HERMES

HERMES applies a molecular formula-oriented strategy to analyze mass spectrometry (MS) and tandem mass spectrometry (MS2) data for enhanced metabolite identification and structural annotation.

Key Features:

• Molecular formula-oriented analysis: Bypasses traditional peak detection by matching molecular formulas to MS signals to enable direct formula-centric identification.
• MS and MS2 structural annotation: Utilizes MS and MS2 spectra for structural annotation and compound identification.
• Improved sensitivity and selectivity: Increases sensitivity and selectivity of metabolite profiling, yielding higher identification rates compared to iterative data-dependent acquisition (DDA) methods.
• Enhanced biological specificity and scoring: Demonstrates increased biological specificity in MS2 scans and improves mass spectral similarity scoring across diverse sample types including environmental water, E. coli extracts, and human plasma.

Scientific Applications:

• Environmental metabolomics: Profiling metabolites in environmental water samples to improve compound identification and annotation.
• Microbial metabolomics: Characterizing metabolites from E. coli extracts with enhanced identification rates and structural annotation.
• Clinical metabolomics: Analyzing human plasma for improved metabolite identification and MS2-based structural annotation.
• Comprehensive metabolome analyses: Increasing overall metabolite identification and annotation coverage in complex biological and environmental samples.

Methodology:

Molecular formula-oriented analysis of MS and MS2 data that bypasses peak detection, employs MS2 structural annotation and mass spectral similarity scoring, and compares identification rates to iterative data-dependent acquisition (DDA).