Metabolic modeling of single Th17 cells reveals regulators of autoimmunity

Metabolism is a major regulator of immune cell function, but it remains difficult to study the metabolic status of individual cells. Here, we present Compass, an algorithm to characterize cellular metabolic states based on single-cell RNA sequencing and flux balance analysis. We applied Compass to associate metabolic states with T helper 17 (Th17) functional variability (pathogenic potential) and recovered a metabolic switch between glycolysis and fatty acid oxidation, akin to known Th17/regulatory T cell (Treg) differences, which we validated by metabolic assays. Compass also predicted that Th17 pathogenicity was associated with arginine and downstream polyamine metabolism. Indeed, polyamine-related enzyme expression was enhanced in pathogenic Th17 and suppressed in Treg cells. Chemical and genetic perturbation of polyamine metabolism inhibited Th17 cytokines, promoted Foxp3 expression, and remodeled the transcriptome and epigenome of Th17 cells toward a Treg-like state. In vivo perturbations of the polyamine pathway altered the phenotype of encephalitogenic T cells and attenuated tissue inflammation in CNS autoimmunity. [Display omitted] •Compass enables studying cellular metabolism based on single-cell transcriptomes•Compass links the pathogenic potential of Th17 cells with their metabolic programs•Th17 pathogenicity is associated with a switch between glycolysis and beta oxidation•The polyamine pathway is required for Th17 induction and restriction of a Treg profile Compass is an algorithm that derives information on cellular metabolic states from single-cell transcriptomic data. When applied to Th17 cells, it provides insights into how targeting the polyamine pathway can modulate encephalitis-associated T cells and attenuate autoimmune disease associated with the CNS.