Comparison of Ambient and Atmospheric Pressure Ion Sources for Cystic Fibrosis Exhaled Breath Condensate Ion Mobility-Mass Spectrometry Metabolomics
Cystic Fibrosis
Transmission Mode Direct Analysis in Real Time
Exhaled Breath Condensate
Breath Metabolomics
01 natural sciences
Mass Spectrometry
3. Good health
0104 chemical sciences
Atmospheric Pressure
Breath Tests
Exhalation
Travelling Wave Ion Mobility Spectrometry-Mass Spectrometry
Ion Mobility Spectrometry
Multivariate Analysis
https://purl.org/becyt/ford/1.4
Humans
Metabolomics
https://purl.org/becyt/ford/1
DOI:
10.1007/s13361-017-1660-9
Publication Date:
2017-03-31T16:08:46Z
AUTHORS (7)
ABSTRACT
Cystic fibrosis (CF) is an autosomal recessive disorder caused by mutations in the gene that encodes the cystic fibrosis transmembrane conductance regulator (CFTR) protein. The vast majority of the mortality is due to progressive lung disease. Targeted and untargeted CF breath metabolomics investigations via exhaled breath condensate (EBC) analyses have the potential to expose metabolic alterations associated with CF pathology and aid in assessing the effectiveness of CF therapies. Here, transmission-mode direct analysis in real time traveling wave ion mobility spectrometry time-of-flight mass spectrometry (TM-DART-TWIMS-TOF MS) was tested as a high-throughput alternative to conventional direct infusion (DI) electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI) methods, and a critical comparison of the three ionization methods was conducted. EBC was chosen as the noninvasive surrogate for airway sampling over expectorated sputum as EBC can be collected in all CF subjects regardless of age and lung disease severity. When using pooled EBC collected from a healthy control, ESI detected the most metabolites, APCI a log order less, and TM-DART the least. TM-DART-TWIMS-TOF MS was used to profile metabolites in EBC samples from five healthy controls and four CF patients, finding that a panel of three discriminant EBC metabolites, some of which had been previously detected by other methods, differentiated these two classes with excellent cross-validated accuracy. Graphical Abstract ᅟ.
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