Single-cell metabolic dynamics of early activated CD8 T cells during the primary immune response to infection

Abstract

Mass cytometry permits high-dimensional analysis of diverse aspects of cellular behavior. Here, we adapted this platform to simultaneously profile metabolism, signaling, cell cycle, and effector function with single-cell resolution. Using this approach, we measured enzymes characterizing glycolysis, the TCA cycle, fatty acid oxidation, oxidative phosphorylation, and nutrient transport.In conjunction, we measured downstream targets of TCR signaling regulating translation, proliferation and cytotoxicity as well as surface markers and transcription factors delineating CD8 T cell differentiation. High-dimensional single-cell metabolic analysis by mass cytometry permits identification of unique metabolic and differentiation states of extremely rare cell populations, such as antigen-specific T cells. We interrogated antigen-specific CD8 T cell activation in vitro as well as the trajectory of CD8 T cells responding to Listeria monocytogenes infection, a well-characterized model for studies of T cell differentiation. This integrated, highdimensional approach revealed a novel, activated, and highly metabolically active transitional T cell subset emerging at four days post-infection. These cells simultaneously exhibit glycolytic and oxidative functional programs, which we propose represents a key metabolic inflection point in CD8+ T cell differentiation. This approach should be useful for mechanistic investigations of metabolic regulation of immune responses in vivo.Recombinant human IL-2 (IL-2; TECIN (Teceleukin)) was provided by the National Cancer Institute.

Recent Advances and Future Prospects in Immune Checkpoint (ICI)-Based Combination Therapy for Advanced HCC

“…Besides transcriptional characterization, cellular metabolomics at the single-cell level defined the rare early activated CD8+T-cells in a primary immune response [ 96 ]. A mass cytometry approach revealed that early activated T-cells exhibited simultaneous peaks in both glycolysis and OXPHOS, which are distinct from naive and committed T-cells.…”

Immunometabolism in the Single-Cell Era

“…In this Perspective, we explore how current and emerging state-of-the-art technologies contribute to our understanding of metabolic regulation of immunity and discuss the transition from bulk to single-cell immunometabolic profiling (Ahl et al, 2020;Levine et al, 2020;Miller et al, 2017;Xiao et al, 2019).…”

A graph neural network model to estimate cell-wise metabolic flux using single cell RNA-seq data

“…Single cell RNA-Seq (scRNA-seq) data has been widely utilized to characterize cell type specific transcriptional states in a complex tissue. Large amount of scRNA-seq data carry the potential to deliver information on a cell’s functioning state and its underlying phenotypic switches (Vasdekis and Stephanopoulos 2015; Damiani et al 2019a; Evers et al 2019a; Honkoop et al 2019; Saurty-Seerunghen et al 2019; Xiao et al 2019a; Levine et al 2020; Rohlenova et al 2020; Xiao et al 2020; Zhang et al 2020). Realizing the strong connections between transcriptomic and metabolomic profiles (Hirayama et al 2009; Lee et al 2012; Mehrmohamadi et al 2014; Damiani et al 2019b; Xiao et al 2019b; Wagner et al 2020), scRNA-Seq has found its application in portraying metabolic variations.…”

“…Realizing the strong connections between transcriptomic and metabolomic profiles (Hirayama et al 2009; Lee et al 2012; Mehrmohamadi et al 2014; Damiani et al 2019b; Xiao et al 2019b; Wagner et al 2020), scRNA-Seq has found its application in portraying metabolic variations. Most of the existing studies examined single cell metabolic changes relying on differential expression and enrichment analysis of key metabolic enzymes and pathways (Vasdekis and Stephanopoulos 2015; Evers et al 2019a; Honkoop et al 2019; Saurty-Seerunghen et al 2019; Xiao et al 2019a; Levine et al 2020; Rohlenova et al 2020; Xiao et al 2020), without considering individual metabolite nodes in a metabolic pathway, or the mass balance constraints of metabolic network. Studies coupling single cell transcriptomics data and the Flux Balance Analysis (FBA) at steady-state framework have only recently emerged (Damiani et al 2019a; Zhang et al 2020).…”