Metabolic modeling of single Th17 cells reveals regulators of autoimmunity

Allon Wagner, Chao Wang, Johannes Fessler, David DeTomaso, Julian Avila-Pacheco, James Kaminski, Sarah Zaghouani, Elena Christian, Pratiksha Thakore, Brandon Schellhaass, Elliot Akama-Garren, Kerry Pierce, Vasundhara Singh, Noga Ron-harel, Vivian Paraskevi Douglas, Lloyd Bod, Alexandra Schnell, Daniel Puleston, Raymond A. Sobel, Marcia HaigisErika L. Pearce, Manoocher Soleimani, Clary Clish, Aviv Regev, Vijay K. Kuchroo, Nir Yosef

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)4168-+
Issue number16
StatePublished - 1 Aug 2021


  • DFMO
  • T helper 17 cell
  • experimental autoimmune encephalomyelitis
  • immunometabolism
  • in silico metabolic modeling
  • multiple sclerosis
  • polyamines
  • putrescine
  • single cell transcriptomics
  • spermidine

All Science Journal Classification (ASJC) codes

  • Biochemistry, Genetics and Molecular Biology(all)


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