Untargeted\nSpatial Metabolomics and Spatial Proteomics\non the Same Tissue Section

An increasing number of spatial multiomic workflows have\nrecently\nbeen developed. Some of these approaches have leveraged initial mass\nspectrometry imaging (MSI)-based spatial metabolomics to inform the\nregion of interest (ROI) selection for downstream spatial proteomics.\nHowever, these workflows have been limited by varied substrate requirements\nbetween modalities or have required analyzing serial sections (i.e.,\none section per modality). To mitigate these issues, we present a\nnew multiomic workflow that uses desorption electrospray ionization\n(DESI)-MSI to identify representative spatial metabolite patterns\non-tissue prior to spatial proteomic analyses on the same tissue section.\nThis workflow is demonstrated here with a model mammalian tissue (coronal\nrat brain section) mounted on a poly(ethylene naphthalate)-membrane\nslide. Initial DESI-MSI resulted in 160 annotations (SwissLipids)\nwithin the METASPACE platform (≤20% false discovery rate).\nA segmentation map from the annotated ion images informed the downstream\nROI selection for spatial proteomics characterization from the same\nsample. The unspecific substrate requirements and minimal sample disruption\ninherent to DESI-MSI allowed for an optimized, downstream spatial\nproteomics assay, resulting in 3888 ± 240 to 4717 ± 48 proteins\nbeing confidently directed per ROI (200 μm × 200 μm).\nFinally, we demonstrate the integration of multiomic information,\nwhere we found ceramide localization to be correlated with SMPD3 abundance\n(ceramide synthesis protein), and we also utilized protein abundance\nto resolve metabolite isomeric ambiguity. Overall, the integration\nof DESI-MSI into the multiomic workflow allows for complementary spatial-\nand molecular-level information to be achieved from optimized implementations\nof each MS assay inherent to the workflow itself.