Application of spectral flow cytometry for comprehensive detection of immune metabolism in patient-derived...

Single-cell metabolic characteristics are powerful indicators of cellular physiological and pathological states. Flow cytometry enables high-throughput single-cell metabolic profiling and immunophenotyping; however, spectral overlap impedes simultaneous detection of multi-parametric features. This limitation imposes larger sample requirements and increased variabilities due to metabolic dynamics-constraints acutely magnified in studies utilizing clinical microsamples. To overcome these shortcomings, we developed a spectral flow cytometry platform for immunometabolic features, using 13 dual-probe combinations and 11 fluorophore probes. Requiring only 100 μL of whole blood per assay, this platform enables concurrent detection of 4 metabolic biomarkers and 16 immune markers. Application to patients with heart failure revealed heterogeneous metabolic landscapes across 20 immune subpopulations, showing reduced frequencies of naive T cells and NK-like T cells, with a metabolic shift from fatty acid dependence to glucose avidity. Our framework captures metabolic interactions previously inaccessible by sequential detection and will help to enable precision immunometabolism research.