Rewiring of liver diurnal transcriptome rhythms by triiodothyronine (T3) supplementation

Abstract

Diurnal (i.e., 24 hr) physiological rhythms depend on transcriptional programs controlled by a set of circadian clock genes/proteins. Systemic factors like humoral and neuronal signals, oscillations in body temperature, and food intake align physiological circadian rhythms with external time. Thyroid hormones (THs) are major regulators of circadian clock target processes such as energy metabolism, but little is known about how fluctuations in TH levels affect the circadian coordination of tissue physiology. In this study, a high triiodothyronine (T₃) state was induced in mice by supplementing T₃ in the drinking water, which affected body temperature, and oxygen consumption in a time-of-day-dependent manner. A 24-hr transcriptome profiling of liver tissue identified 37 robustly and time independently T₃-associated transcripts as potential TH state markers in the liver. Such genes participated in xenobiotic transport, lipid and xenobiotic metabolism. We also identified 10-15% of the liver transcriptome as rhythmic in control and T₃ groups, but only 4% of the liver transcriptome (1033 genes) were rhythmic across both conditions - amongst these, several core clock genes. In-depth rhythm analyses showed that most changes in transcript rhythms were related to mesor (50%), followed by amplitude (10%), and phase (10%). Gene set enrichment analysis revealed TH state-dependent reorganization of metabolic processes such as lipid and glucose metabolism. At high T₃ levels, we observed weakening or loss of rhythmicity for transcripts associated with glucose and fatty acid metabolism, suggesting increased hepatic energy turnover. In summary, we provide evidence that tonic changes in T₃ levels restructure the diurnal liver metabolic transcriptome independent of local molecular circadian clocks.

Keywords: circadian clock; computational biology; hyperthyroidism; liver; mouse; systems biology; thyroid hormones; transcriptome.

Figure 1.. Triiodothyronine (T₃)-treated mice show classic effects of high thyroid hormone levels compared to control mice (CON).

(A–F) Serum levels of T₃ and thyroxine (T₄), 24 hr profiles of locomotor activity, body temperature, O₂ consumption, and respiratory quotient are shown. Rhythm evaluation was performed by JTK_CYCLE (p<0.01, Supplementary file 1). Presence (R) or absence of circadian rhythm (NR) is depicted. In the presence of significant 24 hr rhythmicity, a sine curve was fit. In (A) and (B), data are double plotted to emphasize the absence or presence of rhythms. (G–I) Linear regression of T₃ average levels with average of locomotor activity, temperature, and O₂ consumption. (J–O) Correlation between thyroid hormone levels and normalized levels of metabolic outputs is shown as z-scores (additional information is described in Supplementary file 2). In (A) and (B), n = 4–6 animals per group and/or timepoint. In (C) and (D), n = 4 and 5 for CON and T₃ groups, respectively. In (E) and (F), n = 4 for each group.

Figure 1—figure supplement 1.. Metabolic evaluation of control (CON) and triiodothyronine (T₃) mice.

(A–D) Assessment of body temperature, food and water intake (per cage, n = 8), and body weight. (E–I) Metabolic parameters (described in the y-axis) were obtained from the third week of experiment (days 19/20). Day and night data were obtained by averaging values from Zeitgeber time (ZT) 0–12 (day) and from ZT 12–24 (night) and plot accordingly. Letters represent a difference between the same group in day vs. night comparisons. Asterisks represent significant differences between CON and T₃ mice. In (H), 95% confidence intervals are shown. Comparison of the slope and elevations/intercept between the groups was performed: p=0.30 and 0.01, respectively. Data are shown either as mean ± SEM or by boxplot. n = 24 for (A) and (D). (E–I) n = 4–5 per group.

Figure 2.. Identification of daytime-independent differentially expressed genes (DEGs) in the liver of triiodothyronine (T₃) mice.

(A) Global (all Zeitgeber times [ZTs] included) evaluation of liver transcriptomes revealed 2336 DEGs of which 1391 and 945 were considered as up- or downregulated, respectively, using a false discovery rate (FDR) < 0.1. Genes with an FDR <0.1 were classified as different irrespectively of fold change values. (B) Top 10 list of biological processes from gene set enrichment analysis (GSEA) of up- and downregulated DEGs is represented. Additional processes can be found in Supplementary file 3. (C) Heatmap of liver DEGs showing significant T₃-dependent regulation across all timepoints. Light and dark phases are shown as gray and black, respectively. (D) Diurnal expression profiles of most robustly regulated DEGs. Gene expression of all groups was normalized by CON mesor. Additional information is described in Supplementary file 4. None of these genes showed rhythmic regulation across the day (NR). n = 4 samples per group and timepoint, except for the T₃ group at ZT 22 (n = 3).

Figure 3.. Diurnal evaluation of liver transcriptome of triiodothyronine (T₃) mice.

(A) Rhythmic probes were identified using the JTK_CYCLE algorithm (Supplementary file 5). Venn diagram represents the distribution of rhythmic probes for each group. (B) Rose plot of all rhythmic genes from control (CON) (gray) and T₃ (red) are represented by the acrophase and amplitude. Phase estimation was obtained from CircaSingle algorithm. (C) Phase difference between shared rhythmic genes. Each dot represents a single gene. One-sample t-test against zero value was performed and a significant interaction (mean 0.7781, p<0.001) was found. (D) Top 7 gene set enrichment analysis (GSEA) of exclusive genes from CON, T₃, and shared are depicted. Additional processes are shown in Supplementary file 5. (E) Sine curve was fitted for the selected clock genes. Gene expression of all groups was normalized by CON mesor. (F) For mesor, amplitude, and phase delta assessment, CircaCompare algorithm was used. The CON group was used as baseline. Additional genes (Per3, Rorc, Tef, Hif1a, and Nfil3) were used for these analyses. One-sample t-test against zero value was used and only phase was different from zero (mean 1.036, p<0.001). n = 4 samples per group and timepoint, except for the T₃ group at Zeitgeber time (ZT) 22 (n = 3).

Figure 3—figure supplement 1.. Principal component analysis (PCA) plots of shared rhythmic genes.

Each timepoint was averaged into a single replicate, and PCA were performed using the factoextra package in R and Hartigan-Wong, Lloyd, and Forgy MacQueen algorithms.

Figure 3—figure supplement 2.. Validation of clock gene diurnal profile by qPCR.

CircaCompare was used to evaluate the difference in rhythmic parameters, and one-sample t-test against zero value was performed (mean 0.9069 hr, p=0.0221). Sine curve was fitted for rhythmic genes (R). n = 3–4 samples per group and timepoint.

Figure 4.. Gene expression evaluation of thyroid hormone (TH) regulators and metabolic outputs in triiodothyronine (T₃) compared to control (CON).

(A, B) Genes involved in TH regulation, including transporters, Dio1, TH receptors, and well-known T₃ outputs are presented. Presence (R) or absence of circadian rhythm (NR) detected by CircaCompare is depicted. Sine curve was fitted for rhythmic genes. Gene expression of all groups was normalized by CON mesor. (C) Evaluation of rhythmic parameters from genes described in (B) was performed by CircaCompare using CON group as baseline. One-sample t-test against zero value was used and only mesor was different from zero (mean 1.371, p<0.01). n = 4 samples per group and timepoint, except for the T₃ group at Zeitgeber time (ZT) 22 (n = 3).

Figure 5.. CircaCompare analyses of triiodothyronine (T₃) (red) mice compared to control (CON) (black).

(A) Venn diagram demonstrates the number of probes that displayed differences in each rhythmic parameter (mesor, amplitude, and phase). (B) Top 5 enriched biological processes for each rhythmic parameter category. (C) Summary of the CircaCompare analyses regarding glucose and fatty acid (FA) metabolism. (D, E) Representation of glucose and FA metabolism biological processes obtained from transcriptome data. (F) Diurnal rhythm evaluation of liver triacylglyceride (TAG) and day (Zeitgeber time [ZT] 2–6) vs. night (ZT18–22) serum TAG levels comparisons. (G) Summary of the CircaCompare analyses regarding cholesterol metabolism. (H) Representation of cholesterol homeostasis obtained from transcriptome data. (I) Diurnal rhythm evaluation of liver and serum cholesterol. Gene expression from each biological process was averaged per ZT and plotted. The reader should refer to the text for detailed information regarding the changes found at the gene level of these processes. Sine curve was fitted for each rhythmic biological process. Individual gene expression pertaining to these processes is found in Figure 5—figure supplement 1. n = 4 samples per group and timepoint, except for the T₃ group at ZT 22 (n = 3).

Figure 5—figure supplement 1.. Expression profile of the selected genes pertaining to biological processes identified in CircaCompare.

Diurnal profile of genes from glucose (A), fatty acid (B), and cholesterol metabolism (C). Diurnal overall gene expression was normalized by CON mesor and plotted. Sine curve was fitted for rhythmic genes (R). Absence of rhythmic is represented by connected lines and NR symbol. n = 4 samples per group and timepoint, except for the T₃ group at Zeitgeber time (ZT) 22 (n = 3). CircaCompare data is provided in Supplementary file 6.