Data preprocessing workflow for exhaled breath analysis by GC/MS using open sources

Rosa Alba Sola Martínez,Gema Lozano Terol,Julia Gallego-Jara,José María Pastor Hernández,Luis García-Marcos,Manuel Cánovas Díaz,Teresa De Diego Puente

doi:10.1038/s41598-020-79014-6

Abstract

The noninvasive diagnosis and monitoring of high prevalence diseases such as cardiovascular diseases, cancers and chronic respiratory diseases are currently priority objectives in the area of health. In this regard, the analysis of volatile organic compounds (VOCs) has been identified as a potential noninvasive tool for the diagnosis and surveillance of several diseases. Despite the advantages of this strategy, it is not yet a routine clinical tool. The lack of reproducible protocols for each step of the biomarker discovery phase is an obstacle of the current state. Specifically, this issue is present at the data preprocessing step. Thus, an open source workflow for preprocessing the data obtained by the analysis of exhaled breath samples using gas chromatography coupled with single quadrupole mass spectrometry (GC/MS) is presented in this paper. This workflow is based on the connection of two approaches to transform raw data into a useful matrix for statistical analysis. Moreover, this workflow includes matching compounds from breath samples with a spectral library. Three free packages (xcms, cliqueMS and eRah) written in the language R are used for this purpose. Furthermore, this paper presents a suitable protocol for exhaled breath sample collection from infants under 2 years of age for GC/MS.

Highlights

Over the last decades, the analysis of volatile organic compounds (VOCs) in exhaled breath has been proposed as a promising approach to searching for biomarkers for the diagnosis and monitoring of different diseases, and has been used to check for pollution exposure or smoking activities[1,2,3,4,5,6,7]
The first approach focuses mainly on finding the ion peaks detected in an electron ionization (EI)-mass spectrometry (MS) spectrum or so-called peak-picking, and the second approach aims to determine the compounds of breath samples by a spectral deconvolution process
Searching of the compounds in the breath samples was carried out by the current two main approaches mentioned in the introduction: ion peaks detection and compounds detection

Summary

Introduction

The analysis of volatile organic compounds (VOCs) in exhaled breath has been proposed as a promising approach to searching for biomarkers for the diagnosis and monitoring of different diseases, and has been used to check for pollution exposure or smoking activities[1,2,3,4,5,6,7]. One of the main advantages of this strategy is that it is based on a noninvasive p rocedure[1] This is especially important for populations such as children and elderly people and for diseases whose current standard diagnoses use invasive techniques such as biopsies and b ronchoscopies[8,9,10]. As a result, it is possible to benefit from the advantages of both strategies, including verification to reduce possible errors and avoid compounds duplications (detection of a single compound as two compounds) For this purpose, the functions of three packages based on the R programming language are implemented: xcms[23], cliqueMS28 and eRah[27]

Methods

Results

Discussion

Conclusion