Differentiation of Cystic Fibrosis-Related Pathogens by Volatile Organic Compound Analysis with Secondary Electrospray Ionization Mass Spectrometry.
Jérôme KaeslinSrdjan MicicRonja WeberSimona MüllerNathan PerkinsChristoph BergerRenato ZenobiTobias BrudererAlexander MöllerPublished in: Metabolites (2021)
Identifying and differentiating bacteria based on their emitted volatile organic compounds (VOCs) opens vast opportunities for rapid diagnostics. Secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS) is an ideal technique for VOC-biomarker discovery because of its speed, sensitivity towards polar molecules and compound characterization possibilities. Here, an in vitro SESI-HRMS workflow to find biomarkers for cystic fibrosis (CF)-related pathogens P. aeruginosa, S. pneumoniae, S. aureus, H. influenzae, E. coli and S. maltophilia is described. From 180 headspace samples, the six pathogens are distinguishable in the first three principal components and predictive analysis with a support vector machine algorithm using leave-one-out cross-validation exhibited perfect accuracy scores for the differentiation between the groups. Additionally, 94 distinctive features were found by recursive feature elimination and further characterized by SESI-MS/MS, which yielded 33 putatively identified biomarkers. In conclusion, the six pathogens can be distinguished in vitro based on their VOC profiles as well as the herein reported putative biomarkers. In the future, these putative biomarkers might be helpful for pathogen detection in vivo based on breath samples from patients with CF.
Keyphrases
- cystic fibrosis
- high resolution mass spectrometry
- gas chromatography
- liquid chromatography
- mass spectrometry
- gram negative
- pseudomonas aeruginosa
- ultra high performance liquid chromatography
- antimicrobial resistance
- ms ms
- tandem mass spectrometry
- lung function
- machine learning
- small molecule
- loop mediated isothermal amplification
- gas chromatography mass spectrometry
- high resolution
- magnetic resonance imaging
- capillary electrophoresis
- electronic health record
- respiratory tract