A multiply redundant genetic switch 'locks in' the transcriptional signature of regulatory T cells

Fu, Wenxian; Ergün, Ayla; Lu, Ting; Hill, Jonathan A.; Haxhinasto, Sokol; Fassett, Marlys S.; Gazit, Roi; Adoro, Stanley; Glimcher, Laurie H.; Chan, Susan; Kastner, Philippe; Rossi, Derrick J.; Collins, James J.; Mathis, Diane; Benoist, Christophe

doi:10.1038/ni.2420

Cited by 263 publications

(283 citation statements)

References 50 publications

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“…Overall, combined with our ability to maintain T cell clones with stable levels of FOXP3 expression, these data indicate that lack of Helios expression does not identify an unstable population of nTregs that are poised to lose FOXP3 expression and suppressive function. The data are also consistent with the finding that in mice, Helios is not required for expression of the Treg transcriptional signature (41).…”

Section: Discussionsupporting

confidence: 81%

Helios+ and Helios− Cells Coexist within the Natural FOXP3+ T Regulatory Cell Subset in Humans

Himmel

MacDonald

García

et al. 2013

The Journal of Immunology

191

157

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FOXP3-expressing T regulatory cells (Tregs) can be divided into two distinct subsets: naturally occurring Tregs (nTregs) that develop in the thymus, and induced Tregs (iTregs) that differentiate in peripheral tissues upon exposure to Ag in a tolerogenic environment. Recently it has been proposed that expression of Helios, an Ikaros family transcription factor, may specifically identify nTregs, allowing specific tracking of Tregs from different origins in health and disease. Surprisingly, we found that Helios- cells can be readily identified within naive (CD45RA+CD31+CCR7+CD62L+) FOXP3+ Tregs, a finding inconsistent with the notion that lack of Helios expression identifies Ag-experienced iTregs that should express memory markers. To investigate the phenotype and function of naive Helios+ and Helios− Tregs within the nTreg population, we isolated single-cell clones from each subset. We found that both Helios+ and Helios− nTreg clones have a similar suppressive capacity, as well as expression of FOXP3 and cell surface proteins, including CD39 and CTLA-4. Helios− nTregs, however, produced significantly more CCL3 and IFN-γ compared with Helios+ nTregs. Despite increased cytokine/chemokine production, Helios− FOXP3+ nTreg clones were demethylated at the FOXP3 Treg-specific demethylated region, indicative of Treg lineage stability. When cultured under Th1-polarizing conditions, Helios+ and Helios− nTreg clones had an equal ability to produce IFN-γ. Collectively, these data show that a lack of Helios expression does not exclusively identify human iTregs, and, to our knowledge, the data provide the first evidence for the coexistence of Helios+ and Helios− nTregs in human peripheral blood.

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Section: Discussionsupporting

confidence: 81%

Helios+ and Helios− Cells Coexist within the Natural FOXP3+ T Regulatory Cell Subset in Humans

Himmel

MacDonald

García

et al. 2013

The Journal of Immunology

191

157

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“…Importantly, these transcription factors are also expressed by innate lymphoid cells to engender similar phenotypic traits 118 . Third, the expression of specific STATs and master transcription factors is not sufficient for polarization or plasticity of T helper cell subsets; rather, a collection of additional transcription factors are required 119,120 (FIG. 1).…”

Section: Box 2 | Phenotypic Plasticity In Inflammatory and Regulatorymentioning

confidence: 99%

Harnessing the plasticity of CD4+ T cells to treat immune-mediated disease

2016

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| CD4 + T cells differentiate and acquire distinct functions to combat specific pathogens but can also adapt their functions in response to changing circumstances. Although this phenotypic plasticity can be potentially deleterious, driving immune pathology, it also provides important benefits that have led to its evolutionary preservation. Here, we review CD4 + T cell plasticity by examining the molecular mechanisms that regulate it -from the extracellular cues that initiate and drive cells towards varying phenotypes, to the cytosolic signalling cascades that decipher these cues and transmit them into the cell and to the nucleus, where these signals imprint specific gene expression programmes. By understanding how this functional flexibility is achieved, we may open doors to new therapeutic approaches that harness this property of T cells.

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“…Given the lack of correlation between Foxp3 expression and Foxp3-bound genes in Tregs, and even between Foxp3 and Foxp3-dependent genes, it is reasonable to assume that other regulators are required for defining a Treg-specific transcriptome. So far, several studies have attempted to find key regulators in Treg cells by focusing on genes with highly Treg-specific expression (33) or on regulators associated with a Treg cell signature in expression data obtained from various CD4 + T cells (34). The Immuno-Navigator dataset, on the other hand, allows us to find genes that are highly correlated with Treg-specific genes specifically in Treg-derived expression data.…”

Section: Analysis Of Expression Correlation Of Treg-specific Genes Rementioning

confidence: 99%

Immuno-Navigator, a batch-corrected coexpression database, reveals cell type-specific gene networks in the immune system

Vandenbon

Dinh

Mikami

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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High-throughput gene expression data are one of the primary resources for exploring complex intracellular dynamics in modern biology. The integration of large amounts of public data may allow us to examine general dynamical relationships between regulators and target genes. However, obstacles for such analyses are studyspecific biases or batch effects in the original data. Here we present Immuno-Navigator, a batch-corrected gene expression and coexpression database for 24 cell types of the mouse immune system. We systematically removed batch effects from the underlying gene expression data and showed that this removal considerably improved the consistency between inferred correlations and prior knowledge. The data revealed widespread cell type-specific correlation of expression. Integrated analysis tools allow users to use this correlation of expression for the generation of hypotheses about biological networks and candidate regulators in specific cell types. We show several applications of Immuno-Navigator as examples. In one application we successfully predicted known regulators of importance in naturally occurring Treg cells from their expression correlation with a set of Treg-specific genes. For one high-scoring gene, integrin β8 (Itgb8), we confirmed an association between Itgb8 expression in forkhead box P3 (Foxp3)-positive T cells and Treg-specific epigenetic remodeling. Our results also suggest that the regulation of Tregspecific genes within Treg cells is relatively independent of Foxp3 expression, supporting recent results pointing to a Foxp3-independent component in the development of Treg cells.

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A multiply redundant genetic switch 'locks in' the transcriptional signature of regulatory T cells

Cited by 263 publications

References 50 publications

Helios+ and Helios− Cells Coexist within the Natural FOXP3+ T Regulatory Cell Subset in Humans

Helios+ and Helios− Cells Coexist within the Natural FOXP3+ T Regulatory Cell Subset in Humans

Harnessing the plasticity of CD4+ T cells to treat immune-mediated disease

Immuno-Navigator, a batch-corrected coexpression database, reveals cell type-specific gene networks in the immune system

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