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Data from: Gene editing to induce FOXP3 expression in human CD4+ T cells leads to a stable regulatory phenotype and function.

Cite this dataset

Honaker, Yuchi et al. (2020). Data from: Gene editing to induce FOXP3 expression in human CD4+ T cells leads to a stable regulatory phenotype and function. [Dataset]. Dryad. https://doi.org/10.5061/dryad.02v6wwq08

Abstract

Thymic regulatory T cells (tTreg) are potent inhibitors of autoreactive immune responses and loss of tTreg function results in fatal autoimmune disease.  Defects in Treg number or function are also implicated in multiple autoimmune diseases, leading to growing interest in use of Treg as cell therapies to establish immune tolerance.  Because tTreg are present at low numbers in circulating blood and may be challenging to purify and expand, and also inherently defective in some subjects, we designed an alternative strategy to creating autologous Treg-like cells from bulk CD4+ T cells.  We utilized homology-directed-repair (HDR)-based gene-editing to enforce FOXP3 expression.  Targeted insertion of a robust enhancer/promoter proximal to the first coding exon bypassed epigenetic silencing, permitting stable, high level endogenous FOXP3 expression.  HDR-edited T cells, edTreg, manifested a transcriptional program leading to sustained expression of canonical markers and suppressive activity of tTreg.  Both human and murine edTreg mediated immunosuppression in vivo in models of inflammatory disease.  Further, this engineering strategy permitted generation of antigen-specific edTreg with robust in vitro and in vivo functional activity.  Finally, edTreg could be enriched and expanded at scale using clinically-relevant methods.  Together, these finding suggest edTreg production may permit broad future clinical application.

Methods

RNA-seq was performed on tTreg, primary CD4+T cells (Teff) stably expressing a GFP-FOXP3 fusion protein using AAV6/CRISPR/Cas9 editing (=edTreg) , and non-edited CD4+ Teff cells from four healthy human donors.  tTreg and Teff had been previously sorted (CD4+CD25++CD127- and CD4+CD25-, respectively) and expanded with CD3/CD28 Dynabeads in media containing IL-2 and 0.1 µM rapamycin.  All cell cohorts were simultaneously re-activated with CD3/CD28 beads in IL-2 for 48 hours.  Beads were then removed, and these cells rested for another 48 hours in media containing IL-2 only.  Cells were sorted on the marker of interest directly into 4°C RNA lysis buffer on a FACSAria II (BD Biosciences), and RNA was purified using SMART-Seq v4 Ultra Low Input RNA Kit for Sequencing (Clontech).  cDNA libraries were then prepared using the SMARTseq V4 kit (Clontech).  1,000 cells from each group were directly sorted into lysis buffer.  Cells were re-sorted based on the following markers: Mock-edited cells were CD25-, edTreg were GFPhigh, and tTreg were CD25++CD127-.  Libraries were then prepared per manufacturer’s protocols, and RNAseq was performed on an Illumina HiSeq2500 platform.  RNA sequence reads were aligned to the human genome (hg19) using Tophat2.  Aligned reads mapping to the exons of a gene were quantitated with HTSeq-count.  DESeq2  was used to normalize the data using regularized-logarithm (rlog) and examine the relationship between samples.

Usage notes

File list:

HONAKER_RNASEQ_Readme


Ctl1-activated-Treg_S330_L006_R1_001.fastq.gz
Ctl1-activated-eff_S329_L006_R1_001.fastq.gz
Ctl1-edit_S304_L006_R1_001.fastq.gz

Ctl2-activated-Treg_S332_L006_R1_001.fastq.gz
Ctl2-activated-eff_S331_L006_R1_001.fastq.gz
Ctl2-edit_S327_L006_R1_001.fastq.gz


Ctl3-activated-Treg_S334_L006_R1_001.fastq.gz
Ctl3-activated-eff_S333_L006_R1_001.fastq.gz
Ctl3-edit_S306_L006_R1_001.fastq.gz

Ctl4-activated-Treg_S336_L006_R1_001.fastq.gz
Ctl4-activated-eff_S335_L006_R1_001.fastq.gz
Ctl4-edit_S308_L006_R1_001.fastq.gz


Relationship between files:  
Ctl1, Ctl2, Ctl3, and Ctl4 were 4 unique human peripheral blood donors;
activated Treg = activated tTreg;
edit = edTreg
activated eff = activated T effector cells