Abstract
Molecular networking connects mass spectra of molecules based on the similarity of their fragmentation patterns. However, during ionization, molecules commonly form multiple ion species with different fragmentation behavior. As a result, the fragmentation spectra of these ion species often remain unconnected in tandem mass spectrometry-based molecular networks, leading to redundant and disconnected sub-networks of the same compound classes. To overcome this bottleneck, we develop Ion Identity Molecular Networking (IIMN) that integrates chromatographic peak shape correlation analysis into molecular networks to connect and collapse different ion species of the same molecule. The new feature relationships improve network connectivity for structurally related molecules, can be used to reveal unknown ion-ligand complexes, enhance annotation within molecular networks, and facilitate the expansion of spectral reference libraries. IIMN is integrated into various open source feature finding tools and the GNPS environment. Moreover, IIMN-based spectral libraries with a broad coverage of ion species are publicly available.
Highlights
Molecular networking connects mass spectra of molecules based on the similarity of their fragmentation patterns
We present Ion Identity Molecular Networking (IIMN) and showcase how to fuse MS2-based spectral networks with an additional networking layer based on MS1 feature shape correlation of identified ion species that originate from the same molecule
In conclusion, by establishing relationships between different ion species originating from the same compound and structurally similar compounds, IIMN facilitates molecular network interpretation and compound annotation
Summary
Molecular networking connects mass spectra of molecules based on the similarity of their fragmentation patterns. The fragmentation spectra of these ion species often remain unconnected in tandem mass spectrometry-based molecular networks, leading to redundant and disconnected sub-networks of the same compound classes To overcome this bottleneck, we develop Ion Identity Molecular Networking (IIMN) that integrates chromatographic peak shape correlation analysis into molecular networks to connect and collapse different ion species of the same molecule. As various commonly detected ion adducts exhibit different fragmentation behavior during collisional activation (e.g., in collision-induced dissociation (CID) mode) (Supplementary Fig. 1), MS2 spectral networking on its own does not necessarily connect all ion adducts produced by a single compound This often contributes to the unwanted separation of molecular families (subnetworks) and limits the propagation of library annotations through the networks. We present IIMN results for two datasets of natural products standards as well as 24 publicly available experimental datasets
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