A mosaic of cross-phylum chemical interactions occurs between all metazoans and their microbiomes. A number of molecular families known to be produced by the microbiome have a profound impact on the balance between health and disease 1-9. Considering the diversity of the human microbiome, numbering over 40,000 operational taxonomic units 10 , the impact of the microbiome on the chemistry of an entire animal remains underexplored. In this study, mass spectrometry informatics and data visualization approaches 11-13 were used to provide an assessment of the impacts of the microbiome on the chemistry of an entire mammal by comparing metabolomics data from germ-free (GF) and specific pathogen Reprints and/or permissions can be provided by R. Quinn or P.C. Dorrestein.

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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.