Fig. 2

Bulk metabolic measurements vs. single-cell metabolomic measurements. a Conventional workflow for studying cancer immunometabolism typically begins with formulating a hypothesis to identify cell populations of interest, through various low-throughput or low-resolution methods, including: (i) bulk steady-state metabolomics using mass spectrometry (MS). (ii) Extracellular flux analysis via Seahorse analyzers. (iii) Stable isotope tracing-based fluxomics. (iv) Bulk transcriptomics. These data can be used to construct genome-scale metabolic models (GEMs), thus inferring the state of the metabolic network. b A high-throughput single-cell metabolomic workflow involves preprocessing samples using automated systems such as fluorescence activated cell sorting (FACS), microfluidics, and microsampling. The preprocessed samples are then quenched, enriched (or not), and ionized for MS analysis. Various types of MS, such as time-of-flight (TOF), Orbitrap (OT), and Fourier transform ion cyclotron resonance (FTICR), can be utilized for single-cell metabolomics analysis. Subsequently, the abundance levels of metabolites are quantified, allowing for the clustering of cells into distinct subsets based on their metabolomic signatures. c The workflow for single-cell metabolic regulomics involves using fresh tissues, FFPEs, and frozen sections for single-cell or single-nucleus RNA-seq workflows such as microwell-based and droplet-based methods. Subsequently, the raw data can be analyzed using standard toolkits like Scanpy and Seurat, with metabolic signatures further examined through metabolic scoring tools like scMetabolism and network modeling techniques like scFBA. Additionally, fresh tissues can be utilized for proteome-level single-cell analysis, where key immune and metabolic markers are identified using labeled antibodies and then analyzed using spectral FCM or CyTOF. CE, capillary electrophoresis; CyTOF, cytometry by time-of-flight; FACS, fluorescence activated cell sorting; FCM, flow cytometry; FFPE, formalin-fixed paraffin-embedded section; FTICR, Fourier transform ion cyclotron resonance; GEM, genome-scale metabolic model; MS, mass spectrometry; OT, Orbitrap; RNA-seq, RNA sequencing; scFBA, single-cell Flux Balance Analysis; scRNA-seq, single-cell RNA sequencing; snRNA-seq, single-nucleus RNA sequencing; ssGSEA, single-sample gene set enrichment analysis; TOF, time-of-flight