Mapping Cell Metabolic States by Image-Enabled Gating Metabolomic Cytometry

Area of Science:

• Single-cell biology
• Metabolomics
• Systems biology

Background:

• Cell atlases reveal tissue heterogeneity, but generating single-cell metabolic atlases is challenging due to signal capture difficulties.
• Accurate single-cell signal capture is crucial for understanding complex biological samples.

Purpose of the Study:

• To develop a method for generating single-cell metabolic atlases with verified single-cell profiles from complex samples.
• To introduce CyMeta-ImaGating, a metabolomic cytometry technique with image-enabled gating.

Main Methods:

• CyMeta-ImaGating combines metabolomic cytometry with image-enabled gating.
• Verified single-cell profiles are obtained by matching metabolomic data with brightfield single-cell images.
• The method was tested on HeLa cell suspensions and spleen, liver, and cancer cells.

Main Results:

• Image-enabled gating significantly increased the proportion of single-cell profiles from 28% to 91-100% in HeLa cell suspensions.
• Generated spleen cell atlases distinguished immune cell types and revealed metabolic state transitions post-pathogen activation.
• Characterized doxorubicin's effects on liver and cancer cells, showing drug specificity and metabolic robustness.

Conclusions:

• CyMeta-ImaGating enables the generation of high-quality single-cell metabolic atlases from complex samples.
• Single-cell metabolic atlases are critical tools for resolving cellular metabolic states and dynamics.
• The developed method has implications for understanding immune responses and drug effects.