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Metabolites


Title:Differentiation of Cystic Fibrosis-Related Pathogens by Volatile Organic Compound Analysis with Secondary Electrospray Ionization Mass Spectrometry
Author(s):Kaeslin J; Micic S; Weber R; Muller S; Perkins N; Berger C; Zenobi R; Bruderer T; Moeller A;
Address:"Department of Chemistry and Applied Biosciences, Swiss Federal Institute of Technology, Vladimir-Prelog Weg 1-5/10, 8093 Zurich, Switzerland. Division of Respiratory Medicine and Childhood Research Center, University Children's Hospital Zurich, Steinwiesstrasse 75, 8032 Zurich, Switzerland. Clinical Chemistry and Biochemistry, University Children's Hospital Zurich, Steinwiesstrasse 75, 8032 Zurich, Switzerland. Division of Infectious Diseases and Hospital Epidemiology, University Children's Hospital Zurich, Steinwiesstrasse 75, 8032 Zurich, Switzerland. Department of Chemistry and Industrial Chemistry, University of Pisa, Via Giuseppe Moruzzi, 13, 56124 Pisa, Italy"
Journal Title:Metabolites
Year:2021
Volume:20211111
Issue:11
Page Number: -
DOI: 10.3390/metabo11110773
ISSN/ISBN:2218-1989 (Print) 2218-1989 (Electronic) 2218-1989 (Linking)
Abstract:"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"
Keywords:cystic fibrosis high-resolution mass spectrometry pathogen profiles putative compound identification recursive feature elimination secondary electrospray ionization volatile organic compounds;
Notes:"PubMed-not-MEDLINEKaeslin, Jerome Micic, Srdjan Weber, Ronja Muller, Simona Perkins, Nathan Berger, Christoph Zenobi, Renato Bruderer, Tobias Moeller, Alexander eng Switzerland 2021/11/26 Metabolites. 2021 Nov 11; 11(11):773. doi: 10.3390/metabo11110773"

 
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