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Spatially resolved 3D metabolomic profiling in tissues.

Shambavi Ganesh1,2, Thomas Hu1,2, Eric Woods3,4

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This study introduces a 3D spatially resolved metabolomic profiling framework (3D-SMF) to map metabolic fragments and protein signatures in human immune cells, revealing distinct lipidomic distributions in lymphatic tissue.

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Area of Science:

  • Single-cell biology
  • Metabolomics
  • Immunology

Background:

  • Single-cell RNA and protein analyses reveal cellular heterogeneity.
  • Metabolic analysis of individual cells complements these findings.

Purpose of the Study:

  • To present a novel 3D spatially resolved metabolomic profiling framework (3D-SMF).
  • To map spatial organization of metabolic fragments and protein signatures in human tonsil immune cells.

Main Methods:

  • Utilized time-of-flight secondary ion mass spectrometry for 3D metabolic profiling of up to 189 compounds.
  • Sectioned tonsil tissue into sub-5-nanometer layers across 150 sections.
  • Employed isotope-tagged antibody libraries for cell specificity and performed data reduction, 3D spatial correlations, clustering, and network analyses.

Main Results:

  • Demonstrated spatially distinct lipidomic fragment distributions within immune cells in lymphatic tissue.
  • Successfully mapped metabolic and protein signatures in a 3D spatial context.

Conclusions:

  • The 3D-SMF pipeline provides a powerful tool for studying immune cells in health and disease.
  • Highlights the importance of spatial organization in cellular metabolism and function.