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Towards Mapping Mouse Metabolic Tissue Atlas by Mid-Infrared Imaging with Heavy Water Labeling.

Xinwen LiuLixue ShiLingyan ShiMian WeiZhilun ZhaoWei Min
Published in: Advanced science (Weinheim, Baden-Wurttemberg, Germany) (2022)
Understanding metabolism is of great significance to decipher various physiological and pathogenic processes. While great progress has been made to profile gene expression, how to capture organ-, tissue-, and cell-type-specific metabolic profile (i.e., metabolic tissue atlas) in complex mammalian systems is lagging behind, largely owing to the lack of metabolic imaging tools with high resolution and high throughput. Here, the authors applied mid-infrared imaging coupled with heavy water (D 2 O) metabolic labeling to a scope of mouse organs and tissues. The premise is that, as D 2 O participates in the biosynthesis of various macromolecules, the resulting broad C-D vibrational spectrum should interrogate a wide range of metabolic pathways. Applying multivariate analysis to the C-D spectrum, the authors successfully identified both inter-organ and intra-tissue metabolic signatures of mice. A large-scale metabolic atlas map between different organs from the same mice is thus generated. Moreover, leveraging the power of unsupervised clustering methods, spatially-resolved metabolic signatures of brain tissues are discovered, revealing tissue and cell-type specific metabolic profile in situ. As a demonstration of this technique, the authors captured metabolic changes during brain development and characterized intratumoral metabolic heterogeneity of glioblastoma. Altogether, the integrated platform paves a way to map the metabolic tissue atlas for complex mammalian systems.
Keyphrases
  • high resolution
  • gene expression
  • high throughput
  • single cell
  • type diabetes
  • multiple sclerosis
  • dna methylation
  • mass spectrometry
  • machine learning
  • white matter
  • photodynamic therapy
  • resting state