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Metabolic control of type 1 regulatory T cell differentiation by AHR and HIF1-?.

ABSTRACT: Our understanding of the pathways that regulate lymphocyte metabolism, as well as the effects of metabolism and its products on the immune response, is still limited. We report that a metabolic program controlled by the transcription factors hypoxia inducible factor-1? (HIF1-?) and aryl hydrocarbon receptor (AHR) supports the differentiation of type 1 regulatory T cell (Tr1) cells. HIF1-? controls the early metabolic reprograming of Tr1 cells. At later time points, AHR promotes HIF1-? degradation and takes control of Tr1 cell metabolism. Extracellular ATP (eATP) and hypoxia, linked to inflammation, trigger AHR inactivation by HIF1-? and inhibit Tr1 cell differentiation. Conversely, CD39 promotes Tr1 cell differentiation by depleting eATP. CD39 also contributes to Tr1 suppressive activity by generating adenosine in cooperation with CD73 expressed by responder T cells and antigen-presenting cells. These results suggest that HIF1-? and AHR integrate immunological, metabolic and environmental signals to regulate the immune response.

SUBMITTER: Mascanfroni ID

PROVIDER: S-EPMC4476246 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

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Metabolic control of type 1 regulatory T cell differentiation by AHR and HIF1-α.

Mascanfroni Ivan D ID Takenaka Maisa C MC Yeste Ada A Patel Bonny B Wu Yan Y Kenison Jessica E JE Siddiqui Shafiuddin S Basso Alexandre S AS Otterbein Leo E LE Pardoll Drew M DM Pan Fan F Priel Avner A Clish Clary B CB Robson Simon C SC Quintana Francisco J FJ

Nature medicine 20150525 6

Our understanding of the pathways that regulate lymphocyte metabolism, as well as the effects of metabolism and its products on the immune response, is still limited. We report that a metabolic program controlled by the transcription factors hypoxia inducible factor-1α (HIF1-α) and aryl hydrocarbon receptor (AHR) supports the differentiation of type 1 regulatory T cell (Tr1) cells. HIF1-α controls the early metabolic reprograming of Tr1 cells. At later time points, AHR promotes HIF1-α degradatio ...[more]

PMID: 26005855

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Project description:BackgroundThe reconstruction of context-specific metabolic models from easily and reliably measurable features such as transcriptomics data will be increasingly important in research and medicine. Current reconstruction methods suffer from high computational effort and arbitrary threshold setting. Moreover, understanding the underlying epigenetic regulation might allow the identification of putative intervention points within metabolic networks. Genes under high regulatory load from multiple enhancers or super-enhancers are known key genes for disease and cell identity. However, their role in regulation of metabolism and their placement within the metabolic networks has not been studied.MethodsHere we present FASTCORMICS, a fast and robust workflow for the creation of high-quality metabolic models from transcriptomics data. FASTCORMICS is devoid of arbitrary parameter settings and due to its low computational demand allows cross-validation assays. Applying FASTCORMICS, we have generated models for 63 primary human cell types from microarray data, revealing significant differences in their metabolic networks.ResultsTo understand the cell type-specific regulation of the alternative metabolic pathways we built multiple models during differentiation of primary human monocytes to macrophages and performed ChIP-Seq experiments for histone H3 K27 acetylation (H3K27ac) to map the active enhancers in macrophages. Focusing on the metabolic genes under high regulatory load from multiple enhancers or super-enhancers, we found these genes to show the most cell type-restricted and abundant expression profiles within their respective pathways. Importantly, the high regulatory load genes are associated to reactions enriched for transport reactions and other pathway entry points, suggesting that they are critical regulatory control points for cell type-specific metabolism.ConclusionsBy integrating metabolic modelling and epigenomic analysis we have identified high regulatory load as a common feature of metabolic genes at pathway entry points such as transporters within the macrophage metabolic network. Analysis of these control points through further integration of metabolic and gene regulatory networks in various contexts could be beneficial in multiple fields from identification of disease intervention strategies to cellular reprogramming.

Dataset Information

Metabolic control of type 1 regulatory T cell differentiation by AHR and HIF1-?.

Publications

Metabolic control of type 1 regulatory T cell differentiation by AHR and HIF1-α.

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