Th1 and T17 activation with and without CB839 treatment
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE112244 | GEO | 2019/02/13
REPOSITORIES: GEO
Similar Datasets
Project description:Activated T cells differentiate into functional subsets which require distinct metabolic programs. Glutaminase (GLS) converts glutamine to glutamate to provide substrate for the tricarboxylic acid cycle and epigenetic reactions and here we identify a key role for GLS in T cell activation and specification. Though GLS-deficiency diminished T cell activation, proliferation and impaired differentiation of Th17 cells, loss of GLS also increased Tbet and Interferon-γ expression and CD4 Th1 and CD8 CTL effector cell differentiation. These changes were mediated by differentially altered gene expression and chromatin accessibility, leading to increased sensitivity of Th1 cells to IL-2 mediated mTORC1 signaling. In vivo, GLS-null T cells failed to drive a Th17 mediated Graft-vs-Host Disease model. Transient inhibition of GLS, however, increased Th1 and CTL T cell numbers in viral and chimeric antigen receptor models. Glutamine metabolism thus has distinct roles to promote Th17 but constrain Th1 and CTL effector cell differentiation.
2018-09-01 | E-MTAB-6648 | biostudies-arrayexpress
Project description:In this study, we examined differential gene expression in naïve human CD4+ T cells, as well as in effector Th1, Th17-negative and Th17-enriched CD4- T cell subsets. We observed a marked enrichment for increased gene expression in effector CD4+ T cells compared to naive CD4+ among immune-mediated disease oci genes. Within effector T cells, expression of disease-associated genes was increased in Th17-enriched compared to Th17-negative cells. We used microarray to examine the gene expresssion profile and level of human naïve, Th1 and effector T cell subsets. Human PBMCs were isolated and sorted to naïve, CD161-CCR6- and CD161+CCR6+ memory T cells. Naïve T cells were differentiatied to Th1 cells, and CD161-CCR6- and CD161+CCR6+ memory T cells were in vitro expanded for Th17-negative and Th17-enriched effector T cells. The gene profile was compared among naive, Th1, Th17-negative, and Th17-enriched cell subsets.
2012-05-12 | E-GEOD-32901 | biostudies-arrayexpress
Project description:In this study, we examined differential gene expression in naïve human CD4+ T cells, as well as in effector Th1, Th17-negative and Th17-enriched CD4- T cell subsets. We observed a marked enrichment for increased gene expression in effector CD4+ T cells compared to naive CD4+ among immune-mediated disease oci genes. Within effector T cells, expression of disease-associated genes was increased in Th17-enriched compared to Th17-negative cells. We used microarray to examine the gene expresssion profile and level of human naïve, Th1 and effector T cell subsets.
2012-05-13 | GSE32901 | GEO
Project description:Memory helper T (Th) cells are crucial for secondary immune responses against infectious microorganisms but also drive the pathogenesis of chronic inflammatory diseases. Therefore, it is of fundamental importance to understand how memory T cells are generated. However, the molecular mechanisms governing memory Th cell generation remain incompletely understood. Here, we identified CD30 as a molecule heterogeneously expressed on effector Th1 and Th17 cells, and CD30hi effector Th1 and Th17 cells preferentially generated memory Th1 and Th17 cells. We found that CD30 mediated signal induced Transglutaminase-2 (TG2) expression, and that the TG2 expression in effector Th cells is essential for memory Th cell generation. In fact, Cd30-deficiency resulted in the impaired generation of memory Th1 and Th17 cells, which can be rescued by overexpression of TG2. Furthermore, transglutaminase-2 (Tgm2)-deficient CD4 T cells failed to become memory Th cells. As a result, T cells from Tgm2-deficient mice displayed impaired antigen-specific antibody production and attenuated Th17-mediated allergic responses. Our data indicate that CD30-induced TG2 expression in effector Th cells is essential for the generation of memory Th1 and Th17 cells, and that CD30 can be a marker for precursors of memory Th1 and Th17 cells.
2020-05-28 | GSE151301 | GEO
Project description:Memory helper T (Th) cells are crucial for secondary immune responses against infectious microorganisms but also drive the pathogenesis of chronic inflammatory diseases. Therefore, it is of fundamental importance to understand how memory T cells are generated. However, the molecular mechanisms governing memory Th cell generation remain incompletely understood. Here, we identified CD30 as a molecule heterogeneously expressed on effector Th1 and Th17 cells, and CD30hi effector Th1 and Th17 cells preferentially generated memory Th1 and Th17 cells. We found that CD30 mediated signal induced Transglutaminase-2 (TG2) expression, and that the TG2 expression in effector Th cells is essential for memory Th cell generation. In fact, Cd30-deficiency resulted in the impaired generation of memory Th1 and Th17 cells, which can be rescued by overexpression of TG2. Furthermore, transglutaminase-2 (Tgm2)-deficient CD4 T cells failed to become memory Th cells. As a result, T cells from Tgm2-deficient mice displayed impaired antigen-specific antibody production and attenuated Th17-mediated allergic responses. Our data indicate that CD30-induced TG2 expression in effector Th cells is essential for the generation of memory Th1 and Th17 cells, and that CD30 can be a marker for precursors of memory Th1 and Th17 cells.
2020-06-04 | GSE151691 | GEO
Project description:Next to genetic alterations, it is being recognized that the cellular environment also acts as a major determinant in onset and progression of disease. In cases where different cell types contribute to the final disease outcome, this imposes environmental challenges as different cell types likely differ in their extracellular dependencies. A number of skin diseases, including psoriasis is characterized by a combination of keratinocyte hyperproliferation and immune cell activation. Activation of immune cells involves increased glucose consumption thereby intrinsicly limiting glucose availability for other cell types. Thus, these type of skin diseases require metabolic adaptations that enable coexistence between hyperproliferative keratinocytes and activated immune cells in a nutrient-limited environment. Hsa-microRNA-31-5p (miR-31) is highly expressed in keratinocytes within the psoriatic skin. Here we show that miR-31 expression in keratinocytes is induced by limited glucose availability and enables increased survival of keratinocytes under limiting glucose conditions, by increasing glutamine metabolism. In addition, miR-31 induced glutamine metabolism results in secretion of specific metabolites (aspartate and glutamate) but also secretion of immuno-modulatory factors. We show that this miR-31-induced secretory phenotype is sufficient to induce Th17 cell differentiation, a hallmark of psoriasis. Inhibition of glutaminase (GLS) using CB-839 impedes miR31-induced metabolic rewiring and secretion of immuno-modulatory factors. Concordantly, pharmacological targeting of GLS alleviated psoriasis pathology in a mouse model of psoriasis. Together our data illustrate an emerging concept of metabolic interaction across cell compartments that characterizes disease development, which can be employed to design effective treatment options for disease, as shown here for psoriasis.
2023-02-06 | PXD029030 | Pride
Project description:Through their functional diversification, CD4+ T cells play key roles in both driving and constraining immune-mediated pathology. Transcription factors are critical in the generation and maintenance of cellular diversity and negative regulators antagonistic to alternate fates often act in conjunction with positive regulators to stabilize lineage specification1. Polymorphisms within the locus encoding a transcription factor BACH2 are associated with diverse immune-mediated diseases including asthma2, multiple sclerosis3, Crohn¹s disease4-5, coeliac disease6, vitiligo7 and type 1 diabetes8. A role for Bach2 in maintaining immune homeostasis, however, has not been established. Here, we define Bach2 as a broad regulator of immune activation that stabilizes immunoregulatory capacity while repressing the differentiation programmes of multiple effector lineages in CD4+ T cells. Bach2 was required for efficient formation of regulatory (Treg) cells and consequently for suppression of lethal inflammation in a manner that was Treg cell dependent. Assessment of the genome-wide function of Bach2, however, revealed that it represses genes associated with effector cell differentiation. Consequently, its absence during Treg polarization resulted in inappropriate diversion to effector lineages. In addition, Bach2 constrained full effector differentiation within Th1, Th2 and Th17 cell lineages. These findings identify Bach2 as a key regulator of CD4+ T-cell differentiation that prevents inflammatory disease by controlling the balance between tolerance and immunity. The role of Bach2t to regulate immune homeostasis was investigated by mapping DNA binding profiles of Bach2 in iTreg condition. The function of Bach2 was also evaluated by comparing transcriptome in WT and Bach2-deficient iTreg cells and further comparison was done with transcriptome in naive, Th1, Th2, and Th17 conditions.
2013-06-27 | E-GEOD-45975 | biostudies-arrayexpress
Project description:Cytotoxic CD4 T lymphocytes (CD4-CTL) are important in anti-viral immunity. For example, we have previously shown that in mice, CD4-CTL are important to control ectromelia virus (ECTV) infection. How viral infections induce CD4-CTL responses remains incompletely understood. Here we demonstrate that not only ECTV but also vaccinia virus and Lymphocytic Choriomeningitis virus induce CD4-CTL, but that the response to ECTV is stronger. Using ECTV, we also demonstrate that in contrast to CD8-CTL, CD4-CTL differentiation requires constant virus replication and ceases once the virus is controlled. We also show that Major Histocompatibility Complex Class II molecules on CD11c+ cells are required for CD4-CTL differentiation and for mousepox resistance. Transcriptional analysis indicated that anti-viral CD4-CTL and non-cytolytic T Helper 1 (Th1) CD4 T cells have similar transcriptional profiles, suggesting that CD4-CTL are terminally differentiated classical Th1 cells. Interestingly, CD4-CTL and classical Th1 cells expressed similar mRNA levels of the transcription factors ThPOK and GATA-3, necessary for CD4 T cell linage commitment; and Runx3, required for CD8 T cell development and effector function. However, at the protein level, CD4-CTL had higher levels of the three transcription factors suggesting that further post-transcriptional regulation is required for CD4-CTL differentiation. Finally, using CRISPR-Cas9 deletion of Runx3 in CD4 T cells, we demonstrate that the development of CD4-CTL but not of classical Th1 CD4 T cells requires Runx3 following ECTV infection. These results further our understanding of the mechanisms of CD4-CTL differentiation during viral infection and the role of post-transcriptionally regulated Runx3 in this process.
2021-07-06 | GSE179289 | GEO
Project description:Carbo2013 - Cytokine driven CD4+ T Cell differentiation and phenotype plasticity
CD4+ T cells can differentiate into different phenotypes
depending on the cytokine milieu. Here a computational and mathematical model with sixty ordinary differential equations representing a CD4+ T cell differentiating into either Th1, Th2, Th17 or iTreg cells, has been constructed.
The model includes cytokines,
nuclear receptors and transcription factors that define fate
and function of CD4+ T cells. Computational simulations
illustrate how a proinflammatory Th17 cell can undergo
reprogramming into an anti-inflammatory iTreg phenotype
following PPARc activation.
This model is described in the article:
Systems Modeling of Molecular Mechanisms Controlling Cytokine-driven CD4+ T Cell Differentiation and Phenotype Plasticity.
Carbo A, Hontecillas R, Kronsteiner B, Viladomiu M, Pedragosa M, Lu P, Philipson CW, Hoops S, Marathe M, Eubank S, Bisset K, Wendelsdorf K, Jarrah A, Mei Y, Bassaganya-Riera J
PLoS Computational Biology [2013, 9(4):e1003027]
Abstract:
Differentiation of CD4+ T cells into effector or regulatory phenotypes is tightly controlled by the cytokine milieu, complex intracellular signaling networks and numerous transcriptional regulators. We combined experimental approaches and computational modeling to investigate the mechanisms controlling differentiation and plasticity of CD4+ T cells in the gut of mice. Our computational model encompasses the major intracellular pathways involved in CD4+ T cell differentiation into T helper 1 (Th1), Th2, Th17 and induced regulatory T cells (iTreg). Our modeling efforts predicted a critical role for peroxisome proliferator-activated receptor gamma (PPARγ) in modulating plasticity between Th17 and iTreg cells. PPARγ regulates differentiation, activation and cytokine production, thereby controlling the induction of effector and regulatory responses, and is a promising therapeutic target for dysregulated immune responses and inflammation. Our modeling efforts predict that following PPARγ activation, Th17 cells undergo phenotype switch and become iTreg cells. This prediction was validated by results of adoptive transfer studies showing an increase of colonic iTreg and a decrease of Th17 cells in the gut mucosa of mice with colitis following pharmacological activation of PPARγ. Deletion of PPARγ in CD4+ T cells impaired mucosal iTreg and enhanced colitogenic Th17 responses in mice with CD4+ T cell-induced colitis. Thus, for the first time we provide novel molecular evidence in vivo demonstrating that PPARγ in addition to regulating CD4+ T cell differentiation also plays a major role controlling Th17 and iTreg plasticity in the gut mucosa.
Author's comment:
CD4+ T cell computational model (Version 1.4)
Steady state corrected. There was a problem in the internalization of IL-17 in its mathematical function.
This model is hosted on BioModels Database
and identified
by: MODEL1304230001
.
To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource
for published quantitative kinetic models
.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to the public
domain worldwide. Please refer to CC0 Public Domain
Dedication
for more information.
2013-05-09 | BIOMD0000000451 | BioModels
Project description:Host defense against diverse pathogens involves the recruitment and differentiation of CD4+ T effector subsets including T helper 1 (Th1), Th2, Th17 and induced regulatory T (Treg) cells. Surface phenotype studies have revealed subset-specific surface markers for the identification and purification of human primary CD4+ T effector subsets. In the present study, we aimed to characterize the mRNA and large intergenic non-coding RNA (lincRNA) expression differences between human primary CD4+ T effector subsets and identify potential subset-specific genes. To achieve this goal, mRNA and lincRNA microarray profiling of flow cytometry-sorted human primary Th1, Th2, Th17 and Treg cells was performed. Principal component and pathway analyses revealed subset-specific gene expression patterns. A Th2-specific lincRNA, GATA3-AS1, also termed FLJ45983, was identified in primary immune cells and tissues, as well as in in vitro polarized CD4+ T effector subsets. Further analysis showed that GATA3-AS1 was a potential diagnostic marker in allergy, a Th2-associated disease. This first systematic genome-wide analysis of gene expression differences between primary CD4+ T effector subsets may help to identify novel regulatory protein-coding genes and lincRNAs regulating CD4+ T cell subset differentiation, as well as potential diagnostic markers. As an example, we identified a GATA3-associated Th2-specific marker lincRNA GATA3-AS1. Gene expression microarray analysis of flow-cytometry sorted human primary naïve CD4+ T cells, CD4+ T central memory cells, Th1, Th2, Th17 and Treg cells from buffy coat of four healthy controls Gene expression microarray analysis was performed using SurePrint G3 Human Gene Expression 8X60K microarray.
2013-06-01 | E-GEOD-43005 | biostudies-arrayexpress