Integration of mass cytometry and mass spectrometry imaging for spatially resolved single-cell metabolic profiling

被引:7
|
作者
Nunes, Joana B. [1 ]
Ijsselsteijn, Marieke E. [1 ]
Abdelaal, Tamim [2 ,3 ,4 ]
Ursem, Rick [1 ,5 ]
van der Ploeg, Manon [1 ]
Giera, Martin [5 ,6 ]
Everts, Bart [7 ]
Mahfouz, Ahmed [4 ,8 ]
Heijs, Bram [5 ,6 ]
de Miranda, Noel F. C. C. [1 ]
机构
[1] Leiden Univ, Med Ctr, Dept Pathol, Leiden, Netherlands
[2] Leiden Univ, Med Ctr, Dept Radiol, Leiden, Netherlands
[3] Cairo Univ, Fac Engn, Syst & Biomed Engn Dept, Giza, Egypt
[4] Delft Univ Technol, Pattern Recognit & Bioinformat, Delft, Netherlands
[5] Leiden Univ, Med Ctr, Ctr Prote & Metabol, Leiden, Netherlands
[6] Leiden Univ, Med Ctr, Novo Nordisk Fdn Ctr Stem Cell Med reNEW, Leiden, Netherlands
[7] Leiden Univ, Med Ctr, Ctr Infect Dis, Leiden, Netherlands
[8] Leiden Univ, Med Ctr, Dept Human Genet, Leiden, Netherlands
基金
欧盟地平线“2020”; 欧洲研究理事会;
关键词
D O I
10.1038/s41592-024-02392-6
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
The integration of spatial omics technologies can provide important insights into the biology of tissues. Here we combined mass spectrometry imaging-based metabolomics and imaging mass cytometry-based immunophenotyping on a single tissue section to reveal metabolic heterogeneity at single-cell resolution within tissues and its association with specific cell populations such as cancer cells or immune cells. This approach has the potential to greatly increase our understanding of tissue-level interplay between metabolic processes and their cellular components. The authors present a workflow integrating imaging mass cytometry and imaging mass spectrometry to deconvolute metabolic heterogeneity at the single-cell level.
引用
收藏
页码:1796 / 1800
页数:5
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