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.
Delafiori et al. (2025) studied this question.