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A metabolome atlas of the aging mouse brain

Author

Listed:
  • Jun Ding

    (University of California, Davis
    Wuhan University)

  • Jian Ji

    (Jiangnan University)

  • Zachary Rabow

    (University of California, Davis)

  • Tong Shen

    (University of California, Davis)

  • Jacob Folz

    (University of California, Davis)

  • Christopher R. Brydges

    (University of California, Davis)

  • Sili Fan

    (University of California, Davis)

  • Xinchen Lu

    (University of California, Davis)

  • Sajjan Mehta

    (University of California, Davis)

  • Megan R. Showalter

    (University of California, Davis)

  • Ying Zhang

    (University of California, Davis)

  • Renee Araiza

    (University of California, Davis)

  • Lynette R. Bower

    (University of California, Davis)

  • K. C. Kent Lloyd

    (University of California, Davis)

  • Oliver Fiehn

    (University of California, Davis)

Abstract

The mammalian brain relies on neurochemistry to fulfill its functions. Yet, the complexity of the brain metabolome and its changes during diseases or aging remain poorly understood. Here, we generate a metabolome atlas of the aging wildtype mouse brain from 10 anatomical regions spanning from adolescence to old age. We combine data from three assays and structurally annotate 1,547 metabolites. Almost all metabolites significantly differ between brain regions or age groups, but not by sex. A shift in sphingolipid patterns during aging related to myelin remodeling is accompanied by large changes in other metabolic pathways. Functionally related brain regions (brain stem, cerebrum and cerebellum) are also metabolically similar. In cerebrum, metabolic correlations markedly weaken between adolescence and adulthood, whereas at old age, cross-region correlation patterns reflect decreased brain segregation. We show that metabolic changes can be mapped to existing gene and protein brain atlases. The brain metabolome atlas is publicly available ( https://mouse.atlas.metabolomics.us/ ) and serves as a foundation dataset for future metabolomic studies.

Suggested Citation

  • Jun Ding & Jian Ji & Zachary Rabow & Tong Shen & Jacob Folz & Christopher R. Brydges & Sili Fan & Xinchen Lu & Sajjan Mehta & Megan R. Showalter & Ying Zhang & Renee Araiza & Lynette R. Bower & K. C. , 2021. "A metabolome atlas of the aging mouse brain," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-26310-y
    DOI: 10.1038/s41467-021-26310-y
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    References listed on IDEAS

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    Cited by:

    1. Zidan Wang & Donghui Zhang & Junhan Wu & Wenpeng Zhang & Yu Xia, 2024. "Illuminating the dark space of neutral glycosphingolipidome by selective enrichment and profiling at multi-structural levels," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    2. Shuling Xu & Zhijun Zhu & Daniel G. Delafield & Michael J. Rigby & Gaoyuan Lu & Megan Braun & Luigi Puglielli & Lingjun Li, 2024. "Spatially and temporally probing distinctive glycerophospholipid alterations in Alzheimer’s disease mouse brain via high-resolution ion mobility-enabled sn-position resolved lipidomics," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    3. Kirsty Brown & Carolyn A. Thomson & Soren Wacker & Marija Drikic & Ryan Groves & Vina Fan & Ian A. Lewis & Kathy D. McCoy, 2023. "Microbiota alters the metabolome in an age- and sex- dependent manner in mice," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    4. Maria Osetrova & Anna Tkachev & Waltraud Mair & Patricia Guijarro Larraz & Olga Efimova & Ilia Kurochkin & Elena Stekolshchikova & Nickolay Anikanov & Juat Chin Foo & Amaury Cazenave-Gassiot & Aleksan, 2024. "Lipidome atlas of the adult human brain," Nature Communications, Nature, vol. 15(1), pages 1-18, December.

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