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Spatial mapping of the brain metabolome lipidome and glycome

Author

Listed:
  • Harrison A. Clarke

    (University of Florida
    University of Florida)

  • Xin Ma

    (University of Florida
    University of Florida
    University of Florida)

  • Cameron J. Shedlock

    (University of Florida
    University of Florida)

  • Terrymar Medina

    (University of Florida
    University of Florida)

  • Tara R. Hawkinson

    (University of Florida
    University of Florida)

  • Lei Wu

    (University of Florida
    University of Florida)

  • Roberto A. Ribas

    (University of Florida
    University of Florida)

  • Shannon Keohane

    (University of Florida
    University of Florida)

  • Sakthivel Ravi

    (University of Florida
    University of Florida
    University of Florida)

  • Jennifer L. Bizon

    (University of Florida
    University of Florida
    University of Florida)

  • Sara N. Burke

    (University of Florida
    University of Florida
    University of Florida)

  • Jose Francisco Abisambra

    (University of Florida
    University of Florida
    University of Florida
    University of Florida)

  • Matthew E. Merritt

    (University of Florida)

  • Boone M. Prentice

    (University of Florida)

  • Craig W. Kooi

    (University of Florida)

  • Matthew S. Gentry

    (University of Florida
    University of Florida)

  • Li Chen

    (University of Florida)

  • Ramon C. Sun

    (University of Florida
    University of Florida
    University of Florida)

Abstract

Metabolites, lipids, and glycans are fundamental but interconnected classes of biomolecules that form the basis of the metabolic network. These molecules are dynamically channeled through multiple pathways that govern cellular physiology and pathology. Here, we present a framework for the simultaneous spatial analysis of the metabolome, lipidome, and glycome from a single tissue section using mass spectrometry imaging. This workflow integrates a computational platform, the Spatial Augmented Multiomics Interface (Sami), which enables multiomics integration, high-dimensional clustering, spatial anatomical mapping of matched molecular features, and metabolic pathway enrichment. To demonstrate the utility of this approach, we applied Sami to evaluate metabolic diversity across distinct brain regions and to compare wild-type and Ps19 Alzheimer’s disease (AD) mouse models. Our findings reveal region-specific metabolic demands in the normal brain and highlight metabolic dysregulation in the Ps19 model, providing insights into the biochemical alterations associated with neurodegeneration.

Suggested Citation

  • Harrison A. Clarke & Xin Ma & Cameron J. Shedlock & Terrymar Medina & Tara R. Hawkinson & Lei Wu & Roberto A. Ribas & Shannon Keohane & Sakthivel Ravi & Jennifer L. Bizon & Sara N. Burke & Jose Franci, 2025. "Spatial mapping of the brain metabolome lipidome and glycome," Nature Communications, Nature, vol. 16(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-59487-7
    DOI: 10.1038/s41467-025-59487-7
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    References listed on IDEAS

    as
    1. Lindsey R. Conroy & Harrison A. Clarke & Derek B. Allison & Samuel Santos Valenca & Qi Sun & Tara R. Hawkinson & Lyndsay E. A. Young & Juanita E. Ferreira & Autumn V. Hammonds & Jaclyn B. Dunne & Robe, 2023. "Spatial metabolomics reveals glycogen as an actionable target for pulmonary fibrosis," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    2. Hua Zhang & Yuan Liu & Lauren Fields & Xudong Shi & Penghsuan Huang & Haiyan Lu & Andrew J. Schneider & Xindi Tang & Luigi Puglielli & Nathan V. Welham & Lingjun Li, 2023. "Single-cell lipidomics enabled by dual-polarity ionization and ion mobility-mass spectrometry imaging," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    3. Bishoy Wadie & Lachlan Stuart & Christopher M. Rath & Bernhard Drotleff & Sergii Mamedov & Theodore Alexandrov, 2024. "METASPACE-ML: Context-specific metabolite annotation for imaging mass spectrometry using machine learning," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    4. Caterina Bartolacci & Cristina Andreani & Gonçalo Vale & Stefano Berto & Margherita Melegari & Anna Colleen Crouch & Dodge L. Baluya & George Kemble & Kurt Hodges & Jacqueline Starrett & Katerina Poli, 2022. "Targeting de novo lipogenesis and the Lands cycle induces ferroptosis in KRAS-mutant lung cancer," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    5. Caterina Bartolacci & Cristina Andreani & Gonçalo Vale & Stefano Berto & Margherita Melegari & Anna Colleen Crouch & Dodge L. Baluya & George Kemble & Kurt Hodges & Jacqueline Starrett & Katerina Poli, 2022. "Author Correction: Targeting de novo lipogenesis and the Lands cycle induces ferroptosis in KRAS-mutant lung cancer," Nature Communications, Nature, vol. 13(1), pages 1-1, December.
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