High-mass-resolution imaging mass spectrometry promises to localize hundreds of metabolites in tissues, cell cultures, and agar plates with cellular resolution, but it is hampered by the lack of bioinformatics tools for automated metabolite identification. We report pySM, a framework for false discovery rate (FDR)-controlled metabolite annotation at the level of the molecular sum formula, for high-mass-resolution imaging mass spectrometry (https://github.com/alexandrovteam/pySM). We introduce a metabolite-signal match score and a target-decoy FDR estimate for spatial metabolomics.

The complex natural organic matter standard Suwannee river fulvic acid (SRFA) was analyzed by negative ion mode electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI FTICR MS) using on-resonance collision induced dissociation (CID) of single ultrahigh resolved mass peaks in the ICR cell. Molecular formula assignment of precursor masses resulted in exactly one molecular formula for each of the peaks. Analyses of the corresponding fragment spectra and comparison to different standard substances revealed specific neutral losses and fragmentation patterns which result in structures consisting of a high degree of carboxyl- and fewer hydroxyl groups. The comparison of fragmented mass peaks within different pseudohomologous series (CH(2)-series, and CH(4) vs O exchange) suggested structurally based differences between these series. CID FTICR MS allowed isolating single mass peaks in a very complex natural organic matter spectrum. Subsequently, fragmentation gave structural insights into this material. Our results suggest that the structural diversity in complex humic substances is not as high as expected.