BreathXplorer

BreathXplorer processes real-time exhaled breath data generated from high-resolution mass spectrometry for non-targeted metabolite profiling in human exhaled breath.

Key Features:

• Exhalation Detection: Applies either a topological algorithm or a Gaussian mixture model (GMM) to determine the start and end points of each exhalation.
• Metabolic Feature Clustering: Employs density-based spatial clustering of applications with noise (DBSCAN) to cluster m/z values belonging to the same metabolic feature.
• Feature Filtering: Applies an intensity relative standard deviation (RSD) filter to extract real breath metabolic features.
• Feature Alignment: Aligns metabolic features across samples.
• MS/MS Association: Associates MS/MS spectra with their corresponding metabolic features for downstream compound annotation.

Scientific Applications:

• Exercise Breathomics: Reveals significantly changed metabolites pertinent to exercise in proof-of-concept studies using secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS).
• Real-Time Metabolite Profiling: Enables high-coverage profiling of metabolites in human exhaled breath through processing of information-rich, non-Gaussian metabolic signal shapes from real-time HRMS-based data.
• Quantitative Breath Analysis: Provides accurate quantitative measurements of each breath feature with validated accuracy in identifying exhalation boundaries.

Methodology:

BreathXplorer comprises four main modules: (1) exhalation detection using either a topological algorithm or Gaussian mixture model (GMM), (2) metabolic feature clustering using DBSCAN, (3) feature filtering using an intensity relative standard deviation (RSD) filter, and (4) feature alignment and MS/MS spectra association.