An Investigation into the Metabolic Profiles of Human Tconvs and Tregs Identifies Divergent Metabolic Characteristics in Effector Memory Subsets

Session 4

Abstract

Hisashi Hashimoto, Fadi Issa, Joanna Hester

Introduction

Conventional T cells (Tconvs) are known to switch from oxidative phosphorylation (OXPHOS) to aerobic glycolysis upon activation.  In contrast, studies of mouse in vitro-induced regulatory T cells (Tregs) have revealed an overriding preference for OXPHOS.  However, the metabolic preferences of human Tregs remain unclear and warrant further investigation in order to help identify therapeutic opportunities.

Methods

Human CD4⁺ Tconvs and CD4⁺CD25⁺CD127^lo Tregs were flow sorted from healthy human donors and stimulated with anti-CD3/anti-CD28 beads or left unstimulated. In some experiments, Tconvs and Tregs were sorted into naive, central memory (CM) and effector memory (EM) subsets.  Aerobic glycolysis and oxygen consumption rates were investigated using Seahorse XF.  Cells were also assessed for their glucose consumption rate using the fluorescent glucose analogue 2-NBDG and Glut1 surface staining. Mitochondrial membrane potential and mass were assessed using mitotrackers and Mito-ID by flow cytometry.

Results

In contrast to mouse Tregs, human Tregs switch to glycolysis upon activation. While Tregs appeared to mirror the metabolic profile of Tconvs, there were differences with specific subsets. Activated EM Tregs displayed the lowest glucose consumption rate, whereas their counterpart subset in Tconvs had the highest glucose consumption rate among all subsets. Assessment of mitochondrial function revealed that all subsets of Tregs maintain a high number of polarized mitochondria, whereas memory subsets of Tconvs had a comparatively lower number of mitochondria, particularly in the EM population.

Conclusions

This study provides an in depth characterisation of the metabolic profile of human Tregs.  These data shed light on potential differences in EM metabolic activity between Tregs and Tconvs that could be exploited for therapeutic targeting.