IMFrag: A Tool to Recognize In-Source Fragmentation in Ion Mobility-Enabled Data-Independent Acquisition Workflows.

High-resolution mass spectrometry is a powerful tool for untargeted analysis. However, in-source fragmentation (ISF) could lead to the misidentification of compounds in untargeted metabolomics or exposomics studies. To prevent misidentification and to strengthen compound identification through MS/MS spectral library matching, we developed IMFrag, a Jupyter notebook-based tool that utilizes structural information gained from ion mobility-mass spectrometry (IM-MS) as an orthogonal technique to differentiate independent precursor ions from fragments formed via ISF. We first examined l-tryptophan, which is an essential amino acid that undergoes extensive fragmentation during electrospray ionization (ESI). IM-enabled data-independent acquisition (IM-DIA) analysis revealed distinct mobility signatures for identical fragment ions formed at different instrument sites, enabling discrimination between ISFs generated prior to the IM drift tube and fragments produced via postmobility collision-induced dissociation. Similar patterns were observed for a structurally diverse collection of small molecules. Additional structural information could also be inferred from the IM-DIA workflow, such as unique dimers, protonation sites, and distinct ion types that were not apparent from LC-MS alone. These insights were shown to be useful when applied to healthy human plasma samples, which served as a more complex and biologically relevant matrix that contained ambiguities, such as coeluting, isobaric candidate structures. Thus, IMFrag was developed as an accessible framework for interrogating MS1 and post-IM MS2 chemical features in untargeted data sets and can be integrated into untargeted analysis pipelines or used to support the development of ISF-derived MS/MS spectral libraries.