Comparison of Ambient and Atmospheric Pressure Ion Sources for Cystic Fibrosis Exhaled Breath Condensate Ion Mobility-Mass Spectrometry Metabolomics

• Autores: Zang, Xiaoling; Pérez, José J.; Jones, Christina M.; Monge, Maria Eugenia; McCarty, Nael A.; Stecenko, Arlene A.; Fernández, Facundo M.
• Año de publicación: 2017
• Idioma: inglés
• Tipo de recurso: artículo
• Materia: Transmission Mode Direct Analysis in Real Time; Travelling Wave Ion Mobility Spectrometry-Mass Spectrometry; Exhaled Breath Condensate; Cystic Fibrosis; Breath Metabolomics
• Institución: Consejo Nacional de Investigaciones Científicas y Técnicas

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.
Fil: Zang, Xiaoling. Georgia Institute of Techology; Estados Unidos
Fil: Pérez, José J.. Georgia Institute of Techology; Estados Unidos
Fil: Jones, Christina M.. Georgia Institute of Techology; Estados Unidos. National Institute of Standards and Technology; Estados Unidos
Fil: Monge, Maria Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Bionanociencias "Elizabeth Jares Erijman"; Argentina. Georgia Institute of Techology; Estados Unidos
Fil: McCarty, Nael A.. Georgia State University; Estados Unidos. University of Emory; Estados Unidos
Fil: Stecenko, Arlene A.. University of Emory; Estados Unidos
Fil: Fernández, Facundo M.. Georgia Institute of Techology; Estados Unidos