生物
代谢组学
吞吐量
计算生物学
小分子
生物信息学
遗传学
计算机科学
电信
无线
作者
Jeany Delafiori,Mohammed Shahraz,Andreas Eisenbarth,Volker Hilsenstein,Bernhard Drotleff,Alberto Bailoni,Bishoy Wadie,Måns Ekelöf,Alexander Mattausch,Theodore Alexandrov
出处
期刊:Cell
[Cell Press]
日期:2025-09-05
卷期号:188 (21): 6028-6043.e11
被引量:13
标识
DOI:10.1016/j.cell.2025.08.015
摘要
Single-cell metabolomics (SCM) promises to reveal metabolism in its complexity and heterogeneity, yet current methods struggle with detecting small-molecule metabolites, throughput, and reproducibility. Addressing these gaps, we developed HT SpaceM, a high-throughput SCM method combining cell preparation on custom glass slides, small-molecule matrix-assisted laser desorption ionization (MALDI) imaging mass spectrometry (MS), and batch processing. We propose a unified framework covering quality control, characterization, structural validation, and differential and functional analyses. Profiling HeLa and NIH3T3 cells, we detected 73 small-molecule metabolites validated by bulk liquid chromatography tandem MS (LC-MS/MS), achieving high reproducibility and single-cell resolution. Interrogating nine NCI-60 cancer cell lines and HeLa, we identified cell-type markers in subpopulations and metabolic hubs. Upon inhibiting glycolysis in HeLa cells, we observed emerging glucose-centered metabolic coordination and intra-condition heterogeneity. Overall, we demonstrate how HT SpaceM enables robust, large-scale SCM across over 140,000 cells from 132 samples and provide guidance on how to interpret metabolic insights beyond population averages.
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