Dynamic Changes in Chromatin Accessibility Occur in CD8+ T Cells Responding to Viral Infection - PubMed (original) (raw)

Dynamic Changes in Chromatin Accessibility Occur in CD8+ T Cells Responding to Viral Infection

James P Scott-Browne et al. Immunity. 2016.

Abstract

In response to acute infection, naive CD8+ T cells expand, differentiate into effector cells, and then contract to a long-lived pool of memory cells after pathogen clearance. During chronic infections or in tumors, CD8+ T cells acquire an "exhausted" phenotype. Here we present genome-wide comparisons of chromatin accessibility and gene expression from endogenous CD8+ T cells responding to acute and chronic viral infection using ATAC-seq and RNA-seq techniques. Acquisition of effector, memory, or exhausted phenotypes was associated with stable changes in chromatin accessibility away from the naive T cell state. Regions differentially accessible between functional subsets in vivo were enriched for binding sites of transcription factors known to regulate these subsets, including E2A, BATF, IRF4, T-bet, and TCF1. Exhaustion-specific accessible regions were enriched for consensus binding sites for NFAT and Nr4a family members, indicating that chronic stimulation confers a unique accessibility profile on exhausted cells.

Copyright © 2016 Elsevier Inc. All rights reserved.

PubMed Disclaimer

Figures

Figure 1

Figure 1. High ATAC-seq signal in CD8+ T cells at conserved regions in promoters and distal regulatory elements

A) CD8+ T cell populations collected for ATAC-seq comparison. B) Mean ATAC-seq coverage at the 70kb Ifng locus with a scale of 0-1200 for all tracks. C) k-means clustered heat map of mean normalized counts or log2 fold-change from global mean at all peaks. D) Pairwise euclidian distance comparison of asinh transformed ATAC-seq signal per peak for all populations using all peaks accessible in at least one cell type. Data in B,C,D are from mean of at least 2 independent samples, except for a single d35 KLRG1+ replicate. See also Figure S1.

Figure 2

Figure 2. Dynamic changes in chromatin accessibility occur in antigen specific effector and memory CD8+ T cells responding to acute viral infection

A–C) Scatterplots of mean ATAC-seq counts per peak comparing the indicated samples. D–F) Boxplots of ATAC-seq counts per peak from the indicated samples (labeled at bottom) at common or differentially-accessible regions from the comparison labeled above. Box indicates interquartile range with whiskers +/−1.5 times this range and outlier points. G–K) Mean ATAC-seq coverage at Il7r (G), Ccr7 (H), Gzma (I), Gzmk (J), Dmrta1 (K) loci with a scale of 0-1200 (left) or RNA-seq gene expression for the indicated genes (right). L,M) Venn diagrams illustrating intersection of differentially-accessible regions from pairwise comparisons of naive, effector, and memory CD8+ T cells characterizing regions “specific” to a subset (L) or “not” in a subset (M) with p values and odds ratios from Fisher's test comparisons. ATAC-seq data in A–K are from at least 2 independent replicates. RNA-seq data in G–K are mean of two independent replicates for RNA-seq. See also Figure S2.

Figure 3

Figure 3. Memory precursor effector cells are similar to short lived effector cells with a slight bias towards memory

A) Scatterplot of mean ATAC-seq counts per peak comparing the SLEC and MPEC. B) Boxplot of ATAC-seq counts per peak from the indicated samples (labeled at bottom) at common or differentially-accessible regions from the comparison labeled above. Box indicates interquartile range with whiskers +/−1.5 times this range and outlier points. C) Histograms of the log2 fold-change between effector and memory cells at (top) or SLEC and MPEC (bottom) at regions differentially-accessible between effector and memory. D) Mean ATAC-seq coverage at Klrg1 and Aurkb loci with a scale of 0-1200_._ E) RNA-seq gene expression for Klrg1 and Aurkb. Data in A–D are from 3 independent replicates and E is mean of 2 independent replicates. See also Figure S3.

Figure 4

Figure 4. Chronic activation profile identified by comparison of viral antigen specific effector, memory, and exhausted CD8+ T cells

A,B) Scatterplots of mean ATAC-seq counts per peak comparing the indicated samples. C,D) Boxplots of ATAC-seq counts per peak from the indicated samples (labeled at bottom) at common or differentially-accessible regions from the comparison labeled above. Box indicates interquartile range with whiskers +/−1.5 times this range and outlier points. E–G) Mean ATAC-seq coverage at _Havcr2 (E), Tox2 (F), and Satb1 (_G) loci with a scale of 0-1200 (left) or RNA-seq gene expression for the indicated genes (right). H,I) Venn diagrams illustrating intersection of differentially-accessible regions from pairwise comparisons of effector, memory, and exhausted CD8+ T cells characterizing regions “specific” to a subset (H) or “not” in a subset (I) with p values and odds ratios from Fisher's test comparisons. ATAC-seq data in A–G are from at least 2 independent replicates. RNA-seq data in E–G are mean of two independent replicates. See also Figure S4.

Figure 5

Figure 5. Differentially-accessible regions in CD8+ T cells are associated with bhLH, bZIP, HMG, T-box, NR, and RHD family TFs

A) Two dimensional multidimensional scaling plot of ATAC-seq signal for all replicates of naive, effector, SLEC, MPEC, memory, and exhausted cells at 18,043 regions differentially-accessible regions identified from comparisons of naive, effector, memory, and exhausted cells. B) k-means clustered log2 fold-change from mean ATAC-seq signal for all differentially-accessible regions identified from comparisons between naive, effector, SLEC, MPEC, memory, and exhausted CD8+ T cells. C) Enrichment of all known motifs within each cluster of differentially-accessible regions compared to all accessible regions in naive, effector, memory, and exhausted CD8+ T cells. All motifs with an enrichment log p-value less than −15 and found in 10% or more regions in at least one cluster are shown. D) Percent of each cluster of ATAC-seq peaks that overlap ChIP-seq peaks or the percent of all differentially-accessible regions in each cluster. The total number of ChIP-seq peaks for each TF and the fraction of these that overlap any of these differentially-accessible regions are shown below the plot. E) log2 fold-change from mean RNA-seq counts per transcript are shown for all expressed TFs from families associated with each enriched motif. F) MeDIP-seq coverage compared to input for naive and effector CD8+ T cells 8 days after LCMV Arm5 infection. The top graph is for all accessible regions in CD8+ T cells, where each graph below is associated with the clusters indicated at left in panel B. ATAC-seq data in A and B are mean of at least 2 independent replicates and RNA-seq data in E are mean of 2 independent replicates. See also Figure S5.

Figure 6

Figure 6. Constitutively active NFAT partially recapitulates the chronic activation profile in vitro

A) Scatterplot of ATAC-seq counts per peak comparing in vitro cultured CD8+ T cells after transduction with retroviruses expressing the NFAT-CA-RIT mutant or left untransduced (Mock). B) Boxplots of ATAC-seq counts per peak in naive, effector, memory, and exhausted CD8+ T cells at common or differentially-accessible regions between Mock and NFAT-CA-RIT mutant expressing cells. Box indicates interquartile range with whiskers +/−1.5 times this range and outlier points. C) Scatter plot of NFAT-CA-RIT ChIP-seq coverage with log2 fold-change ATAC-seq signal between Mock and NFAT-CA-RIT mutant expressing cells at regions with lower (top) or higher (bottom) ATAC-seq signal in exhausted compared to effector and memory CD8+ T cells. D) Mean ATAC-seq and NFAT ChIP-seq coverage at the Pdcd1 locus with a scale of 0-1200 for ATAC-seq tracks. E) Nr4 family member gene expression in CD8+ T cells over-expressing the NFAT-CA-RIT mutant or left untransduced (Mock) showing mean plus range. ATAC-seq data in A–D are from at least 2 independent replicates. See also Figure S6.

Similar articles

Cited by

References

    1. Barber DL, Wherry EJ, Masopust D, Zhu B, Allison JP, Sharpe AH, Freeman GJ, Ahmed R. Restoring function in exhausted CD8 T cells during chronic viral infection. Nature. 2006;439:682–687. - PubMed
    1. Best JA, Blair DA, Knell J, Yang E, Mayya V, Doedens A, Dustin ML, Goldrath AW, Immunological Genome Project, C. Transcriptional insights into the CD8(+) T cell response to infection and memory T cell formation. Nat Immunol. 2013;14:404–412. - PMC - PubMed
    1. Blackburn SD, Shin H, Haining WN, Zou T, Workman CJ, Polley A, Betts MR, Freeman GJ, Vignali DA, Wherry EJ. Coregulation of CD8+ T cell exhaustion by multiple inhibitory receptors during chronic viral infection. Nat Immunol. 2009;10:29–37. - PMC - PubMed
    1. Buenrostro JD, Giresi PG, Zaba LC, Chang HY, Greenleaf WJ. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat Methods. 2013;10:1213–1218. - PMC - PubMed
    1. Consortium EP. An integrated encyclopedia of DNA elements in the human genome. Nature. 2012;489:57–74. - PMC - PubMed

Publication types

MeSH terms

Substances

LinkOut - more resources