SpaceM reveals metabolic states of single cells

Abstract

A growing appreciation of the importance of cellular metabolism and revelations concerning the extent of cell-cell heterogeneity demand metabolic characterization of individual cells. We present SpaceM, an open-source method for in situ single-cell metabolomics that detects >100 metabolites from >1,000 individual cells per hour, together with a fluorescence-based readout and retention of morpho-spatial features. We validated SpaceM by predicting the cell types of cocultured human epithelial cells and mouse fibroblasts. We used SpaceM to show that stimulating human hepatocytes with fatty acids leads to the emergence of two coexisting subpopulations outlined by distinct cellular metabolic states. Inducing inflammation with the cytokine interleukin-17A perturbs the balance of these states in a process dependent on NF-κB signaling. The metabolic state markers were reproduced in a murine model of nonalcoholic steatohepatitis. We anticipate SpaceM to be broadly applicable for investigations of diverse cellular models and to democratize single-cell metabolomics.

Extended Data Fig. 1

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Figure 1. The SpaceM workflow and validation.

SpaceM integrates light microscopy and MALDI-imaging mass spectrometry to provide a metabolic profile obtained in situ for each cell. Segmented microscopy images help delineate cells and quantify their morphometric properties, spatial organization, and fluorescence. The cells are further subjected to MALDI-imaging mass spectrometry and metabolite annotation which reveals their metabolomes, followed by normalization. B: SpaceM provides a single-cell spatio-molecular matrix that integrates the metabolic profiles and other information obtained using microscopy. C: We validated SpaceM by predicting cell types of co-cultured human HeLa epithelial cells (H1B-mCherry, magenta) and mouse NIH3T3 fibroblasts (GFP, cyan). Representative image from 2 independent experiments. D: UMAP visualization of 846 co-cultured cells (HeLa, magenta; NIH3T3, cyan) using intensities of 88 metabolites. Unsupervised Leiden clustering applied to the metabolic profiles classified both cell types with an accuracy of 91.3% (see also Figure S7). E: Volcano plot (log2 of the fold change HeLa/NIH3T3 vs. -log10 of the two-tailed independent t-test p-value) showing differential properties of the 88 detected metabolites.

Figure 2. SpaceM identifies a steatotic subpopulation in lipid stimulated human hepatocytes.

A: Microscopy images of the human dHepaRG hepatocytes stimulated with oleic and palmitic fatty acids illustrating their heterogeneity in lipid droplets accumulation; red: LD540 staining for lipid droplets; blue: Hoechst staining for cell nuclei. Representative image from 4 independent experiments. B: UMAP visualization of single-cell metabolic profiles (740 metabolites) of 2,840 single cells revealed two co-existing subpopulations with statistically different lipid droplet levels (see also Figure S9). C: UMAP plots showing single-cell intensities of metabolites most associated with the lipid droplet accumulation: triglyceride TG(48:0), Spearman correlation r=0.38 (two-tailed test p-value=2.04e-100, ***), and an ion corresponding either to lysophosphatidylethanolamine LPE(21:1) or isomeric lysophosphatidylcholine LPC(18:1), negative Spearman r=−0.23 (two-tailed test p-value=1.09e-34, ***). D: Correlation values between LD540 and lipid intensities across 2,840 single-cells, grouped by the lipid class. Tri-(TG) and di-glycerides (DG) are the most correlated which is in line with their reported function to compose the hepatic LDs core. Tukey box plots for each lipid class: center line: median; box limits: upper and lower quartiles; whiskers: 1.5x interquartile range. E: Enriched lipid ontology terms (LO) for lipids with an LD540-correlation >0.1 and <−0.1. Enriched LO terms from lipids with a high correlation with LD540 show enrichment of the neutral lipid metabolism, TGs, DGs, and lipid droplet biology, which is expected and therefore serves as a supportive argument for the capacity of SpaceM to detect and quantify biologically relevant molecules.

Figure 3. SpaceM discovers and characterizes metabolic states of stimulated hepatocytes, cross-validated by preclinical NASH models.

A: Microscopy images of the human dHepaRG hepatocytes (CTRL), also stimulated with: fatty acids (+FA), further with IL-17A (+FA+IL17A), and further with an NF-kB inhibitor TPCA1 (+FA+IL17A+TPCA1); red: LD540 staining for lipid droplets; blue: Hoechst for nuclei; white: cells outlines. Representative images from 4 independent experiments per culture condition. B: PAGA visualization and unsupervised Leiden clustering of single-cell metabolic profiles (740 metabolites) reveal homeostatic, intermediate, and steatotic metabolic states of 29,738 hepatocytes. LD540 levels per metabolic states (homeostatic vs steatotic, two-tailed independent t-test p-value=0, ***; intermediate vs steatotic, two-tailed independent t-test p-value=1.4e-299, ***). Tukey box plots with center line: median; box limits: upper and lower quartiles; whiskers: 1.5x interquartile range. Black line shows a pseudotime trajectory from the homeostatic to steatotic states. C: Each condition separately, with cell values of LD540 in red, highlighting the gradient of the lipid droplet accumulation from the homeostatic to steatotic state. Pie charts show the proportions of the metabolic states in each condition. D: Normalized intensities of metabolic-state markers (t-statistic >60) for all cells along the pseudotime. E: Heatmap for the metabolic-state markers from C. Red star indicates validation by LC-MS/MS in the considered mouse model. For each state, the enriched lipid ontology (LO) terms are displayed. F: Semi-quantitative validation of selected metabolic markers of the homeostatic and steatotic states in an in vivo NASH mouse model with the normal diet (ND) vs Western diet (WD). For HepaRG, intensities of 2,500 randomly-selected cells are shown for each state. For the mouse model, average LC-MS intensity (n=3 replicates) per diet group is shown. Molecular names, left: putative MS1 annotations; right: structurally-validated by LC-MS/MS. ***denotes p-value<0.001.