T cell differentiation
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ABSTRACT:
SUBMITTER: Tomas Helikar
PROVIDER: 2901 | Cell Collective |
REPOSITORIES: Cell Collective
Publications
A method for the generation of standardized qualitative dynamical systems of regulatory networks.
Mendoza Luis L Xenarios Ioannis I
Theoretical biology & medical modelling 20060316
<h4>Background</h4>Modeling of molecular networks is necessary to understand their dynamical properties. While a wealth of information on molecular connectivity is available, there are still relatively few data regarding the precise stoichiometry and kinetics of the biochemical reactions underlying most molecular networks. This imbalance has limited the development of dynamical models of biological networks to a small number of well-characterized systems. To overcome this problem, we wanted to d ...[more]
Similar Datasets
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.
2024-09-02 | BIOMD0000000451 | BioModels
Project description:Despite their enormous importance, the molecular circuits that control the differentiation of Th17 cells remain largely unknown. Recent studies have reconstructed regulatory networks in mammalian cells, but have focused on short-term responses and relied on perturbation approaches that cannot be applied to primary T cells. Here, we develop a systematic strategy – combining transcriptional profiling at high temporal resolution, novel computational algorithms, and innovative nanowire-based tools for performing gene perturbations in primary T cells – to derive and experimentally validate a temporal model of the dynamic regulatory network that controls Th17 differentiation. The network is arranged into two self-reinforcing and mutually antagonistic modules that either suppress or promote Th17 differentiation. The two modules contain 12 novel regulators with no previous implication in Th17 differentiation, which may be essential to maintain the appropriate balance of Th17 and other CD4+ T cell subsets. Overall, our study identifies and validates 39 regulatory factors that are embedded within a comprehensive temporal network and identifies novel drug targets and organizational principles for the differentiation of Th17 cells. Time course microarray data for Th17 differentiation, including Th0 control
2013-03-07 | E-GEOD-43955 | biostudies-arrayexpress
Project description:Despite their enormous importance, the molecular circuits that control the differentiation of Th17 cells remain largely unknown. Recent studies have reconstructed regulatory networks in mammalian cells, but have focused on short-term responses and relied on perturbation approaches that cannot be applied to primary T cells. Here, we develop a systematic strategy – combining transcriptional profiling at high temporal resolution, novel computational algorithms, and innovative nanowire-based tools for performing gene perturbations in primary T cells – to derive and experimentally validate a temporal model of the dynamic regulatory network that controls Th17 differentiation. The network is arranged into two self-reinforcing and mutually antagonistic modules that either suppress or promote Th17 differentiation. The two modules contain 12 novel regulators with no previous implication in Th17 differentiation, which may be essential to maintain the appropriate balance of Th17 and other CD4+ T cell subsets. Overall, our study identifies and validates 39 regulatory factors that are embedded within a comprehensive temporal network and identifies novel drug targets and organizational principles for the differentiation of Th17 cells. DNA binding of TSC22D3 in Th17 cells compared to WCE
2013-03-07 | E-GEOD-43949 | biostudies-arrayexpress
Project description:The role of aromatic gut-derived bacterial metabolites (GDBMs) in shaping immune cell metabolism and function remains poorly explored. Using ex vivo metabolomic profiling of paired plasma and CD4+ T-cells from people living with HIV-1 (PLWH), we identified a network of aromatic GDBMs whose cell-associated abundance, rather than systemic levels, was linked to broad alterations in CD4+ T-cell metabolic and functional states. Among these metabolites, p-cresol sulfate (PCS) emerged as a mechanistic prototype investigated in depth. Ex vivo flow cytometry and single-cell RNA sequencing of CD4+ T-cells stratified by cell-associated PCS levels revealed dose-dependent enrichment of transcriptional programs associated with impaired differentiation capacity, regulatory-like identity, and cellular senescence. Consistently, in vitro transcriptomic and proteomic analyses of PCS-exposed CD4+ T cells demonstrated induction of cell-cycle arrest, mitochondrial dysfunction, and senescence-associated programs, including upregulation of p16 and p21. Integration of these immunometabolic features with measurements of HIV-1 reservoir size in PLWH revealed that CD4+ T-cell states defined by cell-associated GDBMs track with intact proviral DNA levels in vivo. Together, these findings define a microbiome-derived axis that reshapes CD4+ T-cell metabolism and fate and promotes immune aging-associated states in PLWH. Our data suggest that cell-associated GDBMs may foster immunometabolic CD4+ T-cell states previously linked to long-term HIV-1 reservoir persistence in vivo.
2026-06-25 | PXD077610 | Pride
Project description:Despite their enormous importance, the molecular circuits that control the differentiation of Th17 cells remain largely unknown. Recent studies have reconstructed regulatory networks in mammalian cells, but have focused on short-term responses and relied on perturbation approaches that cannot be applied to primary T cells. Here, we develop a systematic strategy – combining transcriptional profiling at high temporal resolution, novel computational algorithms, and innovative nanowire-based tools for performing gene perturbations in primary T cells – to derive and experimentally validate a temporal model of the dynamic regulatory network that controls Th17 differentiation. The network is arranged into two self-reinforcing and mutually antagonistic modules that either suppress or promote Th17 differentiation. The two modules contain 12 novel regulators with no previous implication in Th17 differentiation, which may be essential to maintain the appropriate balance of Th17 and other CD4+ T cell subsets. Overall, our study identifies and validates 39 regulatory factors that are embedded within a comprehensive temporal network and identifies novel drug targets and organizational principles for the differentiation of Th17 cells. RNA-seq of knockdown of 12 genes in Th17 cell differentiation
2013-03-07 | E-GEOD-43948 | biostudies-arrayexpress
Project description:Despite their enormous importance, the molecular circuits that control the differentiation of Th17 cells remain largely unknown. Recent studies have reconstructed regulatory networks in mammalian cells, but have focused on short-term responses and relied on perturbation approaches that cannot be applied to primary T cells. Here, we develop a systematic strategy – combining transcriptional profiling at high temporal resolution, novel computational algorithms, and innovative nanowire-based tools for performing gene perturbations in primary T cells – to derive and experimentally validate a temporal model of the dynamic regulatory network that controls Th17 differentiation. The network is arranged into two self-reinforcing and mutually antagonistic modules that either suppress or promote Th17 differentiation. The two modules contain 12 novel regulators with no previous implication in Th17 differentiation, which may be essential to maintain the appropriate balance of Th17 and other CD4+ T cell subsets. Overall, our study identifies and validates 39 regulatory factors that are embedded within a comprehensive temporal network and identifies novel drug targets and organizational principles for the differentiation of Th17 cells. Time course microarray data for Th17 differentiation, comparing IL23r-/- to WT
2013-03-07 | E-GEOD-43969 | biostudies-arrayexpress
Project description:Chemokine receptor CCR6 is a G-protein-coupled receptor that binds its high-affinity ligand, CCL20. Among the CD4+ T cells, Th17 and regulatory T cells express CCR6, which facilitates their migration in CCL20-enriched, inflamed tissue. Migration of CCR6+ T cells from secondary lymphoid tissues into inflamed tissues exposes them to a distinct metabolic microenvironment. What drives the metabolic adaptation of cells in these tissues and what contributes to their effector or regulatory function is not clearly understood. During colitis, increased gut production of CCL20 promotes the recruitment of these cells. We demonstrated that the intrinsic signaling of CCL20-CCR6 in CD4+ T cells promotes the differentiation of inflamatory Th1-like Th17 cells (T-bet+RORγt+) during colitis in both mouse models and humans. This signaling induces rapamycin-sensitive phosphorylation of PI3K, Akt, mTORC1, and STAT3 in a CCR6-dependent manner. RNA-seq and proteomics analysis revealed alterations in CCL20 during Th17 differentiation, affecting several metabolic pathways, including energy metabolism. CCL20 significantly increased glycolysis and inhibited oxidative phosphorylation, thereby driving the differentiation of pathogenic Th17 cells. Our findings suggest that alterations in CCR6-induced changes in Th17 metabolism offer an interesting therapeutic target for gut inflammation and autoimmunity.
2025-12-10 | PXD071790 | Pride
Project description:The early stages of human Th17 Cell differentiation were studied using label free proteomics to compare Th17 polarized CD4+ human T cells at 24 h and 72 h with activated cells (72 and 24 h) and Thp cells.
2019-01-28 | PXD008973 | Pride
Project description:Despite their enormous importance, the molecular circuits that control the differentiation of Th17 cells remain largely unknown. Recent studies have reconstructed regulatory networks in mammalian cells, but have focused on short-term responses and relied on perturbation approaches that cannot be applied to primary T cells. Here, we develop a systematic strategy – combining transcriptional profiling at high temporal resolution, novel computational algorithms, and innovative nanowire-based tools for performing gene perturbations in primary T cells – to derive and experimentally validate a temporal model of the dynamic regulatory network that controls Th17 differentiation. The network is arranged into two self-reinforcing and mutually antagonistic modules that either suppress or promote Th17 differentiation. The two modules contain 12 novel regulators with no previous implication in Th17 differentiation, which may be essential to maintain the appropriate balance of Th17 and other CD4+ T cell subsets. Overall, our study identifies and validates 39 regulatory factors that are embedded within a comprehensive temporal network and identifies novel drug targets and organizational principles for the differentiation of Th17 cells.
2013-03-07 | GSE43955 | GEO
Project description:Human naïve CD4+ T cells (CD4+ CD45RA+ CD25- CD45RO- CD8- CD14- CD15- CD16- CD19- CD34- CD36- CD56- CD123- TCRγ/δ- HLA-DR- and CD235a-) were magnetically negatively isolated from peripheral blood. Cells were stimulated with anti-CD3/anti-CD28 antibodies plus IL-2, and samples were taken at 6h, 24h, 48h and 6d of stimulation. Mock stimulation control cells (sample group G02) received no further compounds, whereas induced regulatory T cells (iTregs) were either differentiated under addition of TGF-b (sample group G03) or TGF-b + retinoic acid + rapamycin (sample group G05). As control, naïve CD4+ T cells were left unstimulated (0h; sample group G01). Ex vivo isolated CD25-high cells were included as positive control for the Treg signature (“nTreg”; sample group G07). Tregs were defined by expression of FOXP3, the “master” transcription factor of Tregs. Samples from 3 male healthy donors (age 34 to 38 years) were prepared with the Qiagen Allprep kit and protein precipitate was solubilized (5 min, 95°C) in freshly prepared buffer containing 4% (w/v) SDS, 25 mM HEPES pH 7.6, 1mM DTT. Samples were prepared using the FASP assay and peptides were labeled with TMT 10-plex reagents and MS data acquired on a Q Exactive Hybrid Quadrupole-Orbitrap Mass Spectrometer.
Phenotyping, stability and functional analyses for iTregs induced under these conditions are available in Schmidt A et al., PLoSONE 2016, PMID: 26886923). In the publication associated to this dataset, the time-course proteomic profiling during human Treg differentiation is presented and integrated with RNA-Seq data from the same cells (including additional iTreg culture conditions and 2h time points for RNA-Seq). The data underwent clustering, network analysis and disease enrichment, which revealed many known regulators of Tregs along with novel candidate genes putatively involved in FOXP3 induction, the biological importance of which was validated with a targeted shRNA screen.
2018-04-10 | PXD005703 | JPOST Repository