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Updated: Jun 19, 2026

Sample Preparation for Single Cell Mass Spectrometry Metabolomics Studies: Combined Cell Washing, Quenching, Drying, and Storage
Published on: September 16, 2025
Coaxial Hybrid Ionization-Mass Cytometry for High-Throughput and High-Coverage Single-Cell Metabolomics
Yi Zhang1,2, Mingxuan Li2, Qian Li1,2
1Beijing Life Science Academy, Beijing 102209, China.
None:
Single-cell metabolomic analysis is pivotal for deciphering the dynamic and heterogeneous metabolic processes of individual cells. However, the limited metabolite coverage has constrained its broader applicability, primarily due to the low intracellular abundance and wide physicochemical diversity of metabolites. Here, we developed a coaxial hybrid ionization-mass cytometry platform (Hybrid-CytoMS) by integrating a dielectric barrier discharge ionization (DBDI) source with an electrospray ionization (ESI)-based organic mass cytometry system. This integration significantly enhances ionization efficiency through synergistic complementarity of the two ionization mechanisms. The platform features a coaxial architecture that minimizes ion transmission losses while maintaining high-throughput analysis at 30 cells per minute. Hybrid-CytoMS significantly enhances the signal intensities for polar and moderately polar compounds and enables the detection of nonpolar compounds that are invisible in the ESI-only mode. In single-cell metabolomic analysis using Hybrid-CytoMS, >2500 features, >500 single-cell characteristic peaks, and 369 annotated metabolites were detected in positive ion mode. Compared to the results of conventional ESI-based mass cytometry, increasing of >200 characteristic peaks and >100 additional annotated metabolites was achieved. The Hybrid-CytoMS was further applied in the study of benzo[a]pyrene (BaP) - a prototypical polycyclic aromatic hydrocarbon (PAH) - induced metabolic perturbations at single-cell resolution in HepG2 cells. The uptake and clearance curve of intracellular BaP as well as the dynamic metabolic trajectory across exposure time were successfully resolved, initially characterizing the coupling relationship between exogenous exposure and endogenous metabolic status.
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