IMSIS-Americas

@imsis-americas.bsky.social

International non-profit scientific organisation dedicated to foster exchanges in the field of mass spectrometry imaging in the Americas

Congratulations to this year's winner of the IMSIS MS Spatial Biology award at @us-hupo.org ! Dr. Min Ma presented her work in spatial proteomics using a Phos-MASP mapping method. Min is a current postdoc with a Research Assistant Professor in the lab of Jun Qu, SUNY-Buffalo.

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Happy to share this one, outlining our workflow developed through HuBMAP to look into proteoforms in human kidney. We found logical insight into FTU level proteoform differences in healthy samples. Moving forward, diseased tissues hold a lot of secrets! doi.org/10.1186/s120...

Spatial top-down proteomics for the functional characterization of human kidney - Clinical Proteomics

Background The Human Proteome Project has credibly detected nearly 93% of the roughly 20,000 proteins which are predicted by the human genome. However, the proteome is enigmatic, where alterations in ...

doi.org

🇨🇦 As part of our premier TMIC collective on metabolomics, please consider joining the Canadian Metabolomics Conference aka CanMetCon! Abstract deadline 15 MAR 2025 with the event being held 24-25 April in New Residence Hall, McGill University, Montreal, Quebec 🇨🇦

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Introducing the new Editor-in-Chief of @J_ASMS, Jenny Brodbelt! A longtime member and Past President of ASMS, and Associate Editor of JASMS since 2006, she will begin her term as JASMS Editor-in-Chief on Feb. 1. www.asms.org/publications...

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Single tissue untargeted multiomics? Yes, please! Our new paper is now online. @pnnl.bsky.social @bindesh1.bsky.social @imsis-americas.bsky.social pubs.acs.org/doi/10.1021/...

Untargeted Spatial Metabolomics and Spatial Proteomics on the Same Tissue Section

An increasing number of spatial multiomic workflows have recently been developed. Some of these approaches have leveraged initial mass spectrometry imaging (MSI)-based spatial metabolomics to inform the region of interest (ROI) selection for downstream spatial proteomics. However, these workflows have been limited by varied substrate requirements between modalities or have required analyzing serial sections (i.e., one section per modality). To mitigate these issues, we present a new multiomic workflow that uses desorption electrospray ionization (DESI)-MSI to identify representative spatial metabolite patterns on-tissue prior to spatial proteomic analyses on the same tissue section. This workflow is demonstrated here with a model mammalian tissue (coronal rat brain section) mounted on a poly(ethylene naphthalate)-membrane slide. Initial DESI-MSI resulted in 160 annotations (SwissLipids) within the METASPACE platform (≤20% false discovery rate). A segmentation map from the annotated ion images informed the downstream ROI selection for spatial proteomics characterization from the same sample. The unspecific substrate requirements and minimal sample disruption inherent to DESI-MSI allowed for an optimized, downstream spatial proteomics assay, resulting in 3888 ± 240 to 4717 ± 48 proteins being confidently directed per ROI (200 μm × 200 μm). Finally, we demonstrate the integration of multiomic information, where we found ceramide localization to be correlated with SMPD3 abundance (ceramide synthesis protein), and we also utilized protein abundance to resolve metabolite isomeric ambiguity. Overall, the integration of DESI-MSI into the multiomic workflow allows for complementary spatial- and molecular-level information to be achieved from optimized implementations of each MS assay inherent to the workflow itself.

pubs.acs.org