly available on GitHub (https://github.com/HuanLab/breathXplorer). It provides a powerful and convenient-to-use tool for the researchers to process breathomics data obtained by directly analysis using HRMS.
使用高分辨率质谱（HRMS）实时进行非靶向呼吸分析是一种很有前途的方法，可以高覆盖率分析人体呼出呼吸中的代谢物。然而，基于实时 HRMS 的数据具有信息丰富且独特的非高斯代谢信号形状，这对高效的数据处理构成了重大挑战。本工作以一种典型的实时 HRMS 技术为例，即二次电喷雾电离高分辨率质谱（SESI-HRMS），并提出了 BreathXplorer，这是一个用于处理包含多次呼气的实时呼出呼吸数据的开源 Python 包。BreathXplorer 由四个主要模块组成。第一个模块使用拓扑算法或高斯混合模型（GMM）来确定每次呼气的起点和终点。接下来，应用基于密度的带噪声的空间聚类（DBSCAN）对属于同一代谢特征的 / 值进行聚类，然后应用强度相对标准偏差（RSD）滤波器来提取真实呼吸代谢特征。BreathXplorer 还提供了以下功能：（1）在样品之间进行特征对齐；（2）将 MS/MS 谱与相应的代谢特征相关联，以进行下游化合物注释。对 SESI-HRMS 呼吸数据中提取的代谢特征进行手动检查表明，BreathXplorer 可以实现 100%的准确性，准确识别每次呼气的起点和终点，并获得每个呼吸特征的准确定量测量。在使用 SESI-HRMS 进行运动呼吸组学的概念验证研究中，BreathXplorer 成功揭示了与运动相关的显著变化的代谢物。BreathXplorer 可在 GitHub（https://github.com/HuanLab/breathXplorer）上公开获取。它为研究人员提供了一个功能强大且易于使用的工具，用于处理通过直接使用 HRMS 分析获得的呼吸组学数据。
