Spatially resolved 3D metabolomic profiling in tissues.
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IF: 14.957
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Cited by: 22
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Abstract

Spatially resolved RNA and protein molecular analyses have revealed unexpected heterogeneity of cells. Metabolic analysis of individual cells complements these single-cell studies. Here, we present a three-dimensional spatially resolved metabolomic profiling framework (3D-SMF) to map out the spatial organization of metabolic fragments and protein signatures in immune cells of human tonsils. In this method, 3D metabolic profiles were acquired by time-of-flight secondary ion mass spectrometry to profile up to 189 compounds. Ion beams were used to measure sub-5-nanometer layers of tissue across 150 sections of a tonsil. To incorporate cell specificity, tonsil tissues were labeled by an isotope-tagged antibody library. To explore relations of metabolic and cellular features, we carried out data reduction, 3D spatial correlations and classifications, unsupervised K-means clustering, and network analyses. Immune cells exhibited spatially distinct lipidomic fragment distributions in lymphatic tissue. The 3D-SMF pipeline affects studying the immune cells in health and disease.

Keywords

SIMS
TOF-SIMS
Spatial Lipidomics
Spatial Metabolomics

Authors

Ganesh, Shambavi
Hu, Thomas
Woods, Eric
Allam, Mayar
Cai, Shuangyi
Henderson, Walter
Coskun, Ahmet F

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