What this is
- This research investigates the role of sequences in regulating circadian rhythms in mice.
- Specifically, it focuses on how Albumin D-site-Binding Protein (DBP) and interact to influence gene expression.
- The study employs advanced techniques like ChIP-Seq and RNA-Seq to map binding sites and assess gene expression patterns.
- Findings suggest that sequences are crucial for both input and output mechanisms of the circadian clock.
Essence
- sequences play a critical role in resetting circadian rhythms by mediating transcriptional regulation through interactions between DBP and .
Key takeaways
- Identified 1490 genomic regions bound by both DBP and , indicating significant overlap in their regulatory roles.
- induction was shown to cause phase shifts in circadian rhythms, highlighting its essential role in non-photic phase control.
- 359 rhythmic genes lost their expression rhythms in knockout mice, demonstrating the importance of in maintaining circadian gene expression.
Caveats
- The study primarily uses mouse models, which may limit the generalizability of the findings to other species.
- The physiological significance of acid-induced phase shifts in vivo remains unclear and warrants further investigation.
Definitions
- D-box: A DNA cis-element that regulates gene expression rhythms in the circadian clock.
- E4BP4: A transcription factor that represses DBP activity and plays a role in circadian rhythm regulation.
AI simplified
Introduction
Many aspects of animal behavior and physiology show regular patterns based on circadian rhythms, and these rhythms are observed in a wide range of organisms1. Circadian rhythms are governed by the circadian clock system, which is composed of three components: an oscillator that oscillates even under constant conditions; an input that allows the oscillator to synchronize with environmental cycles; and an output that transmits the oscillator’s signals into circadian gene expression and physiological rhythms. In the circadian oscillator, clock genes and their encoded proteins form transcriptional/translational feedback loops, and drive expression rhythms of core clock genes2. In mammals, CLOCK and BMAL1 bind to a DNA cis-element E-box to transactivate a wide range of target genes including their negative regulators, Per and Cry genes. In addition to the E-box element, D-box element and REV-ERB/ROR-binding element (RRE) form a regulatory network of the rhythmic gene expression, governing coordinately the transcriptional oscillations3,4. The D-box element is activated by three members of the PAR bZip family: Albumin D-site-Binding Protein (DBP); Thyrotroph Embryonic Factor (TEF); and Hepatic Leukemia Factor (HLF). D-box-dependent transactivation is repressed by a bZip factor, Adenovirus E4 promoter Binding Protein 4 (E4BP4), also referred to as Nuclear Factor Interleukin 3 regulated (NFIL3)3,5.
DBP was originally identified as a transcription factor that binds to the D-site in the promoter region of the Albumin gene6. DBP activates transcription of the Per1 gene by binding to the promoter region, and mutation of a putative DBP-binding site abolishes the DBP-dependent transactivation7. E4BP4 protein represses the DBP-dependent transactivation by its competitive binding to the same DNA sequence5. A pioneering work in the field of circadian system biology defined TTAYGTAA as the D-box motif, and showed rhythmic expression from reporter constructs including the D-box sequences3. Furthermore, the circadian peak phase of the D-box activity is located between those of the E-box and RRE activities, and combinations of the three DNA cis-elements in the gene loci determine gene expression profiles3,8. Thus, D-box-mediated transcriptional regulation appears to be important for the circadian clockwork, but physiological roles of D-box sequences in the clock system are still elusive. Moreover, the D-box motif has been extracted from a limited number of genes, and hence a comprehensive analysis is required to determine functional sequences that serve as the D-box in vivo. Here, chromatin immunoprecipitation (ChIP)-Seq analysis in mouse liver and an improved bioinformatics method termed MOCCS2 defined functional D-box sequences, among which TTATGCAA and TTATGTAA are the most and second-most preferred sequences, respectively. Furthermore, we found that acute induction of E4BP4 protein caused phase resetting of peripheral clocks, indicating the importance of D-box function not only in the output but also in the input of the circadian clock system.
Results
Genome-wide analysis of DBP-binding and E4BP4-binding sites
To develop genome-wide mapping of DBP-binding sites and E4BP4-binding sites, the ChIP DNA fragments were prepared from E4bp4-KO mouse and littermate control livers at ZT12 for the DBP-ChIP and at ZT24 for the E4BP4-ChIP. The ChIP samples were subjected to deep sequencing, which yielded 70–100 million tags in each sample (Supplementary Data 1). These tags were mapped onto the mouse genome, and the peak calling program MACS2 identified 6066 DBP-binding sites at ZT12 and 3064 E4BP4-binding sites at ZT24 in the control livers (Supplementary Data 1). The E4BP4-ChIP signals at the 3064 E4BP4-binding sites were significantly reduced in E4bp4-KO livers (wild type: 16.0 ± 12.4, E4bp4-KO: 1.8 ± 0.2, p = 1.3 × E-111, two-sided Student’s t test). Among the 3064 E4BP4-binding sites, DBP-binding signals were detected at 1490 sites, which we defined as DBP/E4BP4-common sites. When the 1490 common sites were compared with the previous E4BP4-ChIP data10, E4BP4-binding signals were detected at 1284 sites (1284/1490 = 86.2%), indicating high reliability of the current ChIP-Seq data. Typically, strong peaks of DBP-ChIP tags at ZT12 and E4BP4-ChIP tags at ZT24 were detected at the Per1 TSS region (Fig. 1c), consistent with the ChIP-PCR analysis (Fig. 1d). Notably, our ChIP-Seq data identified a so-far unidentified DBP-binding site in the Per1 −4.2 kb region, where no significant E4BP4-binding signal was detected (Fig. 1c, d; p = 0.49, two-sided Student’s t test). A similar DBP-preference site was detected in the intron 1 region (+2.7 kb region) of the Per2 gene locus, in which a DBP/E4BP4-common site was located in the TSS region (Supplementary Fig. 1c, d).

DBP-ChIP and E4BP4-ChIP analyses in mouse liver.,Anti-phasic expression of DBP and E4BP4 proteins. Liver nuclear extracts were prepared from-KO and control mice at indicated time points, and were subjected to immunoblot analysis by using anti-DBP and anti-E4BP4 antibodies. Zeitgeber time (ZT) 0 and ZT12 correspond to the lights-on time and the lights-off time in LD cycles, respectively. Full images of the blots are shown in Supplementary Fig.. Data shown are the representative from three independent experiments with similar results.ChIP-Seq analysis by using anti-DBP or anti-E4BP4 in thegene locus. ChIP samples were prepared at ZT12 and ZT24 from-KO and control mice, and were subjected to deep sequencing. TSS refers to transcription start site.The ChIP samples were subjected to ChIP-PCR analysis with primer sets that amplify DNA regions indicated by the arrowheads in. Anti-rhodopsin antibody 1D4 was used as a control IgG. Bars and dots represent means and individual data (= 3), respectively. In this study, the numberis equal to the number of mice used for each sample at each time point a b c d c E4bp4 Per1 E4bp4 n n 8
Functional D-box sequences defined by MOCCS2

Simulation for determining standard deviations of AUC in MOCCS2.Shown are 10,000 patterns of cumulative relative frequency curves calculated from random histograms with appearance counts indicated above individual graphs.Standard deviations (SDs) of AUC calculated from indicated patterns of random histograms (axis) were plotted against appearance counts (axis), and well fitted with an exponential equation “= 71.303 ×”. See also Supplementary Fig.for 5000 and 1000 patterns of the cumulative relative frequency curves a b y x Y X −0.5 2

Identification of functional D-box sequences by MOCCS2.MOCCS2 analysis of 1490 DBP/E4BP4-common sites. AUC of all 8-mer sequences (axis) were plotted against their appearance counts (axis). D-box#1-#6 are shown by red dots, D-box#7-#12 by orange, D-box#13-#18 by yellow, and others by black. Shown are also two exponential equations indicating 1 × SD (black line,= 71.303 ×) and 10 × SD (orange line,= 713.03 ×).Frequency distribution of TTATGCAA (D-box#1) and TTACGTAA (D-box#18) around the DBP/E4BP4-common sites. The bin size of theaxis is 10 bp.Cumulative relative frequency curves of D-box#1 and #18 around the common sites. Those of all the D-box#1-#18 sequences are shown in Supplementary Fig..Dual luciferase reporter assays by using all the D-box#1-#18 sequences. The effects of DBP and E4BP4 on transcriptional activities were investigated by using luciferase reporters each harboring the indicated D-box or its related sequence. Ratios of bioluminescence signals from firefly luciferase relative to those fromluciferase (internal control) for D-box reporters were normalized with the ratio for a control reporter (an empty vector, pGL3N). Fold changes of the normalized signal ratios relative to those in the absence of DBP and E4BP4 were shown in a semi-log plot. Bars and dots represent means and individual data (= 3), respectively. See also Supplementary Fig. a b c d y x Y X Y X x Renilla n −0.5 −0.5 3b, c 3d
| Rank | Sequence | AUC | Appearance count | MOCCS2 score |
|---|---|---|---|---|
| D-box#1 | TTATGCAA | 94 | 537 | 30.9 |
| D-box#2 | TTATGTAA | 60.4 | 390 | 16.7 |
| D-box#3 | TGATGTAA | 71.8 | 189 | 13.9 |
| D-box#4 | TTATGTCA | 71.8 | 119 | 11 |
| D-box#5 | TTGTGTAA | 64.7 | 132 | 10.4 |
| D-box#6 | TTATACAA | 60.5 | 75 | 7.3 |
| D-box#7 | TTAGGTAA | 60.1 | 74 | 7.3 |
| D-box#8 | TGATGCAA | 51.2 | 87 | 6.7 |
| D-box#9 | TTATCTAA | 53.5 | 73 | 6.4 |
| D-box#10 | TTACGCAA | 92.3 | 24 | 6.3 |
| D-box#11 | TGCTGTAA | 45.1 | 85 | 5.8 |
| D-box#12 | TTATGAAA | 39 | 107 | 5.7 |
| D-box#13 | TTGTGCAA | 36.5 | 81 | 4.6 |
| D-box#14 | TTTGGCAA | 42 | 58 | 4.5 |
| D-box#15 | TTATATAA | 37.6 | 71 | 4.4 |
| D-box#16 | TTACTCAA | 39.5 | 63 | 4.4 |
| D-box#17 | TTATTGCA | 42 | 55 | 4.4 |
| D-box#18 | TTACGTAA | 50.7 | 35 | 4.2 |
Perturbation of circadian output bydeficiency E4bp4
Among the 1277 rhythmic genes, 359 genes were E4bp4-dependent rhythmic genes that showed robust expression rhythms (p < 0.01) in the control but lost their rhythmicities (p ≥ 0.05) in the E4bp4-KO livers (Supplementary Fig. 4a). Among the E4bp4-dependent rhythmic genes, Marveld1 and Wee1 showed expression peaks at ZT12-16, whereas their expression levels were constantly high in the E4bp4-KO livers (Fig. 4b). These data are consistent with the expression rhythm of the E4BP4 repressor peaking at ZT0-2 (Fig. 1a, b). ChIP-Seq and ChIP-PCR analyses demonstrated rhythmic binding of DBP and E4BP4 to the promoter region of Marveld1 and to the intronic region of Wee1 (Fig. 4c, d). It is noted that D-box#2 (TTATGTAA) was found at around the DBP/E4BP4-common sites in the Marveld1 and Wee1 gene loci. Gene ontology (GO) analysis showed that the E4bp4-dependent rhythmic genes were enriched with genes involved in metabolic pathways (Supplementary Fig. 4b). It has also been reported that E4bp4-KO mice suffer from inflammatory diseases of the intestine14–16. The current study will provide clues to understanding E4bp4-mediated transcriptional regulation in other physiological processes.

Dysfunction of circadian output in-KO liver.Heat maps of mRNA levels of 1277 rhythmic genes determined by the RNA-Seq. Genes were ordered by their peak phases in control mice from early day to late night. The FPKM values were normalized so that the mean and the variance were set to 0 and 3, respectively, for each row of the maps.Temporal profiles of mRNA levels of representative target genes in livers of-KO and control mice, determined by RNA-Seq and qRT-PCR analyses. Data are shown as means with SD (= 2) for RNA-Seq and means with SEM (n = 3) for qRT-PCR.DBP-ChIP-Seq and E4BP4-ChIP-Seq data in the representative target gene loci.DBP-ChIP and E4BP4-ChIP samples were subjected to ChIP-PCR analysis with primer sets that amplify the DNA region indicated by arrowheads in. Bars and dots represent means and individual data (= 3), respectively E4bp4 E4bp4 n n a b c d c
Acute induction ofexpression for circadian input E4bp4
To examine whether E4BP4 induction is required for the acid-evoked phase resetting, we isolated E4bp4-KO/PER2::Luc MEFs, in which circadian rhythms can be examined by real-time monitoring of the bioluminescence from Luciferase fused with endogenous PER2 protein. In the control PER2::Luc MEFs, we observed apparent phase shifts, when pHo of the cultured media was shifted from 7.0 to 6.6 (Fig. 5a) several hours after the trough time of the bioluminescence rhythms (Fig. 5d), as was previously observed in rat-1 fibroblasts20. On the other hand, faint phase shifts were induced by the acidification several hours after the peak time (Supplementary Fig. 5c). Phase response curves and phase transition curves showed phase-dependent phase shifts and revealed type-0 resetting of cellular rhythms in response to the acidification, respectively (Fig. 5e, f, left). Importantly, the acidification-induced phase shifts were almost completely blocked in the E4bp4-KO/PER2::Luc MEFs (Fig. 5d–f, right), indicating an essential role of the acute induction of E4BP4 in acid-evoked phase resetting. The present work revealed physiological roles of D-box-mediated transcriptional regulation, which is important for non-photic phase control in the peripheral clock.

Essential role of E4BP4 for acid-evoked phase resetting.For acid treatment, pHo was changed from 7.0 to 6.6 by adding 1M HCl solution to the culture media. In control experiments, the same volume of water was added (HO).Changes ofandmRNA levels in response to the acid treatment. MEFs collected at the indicated time after the acid treatment were subjected to qRT-PCR analysis. The signal values for each mRNA were normalized to those of Rps29 mRNA (internal control) and the mean value at time 0 was set to 1. Bars and dots represent means and individual data (= 3), respectively. The indicatedvalues were calculated by two-sided Student’stest versus HO.Induction of E4BP4 protein in response to the acid treatment. MEFs collected at the indicated time after the acid treatment were subjected to immunoblot analysis with the indicated antibodies. Full images of the blots are shown in Supplementary Fig.. Data shown are the representative from three independent experiments with similar results.Phase shifts of bioluminescence rhythms in the PER2::LUC MEFs (WT) or PER2::LUC/-KO MEFs (-KO) in response to the acid treatment. The timing of the acid treatment was indicated by arrowheads.,Phase response curves (PRCs) and phase transition curves (PTCs) of the cellular rhythms in response to the acid treatment in the control PER2::LUC MEFs (WT) or PER2::LUC/-KO MEFs (-KO) a b c d e f 2 2 E4bp4 Per2 n p t E4bp4 E4bp4 E4bp4 E4bp4 8
Discussion
In the present study, we generated anti-DBP and anti-E4BP4 antibodies, which enabled us to determine DNA regions recognized by DBP and E4BP4 proteins in a genome-wide manner (Fig. 1, Supplementary Data 1). In general, ChIP-Seq analysis provides information about genomic DNA regions recognized by a transcription factor, and many bioinformatics tools such as MEME and HOMER have been employed to extract a representative DNA-binding motif from ChIP-Seq data. However, a bioinformatics tool that can determine all DNA-binding sequences of a transcription factor is required. In a previous study, we developed a bioinformatics tool termed MOCCS to provide a comprehensive list of DNA-binding sequences of a transcription factor11,12. In the present study, we improved this tool by calculating a new parameter, the MOCCS2 score, which represents the significance of appearance frequency of a sequence around binding sites of a transcription factor (Fig. 2). The original version of MOCCS raised eight candidates for CLOCK-binding sequences (Supplementary Fig. 6), among which TACGTA having the 7th highest AUC but a very low appearance count was considered a false positive sequence because it had no significant activity in promoter assay11. When MOCCS2 was applied to the previous CLOCK-ChIP-Seq data, the MOCCS2 score of TACGTA (6.5) was obviously lower than those of the other candidates (102.8–21.6) (Supplementary Fig. 6). It is clear that MOCCS2 analysis excludes such false positive sequences. In the present study, functional D-box sequences were identified by MOCCS2 analysis of 1490 sites that are recognized commonly by DBP and E4BP4 (Fig. 3, Table 1). On the other hand, our ChIP-Seq analysis identified 4573 DBP-binding sites where no significant binding of E4BP4 was detected (Supplementary Data 1). In MOCCS2 analysis of the 4573 sites, TTACCCAA, a two-mismatched sequence of D-box#1, showed a higher MOCCS2 score (10.6) (Supplementary Data 4), contrasting its lower score (3.0) in MOCCS2 analysis of the 1490 DBP/E4BP4-common sites (Supplementary Data 1). It should be noted that TTACCCAA was found in regions with DBP-preference sites such as the Per1 −4.2 kb region (Fig. 1c) and the Per2 +2.7 kb region (Supplementary Fig. 1). These results indicate that MOCCS2 is a powerful bioinformatics tool in determining all DNA-binding sequences from ChIP-Seq data.
In our previous study11, the ChIP-Score was defined as the total number of sequence tags that were mapped to all the CLOCK-binding sites within ±10 kb of the transcription start site of each gene or in the gene body. ChIP-Score analysis of the current ChIP-Seq identified 6696 genes as the targets of DBP and/or E4BP4 proteins (Supplementary Data 5). Among the 6696 DBP/E4BP4 targets, 3300 genes were judged as expressed based on the liver RNA-Seq data (Supplementary Data 3). Their ratio (3300/6696 = 49.3%) was 2.1-fold higher than the ratio of the number of the expressed genes to that of all genes (12,758/54,733 = 23.3%), suggesting that genes targeted by DBP and E4BP4 are more frequently expressed in the mouse liver. On the other hand, we found 359 E4bp4-dependent rhythmic genes that showed robust expression rhythms in the control but lost their rhythmicities in the E4bp4-KO liver (Supplementary Fig. 4b). Among the 359 genes, 130 genes were also included in the 3300 expressed DBP/E4BP4 targets. Their ratio (130/3300 = 3.94%) was 1.4-fold higher than the ratio of the number of the E4bp4-dependent rhythmic genes to that of the expressed genes (359/12,758 = 2.81%), indicating that genes targeted by DBP and E4BP4 become more frequently arrhythmic in the E4bp4-KO livers.
In Drosophila, an E4bp4 homolog vrille rhythmically represses transcription of dclock gene and serves as a key component of the core circadian oscillation21–23. It was also reported that siRNA-mediated knockdown of E4bp4 lengthened the circadian period in cultured rat-1 cells24. However, our RNA-Seq analysis showed that E4bp4 deficiency resulted in no remarkable changes of expression profiles of the core clock genes (Supplementary Fig. 7a, b). The normal circadian oscillation was also confirmed by monitoring the wheel-running rhythms of E4bp4-KO mice under constant dark conditions (Supplementary Fig. 7c, d; WT: 23.85 ± 0.19 hr, KO: 23.76 ± 0.23 hr). To our knowledge, this is the first report showing that the E4bp4 gene is dispensable for maintaining circadian rhythms of mouse locomotor activities. In contrast to the marginal effect on rhythmic expression of core clock genes (Supplementary Fig. 7a, b), E4bp4 deficiency caused dysregulation of circadian output genes (Fig. 4, Supplementary Fig. 4). Previously, it was reported that locomotor activity rhythms were almost intact in triple KO mice of PAR bZip factors25, whereas these deficiencies caused strong effects on circadian outputs26. DBP single-KO mice showed a shorter free-running period27, contrasting with the longer period phenotype of TEF or HLF single-KO mice (mentioned in the text of ref. 25). These results indicate that the importance of the D-box-mediated transcriptional regulation in mRNA rhythms is diverged among rhythmically expressed genes.
In addition to the role of the D-box in circadian clock outputs, we described an indispensable role of the E4bp4 gene as an input to the clock (Fig. 5). E4bp4 expression is induced in response to various extracellular stimuli such as interleukin 317, glutamate, H2O218, insulin19 (Supplementary Fig. 5a), and acidification of the culture media (Fig. 5b, c). It is not clear whether the acid-induced circadian phase shift has a physiological significance in vivo, but circadian rhythms are phase-shifted by physiological activities such as exercise and feeding28, which activate glycolysis leading to lactic acid accumulation. The acute E4BP4 induction at a time when its expression level is low could competitively interfere with DNA-binding of the PAR bZip factors to D-box. This should lead to a phase shift of the circadian clock. Intraperitoneal injection of insulin caused acute E4BP4 induction in mouse liver (Supplementary Fig. 5d), and thereby elevated its binding to the D-box located in the Per1 and Per2 promoter regions (Supplementary Fig. 5e). It was reported that insulin also induces Per2 expression29 together with its repressor E4bp4 expression (Supplementary Fig. 5d, e), and such feedback action of E4bp4 may be important for transient response of Per2 expression to insulin. In this study, we demonstrated that the acute induction of E4BP4 protein is essential for the type-0 resetting of the cellular rhythms elicited by acidification of the cultured media (Fig. 5d–f). In previous studies on the chicken pineal clock, we showed that light-dependent activation of sterol regulatory element-binding protein (SREBP) transcription factor remarkably elevated E4bp4 mRNA levels, which led to suppression of Per2 transcription and phase shifts30–32. Intriguingly, acidification of extracellular pH (to 6.8) triggers activation of SREBP in cancer cells33, suggesting a potential relationship between the acid-inducible E4bp4 and the acidic microenvironment of tumors. It was also reported that D-box-mediated transcription is important for light-dependent induction of zPer2 in zebrafish34,35. In mice, however, E4bp4 deficiency had no significant effect on light-dependent phase shifts (Supplementary Fig. 7e), and E4BP4 has a pivotal role in non-photic phase control of the peripheral clocks. Collectively, we conclude that transcriptional regulation via D-box sequences plays key roles in the circadian inputs and outputs.
Methods
Animals
The animal experiments were approved by the animal ethics committee of the University of Tokyo. C57BL/6J mice were individually housed in cages with free access to food and water. E4bp4-KO mice were kind gifts from A. Thomas Look (Children’s Hospital Boston, Harvard Medical School). In the E4bp4-KO mice, the exon 2 of E4bp4 gene was replaced by a neomycin cassette, as previously described36. Mice were reared in 12-h light:12-h dark cycles in a light-tight chamber at a constant temperature (23 ± 1 °C). PER2::LUC knock-in mice37 were used for monitoring bioluminescence rhythms. Wheel-running activity rhythms were monitored and analyzed with Clocklab software (Actimetrics) developed on MatLab (Mathworks), as previously described38.
Antibodies for immunoblot and ChIP analyses
We generated anti-DBP and anti-E4BP4 antibodies in rabbits, now commercially available as anti-DBP (MBL, PM079) and anti-E4BP4 antibodies (MBL, PM097). We also used anti-rhodopsin 1D439, anti-TBP (Santa Cruz Biotechnology, sc-421) and anti-beta-actin (Sigma, A2228). In immunoblot analysis, the bound primary antibodies were detected by horseradish peroxidase-conjugated anti-rabbit or anti-mouse IgG antibody (Kirkegaard & Perry Laboratories).
Preparation of nuclear proteins
The nuclear proteins were isolated as previously described40,41. Mouse tissue (1 g, wet weight) was washed with ice-cold PBS and homogenized at 4 °C with 9 ml of ice-cold buffer A (10 mM HEPES-NaOH, 10 mM KCl, 0.1 mM EDTA, 1 mM dithiothreitol (DTT), 1 mM phenylmethylsulfonyl fluoride (PMSF), 4 μg/ml aprotinin, 4 μg/ml leupeptin, 50 mM NaF, and 1 mM Na3VO4; pH 7.8). The homogenate was centrifuged twice (700 × g, 5 min each), and the precipitate was resuspended in 2 ml of ice-cold buffer C (20 mM HEPES-NaOH, 400 mM NaCl, 1 mM EDTA, 5 mM MgCl2, 2% glycerol, 1 mM DTT, 1 mM PMSF, 4 µg/ml aprotinin, 4 µg/ml leupeptin, 50 mM NaF, and 1 mM Na3VO4; pH 7.8). After gentle mixing at 4 °C for 30 min, the suspension was centrifuged twice (21,600 × g, 30 min each), and the final supernatant was used as the “nuclear extract”.
Chromatin immunoprecipitation
ChIP analysis was prepared as described previously11 with minor modifications. Livers were isolated at two time points, ZT12 and ZT24 (n = 3), from E4bp4-KO and the WT littermate mice. They were rinsed with ice-cold PBS and were homogenized with ice-cold buffer A (10 mM HEPES-NaOH, 10 mM KCl, 0.1 mM EDTA, 1 mM DTT, 1 mM PMSF, 4 μg/ml aprotinin, 4 μg/ml leupeptin, 50 mM NaF, and 1 mM Na3VO4; pH 7.8). The homogenate was centrifuged twice (700 × g, 5 min each), and the precipitate (nuclear fraction) was cross-linked by 1% formaldehyde in buffer A for 10 min at 25 °C. The cross-linking reaction was stopped by addition of 125 mM glycine (final concentration). The sample was then centrifuged (700 × g, 5 min), and the nuclei pellet was washed twice with buffer A and resuspended in IPB2 buffer (20 mM HEPES-NaOH, 137 mM NaCl, 1 mM EDTA, 5% glycerol, 1% Triton X-100, 1.67 mM MgCl2, 1 mM DTT, 1 mM PMSF, 4 μg/ml aprotinin, 4 μg/ml leupeptin, 50 mM NaF, and 1 mM Na3VO4; pH 7.8) supplemented with 1% SDS. The sample was then sonicated 16 times for 20 s each at intervals of 40 s (Branson Sonifier 450; set at 50% duty cycle, five output). The supernatant was diluted in IPB2 (final 0.1% SDS), and snap-frozen in liquid nitrogen. After thawing, the sample was centrifuged at 20,000 × g for 10 min at 4 °C, and the supernatant was incubated with anti-DBP antibody, anti-E4BP4 antibody, or an irrelevant antibody 1D4 while being gently rotated for 2 h at 4 °C. Protein G-coupled magnetic beads (Dynabeads, Dynal) were added to the mixture, followed by gentle rotation for 1 h at 4 °C. The beads were washed sequentially with the following buffers by using DynaMag-2 magnet: (i) IPB2 buffer; (ii) IPB2 buffer supplemented with 500 mM NaCl; (iii) TE buffer (10 mM Tris-HCl, 1 mM EDTA; pH 8.0) supplemented with 0.25 M LiCl, 1% NP-40, and 1% deoxycholate; and (iv) TE buffer. Finally, the beads were treated with 500 µl of the elution buffer (1% SDS, 0.1 M NaHCO3) and gently rotated for 30 min at room temperature, and the eluate was mixed with 20 µl of 5 M NaCl and incubated overnight at 65 °C. The de-cross-linked sample was then mixed with 10 μl of 0.5 M EDTA, 20 μl of 1 M Tris-HCl (pH 6.5) and 2 μl of 10 mg/ml Proteinase K, and the mixture was incubated for 2 h at 45 °C. The DNA was purified by extraction with phenol-chloroform-isoamyl alcohol (25:24:1) and subjected to ethanol precipitation. The final precipitate was used as the ChIP sample.
ChIP-Seq analysis
The DBP-ChIP (at ZT12, n = 2) and E4BP4-ChIP samples (at ZT24, n = 2) prepared from E4bp4-KO mice and the WT littermates were sequenced on a HiSeq 3000 sequencer (36 bp, single end). The input samples prior to the immunoprecipitation were also subjected to the deep sequencing as controls. The sequence tags were mapped to the mouse genome by using Bowtie (v1.2.1) with parameter setting of “−a –best –strata -m 1 −p 4”42. BAM files of biological duplicates were merged using the “samtools merge” command. Peak calling was performed for the merged ChIP samples versus the merged input using MACS2 (v2.1.1) with default parameters43. The mapped tags were visualized by using Integrative Genomics Viewer44.
MOCCS2 analysis
The equation that calculates [SD of AUC] from [appearance counts] was mathematically derived as follows. Let W be the size of the analyzed window where k-mer sequences are sought at around ChIP-peak positions. If a k-mer sequence appears only once at a random position within the window, its coordinate follows the uniform distribution U(0, W), whose variance is known to be W2/12. Because (i) AUC is calculated by subtracting W/2 from the coordinate and (ii) constant subtraction does not affect variance of probability distributions, variance of AUC is also W2/12 if the appearance count is 1. Next, assume that a k-mer sequence appears C times at random positions within the window. The variance of the sum of their coordinates becomes CW2/12, because variance of sum of random variables that follow the same probability distribution is proportional to the numbers of the variables. Then, because AUC is calculated by dividing the sum of their coordinates by C and subtracting W/2, the variance of AUC is (CW2/12)/C2 = W2/12 C, if the appearance count is C. Finally, we obtain [SD of AUC] by taking the square root of the variance:\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$[{\mathrm{SD}}\, {\mathrm{of}}\, {\mathrm{AUC}}] = \frac{[{\mathrm{window}}\, ({\mathrm{W}})]}{{\sqrt{12}} \times {\sqrt {[{\mathrm{appearance}}\, {\mathrm{count}}\, ({\mathrm{C}})]}}}$$\end{document}[SDofAUC]=[window(W)]12×[appearancecount(C)]
In MOCCS version 2 (abbreviated as MOCCS2), the “MOCCS2 score” of each sequence was defined as a relative value of AUC normalized by the SD at its appearance count: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathrm{MOCCS2}}\, {\mathrm{score}} = \frac{\mathrm{[AUC]}}{{[{\mathrm{SD}}\, {\mathrm{of}}\, {\mathrm{AUC}}]}}$$\end{document} MOCCS2 score = [AUC] [ ] SD of AUC
In this study, W was set to 250 + 1 – (k/2), because k-mer sequences do not appear at the end of the 250-bp windows. If k = 8, [SD of AUC] was 71.303/C0.5, as shown in the Result section. If k = 6, [SD of AUC] was 71.591/C0.5. The MOCCS2 is freely available via https://github.com/yuifu/moccs↗.
RNA preparation and RNA-Seq analysis
RNA-Seq analysis was performed as previously described45 with minor modifications. The total RNA was prepared from livers of E4bp4-KO/PER2::Luc mice and the littermate PER2::Luc mice at six time points throughout the day (ZT0, 4, 8, 12, 16, and 20; n = 2) by using the TRIzol reagent (Invitrogen) and RNeasy mini kit (QIAGEN) according to the manufacturer’s protocol. Poly(A)-tailed RNA was isolated from the total RNA as the manufacturer’s protocol, and was sequenced on a HiSeq 3000 (36 bp, single end). The mouse genome sequence was obtained from UCSC Genome Browser (mm10, http://genome.ucsc.edu/↗). The annotated gene models (GRCm38) were taken from Ensembl (release 95, http://www.ensembl.org/↗). Hisat2 (v2.1.0) was used for mapping RNA-Seq data with parameter setting of “-p 4 —dta -q -x”46. The expression level of each gene was quantified as fragments per kilobase of exon per million fragments (FPKM) by using both StringTie (v1.3.4) with parameter setting of “-e -G”47 and Ballgown (v2.12.0) with default parameters48. A gene was defined as “expressed” if the average of FPKM values of the 12 samples (6 time points, duplicate) in E4bp4-KO or control mice was higher than 1.0. A gene was defined as “rhythmic” if JTK cycle program49 detected any circadian rhythmicity with p < 0.05.
Quantitative PCR
For quantitative PCR (qPCR) analysis, the ChIP samples were subjected to real-time PCR (Applied Biosystems) using GoTaq Master Mix (Promega) with gene-specific primers (Supplementary Table). For qRT-PCR, the total RNA samples prepared at ZT0, 4, 8, 12, 16, and 20 were reverse transcribed by Go Script Reverse Transcriptase (Promega) with both an anchored (dT)15 primer and a random oligo primer. The cDNA samples were subjected to the qPCR analysis with gene-specific primers (Supplementary Table). 1 1
Dual luciferase reporter assay
HEK293T17 cells in 24-well plates were transiently transfected by using polyethylenimine (Polysciences, #24765) with 100 ng Flag-DBP/pSG5 or Flag-E4BP4/pSG5 in combination with 10 ng of firefly luciferase reporter plasmids and 0.5 ng of a Renilla luciferase plasmid (pRL-SV40) as an internal control. The total amount of DNA was adjusted to 410.5 ng by adding the empty expression plasmid pSG5. A triple tandem repeat of one of D-box sequences was inserted into a BglII site of a firefly luciferase reporter plasmid (pGL3N) as previously described11. The inserted sequences were shown in Supplementary Table 1. The transfected cells were collected 36 h after the transfection and subjected to the dual luciferase assay according to the manufacturer’s protocol with the aid of a fluorescence plate reader (Promega GloMax). Internal control was used to normalize the transfection efficiency.
Real-time monitoring of cellular rhythms and acidification
Cellular bioluminescence rhythms were monitored as described previously50 with minor modifications. In brief, MEFs were prepared from PER2::LUC knock-in mice37. The MEFs were maintained at 37 °C under 5% CO2, 95% air in Dulbecco’s modified Eagle’s medium (SIGMA) supplemented with 25 units/ml penicillin, 25 µg/ml streptomycin, and 10% fetal bovine serum. PER2::Luc MEFs were plated on 35-mm dishes (1.0 × 106 cells/dish) and cultured at 37 °C under 5% CO2. After 24 hr, the cells were treated with 0.1 µM (final) dexamethasone (Dex) for 2 h, and then the media were replaced by a recording media (phenol-red free Dulbecco’s modified Eagle’s medium (SIGMA) supplemented with 10% fetal bovine serum, 3.5 g/l glucose, 25 U/ml penicillin, 25 µg/ml streptomycin, 0.1 mM luciferin, and 10 mM HEPES-NaOH; pH 7.0). The bioluminescence signals of the cultured cells were recorded continuously for 5–10 days at 37 °C in air with Dish Type Luminescencer, Kronos (Atto, AB-2500 or AB-2550) or LumiCycle (Actimetrics).
For acid treatment, extracellular pH (pHo) was shifted from 7.0 to 6.6 by adding a minimal volume of 1 M HCl solution to the cultured media as previously described20. In control experiments, the same volume of water was added (H2O). Circadian time (CT) 0 was defined as the time points of the troughs of the bioluminescence signal waveforms. The phase shifts were calculated from the time of peaks and troughs of the bioluminescence rhythms.
Reporting summary
Further information on research design is available in thelinked to this article. Nature Research Reporting Summary
Supplementary information
Supplementary Information Description of additional supplementary items Reporting Summary Supplementary Data 1 Supplementary Data 2 Supplementary Data 3 Supplementary Data 4 Supplementary Data 5