Cistromic Reprogramming of the Diurnal Glucocorticoid Hormone Response by High-Fat Diet

Abstract

The glucocorticoid receptor (GR) is a potent metabolic regulator and a major drug target. While GR is known to play integral roles in circadian biology, its rhythmic genomic actions have never been characterized. Here we mapped GR's chromatin occupancy in mouse livers throughout the day and night cycle. We show how GR partitions metabolic processes by time-dependent target gene regulation and controls circulating glucose and triglycerides differentially during feeding and fasting. Highlighting the dominant role GR plays in synchronizing circadian amplitudes, we find that the majority of oscillating genes are bound by and depend on GR. This rhythmic pattern is altered by high-fat diet in a ligand-independent manner. We find that the remodeling of oscillatory gene expression and postprandial GR binding results from a concomitant increase of STAT5 co-occupancy in obese mice. Altogether, our findings highlight GR's fundamental role in the rhythmic orchestration of hepatic metabolism.

Keywords: PPARα; STAT5; circadian clock; cistromes; glucocorticoid receptor; glucose and lipid metabolism; high-fat diet; hormones; mouse liver.

Figure 1.. Differences in Genomic Binding of GR during the Day and Night Cycle in Mouse Livers

(A) GR occupancy at the Per1 locus for ZT0, ZT4, ZT8, ZT12, ZT16, and ZT20 as determined by ChIP-seq analysis in mouse livers (normalized tag counts for one representative sample shown). (B) Heatmap of GR genome-wide binding for ZT0–ZT20. Each row shows the normalized unique tag counts for one GR binding event (ChIP peak) of the union (sum of all reproducible peaks from two replicates for all six time points), ordered by signal strength. (C) GR ChIP peak percent distribution over the indicated genomic regions for the six time points. (D) Functional characterization of GR’s genomic occupancy during day and night. The three time points of the light phase (ZT0, ZT4, and ZT8 = day) and the dark phase (ZT12, ZT16, and ZT20 = night) were combined into the Venn diagram. The majority of sites bound during the day (73.1%) were also bound at night. The table displays gene ontology analysis of the genes nearest to the 4,455 day binding sites and the 10,465 night-only binding sites. (E) Motif analyses of the 4,455 day and 10,465 night-specific GR ChIP sequences for co-occurring hepatic transcription factors. Data presented is from two biological replicates per time point (i.e., a total of six samples for each day and night). (F) Number of GREs in GR ChIP peaks for day and night, as defined by the consensus sequence shown.

Figure 2.. GR Binding Overlaps with Core Clock Factors to Generate Transcriptional Rhythms

(A, C, and E) Phase distributions, as number of peaks per time point, for GR with BMAL1/CLOCK (A), PER1/2 (C), and CRY1/2 (E); co-bound sites are solid black. (B, D, and F) Venn diagrams depict the GR union from all time points (14,920 sites) intersecting with unions for BMAL1 (6,184) and CLOCK (9,294) (B), PER1 (12,534) and PER2 (20,944) (D), and CRY1 (34,581) and CRY2 (28,658) (F). Functional annotation of cis-regulatory sites bound by all three factors (black) is in the tables below (Koike et al., 2012). (G) Amplitude distribution for ZT0–ZT20 in livers from GR-liver-specific knock out (LKO) (Alb-Cre × GR^f/f) compared to GR^f/f littermates (WT). 3,400 genes cycling in control mice were binned according to peak time point (4 h). Values are represented as mean ± SEM (n = 3 per group). (H) Phase-sorted heatmap of oscillating transcripts in wild-type (WT) and GR-LKO livers for ZT0, ZT4, ZT8, ZT12, ZT16, and ZT20 (n = 3). (I) Venn diagram showing number of differentially regulated genes in GR-LKO during the day (ZT0, ZT4, and ZT8) and night (ZT12, ZT16, and ZT20). Pathway annotation was performed for transcripts either up- or downregulated in GR-LKO. *p < 0.05, ***p < 0.001 (two tailed t test).

Figure 3.. GR Cistromes Are Reprogrammed by HFD

(A) Heatmap of GR genome-wide binding for ZT0–ZT20 in livers after 12 weeks of HFD. Each row shows the normalized unique tag counts for one GR ChIP peak of the union (sum of all reproducible peaks of the HFD dataset), ordered by signal strength. (B) GR ChIP peak percent distribution over the indicated genomic regions for ZT0–ZT20 on HFD. (C) Normalized distribution of GR ChIP-seq tag density in HFD and control cistromes for the six time points. (D) Motif analyses of the 3,258 day and the 16,954 night-specific HFD GR ChIP-sequences show co-occurring hepatic transcription factors. (E) Venn diagram comparing the GR ChIP peak overlap for the sum of all 3 night samples (ZT12, ZT16, and ZT20) from HFD and control livers. Genomic Regions Enrichment of Annotations Tool (GREAT) functional annotation is based on the nearest genes of the 9,345 additional HFD GR-binding sites. (F) Enriched motifs in the GR ChIP peaks gained on HFD during the dark phase over the GR union used as background. Data presented is from two biological replicates per time point. (G) Heatmap of transcripts associated with gained GR binding from (E) (9,354) and deregulated by HFD during the night (ZT12, ZT16, and ZT20). Pathway annotation for transcripts either up- or downregulated in HFD livers.

Figure 4.. GR, PPARα, and STAT5 Signaling Pathways Intersect at Functional Enhancers

(A) Heatmap of GR, STAT5, and PPARα genome-wide binding in control and HFD livers at ZT12. Each row shows the normalized unique ChIP-seq tag counts for GR, STAT5, and PPARα centered on the GR peak positions and ordered by signal strength. (B) Normalized distribution of GR, STAT5, and PPARα ChIP-seq tag density in control and HFD livers at ZT12 at sites occupied by GR. (C) Venn diagram of GR (12,836 and 16,427 peaks), STAT5 (8,815 and 14,216 peaks), and PPARα (4,317 and 4,438 peaks) cistromes at ZT12 in control and HFD, respectively. (D) Representative examples of normalized GR, STAT5, PPARα, and H3K27ac ChIP-seq tracks in both control and HFD at ZT12. Top: the Pemt locus was not affected by diet. Bottom: the Abat locus gained GR-STAT5 co-occupancy together with increased H3K27ac on HFD. (E) ChIP-seq profiles for H3K27ac centered around GR peaks at ZT0 and ZT12 in HFD and control livers. Each row shows the normalized H3K27ac ChIP-seq tag counts ordered by signal strength. (F) Box plot (median, interquartile range, minimum, and maximum) of the log2 fold change between HFD and control tag density of H3K27ac ZT12 signal mapped to the ‘‘lost’’ (3,076), ‘‘common’’ (10,616), or ‘‘gained’’ (9,354) GR sites from Figure 3E. Only peaks near transcripts upregulated by HFD during the night were used. p values were determined using the Mann-Whitney test.

Figure 5.. Cistromic Reprogramming by HFD Is Driven by STAT5 Occupancy

(A) GR interactomes (ChIP-MS) in HFD and control livers at ZT12. Enrichment (log2 fold change) of GR immunoprecipitation (IP) samples versus immunoglobulin G (IgG) (n = 3) was calculated for control and HFD diet samples (Fisher’s exact test, false discovery rate [FDR] < 0.05, s0 = 1). (B) STAT5 ChIP-qPCR in GR-LKO (Alb-Cre x GR^f/f) and WT (GR^f/f) livers on HFD. The Socs2 locus is a positive control for STAT5 binding that was not changed by HFD; the other loci showed HFD-induced gained GR-STAT5 co-occupancy by ChIP-seq. (C) GR ChIP-qPCR in STAT5a/b-LKO (Alb-Cre x Stat5^f/f) and WT (Stat5^f/f) livers on HFD. The Per1 locus is a positive control for GR binding that was not changed by HFD; the other loci are the same as above. Enrichment is calculated over a negative locus. Values are shown as mean ± SEM (n = 2–6 per group), **p < 0.01, ***p < 0.001 (two tailed t test).

Figure 6.. Liver-Specific GR Mutants Show Deregulation of Glucose and Triglyceride Metabolism

(A) Venn diagram showing number of differentially regulated genes in GR-LKO (Alb-Cre × GR^f/f) during the day (ZT0, ZT4, and ZT8) and night (ZT12, ZT16, and ZT20) after 12 weeks of HFD. (B) Amplitude distribution for ZT0–ZT20 in livers from GR-LKO compared to GR^f/f littermates (WT) on HFD. Values are represented as mean ± SEM (n = 3 per group). (C) Heatmap of deregulated transcripts in GR-LKO during the night (ZT12, 16, 20) associated with ‘‘gained’’ (9,354) GR peaks from Figure 3E. Pathway annotation was performed for transcripts either up- or downregulated in GR-LKO livers. (D) H&E staining of livers from GR-LKO mice and littermate controls after 12 weeks of high-fat or control diet. One representative section from n = 3 biological replicates is shown (scale bar, 100 μM). (E–G) Blood glucose (E), serum triglycerides (F), and liver triglycerides (G) from GR-LKO mice and littermate controls during the day (ZT0, ZT4, and ZT8) or night (ZT12, ZT16, and ZT20) on high-fat or control diet. Values are represented as mean ± SD (n = 8–20 per group). (H) RNA-seq data (normalized read counts, Rlog) for deregulated gluconeogenic (Pck1 and Pfkfb3) and lipid metabolism (Pparγ and CD36) transcripts in GR-LKO mice and controls fed with high-fat or control diet. Values are represented as mean ± SEM (n = 3 per group); *p < 0.05, **p < 0.01, ***p < 0.001 (two tailed t test).

Figure 7.. Ligand-Independent Genomic Responses on HFD

(A) Heatmap of GR genome-wide binding for dexamethasone (Dex)-treated and control livers on high-fat or control diet. Dex was injected at ZT0 and livers processed at ZT1. Each row shows the normalized ChIP-seq tag counts ordered by signal strength. (B) Normalized distribution of GR ChIP-seq tag density, corresponding to (A). (C) Volcano plot showing transcripts differentially responding to Dex treatment in HFD versus control (n = 2, adjusted [adj] p < 0.05). Mice were injected with Dex at ZT0 and analyzed at ZT4. (D) Pathway annotation of transcripts down- (n = 374) and upregulated (n = 608) by Dex treatment in HFD livers compared to controls.