Epigenetic control of T-helper-cell differentiation

Wilson, Christopher; Rowell, Emily; Sekimata, Masayuki

doi:10.1038/nri2487

Cited by 615 publications

(636 citation statements)

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“…17,18,21,32,33 Other helper T-cell phenotypes are regulated in similar ways, such as the Treg phenotype and its master transcription factor FOXP3 19 and the cytokine TGFb, or the Th17 phenotype governed by RORgt and IL17, 34,35 but as of yet little is known about their epigenetic regulatory mechanisms.…”

Section: The Modelmentioning

confidence: 99%

“…Transcription factors can help to alter the epigenetic state of cytokine genes by binding to DNA and preventing remethylation (that is, passive demethylation). 21,45,46 We model this by allowing transcription factors to occupy nonmethylated CpG islets on the cytokine gene, thereby preventing methylation (for instance, through preventing DNMTs from binding to DNA), and promoting a shift to a nonmethylated state. In summary, our model describes a master transcription factor that promotes its own expression, upregulates cytokine expression and inhibits methylation of the cytokine locus.…”

Section: Box 1 Positive Feedback Creates Attractorsmentioning

confidence: 99%

“…Master transcription factors bind to CpG islets within their own cytokine locus, and to those of other cytokines. 21,32 By inducing a permissive epigenetic state in their own cytokine locus, and by promoting CpG islet methylation of opposing cytokine loci, master transcription factors can strongly skew cytokine expression.…”

Section: Activated Cellmentioning

confidence: 99%

“…20 Cytokine loci, which tend to be repressed in naive T cells, are derepressed when the T cell adopts a particular phenotype. 21 Cytokine expression seems …”

mentioning

confidence: 99%

“…20 Cytokine loci, which tend to be repressed in naive T cells, are derepressed when the T cell adopts a particular phenotype. 21 Cytokine expression seems to depend on the number of divisions cells have completed following antigenic activation, suggesting that cell division has a role in ensuing epigenetic changes required for derepression. 22,23 Here, we extend an established model for master transcription factors with epigenetic processes to investigate the differentiation, memory formation and plasticity of helper T cells.…”

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confidence: 99%

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Cell division curtails helper phenotype plasticity and expedites helper T‐cell differentiation

Ham

Boer

2012

Immunol Cell Biol

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Following activation by antigen, helper T cells differentiate into one of many effector phenotypes. Formulating mechanistic mathematical models combining regulatory networks at the transcriptional, translational and epigenetic level, we study how individual helper T cells may adopt their different phenotypes. For each cytokine phenotype, for example, T helper type 1 (Th1) and type 2 (Th2) cells, we find that the intracellular molecular network allows a cell to adopt one of the three states, which we interpret as naive, active and memory states. Cell division markedly speeds up the differentiation into a particular memory state because of DNA demythelation. In a memory state, cells readily resume production of the same cytokine they produced before. Using stochastic models we show that helper T-cell plasticity (that is, the ability to switch phenotype) is low during clonal expansion. Although most memory cells rapidly secrete the original cytokine upon restimulation, some adopt another phenotype and produce different cytokines, allowing for considerable diversity in the phenotypes that are adopted during a memory response. In summary, we show that helper T-cell division expedites cell differentiation by increasing DNA demethylation. We also show that plasticity is low during the clonal expansion phase, but that helper T cells may adopt alternative phenotypes during a memory response. Keywords: epigenetic regulation; helper T-cell phenotypes; mathematical modelling; transcriptional regulation For more than a century, biologists have studied the mechanisms that enable cells to encode genetic information, and how this information is passed on to the cell's progeny. 1 Besides the genetic DNA code of a cell that is replicated faithfully upon every cell division and therefore virtually identical in every cell within an individual, 2 additional 'epigenetic' information fixes differential cell development by prompting daughter cells to express a similar set of genes as their mother cell. 3 This facilitates and thus preserves the differentiation process that the mother cell and its ancestors have undergone as part of cellular diversification within an organism.A variety of biological systems have now been studied using highthroughput technologies, which provide data that allow a better understanding of information processing within a cell. [4][5][6][7] The availability of quantitative data and the apparent complexity of cellular regulatory networks have led to a data-driven mathematical modelling approach that is usually referred to as computational or systems biology. Mathematical models have revealed nonlinearity in genetic networks that allow cells to switch between states. Examples are the Lac operon 8 and cells of the haematopoietic lineage. [9][10][11][12] Recently, epigenetic regulation mediated by histone modification has been studied using similar mathematical models. [13][14][15] At the molecular level these mathematical models describe quite different genetic and epigenetic systems. Mathematically they share im...

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Section: The Modelmentioning

confidence: 99%

Section: Box 1 Positive Feedback Creates Attractorsmentioning

confidence: 99%

Section: Activated Cellmentioning

confidence: 99%

“…20 Cytokine loci, which tend to be repressed in naive T cells, are derepressed when the T cell adopts a particular phenotype. 21 Cytokine expression seems …”

mentioning

confidence: 99%

mentioning

confidence: 99%

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