Integrated Metabolomic and Transcriptomic Profiling Reveals Novel Activation-Induced Metabolic Networks in Human T cells

S. Hiemer, S. Jatav, J. Jussif, J. Alley, S. Lathwal, M. Piotrowski, J. Janiszewski, R. Kibbey, T. Alves, D. Dumlao, A. Jha, H. Bandukwala

Posted on: 21 June 2019

Preprint posted on 15 May 2019

Feeding immunity: TCR stimulation leads to metabolic rewiring in human T cells to promote glucose and amino acid metabolism

Selected by Jonny Coates

Categories: bioinformatics, cell biology, genomics, immunology

Context and background

The primary function of effector CD4⁺ T cells, also known as helper T cells (T_H), is to help activate other cells of the immune response. There are two main types of T_H cells, T_H1 and T_H2 cells. T_H1 cells activate the cellular immune response, usually against bacteria. The key cells that affect this response are CD8⁺ cytotoxic T cells, B cells and macrophages. T_H1 T cells can activate these other immune cells through the secretion of pro-inflammatory cytokines such as TNF-α and IFN-γ. Alternatively, T_H2 cells initiate a humoral immune response, characterised by antibody-producing B cells, eosinophils and mast cells. This is achieved by the release of interleukins such as IL-10 and IL-4 (CD4 T cells are reviewed in (1)).

In recent years, immunometabolism – that is metabolism within immune cells – has become a hot topic in immunology. Often, when immunologist talk about metabolism they are referring to glucose metabolism. In the context of T cells, upon activation T cells switch to a glycolytic metabolism (excellently reviewed in (2)). What makes this preprint by Hiemer et al especially interesting is the investigation into additional metabolites such as glutamine and the revelation of a much broader metabolic reprogramming than previously appreciated.

This preprint investigated the contribution of glucose and glutamine in promoting pro-inflammatory functions of effector T cells.

Key findings

TCR stimulation leads to rapid reprogramming of metabolic pathways and nucleotide synthesis

The authors profiled the kinetics of T cell transcriptional and metabolomics changes at 2, 6 and 24 hours following TCR-stimulation. Among the differentially expressed genes, the authors found 4 distinct patterns:

Decreased expression
Transiently increased expression
Stably increased expression
Decreased expression at early time points and then subsequently increased

The authors confirmed that TCR signalling is required for the activation of metabolic pathways by deleting Zap70 with CRISPR (Zap70 is a key kinase involved in early TCR signalling) which reduced metabolic gene expression. Surprisingly, this reduction occurred to a greater extent than CRISPR-mediated deletion of mTOR (mTOR is a major sensor of metabolism and can promote/repress expression of a large range of genes).

Metabolic pathways synergistically promote nucleotide synthesis and TCA anaplerosis

Different metabolites were shown to be used for anaplerotic filling of TCA intermediates, for example enzymes involved in glutamine utilisation were upregulated, such as those involved in glutamine to glutamate and glutamate to α-ketoglutamate conversion. This is important as it suggests that there may be some degree of compensation between the pathways.

The strength of TCR-stimulation differentially regulates metabolic reprogramming

The authors show that different strengths of TCR stimulation resulted in different metabolic reprogramming. Interestingly, although some different pathways were activated, the cells achieved the same endpoint.

Cyclosporine treatment reduces the expression of genes involved in metabolism

Cyclosporine inhibits the NFAT (nuclear factor of activated T cells) transcription factor and can thereby reduce cytokines such as IL-2 (3). The paper illustrates that cyclosporine treatment also reduces the expression levels of metabolic enzymes, both in pathways activated following TCR-stimulation and in the steady state. This suggests that cyclosporine may be involved in maintaining metabolic homeostasis, supporting other recent literature demonstrating similar results (4,5).

Importance of paper & why I chose it

This paper paints a highly complex picture of T cell metabolism. Whilst the paper aligns well with my research interests, I chose this paper due to the approach that the authors used. The authors made excellent use of complementary techniques to thoroughly investigate their specific question. I think this is a good example of the power of combining –omics and systems biology approaches.

Open questions

Perhaps the biggest open question relates to precisely how the altered metabolism is controlling T cell effector functions at the molecular level. For example, what is the contribution of the other metabolic pathways that were differentially regulated by TCR-stimulation? As it was not the purpose of the study, the authors do not directly manipulate individual metabolic pathways to assess the effect this may have on T cell effector functions. However, it’d be interesting to know what, if any, effects the authors believe this may have.
Although standard culture treatments are used to activate the CD4⁺ T cells, it would be useful to see flow cytometry analysis of these populations, especially following the various treatments or CRISPR knockdowns. For example, are the cells all effector cells or is there a population of memory cells present?
The authors show a reduction in IFN-γ, TNF-α and IL-2 but this evidence would perhaps be strengthened by assaying a wider range of T cell effector molecules in addition to demonstrating that negative regulators/suppressive cytokines (such as IL-10) are decreased.
The authors show that the strength of TCR-stimulation can differentially regulate metabolic reprogramming.
1. What do they think the impact of this finding is in vivo?
2. What impact does this finding have on in vitro Should we take greater care with how we interpret TCR-stimulation experiments? Did the authors look at different affinity peptides?
3. Do they think that this metabolic reprogramming is directly affecting the pro-inflammatory phenotype/response or is this a result of different signalling pathways?

References

Wan YY, Flavell RA. How Diverse—CD4 Effector T Cells and their Functions. J Mol Cell Biol. 2009 Oct;1(1):20–36.
O’Neill LAJ, Kishton RJ, Rathmell J. A guide to immunometabolism for immunologists. Nat Rev Immunol. 2016;16(9):553–65.
Chow C-W, Rincón M, Davis RJ. Requirement for Transcription Factor NFAT in Interleukin-2 Expression. Mol Cell Biol. 1999 Mar;19(3):2300–7.
Vaeth M, Feske S. NFAT control of immune function: New Frontiers for an Abiding Trooper. F1000Research [Internet]. 2018 Mar 2 [cited 2019 Jun 5];7. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5840618/
Klein-Hessling S, Muhammad K, Klein M, Pusch T, Rudolf R, Flöter J, et al. NFATc1 controls the cytotoxicity of CD8+ T cells. Nat Commun. 2017 11;8(1):511.

doi: https://doi.org/10.1242/prelights.11425

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