Spatially resolved 3D metabolomic profiling in tissues

被引:34
作者
Ganesh, Shambavi [1 ,2 ,3 ]
Hu, Thomas [1 ,2 ,3 ]
Woods, Eric [4 ,5 ,6 ]
Allam, Mayar [1 ,2 ]
Cai, Shuangyi [1 ,2 ]
Henderson, Walter [4 ,5 ]
Coskun, Ahmet F. [1 ,2 ]
机构
[1] Georgia Inst Technol, Wallace H Coulter Dept Biomed Engn, Atlanta, GA 30332 USA
[2] Emory Univ, Atlanta, GA 30332 USA
[3] Georgia Inst Technol, Elect & Comp Engn Dept, Atlanta, GA 30332 USA
[4] Georgia Inst Technol, Sch Biol Sci, Atlanta, GA 30332 USA
[5] Georgia Inst Technol, Inst Elect & Nanotechnol, Atlanta, GA 30332 USA
[6] Max Planck Str 1, D-40237 Dusseldorf, Nordrhein Westf, Germany
关键词
IMAGING MASS-SPECTROMETRY; TOF-SIMS; CELLS; METABOLITES; RESOLUTION; SURFACE; IMMUNE; 2D;
D O I
10.1126/sciadv.abd0957
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
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页数:16
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