Tracking the fate of pathogenic CD4 T helper cells in vivo.
Transcriptomics Dataset
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General Information
AccessionGSE68242
TitleTracking the fate of pathogenic CD4 T helper cells in vivo.
DescriptionInflammation is a beneficial host response to infection, but it also contributes to inflammatory disease if unregulated. The Th17 lineage of T helper (Th) cells can cause severe human inflammatory diseases. These cells exhibit both instability (i.e., they can cease to express their signature cytokine, IL-17A) and plasticity (i.e., they can start expressing cytokines typical of other lineages) upon in vitro re-stimulation. However technical limitations prevented the transcriptional profiling of pre- and post-conversion Th17 cells ex vivo during immune responses. Thus, it is unknown whether Th17 cell plasticity merely reflects change in expression of a few cytokines, or if Th17 cells physiologically undergo global genetic reprogramming driving their conversion from one T helper cell type to another, a process known as transdifferentiation. Furthermore, while Th17 cell instability/plasticity has been associated with pathogenicity, it is unknown whether this could present a therapeutic opportunity, whereby formerly pathogenic Th17 cells could adopt an anti-inflammatory fate. Here we used two novel fate-mapping mouse models to track Th17 cells during immune responses to show that CD4+ T cells that formerly expressed IL-17A go on to acquire an anti-inflammatory phenotype. The transdifferentiation of Th17 into regulatory T cells was illustrated by a global change in their transcriptome and the acquisition of potent regulatory capacity. Comparisons of the transcriptional profiles of pre- and post-conversion Th17 cells also revealed a role for canonical TGF- signaling and the aryl hydrocarbon receptor (AhR) in conversion. Thus, Th17 transdifferentiate into regulatory cells, and contribute to the resolution of inflammation. Our data suggest Th17 cell instability and plasticity is a therapeutic opportunity for inflammatory diseases.
Landing Pagehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE68242
RepositoryGene Expression Omnibus
Tools used to analyze the dataset

Dataset Accession

Clustergrammer
Published October 2017
Web-based tool for visualizing and analyzing high-dimensional data as interactive and shareable heatmaps
4645
ARCHS4
Published September 2017
ARCHS4 provides access to gene counts from HiSeq 2000 and HiSeq 2500 platforms for human and mouse experiments from GEO ...
4645
Canned Analyses generated with the dataset

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Interactive heatmap visualization of RNA-seq dataset GSE68242
Highly interactive web-based heatmap visualization of the top 500 most variable genes in t...
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