Compositions and methods for regulating adipocytes

Abstract

In one aspect, a method of suppressing expression of JunB in BAT adipocytes is disclosed. In another aspect, a method of interfering with JunB binding to a tetradecanoylphorbol-13-acetate-responsive element (TRE) is disclosed. In either aspect, the methods may be used to increase high-thermogenic adipocytes in brown adipose tissue (BAT), decrease low-thermogenic adipocytes in brown adipose tissue (BAT), enhance basal or cold-induced energy expenditure in a subject, treat diet-induced obesity in a subject, and / or treat insulin resistance in a subject.

Description

[0001]International Patent Application Attorney Docket No.0310.000185WO01 COMPOSITONS AND METHODS FOR REGULATING ADIPOCYTES CROSS-REFERENCE TO RELATED APPLICATION This application claims the benefit U.S. Provisional Patent Application No.63 / 544,662, filed October 18, 2023, the disclosure of which is incorporated by reference herein in its entirety. GOVERNMENT FUNDING This invention was made with government support under DK132643 and DK110439 awarded by the National Institutes of Health. The government has certain rights in the invention. SEQUENCE LISTING This application contains a Sequence Listing electronically submitted via Patent Center to the United States Patent and Trademark Office as an .xml file entitled “0310.000185WO01 Sequence Listing.xml” having a size of 36 kilobytes and created on October 8, 2024. The information contained in the Sequence Listing is incorporated by reference herein. SUMMARY This disclosure describes, in one aspect, a method of increasing high-thermogenic adipocytes in brown adipose tissue (BAT). Generally, the method includes suppressing expression of JunB in BAT adipocytes. In another aspect, this disclosure describes a method of decreasing low-thermogenic adipocytes in BAT. Generally, the method includes suppressing expression of JunB in BAT adipocytes. In another aspect, this disclosure describes a method of enhancing basal or cold-induced energy expenditure in a subject. Generally, the method includes suppressing expression of JunB BAT adipocytes in the subject. In another aspect, this disclosure describes a method of treating diet-induced obesity in a subject. Generally, the method includes suppressing expression of JunB in BAT adipocytes in the subject. In another aspect, this disclosure describes a method of treating insulin resistance in a subject. Generally, the method includes suppressing expression of JunB in BAT adipocytes in the subject. In another aspect, this disclosure describes a method of increasing high-thermogenic adipocytes in BAT. Generally, the method includes interfering with JunB binding to a tetradecanoylphorbol-13-acetate-responsive element (TRE). In another aspect, this disclosure describes a method of decreasing low-thermogenic adipocytes in BAT. Generally, the method includes interfering with JunB binding to a TRE. In another aspect, this disclosure describes a method of enhancing basal or cold-induced energy expenditure in a subject. Generally, the method includes interfering with JunB binding to a TRE. In another aspect, this disclosure describes a method of treating diet-induced obesity in a subject. Generally, the method includes interfering with JunB binding to a TRE. In another aspect, this disclosure describes a method of treating insulin resistance in a subject, Generally, the method includes interfering with JunB binding to a TRE. The above summary is not intended to describe each disclosed embodiment or every implementation of the present invention. The description that follows more particularly exemplifies illustrative embodiments. In several places throughout the application, guidance is provided through lists of examples, which examples can be used in various combinations. In each instance, the recited list serves only as a representative group and should not be interpreted as an exclusive list. BRIEF DESCRIPTION OF THE FIGURES FIG.1. JunB expression in thermogenic fat is positively correlated with obesity. (A) mRNA levels of JunB, Jun, JunD, and UCP1 in gWAT, iWAT and BAT of 10-week-old male mice. (B) Protein levels of JunB, Jun, JunD, and UCP1 in gWAT, iWAT and BAT of 10-week-old male mice. (C) JunB protein expression was induced in the deep neck fat of obese patients. (D) The quantified data of JunB expression in (C). (E) mRNA levels of JunB in human deep neck fat positively correlated with body fat (%). (F) mRNA levels of JunB in human deep neck fat positively correlated with BMI. (G) Protein levels of JunB in brown fat positively correlated with Body Weight (BW) in rodents. (H) Protein levels of JunB in brown fat were positively correlated with Fat Mass (FM) in rodents. (I) The mRNA levels of JunB in the BAT fractions of adipocyte and stromal vascular fraction (SVF) were enhanced in diet-induced obesity. (J) Expression of JunB mRNA was induced by treatment with 20 ng / ml IL-6 or 20 ng / ml TNFα for 24 hours in Day 6 differentiated brown adipocytes. (K) Expression of JunB protein was induced by the treatment of 20 ng / ml IL-6 or 20 ng / ml TNFα for 24 hours in Day 6 differentiated brown adipocytes. The data in (K) was the representative data from three individual experiments. All data in this figure were analyzed by T-Test and are presented as mean ±SEM. *P<0.05 or **P<0.01. FIG.2. A distinct adipocyte subset that expresses JunB is present in the brown and inguinal fat depots and increased by obesity in abundance. (A) Immunostaining shows the localization of JunB+adipocytes in BAT, iWAT and gWAT of AdipoChaser mice. Antibodies against JunB (Red), Adipoq (Green), Perilipin 1 (White) and Nucleus (Blue) were used for the staining. (B) Quantification of JunB-expressing adipocytes in various fat depots as indicated in (A). (C) Immunostaining of BAT from mice fed with NC or HFD for 4 weeks. Antibodies recognizing JunB (Red), Plin1 (Green) Nucleus (Blue) were used. (D) Quantification of BAT JunB-expressing adipocytes in (C). (E) The generation strategy of JunBChaser-YFPmouse. (F) YFP- expressing adipocytes (Green) were more enriched in BAT, albeit in modest numbers in iWAT and gWAT in JunBChaser-YFPmice. Perilipin 1 (Red) and Nucleus (Blue). (G) YFP+adipocytes were increased in BAT of JunBChaser-YFPmouse post 4-week HFD feeding. Antibodies recognizing YFP (Green), Perilipin 1 (Red) and Nucleus (Blue) were used. (H) Quantification of BAT YFP+adipocytes in (G). (I) YFP+adipocytes (Green) were increased by the treatment of 20 ng / ml TNFα or 20 ng / ml IL-6 for 24 hours in primary differentiated brown adipocytes. (J) Quantification of YFP+adipocytes in (I). n=3 / group for (A), (C), (F), (G) and (I) is the representative data from three individual experiments. Microscopic pictures (20x objective) were taken. Data in (B), (D), (H), and (J) are presented as mean ±SEM. T-Test was used to analyze the data. *P<0.05, **P<0.01. Data represent mean ± SEM. *P<0.05. FIG.3. Adipose-specific JunB deficient (JunB FKO) mice exhibit enhanced thermogenesis and cold adaptation. (A) Expression of JunB protein in BAT and WAT was suppressed by depletion of JunB in adipocyte with little effect on other tissues. Mus, skeletal muscle; Liv, liver; Pan, pancreas; Hyp, hypothalamus; Control, Ctrl. (B) Expression of JunB mRNA in BAT and WAT was suppressed by depletion of JunB in adipocyte with little effect on other tissues. Mus, skeletal muscle; Liv, liver; Pan, pancreas; Hyp, hypothalamus; Control, Ctrl. (C) JunB deficiency enhanced cold-induced oxygen consumption at both light and dark cycles. (D) Data analysis of oxygen consumption from (C) using CaIR software. (E) JunB deficiency prevented the decrease in core body temperature under cold stress conditions. (F) JunB deficiency induced mRNA expression of mitochondria and thermogenic markers in BAT compared to controls. (G) Depletion of JunB increased the average copy number of mitochondria and the proportion of high-mitochondria cells in BAT (n=4 / group). LD, lipid droplet; N, nucleus. (H) Quantification of mitochondria number in individual cells from (G). (I) JunB deficiency significantly increased the ratio of mtDNA / nDNA. (J) Elimination of JunB+adipocytes significantly increased oxygen consumption at both light and dark cycles. (K) Analysis of oxygen consumption from (J) using CaIR. Data in (E) and (H) were analyzed by ANOVA analysis, and data in the rest of the panels were analyzed by T-Test. Data are presented as the mean ±SEM. *P<0.05 or **P<0.01. FIG.4. Specific depletion of JunB in UCP1+adipocyte (JunB BKO) enhances energy expenditure and protects against diet-induced obesity and insulin resistance. Six-weeks-old male JunB BKO and control mice were fed with HFD for 16 weeks for the following studies. Control, Ctrl. (A) JunB deficiency in UCP1+cells protected against HFD-induced obesity. (B) JunB BKO mice displayed decreased body mass, fat mass and fat percentage compared to control littermates after HFD feeding. The lean mass, fat mass, total mass and fat percentage were measured using DEXA scanning. (C) The mass of eWAT, iWAT, BAT and Liver were reduced by JunB deficiency after HFD feeding. The organs were weighed after mice were euthanized. (D) Representative images of gWAT, iWAT, BAT, and liver in JunB BKO and control mice. (E) H&E staining of gWAT, iWAT and BAT of HFD-fed JunB BKO and control mice. (F) Quantification of fat cell size of HFD-fed JunB BKO and control mice in (E). (G) Depletion of JunB in UCP1+adipocytes improved glucose tolerance. (H) Depletion of JunB in UCP1+adipocytes improved insulin tolerance. (I) JunB BKO mice displayed improved diet-induced hepatic steatosis and fatty liver as reflected in the H&E staining and Bodipy / DAPI immunofluorescence staining. (J) Quantification of lipid droplets area in the liver in (I). Data in (A), (F), (G) and (H) were analyzed by ANOVA analysis; data in (B), (C), and (J) were analyzed by T-Test. Data are presented as the mean ± SEM. *P < 0.05; **P < 0.01. FIG.5. JunB deficiency induces a shift of low to high-thermogenic adipocytes in BAT. (A) Uniform manifold approximation and projection (UMAP) plots and 7 distinct cell clusters of BAT by unsupervised clustering. (B) Dot plot showing the average expression of marker genes for each cluster in BAT. (C) UMAP showing the 10 adipocyte subpopulations formed by 8324 nuclei (4177 for Control, 4147 for KO). (D) Violin plots for Adipoq, Ucp1, Ppargc1α, and marker genes for each subpopulation of adipocytes. Expression level (y axis) refers to the log normalized ratio of gene-expression reads, normalized to the sum of all reads within each nucleus. (E) UMAPs of adipocytes for control and KO BAT and the percentage of each adipocyte fraction in total adipocytes. (F) Analysis of UCP1high, UCP1mid-high, and UCP1lowadiponectin positive cells in JunB KO BAT. -, control; +, FKO. Neg, negative. n=5 / group. (G) Quantification of UCP1high, UCP1mid-high, and UCP1lowadiponectin positive cells in (F). (H) The fraction of Pgc1αhighadiponectin+cell was increased in JunB KO BAT. (I) The number of high mitochondria content cells in isolated adipocyte fraction was significantly increased in JunB KO BAT. (J) Quantification of mitochondriahighadipocytes in (I). (K) JunB deficiency increased the mitochondria mass indicated by the fluorescence staining of MitoTracker using high-content cell scanning system. Primary differentiated JunB KO and control brown adipocytes were incubated with 100 nM Mitotracker for 20 min. (L) Quantification of mitochondria intensity per cell in (K). Data in (J) and (L) were analyzed by T-Test. Data are presented with means ± S.E.M. * p<0.05. FIG.6. JunB suppresses the formation of high-thermogenic adipocytes by binding to PGC1α effector ERRα. (A) The JunB binding site on Errα promoter at -1305 / -1315 region is underlined. WT: nucleotides 3 through 21 of SEQ ID NO:5; Mut: nucleotides 3 through 22 of SEQ ID NO:7. (B) Overexpression of JunB suppressed basal and PGC1α-induced activation of Errα promoter in HEK293T cells. (C) Knock down of JunB increased basal and PGC1α-induced activation of Errα promoter in primary preadipocytes. (D) ChIP assay showed that JunB bound to the Errα promoter in brown adipose tissue. (E) The electrophoretic mobility shift assay (EMSA) showed the direct interaction between JunB recombinant protein and DNA probe of Errα promoter at-1305 / -1315 region. (F) The ability of JunB to induce basal and PGC1α- induced Errα gene activation was blocked when the TRE site is mutated on the luciferase reporter of Errα promoter. (G) The ability of JunB to induce basal and PGC1α-induced Errα gene activation was blocked when the TRE site was depleted on the luciferase reporter of Errα promoter. (H) Suppressing JunB increased the mRNA of ERRα in primary preadipocytes. (I) Suppressing ERRα abolished increased oxygen consumption in JunB KO differentiated brown adipocytes. (J) The effect of suppressing ERRα on maximum respiration capacity in JunB KO differentiated brown adipocytes. (K) The effect of suppressing ERRα on mitochondriahighadipocytes in JunB KO differentiated brown adipocytes. (L) The effect of suppressing ERRα on mitochondriahighadipocytes in JunB KO differentiated brown adipocytes. Data in this figure were analyzed by T-Test and are presented as mean±S.E.M. * p<0.05, **P<0.01. FIG.7. JunB suppresses BAT mitochondrial biogenesis and energy expenditure through ERRα in vivo. (A) Diagram of the following animal study. (B) Administration of AAV-shRNA- Errα into BAT significantly suppressed ERRα expression compared to scramble group in JunB FKO mice. (C) JunB deficiency-induced cold-induced oxygen consumption was compromised when ERRα was suppressed under cold stress conditions. (D) Data analysis of oxygen consumption from (C) using CaIR software. (E) The upregulated expression levels of UCP1 and TFAM were attenuated by Errα suppression in JunB KO BAT under cold stress conditions. (F) The increased ratio of mtDNA / nDNA was diminished by Errα suppression in JunB KO BAT upon cold stimulation. (G) Suppressing ERRα partially reversed the increase in mitochondria copy number in JunB deficient BAT. (H) Quantification of mitochondria copy number in (G). Data in this figure were analyzed by T-Test and are presented as mean±S.E.M, * p<0.05, **P<0.01. FIG.8. Schematic summary of identification and characterization of JunB-expressing adipocyte subpopulation. FIG.9. The mRNA levels of JunB were upregulated by inhibition of mTORC1 and by obesity in BAT. (A) The layout of fold changes (rapamycin: control) of 96 genes that are cAMP responsive in PCR array analysis. The reverse transcription was performed with total RNA extracted from BAT in mice treated with or without rapamycin (n=3 / group), and then the synthesized cDNAs was used for PCR array analysis. (B) RNA-sequencing gene expression signatures of iWAT from 10-week-old male Raptor KO and control mice. n=2–3 / group. (C) The protein levels of JunB were upregulated by HFD feeding in adipose tissue. (D) mRNA levels of JunB were induced in WAT of HFD-fed mice. (E) mRNA levels of Ucp1 and Pgc1α in human deep neck fat were negatively correlated with BMI. (F) The expression pattern of JunB in adipocyte subsets and APCs in human BAT. (G) JunB is expressed in Plin1-enriched primary differentiated adipocytes. (H) JunB was highly enriched in primary preadipocytes which declined during differentiation. All data in this Figure were analyzed by T-Test and are presented as the mean ±SEM. *P<0.05 or **P<0.01. FIG.10. The JunBChaser mouse model was generated to show the presence of JunB expressing adipocytes in fat. (A) The generation strategy for JunBCreERT2 mice as described in the genomic structure. An internal ribosome entry site (IRES) fused to a CreERT2 fusion gene was inserted downstream of the internal stop codon of Junb gene. (B) Representative tissue distribution of iCre and Junb mRNA in adult JunBCreERT2 transgenic mice as determined by qPCR. (C) Immunofluorescence staining of YFP+cells in liver and pancreas of JunBCreERT2 mice. (D) Imaging shows differentiated YFP+brown adipocytes were present during primary adipogenesis in primary brown adipocytes of JunBCreERT2 mice. (E) Flow cytometry data shows differentiated YFP+brown adipocytes were present during primary adipogenesis in primary brown adipocytes of JunBCreERT2 mice. (F) JunB+adipocytes were increased by the treatment of 20 ng / mL TNFα or 20 ng / mL IL-6 for 24 hours post primary adipogenesis. (G) Quantification of JunB-expressing adipocytes in Figure F. (H) JunB+adipocytes were increased by the treatment of 20 ng / mL TNFα or 20 ng / mL IL-6 for 24 hours post primary adipogenesis. Preadipocytes were isolated from AdipoChaser-YFP mice and differentiated into adipocytes. (I) Quantification of JunB-expressing adipocytes in (H). All data in this Figure were analyzed by T- Test and are presented as the mean ±SEM. *P<0.05 or **P<0.01. FIG.11. Both JunB FKO and BKO mice display enhanced energy expenditure and cold adaptation.10-week-old male were individually housed in Phenotyping Systems (Sable Systems International) coupled with a temperature controllable chamber. (A) Respiratory exchange ratio (RER) was decreased in adipocyte specific JunB KO (JunB FKO) mice compared to control littermates under cold stress conditions. (B) Food intake was only slightly affected by JunB deficiency in fat. (C) shows motor activities were slightly affected by JunB deficiency in fat. (D) mRNA levels of JunB were significantly downregulated in BAT but not in gWAT of UCP1+cell specific JunB KO (JunB BKO) mice compared to the controls. (E) JunB BKO mice exhibited enhanced basal and cold-induced O2 consumption throughout light and dark cycles compared with controls. (F) JunB BKO mice exhibited enhanced basal and cold-induced O2 consumption throughout light and dark cycles compared with controls. (G) There was little difference in food intake between JunB BKO and control mice. (H) Motor activities were slightly reduced under cold stress conditions in JunB BKO mice compared to control mice. (I) JunB deficiency significantly increased oxygen consumption in primary brown adipocytes. (J) JunB deficiency significantly increased oxygen consumption in primary brown adipocytes. (K) Ablation of JunB- expressing adipocytes upregulated the expression levels of UCP1, Ppargc1α, and Errα. Data in (I) were analyzed by ANOVA analysis, and the data in the rest of the panels were analyzed by T- Test and are presented as the mean±SEM. *P<0.05 or **P<0.01. FIG.12. Both JunB FKO and BKO mice exhibit improved diet-induced insulin resistance, while they are distinct in anti-obesity effect. Six-week-old male JunB FKO and control mice were fed with HFD for 16 weeks and used for the studies. (A) The percentage of larger adipocytes was decreased accompanied with an increase in smaller adipocytes in iWAT of HFD-fed JunB BKO mice compared to controls. (B) The percentage of larger adipocytes was decreased accompanied with an increase in smaller adipocytes in BAT of HFD-fed JunB BKO mice compared to controls. (C) Depletion of JunB in adipocytes improved glucose tolerance after 16-week HFD feeding. (D) Depletion of JunB in adipocytes improved insulin tolerance after 16- week HFD feeding. (E) JunB FKO mice displayed improved hepatic steatosis compared with control mice under HFD feeding conditions. (F) JunB FKO mice displayed improved triglyceride content in the liver compared with control mice under HFD feeding conditions. (G) O2consumption was significantly increased in JunB FKO mice compared to controls after feeding with HFD for 12 weeks. (H) O2 consumption was significantly increased in JunB FKO mice compared to controls after feeding with HFD for 12 weeks. Data in (A-D) were analyzed by ANOVA analysis, and data in the rest of the panels were analyzed by T-Test and are presented as the mean ±SEM. *P<0.05 or **P<0.01. FIG.13. Both JunB FKO and BKO mice exhibit improved diet-induced insulin resistance, while they are distinct in anti-obesity effect. Six-week-old male JunB FKO and control mice were fed with HFD for 16 weeks and used for the studies. (A) Under HFD feeding conditions, JunB FKO displayed similar RER compared to control mice. (B) Under HFD feeding conditions, JunB FKO displayed similar food intake compared to control mice. (C) Under HFD feeding conditions, JunB FKO exhibited a significant decrease in motor activities compared to control mice. (D) There was no significant difference in body mass between JunB FKO and control mice when challenged with HFD. (E) There was no significant difference in fat mass or fat percentage between JunB FKO and control mice when challenged with HFD. (F) There was no significant difference in the appearance of individual livers between JunB FKO and control mice when challenged with HFD. (G) There was no significant difference in the weight of individual livers between JunB FKO and control mice when challenged with HFD. Data are presented as the mean ±SEM. *P<0.05 or **P<0.01. FIG.14. JunB deficiency induces a shift of low to high-thermogenic adipocytes in BAT. (A) The sorting strategy of isolated nuclei. The nuclei were first sorted based on forward scatter height (FSC) and side scatter height (SSC), and singlets were then sorted based on the combination of area and heights of FSC followed with sorting of DAPI-positive events used for the snRNA-Seq. (B) Heat map of gene signature for each population of brown adipocyte nuclei (AD1-AD10). (C) Feature plots for Adipoq, JunBI, Ucp1, Ppargc1a, Cyp2e1, Fuca1, Slc12a2, Bmpr1a, Gm19951, Acly, Aco1, Flvcr1, Fam13a, and Kcnd2. FIG.15. JunB deficiency induces a shift of low to high-thermogenic adipocytes in BAT. (A) JunB is mainly expressed in UCP1lowadipocytes. (B) The majority of YFP+(JunB+) differentiated adipocytes are Mitochondriallow, as indicated by the staining with MITOTRACKER (Molecular Probes, Inc., Sunnyvale, CA). (C) Bar graph representation of the flow cytometry data in (B). (D) YFP+(JunB+) differentiated adipocytes showed significantly upregulated expression of thermogenic genes compared to YFP- (JunB-) adipocytes. (E) Partition trajectory of adipocytes analyzed by Monocle (Trapnell et al., 2014, Nature Biotechnology 32:381-386). (F) Pseudotime trajectory of adipocytes analyzed by Monocle. (G) Violin plots for Adipoq, Plin1, JunB, Ucp1, Erra, and Ppargc1α for each sub-population of adipocytes in JunB KO and control BAT. (H) Volcano plot showing the up regulation of Ucp1, Erra, and Ppargc1a in JunB KO BAT compared to control. FIG.16. JunB deficiency induces a shift of low to high-thermogenic adipocytes in BAT. (A) Feature plots for Adipoq, JunB, Ucp1, and Ppargc1a in JunB KO adipocytes and control cells. (B) Mapping the present data sets of BAT snRNAseq with comparative data previously described (Sun et al., Nature 587:98-102 (2020)). (C) UMAP of KO BAT adipocytes and controls after mapping with comparative work previously described (Sun et al., Nature 587:98- 102 (2020)). FIG.17. JunB deficiency induces a shift of low to high-thermogenic adipocytes in BAT. (A) JunB FKO mice displayed increased mitochondriahighand decreased mitochondrialowadipocytes in BAT. LD, lipid droplet; N, nucleus. (B) The quantified data of mitochondriahighand mitochondrialowadipocytes from (A). (C) JunB deficiency had little effect on the primary adipogenesis. (D) Quantification of lipid droplet area of JunB FKO and control primary adipocytes in (C). (E) Gene Set Enrichment Analysis (GSEA) of SnRNA-Seq in JunB FKO and Control mice. Data in (B) were analyzed by ANOVA analysis, and the data in the rest of the panels were analyzed by T-Test. Data are presented as the mean ± SEM. *P < 0.05; **P < 0.01. DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS The coexistence of brown adipocytes with low and high thermogenic activity is a fundamental feature of brown adipose tissue (BAT) heterogeneity and plasticity. However, the mechanisms that govern thermogenic adipocyte heterogeneity and its significance in obesity and metabolic disease have remained poorly understood. This disclosure describes a population of JunB-enriched adipocytes (JunB+adipocytes) within the brown fat depot that exhibits lower thermogenic capacity and smaller lipid droplets compared to high-thermogenic adipocytes. This population of JunB+adipocytes exhibited marked expansion during obesity, possibly mediated by pro-inflammatory cytokines TNFα and IL-6. Depletion of JunB in adipocytes or UCP1+adipocytes increased the fraction of adipocytes exhibiting high mitochondrial content and thermogenic capacity, leading to enhanced basal and cold-induced energy expenditure and protection against diet-induced obesity and insulin resistance. Mechanistically, JunB directly binds to the promoter of estrogen-related receptor α (Errα), a downstream effector of PGC1α, and suppresses its transcriptional function. JunB antagonizes the stimulatory effects of PGC1α- ERRα on mitochondrial biogenesis and high-thermogenic adipocyte formation. Taken together, the studies uncover methods of maintaining systemic metabolic health. The methods involve regulating JunB activity that affects integration of metabolic and inflammatory signals, and / or shapes thermogenic adipocyte heterogeneity. Brown adipose tissue (BAT), which dissipates chemical energy in the form of heat, increases energy expenditure and exerts anti-obesity and cardioprotective properties. Upon activation, brown adipocytes within the BAT also function as an effective energy sink that disposes of excess lipids and glucose, leading to improvements in energy and glucose homeostasis. Distinct subsets of brown adipocytes exist that exhibit a high degree of diversity in identity and function. Low-thermogenic and high-thermogenic adipocytes coexist within BAT. The low- thermogenic brown adipocytes, which do not exhibit typical brown adipocyte morphology (low UCP1 expression and low in mitochondrial content), have a distinct physiological function and display a unique metabolic profile with regard to thermogenic gene expression, mitochondrial content, active metabolic pathways, and the secretome. A subset of obesity-associated brown adipocytes with lower thermogenic capacity has recently been identified in humans, and they have been shown to exert inhibitory effects on their neighboring adipocytes by producing juxtracrine signals. In addition to lower levels of UCP1 and adiponectin expression, and decreased mitochondrial content, the low-thermogenic brown adipocytes also have larger lipid droplets, decreased basal mitochondrial respiration, and specialized fatty acid uptake. Environmental stimuli such as cold stress can promote the conversion of low- thermogenic adipocytes to high-thermogenic adipocytes, yet the underlying mechanisms regulating interconversion of low-thermogenic adipocytes and high-thermogenic adipocytes have not been fully characterized. Transcriptional co-factors PPARγ coactivator-1α (PGC-1α) and PRDM16 are well-studied thermogenic program determinants and have been shown to co- activate C / EBPβ, PPARγ, and PPARα to promote brown fat differentiation and thermogenic gene expression. However, there remains a knowledge gap regarding the developmental patterns of high--thermogenic adipocytes and low-thermogenic adipocytes as well as the interconversion of these unique cell populations. JunB is a member of the Jun transcription factor family (c-Jun, JunB and JunD) and is involved in multiple physiological processes including placentation, bone formation, cell proliferation, inflammation, and skin homeostasis. As part of the activating protein (AP)-1 complex, JunB contains a highly charged DNA binding domain and an amphipathic dimerization domain referred to as a “leucine zipper.” JunB regulates downstream target gene transcription mainly through binding to consensus-specific DNA regulatory elements, namely, tetradecanoylphorbol-13-acetate-responsive elements (TREs) TGA(C / G)TCA. The dysregulation of JunB is associated with various diseases such as atherosclerosis, hepatitis, cardiovascular disease, autoimmune disease, and cancer. The expression and activity of JunB are increased in response to environmental stimuli such as insulin and IL-6 in a variety of cell types, both of which are associated with measures of obesity. This disclosure provides data demonstrating that JunB is enriched in the interscapular BAT vs inguinal WAT (iWAT or beige fat) and gWAT, and only about 3.0% of brown adipocytes express JunB within the brown fat depot. JunB-expressing (JunB+) adipocytes exhibit low-thermogenic (UCP1lowPGC1αlow) properties with smaller lipid droplets and show increased abundance in obesity, possibly mediated by pro-inflammatory cytokines TNFα and IL-6. Depleting JunB in adipocyte or UCP1+cells led to a significant increase in the fraction of high- thermogenic adipocytes, resistance to diet-induced obesity, and a decrease in insulin resistance. Furthermore, JunB antagonizes PGC1α action and suppresses high-thermogenic adipocyte formation by directly binding to the promoter of Errα, a well-known effector of PGC1α. Taken together, JunB directs metabolic and inflammatory signaling in governing thermogenic adipocyte heterogeneity, providing a new mechanism linking inflammation to BAT dysfunction in obesity. This disclosure relates to targeting JunB as a therapeutic approach to increase high-thermogenic adipocytes and to treat obesity and its related metabolic disorders. JunB is highly expressed in BAT and its expression is positively correlated with obesity in humans and rodents Mammalian target of rapamycin complex 1 (mTORC1) is involved in regulating thermogenesis in BAT and iWAT. Data from a microarray assay of cAMP-responsive genes in rapamycin-treated BAT, and RNA-seq analysis of Raptor KO iWAT (FIG.9A, 9B) indicate interaction of mTORC1 and PKA pathways. Both assays indicate that the cAMP-responsive gene Junb, a member of activator protein 1 (AP1) family, is inhibited by mTORC1 in thermogenic fat, indicating a role for JunB in regulating metabolism. To determine if JunB is implicated in obesity, the expression levels of Jun family members JunB, c-Jun, and JunD were examined in various fat depots in mice. The mRNA and protein levels of JunB were notably higher in BAT than that in iWAT and gWAT, while there was no significant difference for the mRNA levels of JunD and c-Jun between various fat depots with a slight increase in their protein levels in BAT (FIG.1A, 1B). Moreover, JunB expression levels were induced by obesity in human deep neck fat and inversely correlated with thermogenic markers UCP1 and PGC1α (FIG. 1C, 1D). In addition, a positive correlation between JunB expression in deep neck fat and fat mass / BMI was previously observed (Sun et al., Nature 587:98-102 (2020)) in a human study despite no significance in the correlation between JunB expression and BMI (FIG.1E, 1F). Such a correlation was also observed in proteomic datasets (FIG.1G, 1H; Xiao, et al., Cell 185:4654- 4673 e4628 (2022)). In line with these results, the protein and mRNA levels of JunB were both induced by HFD in mice (FIG.9C, 9D). In contrast, JunB expression in deep neck fat was inversely correlated with thermogenic markers UCP1 and PGC1α, and JunB was more enriched in stromal vascular fractions (SVFs) than in adipocytes in humans (FIG.9E, 9F; Sun et al., Nature 587:98-102 (2020)). Given the role of JunB in cell proliferation, JunB expression in adipocytes or adipocyte progenitor cells (APCs) was examined. The mRNA levels of JunB in SVFs were higher than in adipocytes isolated from BAT (FIG.1I), while both were upregulated by diet-induced obesity in mouse BAT (FIG.1I). Consistent with this, pro-inflammatory cytokines TNFα and IL6 significantly induced JunB expression in mRNA and protein in brown adipocytes (FIG.1J, 1K). These results indicate that JunB is involved in regulating thermogenesis and obesity development. Subpopulation of adipocytes that express JunB is localized in BAT and iWAT and increased by obesity in abundance The expression of JunB in brown adipocytes was explored in single-cell resolution given its differential expression in SVFs versus adipocytes in humans and rodents (FIG.1I, FIG.9F). Using AdipoChaser-GFP mice, the existence of a distinct population of adiponectin+adipocytes that express JunB was observed primarily in BAT (FIG.2A). Moreover, the percentages of JunB+adipocytes varied in different fat depots, with the highest level (11.8% ± 1.4 %) found in BAT and the lowest level (0.9% ± 0.3%) in gWAT of adult male mice (FIG.2B). The distinct adipocyte population that expresses JunB was localized at both the edge of and within the brown fat pad, although a significant reduction in the number of JunB-positive cells was found in iWAT and gWAT compared to BAT (FIG.2B). The presence of JunB+adipocytes was also evidenced by immunostaining for JunB and perilipin 1 (Plin1) in BAT, and the abundance of JunB+adipocytes in BAT was increased from 8.7% to 24.9% by HFD feeding for four weeks in mice (FIG.2C, 2D). The existence of JunB+adipocytes (multilocular cells) with smaller lipid droplets was also verified by co-staining with the adipocyte marker Plin1 in primary differentiated adipocytes (FIG.9G). Although 87.0 % of inherent SVF cells isolated from BAT were JunB positive, as indicated by immunostaining, the enrichment of JunB+cells was significantly reduced to 16.8% in differentiated adipocytes (FIG.9H). To track the JunB-expressing cells genetically, JunBCreERT2knock-in mice were generated (FIG.2E, FIG.10A). The expression pattern of Junb is aligned with iCre in various tissues in JunBCreERT2mice (FIG.10B), indicating that Cre expression is driven by Junb gene. The JunBChaser-YFP mice were generated by crossing JunBCreERT2knock-in and Rosa26-YFP floxed mice and used to track JunB-expressing cells. Post administration of tamoxifen, 2.3% adipocytes were YFP+in brown fat with lesser number in iWAT and gWAT, and YFP was expressed in the cytoplasm of the cells (FIG.2F). YFP+cells were observed in other tissues such as liver and pancreas (FIG.10C). Moreover, YFP+adipocyte fraction showed a significant increase (4.9%) by 4-week HFD feeding in BAT (FIG.2G, 2H). Consistent with this, 2.5% of differentiated brown adipocytes were YFP+indicated by imaging and flow cytometry post primary adipogenesis (FIG.10D-10E). Moreover, the treatment of TNFα and IL-6 notably increased the fraction of YFP+(or JunB+) adipocytes to 5.5% and 7.9%, respectively (FIG.2I, 2J; FIG.10F-I). These results indicate that JunB+adipocytes are increased by obesity in abundance, possibly mediated by obesity-associated pro- inflammation. JunB deficiency in adipocytes or UCP1+cells enhances thermogenesis and energy expenditure To investigate the in vivo role of JunB in regulating energy metabolism, adipose-specific JunB KO (JunB FKO) mice were generated by crossing JunB-floxed mice with adiponectin-Cre transgenic mice. Adipocyte-specific ablation of JunB led to a robust suppression of JunB in BAT and reduced levels of JunB in gWAT in 10-week-old JunB FKO mice (FIG.3A, 3B) but not in other tissue / organs. JunB deficiency overall increased energy expenditure under room temperature conditions and more pronounced under cold stress despite no significant effect on thermoneutrality (FIG.3C, 3D). Consistent with this, the respiratory exchange ratio was decreased, whereas similar levels of food intake and activity levels were observed in JunB FKO mice compared to control mice (FIG.11A-C). JunB FKO mice also displayed an increased core body temperature during cold exposure (FIG.3E). Moreover, JunB depletion significantly upregulated expression of thermogenic / mitochondria markers UCP1, PGC1α, TFAM and ERRα in BAT concurrent with a significant increase in the fraction of mitochondria-rich adipocytes (FIG.3F-H) and the ratio of mtDNA / nDNA (FIG.3I) in BAT. Consistent with this, the mice lacking JunB in UCP1+cells (JunB BKO) also displayed significantly increased basal and cold- induced O2 consumption with little effect on food intake and a slight decrease in activity (FIG. 11D-H). Additionally, JunB deficiency significantly increased the oxygen consumption rate in primary brown adipocytes (FIG.11I, 11J). Along this line, the elimination of JunB+adipocytes increased oxygen consumption (FIG.3J, K) and thermogenic gene expression (FIG.11K) with little effect on body weight, locomotor activity, and food intake (data not shown) in tamoxifen- treated JunBCreERT2-DTA+mice compared to the controls. The basal oxygen consumption declined in tamoxifen-treated mice compared to non-treated animals (FIG.3J, 3C), which may explain tamoxifen-caused toxicity. These results indicate a role for JunB and JunB-expressing adipocytes in regulating BAT function and energy expenditure. Depletion of JunB in UCP1+cells reduces diet-induced obesity and insulin resistance To further investigate the physiological role of JunB in thermogenic adipocytes, 6-week- old JunB BKO and control mice were fed with a HFD for 16 weeks. JunB BKO mice displayed a significant decrease in body mass, fat mass, and fat percentage during HFD feeding (FIG.4A-D). Moreover, adipocyte size in iWAT, gWAT, and BAT was decreased by JunB deficiency in UCP+adipocyte (FIG.4E, 4F; FIG.12A, 12B). JunB BKO mice exhibited enhanced glucose tolerance and insulin tolerance compared to control mice under HFD conditions (FIG.4G, 4H), suggesting the improved glucose metabolism upon JunB depletion. Consistent with this, diet- induced hepatic steatosis was improved by JunB deficiency in UCP1+cells (FIG.4C, 4D, 4I, and 4J). Similarly, increased insulin sensitivity and diet-induced hepatic steatosis were improved in JunB FKO mice (FIG.12C-F). The increased energy expenditure was also observed in JunB FKO mice with no significant effect on respiratory exchange ratio or food intake following HFD for 16 weeks (FIG.12G, 12H; FIG.13A, 13B). Locomotor activities were decreased in HFD-fed JunB FKO mice, although the difference did not reach significance. The expected protection against obesity is diminished at certain level in FKO mice (FIG.13C-G). These data indicate that JunB regulates BAT function and systemic metabolic homeostasis. JunB deficiency induces a shift from low to high-thermogenic adipocytes in BAT To determine if JunB plays a role in the control of brown adipocyte heterogeneity in thermogenesis, single-nucleus RNA sequencing (snRNA-seq) was performed on BAT from JunB FKO and control mice (3-month-old male mice (5 / group)) housed at room temperature. An integrated analysis and unsupervised clustering of 9863 nuclei (Control=4988, KO=4875) revealed the dominance of adipocyte clusters and subpopulations of epithelial, macrophage, endothelial, pericytes and Adipose Stem and Progenitor Cells (ASPCs), yielding 1040 genes (median) for control and 913 genes for KO (FIG.5A, 5B). Further analysis of adipocytes reveals 10 adipocyte clusters (AD1-AD10), based on the gene signature and distinct marker genes (FIG. 5C, 5D; FIG.14B, 14C; Table 2). The recently discovered Cyp2e1-expressing adipocytes were annotated as the AD1 in the datasets (FIG.5C, 5D). Among those distinct subpopulations, the average expression levels of Ucp1 and Ppargc1α in the clusters AD2, AD3, AD4, and AD10 were notably higher compared with clusters AD1, AD8, and AD9 (FIG.5C, 5D; FIG.14C). The clusters AD5, AD6, and AD7 are the intermediate adipocyte with the mid-range in Ucp1 and Ppargc1α (FIG.5C, 5D; FIG.14C). JunB+cells (3.0% in control sample) were mainly present in the adipocyte fraction with lower thermogenic activities (expression levels <2 described in FIG. 5F; FIG.14C; FIG.15A). Consistent with this observation, primary YFP+differentiated JunB- expressing adipocytes displayed less mitochondrial content (FIG.15B, 15C) and lower thermogenic capacity (FIG.15D). In addition, JunB depletion dramatically increased the fraction of the subpopulation with higher average thermogenic markers (AD4) from 0.4% to 8.1% in BAT (FIG.5E). In support of this, the pseudotime trajectories analysis showed three partitions for adipocyte clusters and that each partition was initiated in the JunB enriched cells with low thermogenic activity and shifted into JunB negative cells with the high thermogenic activity (FIG.15E, 15F). Furthermore, JunB depletion markedly upregulated expression levels of UCP1, PGC1α, and ERRα in the individual clusters (FIG.15G, 15H; FIG.16A). By mapping the datasets with the BAT snRNAseq data previously described (Sun et al., Nature 587:98-102 (2020)), those high-thermogenic adipocyte fractions AD2, AD3, AD4 and AD10 appear to be P1 that favors cold stress, while low-thermogenic adipocyte cluster AD1 shared gene signature with P4, a cluster of adipocytes that is dominant under thermoneutral conditions (FIG.16B). The intermediate adipocytes AD5, AD6, and AD7 and low-thermogenic AD8 are P2-like and associated with room temperature despite that another low-thermogenic cluster AD9 reflected P1 better (FIG.16B). In addition, JunB KO notably increased the fraction of P1, while decreased P2 (FIG.16B, 16C), pointing to a potent inhibition by JunB in the conversion from low- to high- thermogenic adipocyte. Considering that within each individual cluster, the adipocytes varied in the expression of thermogenic genes (FIG.5D), adiponectin+cells that differentially express Ucp1 and Pgc1α were further analyzed. The adiponectin+cells with UCP1high(>or =3), UCP1mid-high(<3 and > or =2), and UCP1low(<2) were defined as high-thermogenic, mid-high-thermogenic (or intermediate), and low-thermogenic adipocytes, respectively (FIG.5F-H). In the control BAT, 45.3% of adipocytes are low-thermogenic (UCP1low), 48.9% of adipocytes are mid-high-thermogenic (or intermediate), and 5.8% of adipocytes are high-thermogenic. However, the depletion of JunB led to a significant increase of high-thermogenic adipocytes from 5.8% to 19.5% and a decrease of low-thermogenic adipocytes from 45.3% to 30.0% despite no significant changes in mid-high (or intermediate) adipocytes (FIG.5F, 5G), indicating a shift from low-thermogenic to high- thermogenic adipocytes. The PGC1αhighadiponectin+cells were also increased in JunB-deficient BAT (FIG.5H). In agreement with this, the fraction of isolated primary adipocytes with high- thermogenic activity, presented by mitochondriahighcells with MitoTracker staining, was increased in JunB-deficient BAT compared to controls (FIG.5I, 5J). Along these lines, depletion of JunB increased the frequency of mitochondriahighcells indicated by MitoTracker staining (FIG.5K, 5L) and Electron Microscopy (FIG.17A, 17B) in differentiated primary brown adipocytes. However, JunB deficiency had little effect on adipogenesis (FIG.17C, 17D). Furthermore, Gene Set Enrichment Analysis (GSEA) of significantly differentially expressed genes also indicates the primary functions of JunB+adipocytes in the regulation of fatty acid metabolism, glycolysis, and mitochondria biogenesis (FIG.17E). These results indicate that JunB is involved in governing adipocyte heterogeneity and thermogenic capacity. JunB represses high-thermogenic adipocyte generation through the PGC1α / ERRα pathway To elucidate the regulatory mechanisms exerted by JunB signaling in high-thermogenic adipocyte formation, a bioinformatic analysis of Ucp1 and mitochondria master regulators Pgc1α, Tfam, and Errα, was performed using JASPAR (http: / / jaspar.genereg.net), a widely-used online bioinformatics tool for analysis of the potential binding sites of transcriptional factor (Khan et al., 2018, Nucleic Acids Res 46:D260-D266). The results showed that there is a JunB binding site TRE (TGA(C / G)TCA) on the Errα promoter (-1305 to -1315) despite no typical TREs on the promoters of Ucp1, Pgc1α, and Tfam (FIG.6A), implying that JunB may suppress mitochondria biogenesis by targeting Errα, a downstream effector of PGC1α that regulates mitochondrial respiration, oxidative phosphorylation, and activation of thermogenic adipocytes. JunB-deficient BAT displayed an enrichment of high-thermogenic adipocytes with higher levels of Errα as well as Ucp1, PGC1α, (FIG.3F; FIG.15D, 15G, 15H; FIG.16A), and overexpressing JunB decreased PGC1α overexpression-induced luciferase activity of the Errα promoter in HEK293 cells (FIG.6B). In contrast, knockdown of JunB increased basal and PGC1α overexpression-induced luciferase activity of the Errα promoter in primary preadipocytes (FIG. 6C). ChIP assays further verified that JunB can bind to Errα promoter region (-1305 to -1315) containing TRE site in BAT (FIG.6D), and electrophoretic mobility shift assay (EMSA) showed the direct interaction between JunB and Errα promoter region (-1305 to -1315) (FIG.6E). Consistent with this, the enhanced PGC1α-mediated activation of the Errα gene by JunB deficiency was abolished by TRE site mutation (FIG.6F) or TRE site depletion (FIG.6G) of the Errα promoter. In support of this, the expression level of ERRα was significantly increased in JunB-suppressed preadipocytes (FIG.6H). Moreover, knockdown of ERRα using ShRNA abolished JunB deficiency-induced oxygen consumption and maximum respiration (FIG.6I, 6J) and increased frequency of mitochondriahighcells (FIG.6K, 6L) in primary differentiated brown adipocytes. These results indicate that JunB suppresses high-thermogenic adipocyte formation by directly binding to the Errα promoter and substantially targeting the PGC1α / ERRα axis. Knockdown of ERRα in BAT abrogates JunB deficiency-induced high-thermogenic adipocyte formation and energy expenditure To dissect the role of ERRα in JunB suppression of high-thermogenic adipocyte formation, metabolic phenotyping was performed three weeks after AAV-ShRNA-ERRα (10 μl of 1013vg / ml) or scramble virus was administered into BAT of JunB FKO and control mice (FIG.7A). The administration of AAV-ShRNA-ERRα significantly suppressed ERRα expression in BAT as shown by qPCR (FIG.7B). Consistent with the in vitro study (FIG.6I, 6J), JunB deficiency-increased energy expenditure was compromised when ERRα was suppressed in BAT despite little effect on activity or food intake under cold stress conditions in vivo (FIG.7C, 7D). In addition, suppressing ERRα attenuated cold-induced expression levels of UCP1 and TFAM in JunB deficient BAT (FIG.7E) and the ratio of mtDNA / nDNA (FIG.7F). Moreover, the increased mitochondrial content was partially reversed by suppression of ERRα in JunB KO primary adipocytes (FIG.7G, 7H), indicating that JunB suppresses thermogenic capacity and energy expenditure via an ERRα-dependent mechanism. This disclosure therefore describes a method of regulating adipocytes in vitro and in vivo. This disclosure describes a mechanism involving JunB that integrates inflammatory and metabolic signals and suppresses the conversion from low-thermogenic to high-thermogenic adipocytes through PGC1α-ERRα pathway. The data presented herein also identify a distinct subpopulation of thermogenic adipocytes that expresses JunB and is associated with obesity and inflammation, representing a novel noncanonical subpopulation of adipocytes that contributes to energy and metabolic health. Suppressing JunB expression causes a detectable shift in low- thermogenic brown adipose tissue (BAT) cells to high-thermogenic BAT cells. JunB is highly expressed in BAT and its expression is positively correlated with obesity in humans and rodent- based models. The subpopulation of adipocytes that express JunB is localized in BAT and iWAT and increases in abundance in obesity. JunB deficiency in adipocytes or UCP1+cells enhances thermogenesis and energy expenditure. Depletion of JunB in UCP1+cells reduces diet-induced obesity and insulin resistance. JunB deficiency induces a shift from low to high-thermogenic adipocytes in BAT. JunB represses high-thermogenic adipocyte generation through the PGC1α / ERRα pathway. Finally, knockdown of ERRα in BAT abrogates JunB deficiency- induced high-thermogenic adipocyte formation and energy expenditure. As demonstrated herein, JunB is shown to be a factor that integrates inflammatory signals and overnutrition to shape thermogenic adipocyte heterogeneity through JunB-expressing adipocytes. The aberrant induction of JunB and JunB-expressing adipocytes contributes to the energy imbalance in obesity. Depleting JunB leads to a notable increase in high-thermogenic adipocytes (over 13% of total adipocytes) in brown fat, although only 3% of total adipocytes expresses JunB (FIG.5F, 5G). The data disclosed herein indicate that JunB-expressing adipocytes influence the thermogenic capacity of surrounding cells. These data also indicate that JunB modulates systemic energy homeostasis through adipocyte-derived factors, given the selective anti-obesity effects of JunB BKO but not JunB FKO (FIG.12; FIG.13). As an activating protein 1 (AP1) family member (Fos, FosB, Fra1, C-Jun, JunB, JunD), JunB is induced by the cAMP / PKA / CREB pathway in various cell types. JunB regulates downstream target gene transcription by binding to two consensus-specific DNA regulatory elements, namely, tetradecanoylphorbol-13-acetate-responsive elements (TREs) TGA(C / G)TCA and cAMP-responsive elements (CREs, CREB binding sites) TGACGTCA, in hepatocytes and cancer cells. Activation of JunB provides a negative regulatory mechanism on β3-adrenoceptor- mediated thermogenic program by targeting PGC1α / ERRα axis. Although there is no canonical JunB binding site TRE on Ucp1 and Pgc1α promoters, the Errα promoter (-1443 to +187) contains a TRE site based on bioinformatics analysis. Through binding to this site, JunB suppresses Errα gene activity and antagonizes the stimulatory effects of PGC1α-ERRα on thermogenesis and mitochondria biogenesis. Together with the inducing effects of pro- inflammatory cytokines TNFα and IL-6 on expression of JunB in BAT as well as JunB+adipocytes (FIG.1J, 1K; FIG.10F-I), the data presented herein indicate a new regulatory mechanism of β3-adrenoceptor-mediated thermogenesis. Distinct from other Jun-family transcription factors such as c-Jun and JunD, which are ubiquitously expressed in all fat depots, JunB is selectively expressed in BAT compared to other fat depots iWAT and gWAT (FIG.1A-K). Despite JunB being involved in the control of adipogenesis in bone marrow and lipolysis in adipose tissue, little had been known about whether JunB plays a direct role in regulating thermogenesis. JunB directly binds to the promoter of Errα, a potent mediator of PGC1α pathway, and suppresses Errα gene activity in brown adipocytes, therefore antagonizing PGC1α-ERRα on thermogenesis and mitochondria function (FIG.7A-H). JunB has previously been characterized as a cAMP-responsive gene and is best known for its role in transcriptional control of cell proliferation and differentiation. The antagonizing effects of JunB on thermogenesis indicate a negative feedback mechanism on cold- induced thermogenesis at the transcriptional level, blocking high-thermogenic adipocyte formation. On the other hand, mTORC1 shows distinct regulatory effects on thermogenesis and energy expenditure in BAT and WAT, and the data indicates JunB partially mediates its inducing effects on BAT thermogenic programming (FIG.9A, 9B). In addition to regulating low-thermogenic and high-thermogenic adipocyte interconversion, the high enrichment of JunB in preadipocytes and its substantial declines during adipogenesis indicates JunB involvement in the early determination of differentiation in preadipocytes (FIG.10D-H). The study reported herein found a positive association between JunB mRNA levels in human neck fat and obesity that is consistent with previously reported observations (FIG.1E, 1F; Sun et al., Nature 587:98-102 (2020)). This study uncovers a noncanonical subpopulation of adipocytes that express JunB with higher abundance in obesity. The aberrant induction of JunB is a checkpoint of impaired BAT function by shaping thermogenic adipocyte heterogeneity. As a transcriptional regulator, JunB integrates inflammatory and metabolic signals and governs the interconversion of low- and high- thermogenic adipocytes via PGC1α-ERRα pathway-dependent mechanisms. These results provide novel insight into the biology of brown adipocytes and a solid foundation to aid in the development of therapeutic interventions for obesity, inflammation, and its associated disorders. In one aspect, this disclosure describes methods that generally include suppressing expression of JunB in BAT adipocytes. In one or more embodiments, the method may be used to increase high-thermogenic adipocytes in brown adipose tissue (BAT). In one or more embodiments, the method may be used to decrease low-thermogenic adipocytes in brown adipose tissue. In one or more embodiments, the method may be used to enhance basal or cold- induced energy expenditure in a subject. In one or more embodiments, the method may be used to treat diet-induced obesity in a subject. In one or more embodiments, the method may be used to treat insulin resistance in a subject. In another aspect, this disclosure describes methods that generally include interfering with JunB binding to a tetradecanoylphorbol-13-acetate-responsive element (TRE). Exemplary active agents that interfere with JunB binding to a tetradecanoylphorbol-13-acetate-responsive element (TRE) include, but are not limited to, small molecule inhibitors that target AP-1 or its components, such as curcumin, SR11302, T-5224, and SP6001252. In one or more embodiments, the method may be used to increase high-thermogenic adipocytes in brown adipose tissue (BAT). In one or more embodiments, the method may be used to decrease low-thermogenic adipocytes in brown adipose tissue (BAT). In one or more embodiments, the method may be used to enhance basal or cold-induced energy expenditure in a subject. In one or more embodiments, the method may be used to treat diet-induced obesity in a subject. In one or more embodiments, the method may be used to treat insulin resistance in a subject. The subject can be a human or a non-human animal such as, for example, a livestock animal, a laboratory animal, or a companion animal. Exemplary non-human animal subjects include, but are not limited to, animals that are feline (including, for example, domesticated cats, tigers, lions, etc.), canine (including, for example, domesticated dogs, wolves, etc.), avian (including, for example, turkeys, chickens, ducks, geese, etc.), a rodent (including, for example, mice, rats, etc.), a member of the family Leporidae (including, for example, rabbits or hares), members of the family Mustelidae (including, for example ferrets), or a member of the order Chiroptera (including, for example, bats). “Treat” or variations thereof refer to reducing, limiting progression, ameliorating, or resolving, to any extent, the symptoms or signs related to a condition. A “treatment” may be therapeutic or prophylactic. “Therapeutic” and variations thereof refer to a treatment that ameliorates one or more existing symptoms or clinical signs associated with a condition. “Prophylactic” and variations thereof refer to a treatment that limits, to any extent, the development and / or appearance of a symptom or clinical sign of a condition. Generally, a “therapeutic” treatment is initiated after the condition manifests in a subject, while “prophylactic” treatment is initiated before a condition manifests in a subject. Treating a condition can be prophylactic or, alternatively, can be initiated after the subject exhibits one or more symptoms or clinical signs of the condition. Treatment that is prophylactic—e.g., initiated before a subject manifests a symptom or clinical sign of the condition—is referred to herein as treatment of a subject that is “at risk” of having the condition. As used herein, the term “at risk” refers to a subject that may or may not actually possess the described risk. Thus, for example, a subject “at risk” of a condition is a subject possessing one or more risk factors associated with the condition such as, for example, genetic predisposition, ancestry, age, sex, geographical location, lifestyle, or medical history. Treatment may also be continued after symptoms have resolved, for example to prevent or delay their recurrence. Accordingly, a therapeutic composition for treating the condition can be administered before, during, or after the subject first exhibits a symptom or clinical sign of the condition. Treatment initiated before the subject first exhibits a symptom or clinical sign associated with the condition may result in decreasing the likelihood that the subject experiences clinical evidence of the condition compared to a subject to which the composition is not administered, decreasing the severity of symptoms and / or clinical signs of the condition, and / or completely resolving the condition. Treatment initiated after the subject first exhibits a symptom or clinical sign associated with the condition may result in decreasing the severity of symptoms and / or clinical signs of the condition compared to a subject to which the composition is not administered, and / or completely resolving the condition. Thus, the method includes administering an effective amount of the composition to a subject having, or at risk of having, a particular condition. In this aspect, an “effective amount” is an amount effective to reduce, limit progression, ameliorate, or resolve, to any extent, a symptom or clinical sign related to the condition. In one or more embodiments, an effective amount is an amount effective to increase high-thermogenic adipocytes in brown adipose tissue (BAT). In one or more embodiments, an effective amount is an amount effective to decrease low-thermogenic adipocytes in brown adipose tissue. In one or more embodiments, an effective amount is an amount effective to enhance basal or cold-induced energy expenditure in a subject. In one or more embodiments, an effective amount is an amount effective to reduce diet-induced obesity in a subject. In one or more embodiments, an effective amount is an amount effective to reduce insulin resistance in a subject. In the preceding description and following claims, the term “and / or” means one or all of the listed elements or a combination of any two or more of the listed elements; the terms “comprises,” “comprising,” and variations thereof are to be construed as open ended—i.e., additional elements or steps are optional and may or may not be present; unless otherwise specified, “a,” “an,” “the,” and “at least one” are used interchangeably and mean one or more than one; and the recitations of numerical ranges by endpoints include all numbers subsumed within that range (e.g., 1 to 5 includes 1, 1.5, 2, 2.75, 3, 3.80, 4, 5, etc.). As used herein, “have,” “has,” “having,” “include,” “includes,” “including,” “comprise,” “comprises,” “comprising” or the like are used in their open-ended inclusive sense, and generally mean “include, but not limited to,” “includes, but not limited to,” or “including, but not limited to.” Further, wherever embodiments are described herein with the language “have,” “has,” “having,” “include,” “includes,” “including,” “comprise,” “comprises,” “comprising” and the like, otherwise analogous embodiments described in terms of “consisting of” and / or “consisting essentially of” are also provided. The term “consisting of” means including, and limited to, that which follows the phrase “consisting of.” That is, “consisting of” indicates that the listed elements are required or mandatory, and that no other elements may be present. The term “consisting essentially of” indicates that any elements listed after the phrase are included, and that other elements than those listed may be included provided that those elements do not interfere with or contribute to the activity or action specified in the disclosure for the listed elements. As used herein, the word “exemplary” means to serve as an illustrative example and should not be construed as preferred or advantageous over other embodiments. As used herein, the terms “preferred” and “preferably” refer to embodiments of the invention that may afford certain benefits under certain circumstances. However, other embodiments may also be preferred under the same or other circumstances. Furthermore, the recitation of one or more preferred embodiments does not imply that other embodiments are not useful and is not intended to exclude other embodiments from the scope of the invention. In the preceding description, particular embodiments may be described in isolation for clarity. Reference throughout this specification to “one embodiment,” “an embodiment,” “certain embodiments,” “one or more embodiments,” or “some embodiments,” etc., means that a particular feature, configuration, composition, or characteristic described in connection with the embodiment is included in at least one embodiment of the disclosure. Thus, the appearances of such phrases in various places throughout this specification are not necessarily referring to the same embodiment of the disclosure. Furthermore, the particular features, configurations, compositions, or characteristics may be combined in any suitable manner in one or more embodiments. Thus, features described in the context of one embodiment may be combined with features described in the context of a different embodiment except where the features are necessarily mutually exclusive. In several places throughout the above description, guidance is provided through lists of examples, which examples can be used in various combinations. In each instance, the recited list serves only as a representative group and should not be interpreted as an exclusive list. For any method disclosed herein that includes discrete steps, the steps may be performed in any feasible order. And, as appropriate, any combination of two or more steps may be performed simultaneously. EXAMPLES The present invention is illustrated by the following examples. It is to be understood that the particular examples, materials, amounts, and procedures are to be interpreted broadly in accordance with the scope and spirit of the invention as set forth herein. Plasmids The mouse Junb coding sequence was cloned into the pCDNA3.1B-Myc vector at the BamHI and XbaI sites and into pGEX-4T-1 vector at the EcoRI and XhoI sites. The PGC1α plasmid was kindly provided by Dr. Even Rosen at Harvard University. The mouse Errα promoter (-1443 / +187) named as pGL3-Errα was amplified from mouse genome DNA and inserted into the EcoRI and HindIII sites of pGL3-basic (Promega, Madison, WI). The plasmid of pGL3-Erra-Mut (-1305 / -1315-TtACTtgA) was obtained through site directed mutagenesis. Generation of adipocyte-specific JunB deficient, JunBCreERT2knock-in, JunBChaser-YFP, and JunBCreERT2-DTA+mice Adipose-specific JunB KO (JunB FKO) mice were generated by crossing Junb floxed (Jackson Laboratory, Bar Harbor, ME; Stock number: 012369) and Adipoq-cre mouse (Jackson Laboratory, Bar Harbor, ME; Stock number: 010803), and UCP1+adipocyte-specific JunB KO (JunB BKO) mice were generated by crossing Junb floxed mice with Ucp1-cre mice (Jackson Laboratory, Bar Harbor, ME; Stock number: 024670), as previously described (Zhang, et al., Cell Rep 24:3180-3193 (2018); Zhang, et al., Autophagy 16:1668-1682 (2020); Liu, et al., Diabetes 61:2776-2786 (2012); Wang, et al., JCI Insight 7 (2022)). The strategy for generating JunBCreERT2mice is shown in the genomic structure (FIG.10A). An internal ribosome entry site (IRES) fused to a CreERT2 gene was inserted downstream of the internal stop codon of Junb gene (FIG.10A). To ablate JunB+adipocytes in vivo, Adiponectin-Flex-DTA mouse (kindly provided by Dr. Yiping Chen at Tulane University) were crossed with JunBCreERT2mouse to generate JunBCreERT2; adiponectin-Flex-DTA mice (named as JunBCreERT2-DTA+mice). JunB+adipocytes were ablated post tamoxifen administration via intraperitoneal injection at the dose of 100 mg / kg body weight for three days as previously described (Liu, et al., Elife 11(2022); Plummer, et al., Genesis 55(2017)). The adiponectin-Flex-DTA mice treated with tamoxifen were used as controls. After 48-hour recovery, mice underwent metabolic phenotyping. AdipoChaser-YFP or JunBChaser-YFP mice were generated by crossing Rosa26-EYFP mouse (Jackson Laboratory, Bar Harbor, ME; Stock number: 006148) with Adipoq-cre (Jackson Laboratory, Bar Harbor, ME; Stock number: 010803) or JunBCreERT2mouse, respectively. The generation of AdipoChaser-GFP (adiponectin rtTA;Tre Cre;R26RmT / mG) mice were described previously (Song, et al., The Journal of Clinical Investigation 130:247-257 (2020)).10-week-old male mice were used for the studies unless otherwise stated. Six-week-old mice were fed with normal chow (NC) or high fat diet (HFD) with 45% kcal from fat from Research Diets (D12451) for up to 16 weeks. All animals were housed in a pathogen-free barrier facility with a 12-hour light / 12-hour dark cycle with food and water ad libitum. All animal experimental protocols were reviewed and approved by the Animal Care Committee of the University of New Mexico Health Sciences Center. Human study Patients were identified either before undergoing anterior cervical spine surgery, before undergoing parathyroidectomy, or before undergoing thyroidectomy (18-60 years old for both male and female subjects), and then were recruited in the ENT clinic at time of consent for primary surgery as previously described (Zhang, et al., Cell Rep 34:108794 (2021)). The patients who had bleeding diathesis, known allergy to any study medication including sedatives or analgesics, coagulopathy (INR of 1.5 or greater, platelet count of <50,000 / microliter), use of anticoagulant medication or diabetes mellitus (type I or II) were excluded from this study. Participant’s BMI was either < 25 (lean) or >30 (obese), and the subject information for sex, age, and BMI were included (Table.1). A total of 10 subjects were recruited into this study. Samples 1-8 were used for the Western blot analysis, and samples 9-10 were paired (1 male and 1 female) for the primary culture study as previously described (Zhang, et al., Cell Rep 34:108794 (2021)). This study has been reviewed and approved by Human Research Review Committee at UNMHSC. 5-10 μg neck fat was harvested during anterior cervical spine surgery, parathyroidectomy, or thyroidectomy. Inclusion criteria: English and / or Spanish speaking, male and female adults undergoing anterior cervical spine surgery, parathyroidectomy, or thyroidectomy (18-60 years old), who are able to sign the consent form. Both male and female subjects will be included in the proposed studies and the data will be analyzed based on the sex. Exclusion criteria: bleeding diathesis, known allergy to any study medication including sedatives or analgesics, coagulopathy (the international normalized ratio (INR) of 1.5 or greater, platelet count of <50,000 / microliter), pregnant women, prisoner, use of an anticoagulant medication, or Diabetes mellitus (type I or II). Table 1. The present human subject characteristics for age, sex and BMI. Sample Gender Group BMI Age 1 Female Lean 23.2 45 assay Primary brown pre-adipocytes were fixed with 1% formaldehyde, washed twice with cold PBS containing protease inhibitor cocktail, and then lysed followed with sonication until DNA fragments of 200-1,000 bp were achieved. Sonicated solution was diluted in ChIP dilution buffer as previously described (Zhang, et al., Cell Rep 34:108794 (2021)). The immuno-complexes were precipitated using an anti-JunB (ABclonal) antibody or IgG as the control. Precipitated complexes were reverse cross-linked at 65°C. The amount of precipitated DNA was detected by semiquantitative PCR using the primer pairs TRE-F-5′-GTAGGCACAGGCCGACTCAA-3′ (SEQ ID NO:1) and TRE-R 5′ -GGAGTGAAGCAAAGCTACCCA-3′ (SEQ ID NO:2); TRE- Adjacent-F:5′-TGTGGTTCCTCAAATGGGGG-3′ (SEQ ID NO:3) and TRE-Adjacent-R:5′- CGCTTCCTGATCCCTTCGAT-3’ (SEQ ID NO:4). Primary culture, differentiation, and treatment of brown adipocytes Primary stromal vascular fractions (SVFs) were isolated from brown fat depots of three- week-old Junb FKO and control mice, cultured, and differentiated into adipocytes as described previously (Zhang, et al., Cell Rep 34:108794 (2021); Zhang et al., Autophagy 16:1668-1682 (2020)). The SVFs cells were seeded in a 12-well plate and induced to differentiate by adding induction medium of DMEM with 10% FBS containing 2 mg / ml dexamethasone, 0.25 mM IBMX, and 0.125 M indomethacin for 72 hours. Medium was changed into differentiation medium of DMEM with 10% FBS containing 1 µM T3 and 20 µM insulin for 48 hours. Cells were then maintained in the regular medium of DMEM with 10% FBS for 24 hours. Day 6 primary differentiated adipocytes were treated with 20 ng / ml TNFα (BioLegend, San Diego, CA) or 20 ng / ml IL-6 (BioLegend, San Diego, CA) for 24 hours. Cells were then harvested for the extraction of RNA and protein or used for the staining. Immunofluorescence staining Adipose tissue samples were fixed in 4% paraformaldehyde (PFA) at room temperature overnight, and then processed into paraffin-embedded serial sections at 7 μm. Tissue samples were then de-paraffinized for three times in xylene and subsequently rehydrated from serial ethanol (100% ethanol, 95% ethanol, 85% ethanol, or 70% ethanol) to ddH2O. Slides were placed in boiling Tris-EDTA antigen retrieval buffer (pH=9.0) for 30 minutes, and then blocked in PBS containing 5% BSA (Thermo Fisher Scientific, Inc., Waltham, MA) for 60 minutes followed by incubation with primary antibodies against GFP (1:500), perilipin 1 (Plin1) (1:500) or JunB (1:100) at 4 °C overnight. Slides were then incubated with secondary antibodies (1:500) at room temperature for 60 minutes. After washing, slides were processed with an autofluorescence quenching kit treatment (Vector Laboratories, Newark, CA) for five minutes to remove unspecific fluorescence on sections. Slides were then mounted with mounting medium (EVERBRITE, Biotium, Inc., Fremont, CA) with 4,6-diamidino-2-phenylindole (DAPI). The images were captured using a cell imaging system (EVOS FL, Thermo Fisher Scientific, Inc., Waltham, MA) and analyzed with Image J software. For quantification of GFP+, YFP+, or JunB+adipocytes, 10-12 images in each tissue sample were randomly chosen and underwent analysis. Microscopic pictures (20x objective) were taken, and JunB+adipocyte within each image were counted. For cell studies, primary pre-adipocytes or differentiated adipocytes were seeded in 96- well plates and fixed. Cells were then permeabilized with 0.2% Triton X-100 (Thermo Fisher Scientific, Inc., Waltham, MA) in 5% bovine serum albumin (BSA; Thermo Fisher Scientific, Inc., Waltham, MA) for 10 minutes followed with 5% BSA blocked for 60 minutes. Cells were incubated with primary anti-JunB (1:100), anti-Plin1 (1:500), anti-GFP (1:500), and / or anti- PDGFRA (1:100) for overnight followed with secondary antibodies (1:1000) for 60 minutes, DAPI (1:1000) and Bodipy (1:2000) for five minutes. High content microscopy with automated image acquisition and quantification was performed using a high content scanner (HCS; CELLOMICS, Thermo Fisher Scientific, Inc., Waltham, MA) and iDEV software. Automated epifluorescence image collection was performed using a minimum of 2000 cells per well. Epifluorescence images were machine analyzed using preset scanning parameters and object mask definitions. DAPI staining was used for autofocusing and to automatically define cellular outlines based on background staining of the cytoplasm. Within primary objects defined as cells, regions of interest (ROI) or targets were algorithm-defined for shape / segmentation, maximum / minimum average intensity, total area, and total intensity minima and maxima limits, to automatically identify puncta or other profiles within valid primary objects. All data collection, processing (object, ROI, and target mask assignments), and analyses were performed by software, independently of human operators, as described previously (Zhang et al., Autophagy 16:1668-1682 (2020)). BAT nuclei isolation and snRNA-seq analysis Brown fat depots were collected from 10-week-old JunB FKO and control mice. Tissue samples were minced into 1 mm3, homogenized in Nuclei EZ Lysis Buffer (NUC101, Sigma- Aldrich; St. Louis, MO) with pre-chilled Dounce homogenizer. The homogenate was filtered using a 40-μm cell strainer (VWR International, LLC, Radnor, PA). After centrifugation, the pellet was washed, re-suspended, and stained with DAPI, the single and healthy nuclei were isolated using sorting. Reconstituted nuclei with concentration of 700-1,200 nuclei / μl were used for the sequencing (Sun et al., Nature 587:98-102 (2020)). Single-nuclei RNA libraries were prepared using a kit according to the manufacturer’s instructions (CHROMIUM single cell 3´ kits; 10x Genomics, Inc., Pleasanton, CA). Approximately 10,000 cells were loaded on a single cell controller instrument (CHROMIUM single cell 3´ kits; 10x Genomics, Inc., Pleasanton, CA) to generate single cell gel beads in emulsion (GEMs). The barcoded sequencing libraries were constructed using a single-cell 3′ library kit (CHROMIUM single cell 3´ kits; 10x Genomics, Inc., Pleasanton, CA) for enzymatic fragmentation, end-repair, A-tailing, adaptor ligation, ligation cleanup, sample index PCR, and PCR cleanup. Libraries were sequenced with system for sequencing-by-synthesis a (NOVASEQ, Illumina, Inc., San Diego, CA) with a depth of 50,000 to 100,000 reads per targeted cell. Raw sequencing data were processed using processing software (CELL RANGER PIPELINE (version 2.0); 10x Genomics, Inc., Pleasanton, CA) to generate FASTQ files and aligned to mm10 genome sequence file in gene expression count. Knockdown of Errα in brown fat and brown adipocytes 10-week-old JunB FKO and control mice underwent a surgery for intra-BAT administration. A longitudinal incision at the interscapular region was performed followed with six injections with 10 μl of 1013vg / ml adeno-associated virus (AAV) that encoded shRNA of mouse Errα or scramble shRNA (VectorBuilder Inc, Chicago, IL) into brown fat depot. Mice were euthanized 21 days post virus administration. For the cell study, constructs encoding Errα, or scramble shRNA were introduced into day 5-differentiated primary brown adipocytes using a transfection system (NEON NxT, Thermo Fisher Scientific, Inc., Waltham, MA) as previously described (116). Cells were then seeded in the seahorse plate at a density of 20,000 cells per well for the respiration analysis as previously described (Zhang, et al., Cell Rep 34:108794 (2021)). Antibodies Anti-JunB (10486-1-AP) for immunofluorescence staining was from Thermo Fisher Scientific, Inc. (Waltham, MA). Anti-JunB (A5290) for chromatin immunoprecipitation (ChIP) assay and Western Blot was from ABclonal Technology (Woburn, MA). Anti- Adipoq / adiponectin was home-made antibody as described previously (Liu, et al., Proc Natl Acad Sci U S A 105:18302-18307 (2008)). Anti-UCP1 (ab23841), anti-perilipin 1 (ab61682), anti-GFP (ab13970) were from Abcam (Cambridge, UK). Anti-PGC1α (ST1204-100UL) was purchased from EMD Millipore (Burlington, MA). Anti-JunD (sc-74) and anti-C-Jun (sc-1694) were from Santa Cruz Biotechnology, Inc. (Dallas, TX). Anti-PDGFRA (CD140) (17-1401-81) was from Thermo Fisher Scientific, Inc. (Waltham, MA). DAPI (4',6-Diamidino-2-Phenylindole, Dilactate) (D3571), BODIPY 493 / 503 (D3922), pre-stained protein ladder (26616), rabbit anti- goat IgG secondary antibody, Alexa Fluor 568 (A-11079), rabbit anti-mouse IgG secondary antibody, Alexa Fluor 647 (A-21239), goat anti-rabbit IgG secondary antibody, Alexa Fluor 488 (A-11008) / Alexa Fluor 568 (A11036) / Alexa Fluor 647 (A-21244), donkey anti-goat IgG secondary antibody, Alexa Fluor 488 (A-11055), goat anti-chicken IgY secondary antibody, and Alexa Fluor Plus 488 (A-11039) were from Thermo Fisher Scientific, Inc. (Waltham, MA). Anti- tubulin (T8328) was from Sigma-Aldrich (St. Louis, MO). Isolation of adipocytes and stromal vascular fractions (SVFs) Brown fat samples were minced into 1 mm pieces and digested with tissue isolation buffer (123 mM NaCl, 5 mM KCl, 5 mM Glucose, 1.3 mM CaCl2and 100 mM HEPES) supplemented with 4% fatty acid free bovine albumin, 1.5 mg / mL collagenase A (10103586001, Sigma-Aldrich, St. Louis, MO). Digested tissue samples were filtered through 70-μm nylon filters into 15-ml conical tubes followed by centrifugation at 500 rpm for five minutes. The bottom cell pellets were saved as SVFs, and the top layer containing mature adipocytes was washed with PBS supplemented with 3% bovine albumin three times. Isolated SVFs and adipocytes were used for extraction of total RNA and then RT-PCR. MITOTRACKER (Molecular Probes, Inc., Sunnyvale, CA) staining of primary adipocytes Primary differentiated JunB KO and control adipocytes were cultured in the fresh medium of DMEM with 10% FBS, and treated with 100 nM MITOTRACKER staining dye for 20 minutes. The mitochondria in live cells were assessed by quantifying MITOTRACKER red CMXRos (M7512, Thermo Fisher Scientific, Inc., Waltham, MA) using automated high-content imaging and analysis. The average intensity was identified and counted by the system. In brief, total 2000 primary objects were randomly selected by the machine and counted by DAPI in each well. Adipocytes was determined by Bodipy area, and MITOTRACKER signal in each single cell was calculated by average intensity. Quantification of MITOTRACKER intensity was normalized by each field per well. Transmission electron microscopy (TEM) For brown adipose tissue, tissue samples were collected from 10-week-old mice exposed with or without cold stress for two days and fixed with 0.1 M sodium cacodylate buffer containing 3% formaldehyde and 2% glutaraldehyde for one hour. For adipocytes, day 6- differentiated primary adipocytes on the coverslip were fixed in 0.1 M sodium cacodylate buffer containing 3% formaldehyde and 2% glutaraldehyde for one hour. Tissue or cell samples were washed with cacodylate buffer followed by secondary fixation in 1% osmium-1.5% potassium ferricyanide at room temperature (RT) for one hour. Cells were then washed, stained in 1% uranyl acetate at RT for one hour, and dehydrated in a graded series of ethanol. The cell sample was then infiltrated with Epon-Araldite resin, embedded and heat-cured. The coverslips were removed from the cured resin blocks, and the pieces from the resin blocks were re-mounted for en face sectioning. Thin sections (~80 nm) were mounted on Cu grids, post-stained with uranyl acetate and Reynold’s lead citrate, and examined in a transmission electron microscope (HT7700; Hitachi High-Tech Corp., Tokyo, Japan) at 80 kV. Images were captured with a charge-coupled device (CCD) camera (XR-81; Advanced Microscopy Techniques Imaging, Woburn, MA) and a total of 25 cells / slide underwent imaging. A total of three images / cell were taken. For quantification, the total number of mitochondria in the defined areas (272475 µm2) / cell were counted and analyzed using the average number in each area. The number of mitochondria was expressed as the number of mitochondria and lysosomes per nucleus as described previously (Zhang, et al., Autophagy 16:1668-1682 (2020)). Analysis of mtDNA / nDNA ratio in brown adipose tissue About 10 mg brown fat samples were collected from 10-week-old JunB FKO and control mice and used for DNA isolation. About 20 ng DNA was used for the qPCR analysis, and the ratio of mtDNA / nDNA was calculated using the copy number of mtDNA genes ND1 and 16S normalized against nDNA hexokinase gene (HK) as described previously (Quiros, et al., Curr Protoc Mouse Biol 7:47-54 (2017)). Luciferase reporter assays HEK293T cells were cultured in 24-well plates and introduced with constructs that encode PGC-1α, JunB, luciferase reporter, and pSV-β-galactosidase control vector (E1081, Promega, Madison, WI) with transfection reagent (LIPOFECTAMINE 3000, Thermo Fisher Scientific, Inc., Waltham, MA), according to the manufacturer’s protocol. The mass of transfected plasmids was balanced with empty vector (pCDNA3.1B). After 48 hours, cells were harvested for the measurement of the luciferase with the Luciferase Assay Kit (Promega, Madison, WI) and for the analysis of β-galactosidase activities using a luminometer (TD20 / 20, Turner Designs, Inc., San Jose, CA). The luciferase activity was normalized by β-galactosidase activity. To study the effect of JunB on the promoter activity of Errα, primary brown preadipocytes isolated from JunB floxed BAT were transfected with reporter construct along with PCDNA3.1B or PCDNA3.1B-Cre, pcDNA-PGC-1α with pSV-β-galactosidase expression vector using electroporation with a transfection system (NEON NxT, Thermo Fisher Scientific, Inc., Waltham, MA; 1,400 V, 20 mS / pulse, two pulses) as previously described (Luo, et al., J Mol Cell Biol 9:422-434 (2017)). Cells were harvested and measured using the Luciferase Reporter assay system 48 hours post transfection. For the luciferase assay, three independent experiments were performed with triplication in each single experiment. Electrophoretic mobility shift assay (EMSA) The recombinant GST-JunB protein was expressed and purified as described (Ding et al., Journal of Cellular Biochemistry 106:285-295 (2009)). The specific DNA probes covering JunB binding sites in the Errα promoter region were synthesized and labeled with biotin at the 3′ end. The following specific DNA probes were used: WT Sense: 5′-AGTGAGTGACTCAGAGGACTT-3′, SEQ ID NO:5; WT Anti-Sense: 5′-AAGTCCTCTGAGTCACTCACT-3′, SEQ ID NO:6; Mut Sense: 5′-AGTGAGTtACTtgAGAGGACTT-3′, SEQ ID NO:7; and Mut Anti-Sense:5′-AAGTCCTCTcaAGTaACTCACT-3′, SEQ ID NO:8. Following the manufacturer’s instructions of the EMSA / Gel-Shift Kit (Beyotime, Shanghai, China), the binding reaction was carried out in a mixture containing 2 pmol biotin- labelled wild-type or mutated DNA sequences and 5 μg GST-JunB in 15 μl of binding buffer with or without unlabeled DNA probes for 30 minutes at room temperature. The reaction mixtures were loaded onto a 4% non-denatured gel at 100 V for 60 minutes and transferred onto nylon membrane to perform chromogenic reaction. Seahorse assays and tissue respiration Primary preadipocytes from brown fat were cultured and differentiated into adipocytes as described previously (Liu, et al., Cell Metabolism 19:967-980 (2014)). The differentiated adipocytes were then cultured in a plate with assay media (XF Assay media, Seahorse Bioscience, North Billerica, MA) containing 4,500 mg / L glucose free of CO2and incubated at 37 °C overnight. Injection ports of an analyzer instrument (XF24 Extracellular Analyzer, Seahorse Bioscience, North Billerica, MA) were loaded with oligomycin at a final concentration of 1.5 μM for 24 minutes followed by the addition of carbonyl cyanide p-[trifluoromethoxy]- phenyl-hydrazone (FCCP) at a final concentration of 1.0 μM for 24 minutes. Post FCCP measurements, rotenone was added in for another 24 minutes to achieve a 0.5 μM final concentration. Oxygen consumption (OCR) was normalized by the cell number scanned using a multimode reader (BIOTEK CYTATION, Agilent Technologies, Inc., Santa Clara, CA) in each well. Isolation of primary high thermogenic adipocytes Brown fat tissues were collected from 10-week old JunB FKO and Control mice exposed with cold stress (6 ℃) for four days. In brief, 100 mg tissue samples were minced into small pieces and digested in collagenase-dispase buffer (Gibco, Thermo Fisher Scientific, Inc., Waltham, MA) with water bath shaking (New Brunswick Scientific Co., Inc., Edison, NJ) at 70 rpm and 37℃ for one hour. The cell suspension was filtered through a 200 μm nylon filter (Spectrum Chemical Mfg. Corp., New Brunswick, NJ) to remove undigested tissues followed by three volumes of wash buffer (DMEM, Gibco, Thermo Fisher Scientific, Inc., Waltham, MA) containing 10% FBS and the filtrate was centrifuged at 100×g for five minutes at room temperature. The cell fraction in the pellets was collected as the fraction of high thermogenic adipocytes previously described (15). The cell fraction was cultured in 96-well plate for cell counting after staining with DAPI / Bodipy / Mitotracker for the imaging using a high content scanner (HCS; CELLOMICS, Thermo Fisher Scientific, Inc., Waltham, MA) Body composition To check body composition, 10-week-old mice were anesthetized by intraperitoneal injection with ketamine / xylazine (10 mg / ml ketamine and 1 mg / ml xylazine) (0.1 ml / 10 gram body mass). Bone mineral density, fat mass, lean mass, and percentage of fat were determined using dual-energy X-ray absorptiometry (DEXA) (GE Medical Systems, Madison, WI). Hematoxylin and eosin and Bodipy staining For hematoxylin and eosin (H&E) staining, adipose tissues from 10-week-old mice were fixed with 4% formalin for 48 hours and embedded in paraffin. Tissue sections (5 μm thick) were stained with H&E according to standard protocols then analyzed using the NIH ImageJ software. Immunohistochemistry was performed as previously described (Zhang, et al., Cell Rep 34:108794 (2021)). For Bodipy staining of liver tissue, frozen tissue sections (6 μm thick) were fixed with 95% ethanol and 4% PFA for five minutes, followed with stained Bodipy (1:1000) for five minutes. Slides were then mounted with mounting medium (EVERBRITE, Biotium, Inc., Fremont, CA) with 4,6-diamidino-2-phenylindole (DAPI). The images were captured using a cell imaging system (EVOS FL, Thermo Fisher Scientific, Inc., Waltham, MA) Liver triglyceride content Frozen liver tissue samples (100-300 mg) were digested using 350 μl potassium hydroxide (ethanol:30% potassium hydroxide=2:1) at 55 ℃ overnight. The solution (H2O: ethanol (1:1)) was added into the tissue sample 1,000 μl of total volume followed with centrifugation.200 μl supernatant was mixed with 215 μl 1 M MgCl2 and chilled on ice for 10 minutes. After centrifugation, the supernatant was used for the measurement of free glycerol levels using Free Glycerol Reagent (Sigma-Aldrich, F6428) to reflect TG content, according to the protocol (Wang, et al., JCI Insight 7(2022)). Energy expenditure The 10-week-old mice were individually housed in eight separate metabolic phenotyping systems (PROMETHION CORE, Sable Systems International, North Las Vegas, NV) coupled with a temperature controllable chamber. Oxygen consumption (VO2), carbon dioxide release (VCO2), food intake, water intake, and the activity of each animal were monitored at room temperature (22°C) for 72 hours, then in cold stress conditions (6°C) for seven days. The data was analyzed using CaIR (version 1.3) (https: / / calrapp.org / ) (Mina, et al., Cell Metabolism 28:656-666 e651 (2018)). Telemetry study A telemetry system was used for the measurement of core body temperature in JunB FKO and Control mice as previously described (45). Briefly, an implantable biotelemetric thermosensor (Mini Mitter Co., Inc., Bend, OR) was surgically implanted into the peritoneal cavity of 10-week-old male mice.10-day post-surgery, mice were individually housed in the cage with free access to food and water at room temperature (22 °C) for 12 hours (8 a.m. to 8 p.m.) followed by exposure to cold stress (6 °C) for 12 hours (8 p.m. to 8 a.m.). The body temperature and locomotor activity were recorded every five minutes and analyzed with VITALVIEW software (Starr Life Sciences Corp., Oakmont, PA) (Wang, et al., J Exp Med 218 (2021)). Primary culture, differentiation, and treatment of IL-6 and TNFɑ in brown adipocytes Primary SVFs from brown fat depots of three-week-old Junb FKO and control mice were isolated and cultured as previously described (Zhang, et al., Cell Rep 24:3180-3193 (2018); Zhang, et al., Autophagy 16:1668-1682 (2020)). Differentiation of adipocytes was performed as previously described (Zhang, et al., Cell Rep 24:3180-3193 (2018); Zhang, et al., Autophagy 16:1668-1682 (2020)). The SVFs were cultured in DMEM with 20% FBS overnight, and the floating and dead cells were washed away twice with PBS. Adherent cells were cultured and split for three passages. Cells were seeded in a 12-well plate and induced to differentiate by adding induction medium of DMEM with 10% FBS containing 2 mg / ml dexamethasone and 0.25 mM IBMX, and 0.125 M indomethacin for 72 hours. Medium was be changed into differentiation medium of DMEM with 10% FBS containing 1 µM T3 and 20 µM insulin for 48 hours. Cells were then maintained in the regular medium of DMEM with 10% FBS for 24 hours. Day 6 differentiated primary adipocytes from SVFs of C57 / BL6, AdiopChaser-YFP and JunB-Chaser- YFP mice were treated with TNFα (20 ng / ml, BioLegend, San Diego, CA) or IL-6 (20 ng / ml, BioLegend, San Diego, CA), for 24 hours. Cells were harvested for the extraction of RNA or Protein. Analysis of adipocyte size and number For in vivo analysis, H&E staining was performed on tissues from 10-week old mice. Stained tissues were visualized with slide scanner (NANOZOOMER, Hamamatsu Photonics, Shizuoka, Japan). Five sections per animal were stained. Eight representative images per section were used to determine adipocyte size. Size of adipocytes were determined with ImageJ Analysis of H&E stained tissues (Zhang, et al., Cell Rep 24:3180-3193 (2018); Zhang, et al., Autophagy 16:1668-1682 (2020)). Number of adipocytes per area was determined by manual counting cells on H&E slides from at least three 20× fields of three mice per genotype as previously described (Zhang, et al., Cell Rep 24:3180-3193 (2018); Zhang, et al., Autophagy 16:1668-1682 (2020)). RNA extraction and Real-time PCR Total RNA was extracted from tissue samples using a commercial kit (PURELINK RNA Mini Kit, Thermo Fisher Scientific, Inc., Waltham, MA). The purity and concentration of total RNA were determined using a spectrophotometer (NANO DROP, Thermo Fisher Scientific, Inc., Waltham, MA).1 μg of total RNA was reverse-transcribed using a commercial kit (High- Capacity cDNA Reverse Transcription kit, Thermo Fisher Scientific, Inc., Waltham, MA). Real- time PCR amplification was detected using SYBR Green PCR master mixture (Qiagen, Hilden, Germany) on a real-time PCR system (LIGHTCYCLER 480, Roche Diagnostics Corp., Indianapolis, IN). Primer sequences are listed in Table 1. Each pair of primers amplified products spanning several exons, distinguishing spliced mRNA from genomic DNA contamination. The reaction yielded about 200 bp of PCR products for specified genes and internal control genes. The relative expression levels of target genes were normalized to 36b4. Table 2. Primers SEQ SEQ Gene Forward primer ID Reverse primer ID : PCR arrays of BAT To determine if there is crosstalk between mTOR and the cAMP signaling pathways in adipose tissue, cAMP responsive gene expression was examined using PCR arrays. Four-month- old male C57 / BL6 were treated with rapamycin by intraperitoneal injection with 4 mg / kg rapamycin or vehicle solution three times a week for eight weeks. The mRNA from BAT of mice treated with or without rapamycin (n=3 / group) was extracted and used for reverse transcription. The PCR array analysis was performed by using a synthesized cDNA and PCR array (Qiagen, Hilden, Germany, catalog PAMM-066Z) according to the manufacturer’s instructions. The p values are calculated based on a student’s t-test of the replicate 2-ΔΔCtvalues for each gene in the control and treatment groups, and p values less than 0.05 is considered significant. Although mRNA levels of several genes as indicated (FIG.9A) are up-regulated or down-regulated two- fold more in rapamycin-treated mice compared to the control mice, some of the genes were not further considered due to the relatively high (> 30) threshold cycle or greater variations for the fold-change. Statistical analysis Statistical analysis of the data was performed using a two-tailed Student’s t-test between two groups or one-way ANOVA among three different groups. All the results were presented as the mean ± S.E.M., and P value of <0.05 was considered to be statistically significant. The complete disclosure of all patents, patent applications, and publications, and electronically available material (including, for instance, nucleotide sequence submissions in, e.g., GenBank and RefSeq, and amino acid sequence submissions in, e.g., SwissProt, PIR, PRF, PDB, and translations from annotated coding regions in GenBank and RefSeq) cited herein are incorporated by reference in their entirety. In the event that any inconsistency exists between the disclosure of the present application and the disclosure(s) of any document incorporated herein by reference, the disclosure of the present application shall govern. The foregoing detailed description and examples have been given for clarity of understanding only. No unnecessary limitations are to be understood therefrom. The invention is not limited to the exact details shown and described, for variations obvious to one skilled in the art will be included within the invention defined by the claims. Unless otherwise indicated, all numbers expressing quantities of components, molecular weights, and so forth used in the specification and claims are to be understood as being modified in all instances by the term “about.” Accordingly, unless otherwise indicated to the contrary, the numerical parameters set forth in the specification and claims are approximations that may vary depending upon the desired properties sought to be obtained by the present invention. At the very least, and not as an attempt to limit the doctrine of equivalents to the scope of the claims, each numerical parameter should at least be construed in light of the number of reported significant digits and by applying ordinary rounding techniques. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the invention are approximations, the numerical values set forth in the specific examples are reported as precisely as possible. All numerical values, however, inherently contain a range necessarily resulting from the standard deviation found in their respective testing measurements. All headings are for the convenience of the reader and should not be used to limit the meaning of the text that follows the heading, unless so specified. Sequence Listing Free Text SEQ ID NO:1 – TRE forward primer GTAGGCACAG GCCGACTCAA SEQ ID NO:2 – TRE reverse primer GGAGTGAAGC AAAGCTACCC A SEQ ID NO:3 – TRE Adjacent forward primer TGTGGTTCCT CAAATGGGGG SEQ ID NO:4 – TRE Adjacent reverse primer CGCTTCCTGA TCCCTTCGAT SEQ ID NO:5 – WT sense probe AGTGAGTGAC TCAGAGGACT T SEQ ID NO:6 – WT anti-sense probe AAGTCCTCTG AGTCACTCAC T SEQ ID NO:7 – Mut sense probe AGTGAGTTAC TTGAGAGGAC TT SEQ ID NO:8 – Mut anti-sense probe AAGTCCTCTC AAGTAACTCA CT SEQ ID NO:9 – 36b4 Forward Primer GAAACTGCTG CCTCACATCC G SEQ ID NO:10 – 36b4 Reverse Primer GCTGGCACAG TGACCTCACA CG SEQ ID NO:11 – JunB Forward Primer GGCTTTGCGG ACGGTTT SEQ ID NO:12 – JunB Reverse Primer GGCGTCACGT GGTTCATCT SEQ ID NO:13 – Jun Forward Primer TTGAAAAGTA GCCCCCAACC T SEQ ID NO:14 – Jun Reverse Primer GACAGGGGAC ACAGCTTTCA C SEQ ID NO:15 – Jund Forward Primer GAAACGCCCT TCTATGGCGA SEQ ID NO:16 – Jund Reverse Primer CAGCGCGTCT TTCTTCAGC SEQ ID NO:17 – Ucp1 Forward Primer AAGACAGAAG AGCATAGCAT TCA SEQ ID NO:18 – Ucp1 Reverse Primer CCAGTCATAC ACTCCCACCT C SEQ ID NO:19 – H-JunB Forward Primer ACGACTCATA CACAGCTACG G SEQ ID NO:20 – H-JunB Reverse Primer GCTCGGTTTC AGGAGTTTGT AGT SEQ ID NO:21 – H-Ucp1 Forward Primer AGGTCCAAGG TGAATGCCC SEQ ID NO:22 – H-Ucp1 Reverse Primer TTACCACAGC GGTGATTGTT C SEQ ID NO:23 – H-Pgc1α Forward Primer TCTGAGTCTG TATGGAGTGA CAT SEQ ID NO:24 – H-Pgc1α Reverse Primer CCAAGTCGTT CACATCTAGT TCA SEQ ID NO:25 – H-Gapdh Forward Primer CGTGCCGCCT GGAGAAACC SEQ ID NO:26 – H-Gadph Reverse Primer TGGAAGAGTG GGAGTTGCTG TTG SEQ ID NO:27 – Errα Forward Primer TGCTCAGCTC TCTACCCAAA C SEQ ID NO:28 – Errα Reverse Primer GGACAGCTGT ACTCGATGCT C SEQ ID NO:29 – Tfam Forward Primer CAGGAGGCAA AGGATGATTC SEQ ID NO:30 – Tfam Reverse Primer CCAAGACTTC ATTTCATTGT CG SEQ ID NO:31 – Pgc1α Forward Primer CCGAAGCACC TACAGGTTCC ATA SEQ ID NO:32 - Pgc1α Reverse Primer GGGAGGGAGA GAGGAGAGAG G SEQ ID NO:33 – 16S Forward Primer CCGCAAGGGA AAGATGAAAG AC SEQ ID NO:3416S Reverse Primer TCGTTTGGTT TCGGGGTTTC SEQ ID NO:35 – Nd1 Forward Primer CTAGCAGAAA CAAACCGGGC SEQ ID NO:36 – Nd1 Reverse Primer CCGGCTGCGT ATTCTACGTT SEQ ID NO:37 – iCre Forward Primer CCTGGAAGAT GCTCCTGTCT GTGTG SEQ ID NO:38 – iCre Reverse Primer AGGTGCTGTT GGATGGTCTT CACAG SEQ ID NO:39 – Gfp Forward Primer AAGGGCATCG ACTTCAAGG SEQ ID NO:40 – Gfp Reverse Primer TGCTTGTCGG CCATGATATA G

Claims

What is claimed is:

1. A method of increasing high-thermogenic adipocytes in brown adipose tissue (BAT), the method comprising suppressing expression of JunB in BAT adipocytes.

2. A method of decreasing low-thermogenic adipocytes in brown adipose tissue (BAT), the method comprising suppressing expression of JunB in BAT adipocytes.

3. A method of enhancing basal or cold-induced energy expenditure in a subject, the method comprising suppressing expression of JunB BAT adipocytes in the subject.

4. A method of treating diet-induced obesity in a subject, the method comprising suppressing expression of JunB in BAT adipocytes in the subject.

5. A method of treating insulin resistance in a subject, the method comprising suppressing expression of JunB in BAT adipocytes in the subject.

6. A method of increasing high-thermogenic adipocytes in brown adipose tissue (BAT), the method comprising interfering with JunB binding to a tetradecanoylphorbol-13-acetate- responsive element (TRE).

7. A method of decreasing low-thermogenic adipocytes in brown adipose tissue (BAT), the method comprising interfering with JunB binding to a TRE.

8. A method of enhancing basal or cold-induced energy expenditure in a subject, the method comprising interfering with JunB binding to a TRE.

9. A method of treating diet-induced obesity in a subject, the method comprising interfering with JunB binding to a TRE.

10. A method of treating insulin resistance in a subject, the method comprising interfering with JunB binding to a TRE.

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