Significance Circadian coordination of food availability, energy expenditure, and lipid metabolism is crucial for metabolic adaptation to environmental challenges. Here, we demonstrate that chronic cold temperature causes new circadian rhythms of de novo lipogenesis in brown adipose tissue (BAT). These cyclic changes are caused by a cold-induced rhythm of transcription factor SREBP1c, which is required for maximal thermogenesis and maintenance of body temperature both at the time of the physiological circadian trough as well as when food is unavailable during chronic cold exposure. Our findings demonstrate the circadian plasticity of lipid metabolism in BAT during chronic cold and the unexpected requirement of fatty acid synthesis for chronic maintenance of thermogenesis, suggesting strategies for increasing energy expenditure to combat metabolic diseases.

Abstract Ambient temperature influences the molecular clock and lipid metabolism, but the impact of chronic cold exposure on circadian lipid metabolism in thermogenic brown adipose tissue (BAT) has not been studied. Here we show that during chronic cold exposure (1 wk at 4 °C), genes controlling de novo lipogenesis (DNL) including Srebp1, the master transcriptional regulator of DNL, acquired high-amplitude circadian rhythms in thermogenic BAT. These conditions activated mechanistic target of rapamycin 1 (mTORC1), an inducer of Srebp1 expression, and engaged circadian transcriptional repressors REV-ERBα and β as rhythmic regulators of Srebp1 in BAT. SREBP was required in BAT for the thermogenic response to norepinephrine, and depletion of SREBP prevented maintenance of body temperature both during circadian cycles as well as during fasting of chronically cold mice. By contrast, deletion of REV-ERBα and β in BAT allowed mice to maintain their body temperature in chronic cold. Thus, the environmental challenge of prolonged noncircadian exposure to cold temperature induces circadian induction of SREBP1 that drives fuel synthesis in BAT and is necessary to maintain circadian body temperature during chronic cold exposure. The requirement for BAT fatty acid synthesis has broad implications for adaptation to cold.

Circadian rhythms orchestrate numerous physiological processes and behaviors, allowing coordinated anticipation and adaptation to environmental challenges. Several external environmental cues entrain the central and peripheral clocks including food availability, light, and temperature (1). The perturbation of these zeitgebers can induce pathologic misalignments that predispose both humans and mice to metabolic disorders including obesity and type 2 diabetes, hypertension, and cancer (2⇓–4).

Homeostatic regulation of body temperature in response to cold environments is controlled by thermogenic brown adipose tissue (BAT), particularly in rodents, although it is increasingly clear that humans have functional brown adipocytes (5, 6). Circadian rhythm of BAT activity regulates circadian body temperature and circadian cold sensitivity (7⇓⇓⇓–11), allowing mammals to live in near-freezing temperature by a profound remodeling of lipid metabolism and an impressive increase in metabolic rate and heat production (12⇓–14). Time-of-day modulation of substrate mobilization and oxidation during acute cold exposure has been reported (8), but the impact of chronic cold exposure on circadian regulation of lipid metabolism in BAT has not been explored to date.

We recently noted that long-term exposure to an obesogenic diet amplified and synchronized circadian rhythms of genes controlling fat synthesis and oxidation in liver, without a similar effect in adipose tissue (15), indicating that chronic noncircadian environmental challenges can alter circadian metabolism in a tissue-specific manner. Here we have investigated the effect of constant, chronic cold temperature on circadian rhythms of gene expression. Remarkably, expression of genes critical for fatty acid oxidation (FAO) and de novo lipogenesis (DNL) gene expression, as well as the master transcriptional regulator of DNL, Srebp1, acquired high-amplitude circadian rhythms in BAT, but not in liver upon chronic cold exposure. These conditions activated mechanistic target of rapamycin 1 (mTORC1), an inducer of Srebp1 expression, and engaged circadian transcriptional repressors REV-ERBα and β as rhythmic regulators of Srebp1. Moreover, we show that BAT SREBP activity was necessary for maximal thermogenic capacity and maintenance of body temperature during the light phase and fasting.

Discussion We have demonstrated that chronic cold exposure induces a profound remodeling of lipid metabolism in thermogenic BAT. Both DNL and FAO gene expression acquire high-amplitude circadian rhythms, as does the master lipogenic transcriptional factor SREBP1. During chronic cold housing, SREBP activity is necessary for DNL gene expression, maximal thermogenic capacity, and maintenance of body temperature during the light phase and fasting. The high-amplitude circadian rhythms of DNL and FAO gene expression in BAT of mice exposed to chronic cold is reminiscent of the finding that chronic overnutrition induces in-phase circadian rhythms of DNL and FAO in liver (15) and suggests that this adaptive mechanism may be a general feature of tissue-specific physiological responses to chronic metabolic challenges from the environment. In BAT, our results suggest that chronic cold exposure leads to a phase shift in expression and enhanced genomic binding of REV-ERBα that impose circadian rhythmicity on the expression of SREBP and its target genes that are simultaneously activated by the mTORC1 pathway (Fig. 7). We did not investigate the effect of rapamycin treatment on DNL during acute and chronic cold exposure because mTORC1 presents pleotropic effects, including mitochondrial biogenesis, oxidative metabolism, TCA, and nucleotide synthesis (33). Fig. 7. Model depicting the circadian regulation of DNL by chronic cold exposure. In response to chronic cold stimulation, mTORC1 pathway is activated and triggers SREBP activity, as previously described (28⇓–30). In parallel, chronic cold shift-advances REV-ERBα expression to the light phase and remodels its cistrome, targeting SREBP and DNL gene induction. Continuous activation of SREBP by mTORC1 combined with its circadian inhibition by REV-ERB results in the circadian expression of SREBP and DNL genes, which maximize thermogenic capacity and maintain body temperature during the light phase and fasting. Our results demonstrate that BAT REV-ERBα and β regulated expression of SREBP1/DNL genes and allowed mice to maintain their body temperature during fasting in chronic cold exposure. The mechanisms underlying the changes in REV-ERB expression and genomic binding near metabolic circadian target genes during chronic cold exposure remain to be determined, but could indicate a role for cold-induced cooperating transcription or posttranslational modifications of REV-ERBα. Of note, the REV-ERBα/β deletion occurred during development (Ucp1-Cre), whereas SCAP deletion was induced in BAT by tamoxifen treatment prior to chronic cold exposure (Ucp1-CreER), such that Cre activity would not be increased in cold-induced BAT-like adipocytes in iWAT. Nevertheless, our findings demonstrate the circadian plasticity of lipid metabolism in BAT during chronic cold and, moreover, that DNL in BAT plays an important role in maintaining fuel sources under these conditions. FAO is essential for BAT thermogenesis (13, 14, 43, 44), but the relative importance of circulating versus intracellular de novo synthesized lipids, as a fuel source, is not well understood. Previous studies have also demonstrated induction of DNL in thermogenic BAT (16, 17, 45⇓–47). Here, we report that these changes in lipid metabolism are circadian. Moreover, our findings reveal a cold-induced circadian rhythm of SREBP1c by REV-ERBα that is required for the rhythmic increase in DNL genes, as well as Chrebpß, another powerful inducer of DNL (46). Physiologically, SREBP was required for maintenance of body temperature during chronic cold exposure, both at the time of the physiological circadian trough as well as when food was unavailable. The reliance on increased DNL as a physiological adaptation to cold temperature reveals that two other well-known sources of fuel in BAT (i.e., fatty acids derived from lipolysis in WAT as well as glucose-generated electrons through glycolysis) are insufficient to maintain body temperature under these conditions. Of note, Guilherme et al. (48) recently demonstrated that DNL in BAT is not necessary to maintain euthermia during acute cold exposure. The present findings are consistent with these results, as the SCAP-deficient mice survived the acute phase of cold exposure in our studies. Interestingly, lipolytic regulators ATGL and CGI-58 have been found to be dispensable for BAT thermogenesis (41, 49), raising the possibility that newly synthesized SREBP/CHREBP-dependent fatty acids are directly oxidized. Our findings of simultaneous induction of FAO and DNL are consistent with earlier studies showing that adrenergic stimulation induces both FAO and DNL (16, 17, 45⇓–47). In their elegant studies, McGarry and Foster characterized simultaneous fatty acid synthesis and oxidation as a futile cycle that wastes energy and produces heat and suggested that this is prevented in liver by malonyl CoA inhibition of carnitine palmitoyltransferase 1 (50, 51). The mechanisms overriding malonyl CoA inhibition of CPT1 in BAT are not clear at this time. However, given the physiological role of BAT as a thermogenic organ, heat production by cycling of DNL and FAO could represent an adaptive response to chronic cold. Indeed, BAT lacking ANGPTL3/8 has recently been shown to exhibit simultaneous induction of DNL and FAO (52). Thus cold-induced synchronization of both DNL and FAO is likely an adaptive response to the high energy demand. The survival disadvantage of BAT-specific KO of Scap/Srebp during fasting under chronic cold conditions strongly supports this hypothesis. The revelation that fatty acid synthesis in BAT is required for long-term adaptation to cold and could be a fuel source for BAT thermogenesis suggests strategies for increasing energy expenditure to combat metabolic diseases.

Methods Mice. All animal studies were performed under protocols approved by the University of Pennsylvania Perelman School of Medicine Institutional Animal Care and Use Committee. Mice were group-housed in a temperature- and humidity-controlled, specific-pathogen–free animal facility at 22 °C under a 12:12-h light–dark cycle (lights on at 7 AM, lights off at 7 PM) with free access to standard chow (LabDiet, 5010) and water. All experiments were carried out on 11- to 14-wk-old male littermates. Wild-type C57BL/6J male mice were obtained from Jackson Labs Technologies, Inc. ScapFlox/Flox mice (25) were backcrossed to the C57BL/6J genetic background for at least 7 generations (kindly provided by Tim Osborne, Johns Hopkins All Children’s Hospital, St. Petersburg, FL). ScapFlox/Flox mice were bred to Ucp1-CreER mice on a C57BL/6J background [kindly provided by David Guertin, University of Massachusetts Medical School, Worcester, MA with generous permission from Christian Wolfrum, ETH Zürich, Zürich, Switzerland (35)]. To induce the expression of the Ucp1-CreER, 6-wk-old mice were injected i.p. for 5 d with 1.5 mg/mouse/day of tamoxifen dissolved in castor oil/ethanol (9:1 vol/vol). Both ScapFlox/FloxUcp1-CreER+ and ScapFlox/FloxUcp1-CreER- mice (control) were injected with tamoxifen. Rev-erbαfl/fl/Rev-erbβfl/fl mice (27) were bred to Ucp1-Cre mice maintained on a C57BL/6J background (Jackson Labs Technologies, Inc., B6.FVB-Tg[Ucp1-Cre]1Evdr/J, Stock 024670). Generation of Epitope-Tagged REV-ERBα Mice by CRISPR. To generate Cas9 mRNA, a plasmid containing Cas9-HA-2NLS was linearized with XbaI (gift from Jorge Henao-Mejia, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA). Approximately 1 μg of linearized plasmid was incubated with HiScribeTM T7 Quick High Yield RNA Synthesis kit (NEB #E2050S). RNA was purified using RNeasy mini columns (Qiagen #74106), and the capping reaction used Vaccinia Capping System (NEB #M2080S). RNA was purified using RNeasy Micro clean-up columns (Qiagen #74004). Capped Cas9 mRNA was then subject to polyadenylation (NEB #M0276S) and purified over a RNeasy Micro clean-up column and eluted in RNase-free water. Cas9 mRNA integrity was validated using RNA BioAnalyzer. T7 promoter was added onto gRNA template targeting the ATG start site by PCR amplification using specific primers (targeting guide sequence: TGGTGAAGACATGACGACCC). The T7-sgRNA product was purified using a PCR purification kit (Qiagen) and used as the template for in vitro transcription using the MegaShortScript kit (Life Technologies) following the manufacturer’s instructions. Subsequent sgRNA was purified using the MegaClear Kit (Life Technologies) and verified by RNA BioAnalyzer before dilution for microinjection. The ssDNA homology donor (IDT) containing the 3xHA tag was resuspended in water and prepared using DNA Clean and Concentrator (Zymo): A*G*T*TTGTGTCAAGGTCCAGTTTGAATGACCGCTTTCAGCTGGTGAAGACATGTATCCATACGATGTTCCTGACTATGCGGGCTATCCCTATGACGTCCCGGACTATGCAGGATCGTATCCTTATGACGTTCCAGATTACGCTGGCACGACCCTCGACTCCAATAACAACACAGGTACTGAGATTCTTATCTTTGCTC*T*G*T. Microinjection was performed by the Transgenic and Chimeric Mouse Facility at the University of Pennsylvania using C57BL/6J mice from JAX. Microinjection buffer consisted of 1 mM Tris pH 8.0, 0.1 mM EDTA, 100 ng/μL Cas9 mRNA, 50 ng/μL sgRNA, and 100 ng/μL of ssDNA homology donor. Insertion of epitope tag coding sequence was detected by PCR and confirmed by Sanger sequencing. HA-REV-ERBα mice were backcrossed to the C57BL/6J genetic background for at least 7 to 8 generations and genotyped using the PCR primers 5′-TAAGCCTTGGATGGAAATGG-3′ and 3′-AGCCACCCCAAGACCTTACT-5′. Cold Exposure and Core Body Temperature Measurements. Mice acclimated at 22 °C were placed in single-housed cages at 4 to 5 °C or 29 °C for 1 wk. After 5 to 6 d in cold, rectal temperatures were recorded as previously described (53). For the fasting experiments in the cold, mice were housed for 6 d at 4 °C, and the food was removed for 5 to 6 h at ZT1 (8 AM) on day 7. In Vivo Metabolic Phenotyping. Whole-body energy metabolism was evaluated using a Comprehensive Lab Animal Monitoring System (CLAMS, Columbia Instruments), as previously described (53). Mice maintained at 29 °C or 4 °C for 2 d were singly housed in metabolic chambers at 29 °C or 4 °C. Mice were acclimated for 48 h, and data were collected at days 5, 6, and 7 of thermoneutrality or cold housing. Whole-Animal Energy Expenditure in Response to Norepinephrine. After housing at 29 °C or 4 °C during 1 wk of 12-wk-old male mice, oxygen-consumption rates and heat production were measured in response to norepinephrine using Comprehensive Laboratory Animal Monitoring System (CLAMS, Columbus Instruments), as previously described (54). RNA Isolation and Gene Expression Analysis (RT-qPCR). Total RNA was isolated from snap-frozen brown adipose tissue, white adipose tissue, and liver as previously described (53). All qPCR data were analyzed using a standard curve and normalized to 36B4 (Arbp) expression. Specific primer sequences are listed in SI Appendix, Table S1. For circadian gene expression, results are expressed relative to the mean of biological replicates at ZT10 29 °C, which was set to 1. Western Blot. BAT samples were homogenized as previously described (53). For SREBP1, nuclear enrichment was performed in mouse BAT as previously described (55). Western blot images were images using Bio-Rad ChemiDoc Imaging Systems and analyzed by Image Lab software (v5.2). Antibodies used are listed in SI Appendix, Table S1. Measurement of Triglycerides and Insulin. For TG measurement, brown adipose tissues were homogenized in lysis buffer (140 mM NaCl, 50 mM Tris pH 7.4, and 1% Triton X-100). TG concentration was then measured in both BAT and blood serum using the LiquiColor Triglyceride kit following the manufacturer’s protocol (StanBio). Insulin was measured in blood serum using mouse ultrasensitive ELISA kit (Crystal Chem). Histology. Histological procedures were performed as previously described (53) by the Penn Histology and Gene Expression Core. Chromatin Immunoprecipitation. HA-REV-ERBα ChIP was performed as previously described (53). HA magnetic beads (Pierce, 88837) were used to perform the immunoprecipitation. For BAT ChIP-seq of HA-REV-ERBα, 4 biological replicates ChIPs were pooled for sequencing, and WT mice were used as negative control. The Chip-seq library has been performed as previously described (53). ChIP-seq Data Analysis. Sequencing reads of individual biological replicates were aligned to the mouse mm9 genome build using bowtie2-2.1.0, allowing for one mismatch (-N1) and reporting the best alignment (-k1). Tag directories were generated from alignment files using homer-v4.10.1, with a fragment length of 150 base pairs, allowing a maximum of 1 tag per base pair to remove redundant reads. Tag directories from individual replicates were pooled together to generate pooled tag directories without the -tbp 1 option. Peaks were called with homer-v4.10.1 findPeaks with default parameters using the corresponding pooled WT samples as input. Visualization tracks were generated using homer-v4.10.1 with the following parameters (-fsize 5e7, -tbp 1, -res 1, -norm 3e7) and by subtracting the corresponding WT inputs. To retrieve the most significant peaks, peaks called on pooled tag directories were annotated using homer-v4.10.1 annotatePeaks, and tags were counted in pooled tag directories and reported as Fragments Per Kilobase per Million reads (FPKM). Annotated peak files were filtered using R and RStudio (R version 3.5.0 [2018-04-23], Platform: x86_64-apple-darwin15.6.0 [64-bit], Running under: macOS Sierra 10.12.6) to retrieve peaks with an FPKM value greater than 3. For the scatterplot analysis, annotated peaks were transposed to a bed format using homer-v4.10.1 pos2bed Perl script. The resulting files were then concatenated, sorted, and merged using a custom script using bedTools v2.27.1, using a maximum merging distance of 100 base pairs. The resulting file was then annotated using homer-v4.10.1 annotatePeaks using the mouse mm9 genome build as a reference genome, and tags were counted in pooled tag directories and reported as FPKM. Peaks were deemed as shared or selective for one or the other condition based on an HA FPKM/WT FPKM ratio. Genome-browser tracks were generated with IGV 2.3.92. ChIP-seq data have been deposited to Gene Expression Omnibus under accession number GSE128960. Quantification and Statistical Analysis. Data are presented as means ± SEM. To facilitate reading, circadian measurements (gene expression, protein quantification, TG, and insulin levels) were double-plotted. To characterize circadian rhythm in gene expression data, 4-time point datasets were analyzed using JTK_CYCLE (56). As indicated in the respective figure legends, statistical analyses were performed using unpaired 2-tailed t test for comparisons between 2 groups or 2-way analysis of variance (ANOVA) for assessment of variables effects (time, temperature, genotype), with multiple comparisons (Sidak’s multiple comparisons test). All of the statistical analyses were performed with GraphPad Prism software (*P < 0.5, **P < 0.1, ***P < 0.001). RStudio (v1.0.153) software was used for graphing and statistical analysis of sequencing data.

Acknowledgments We gratefully acknowledge R. Papazyan, P. Titchenell, M. J. Emmett, and A. Angueira for valuable discussions. We thank A. Hauck and J. Weaver for critically reading the manuscript. We also thank T. Osborne (Johns Hopkins All Children’s Hospital) for the ScapFlox/Flox mice and D. Guertin (University of Massachusetts Medical School) and C. Wolfrum (ETH Zürich) for the Ucp1-CreER mice. We thank the Penn Histology and Gene Expression Core for help with histology. We thank J. Henao-Mejia, J. Richa, and the Penn Transgenic and Chimeric Mouse Facility for help generating the HA-REV-ERBα mice. This work was supported by NIH R01DK45586, the JPB Foundation, and the Cox Institute for Medical Research (to M.A.L.). M.A. was supported by American Diabetes Association Training Grants (1-18-PDF-126).

Footnotes Author contributions: M.A. and M.A.L. designed research; M.A., B.J.C., and L.C.P. performed research; M.A., J.R.R., and H.J.R. contributed new reagents/analytic tools; M.A., B.J.C., Y.A., L.C.P., and M.A.L. analyzed data; and M.A. and M.A.L. wrote the paper.

Reviewers: J.B., Northwestern University Medical School; and D.D.M., Baylor College of Medicine.

Conflict of interest statement: The sponsor declares a conflict of interest. M.A.L. is a scientific advisory board member for Pfizer and Lilly and receives research support from Pfizer unrelated to the present work. The authors declare a conflict of interest. M.A.L. is an advisory board member for Eli Lilly and Pfizer Inc., consultant to Novartis, and receives support from Pfizer for research not overlapping with the work reported here. Joseph Bass and M.A.L. are coauthors on a 2016 review article.

Data deposition: ChIP-seq data have been deposited to Gene Expression Omnibus (accession no. GSE128960).

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