MSdeCIpher: A Tool to Link Data from Complementary Ionization Techniques in High-Resolution GC-MS to Identify...

Area of Science:

• Analytical Chemistry
• Computational Chemistry

Background:

• Electron ionization (EI) and chemical ionization (CI) are complementary gas chromatography-mass spectrometry (GC-MS) ionization techniques.
• Accurate molecular ion assignment to fragment spectra traditionally requires manual curation and expert knowledge.
• Combining rich EI spectra with soft ionization data containing molecular ion candidates presents a challenge.

Purpose of the Study:

• To introduce MSdeCIpher, a novel software tool for integrating EI and CI datasets in GC-MS.
• To automate and improve the accuracy of molecular ion identification in complex mass spectrometry data.
• To facilitate compound identification in untargeted GC-MS analyses.

Main Methods:

• MSdeCIpher combines fragment-rich EI spectra with soft ionization spectra containing molecular ion candidates.
• Utilizes high-resolution GC-MS data, retention time matching, user-defined adduct/neutral loss criteria, and sum formula matching for identification.
• Evaluated performance on three distinct test datasets.

Main Results:

• MSdeCIpher consistently ranks the correct molecular ion among the top positions for each fragment spectrum (average ranks 1.5, 1, and 1.2).
• The software effectively reduces the number of candidate molecular ions for each spectrum.
• Demonstrates a unique capability to combine fragment-rich and soft ionization datasets.

Conclusions:

• MSdeCIpher significantly aids in the accurate assignment of molecular ions in GC-MS analysis.
• The tool enables the use of compound identification software that requires molecular masses.
• MSdeCIpher facilitates rapid, automated annotations in untargeted high-resolution GC-MS analyses.