SRA

The molecular mechanisms governing orderly shutdown and retraction of CD4+ T helper (Th)1 responses remain poorly understood. Here, we show that complement triggers contraction of Th1 responses by inducing intrinsic expression of the vitamin D (VitD) receptor (VDR) and the VitD-activating enzyme CYP27B1, permitting T cells to both activate and respond to VitD. VitD then initiated transition from pro-inflammatory IFN-?+ Th1 cells to suppressive IL-10+ cells. This process was primed by dynamic changes in the epigenetic landscape of CD4+ T cells, generating super-enhancers and recruiting several transcription factors, notably c-JUN, STAT3 and BACH2, which together with VDR shaped the transcriptional response to VitD. Accordingly, VitD did not induce IL-10 in cells with dysfunctional BACH2 or STAT3. Bronchoalveolar lavage fluid CD4+ T cells of COVID-19 patients were Th1-skewed and showed de-repression of genes down-regulated by VitD, either from lack of substrate (VitD deficiency) and/or abnormal regulation of this system. Overall design: Memory CD4+ cells were isolated by negative selection and treated with 1,25-VitD (10nM) or carrier alone for set amounts of time. Cells were prepared for RNA-seq of poly-adenylated RNA, CUT&RUN against H3K27Ac, c-JUN, and non-specific targeting (IgG), or CUT&Tag against VDR, STAT3, BACH2, and IgG. RNA-sequencing and analysis Memory CD4+ T cells, including from BACH2 WT or L24P patients, were activated with VitD or carrier. 600,000 cells were pelleted at 300g for 5 min and RNA extracted by RNAqeous Micro (Thermo Fisher Scientific). 1µg total RNA for each sample was subjected to NEBNext Poly(A) mRNA Magnetic Isolation (E7490) and resulting mRNA prepared for RNA-seq by NEB Ultra II (New England Biolabs) and sequenced by HiSeq (Illumina). The expression levels of all genes in RNA-seq libraries were quantified by 'rsem-calculate-expression' in RSEM/v1.3.1 with parameters '--bowtie-n 1 --bowtie-m 100 --seed-length 28 --bowtie-chunkmbs 1000'. The bowtie index for RSEM alignment was generated by 'rsem-prepare-reference' on all RefSeq genes, downloaded from UCSC table browser in April 2017. EdgeR/v3.26.8 was used to normalize gene expression among all libraries and identify DEGs among samples. Microarray analysis sourced from GSE119416 was carried out using Partek Genomics Suite (Partek, Inc.). DEGs were defined using the following criteria: at least 1.5-fold change in either direction at p-value<0.05 for microarray; at least 1.75-fold change in either direction at FDR<0.05 for RNA-seq. H3K27Ac and c-JUN CUT&RUN CUT&RUN sequencing was performed on memory CD4+ T cells activated as above in the presence of carrier or VitD for 0.75h, 48h and 72h using the published protocol of Skene et al (Nature Protocols 2018). Antibodies against H3K27Ac (ab4729, Abcam), c-JUN (60AB, Cell Signaling Technologies), and non-specific IgG (31235, Thermo Fisher Scientific) were used with pAG-MNase (123461, Addgene) on 50,000 cells per target. CUT&RUN (and CUT&Tag below) buffer components were purchased from Sigma-Aldrich and Thermo Fisher Scientific. Post-CUT&RUN, short DNA fragments were prepared for paired-end sequencing (NEB Ultra II, New England Biolabs) with NovaSeq (Illumina). Amplified libraries were quantified by high sensitivity fluorometry (DeNovix) and sized via the 4200 TapeStation (Agilent Technologies). H3K27Ac reads aligned to the human reference genome (GRCh37; hg19) using Bowtie2 with parameters '--local --maxins 250' with sorting and indexing of aligned reads by samtools/v1.10, reads with mapping quality <30 removed. H3K27Ac peaks were called by MACS2 with parameter '-f BAMPE --nomodel'. JUN reads were mapped without '--local' parameter. <120 bp fragments were further sorted and indexed by samtools. JUN induced peaks called by MACS2 parameters '--nomodel -g hs -f BAMPE -q 0.01 --SPMR --keep-dup all'. IgG BAM files were included as controls for MACS2. Peaks for H3K27Ac and JUN experiments were screened against previously characterized hypersequencable-regions (Hg19 Blacklist, CutRunTools). H3K27ac and JUN mean binding intensities in peak regions calculated by UCSC bigWigAverageOverBed. Peaks, combined from two conditions, with mean binding intensity greater than 0.2 in at least one condition and fold change of signal>1.5 were differential. Known motifs +/-100bp from differential peak summits were identified (HOMER, findMotifsGenome.pl, parameter '-size given'). De novo motif footprinting for c-JUN was performed (CutRunTools). Average cuts per bp proximal to JUN peaks was plotted as a histogram relative to IgG. CUT&RUN tracks and heatmaps were visualized using IGV (Broad Institute) and deepTools, respectively. VDR, STAT3, and BACH2 CUT&Tag VDR, STAT3, and BACH2 genome-wide binding in memory CD4+ T cells activated in the presence of 10nM VitD or carrier for 96h was detected by CUT&Tag as per the published protocol (CUT&Tag V.3, dx.doi.org/10.17504/protocols.io.bcuhiwt6) using fixed nuclei (2min fixation of isolated nuclei, RT) with 75,000 nuclei/target and antibodies targeting either VDR (D2K6W, Cell Signaling Technologies), STAT3 (D3Z2G, Cell Signaling Technologies), BACH2 (D3T3G), or non-specific IgG (31235) diluted 1:50 accordingly and incubated with fixed-nuclei for 1h, RT. Secondary antibody (1:100) (ABIN101961, antibodies-online) was bound for 0.5h, RT. Preloaded pA-Tn5 (C01070001, Diagenode) was tethered to antibodies for 1h, RT. Libraries were sequenced paired-end by Novaseq. Resulting reads were processed and mapped to Hg19 (CutRunTools), with peaks called (SEACR/v1.2, stringent, all mapped fragments) and hypersequencable-regions subtracted. Known motif enrichment was determined +/-200bp from peak summits and data visualized as in CUT&RUN.