Project Overview

Multiple sclerosis (MS) is a chronic autoimmune disease in which immune cells attack the central nervous system, leading to inflammation and neurological damage. T helper 17 (Th17) cells are key drivers of this process, but the molecular mechanisms that regulate their function are not fully understood. This project focuses on SLC31A1, a protein responsible for transporting copper into cells, and investigates how it controls Th17 cell activity. Using a mouse model of MS, researchers examine whether blocking copper uptake by deleting SLC31A1 reduces disease severity. The study also examines how copper influx through SLC31A1 regulates mitochondrial metabolism — including the TCA cycle and OXPHOS — and drives the synthesis of metabolites that epigenetically control gene expression through DNA methylation, providing new mechanistic insight into how Th17 cell function is controlled.

Impact & Innovation

A new metabolic lever in MS.

 

Having established that copper transport via SLC31A1 is essential for Th17 cell function and EAE induction, this project charts a path to suppressing autoimmune brain inflammation at its source — even after disease onset.

  • Demonstrates that SLC31A1 controls Th17 function through mitochondrial metabolism (TCA cycle, OXPHOS) and epigenetic regulation via DNA methylation
  • Lays the foundation for monoclonal antibodies against SLC31A1, with applicability to other Th17-mediated autoimmune diseases
  • Advances the Consortium’s Shared Mechanisms Across Autoimmune Diseases pillar by linking immune cell metabolic regulation to neuroinflammation across autoimmune conditions
Research Approach

A framework designed for discovery

This project combines molecular immunology, metabolic analysis, and animal models to investigate how copper transport regulates autoimmune T cell function. By manipulating SLC31A1 expression and tracking downstream effects on immune cell behavior, the study aims to link cellular metabolism with disease outcomes in multiple sclerosis.

Genetic deletion of SLC31A1 in T cells, combined with experimental autoimmune encephalomyelitis (EAE) mouse models of MS, and molecular and metabolic profiling of Th17 cell function.

Mouse models of MS (EAE), genetically modified T cells lacking SLC31A1, and cellular assays measuring gene expression, metabolic activity (including mitochondrial function), and epigenetic regulation.


Identification of SLC31A1-dependent pathways that drive Th17-mediated inflammation, with the goal of validating copper transport as a therapeutic target. The work supports development of targeted interventions, including monoclonal antibodies, to inhibit SLC31A1 and treat MS and related autoimmune diseases.

Investigators & Institutions

Powering the science

Principal Investigator

Stefan Feske, MD, Colton Consortium Member

Jeffrey Bergstein Professor of Medicine (Department of Pathology); Vice Chair, Research; Director, Ion Channel and Immunity Program, Department of Pathology; Department of Medicine, NYU Grossman School of Medicine, NYU Langone Health

Research Outputs

From insight to impact

Publications

CLNS1A regulates genome stability and cell cycle progression to control CD4 T cell function and autoimmunity

Science Immunology
Wang, L; Noyer, L; Jishage, M; Wang, YH; Tao, AY; McDermott, M; Gando, I; Sidhu, I; Hu, K; Zhong, L; Sun, K; Drmic, D; Kaufmann, U; Feske, S June 2025
Adaptive ImmunityAnimal ModelsBiological & MechanisticCytokine SignalingExperimental Platforms & ModelsFunctional Genomics & CRISPRHuman GeneticsImmune ToleranceIn Vitro ModelsT Cell BiologyTherapeutic DevelopmentTranslational & ClinicalOtherNew York University

IFN-γ–producing TH1 cells and dysfunctional regulatory T cells contribute to the pathogenesis of Sjögren’s disease

Science Translational Medicine
Wang, YH; Li, W; McDermott, M; Son, GY; Maiti, G; Zhou, F; Tao, AY; Raphael, D; Moreira, AL; Shen, B; Vaeth, M; Nadorp, B; Chakravarti, S; Lacruz, RS; Feske, S December 2024
Adaptive ImmunityAnimal ModelsBiological & MechanisticCytokine SignalingExperimental Platforms & ModelsHuman CohortsImmune ToleranceSingle Cell TechnologiesT Cell BiologyTherapeutic DevelopmentTranslational & ClinicalSjögren’s DiseaseSystemic DiseasesNew York University

Machine learning approach to single cell transcriptomic analysis of Sjogren's disease reveals altered activation states of B and T lymphocytes

Journal of Autoimmunity
McDermott, M; Li, W; Wang, YH; Chen, AY; Lacruz, R; Nadorp, B; Feske, S June 2025
Adaptive ImmunityB Cell BiologyBioinformaticsBiological & MechanisticCytokine SignalingData-Driven & QuantitativeExperimental Platforms & ModelsHuman CohortsImmune ProfilingMachine Learning & AIMulti-omics IntegrationSingle Cell TechnologiesT Cell BiologySjögren’s DiseaseSystemic DiseasesNew York University