Sex difference in BAT thermogenesis depends on PGC-1α-ChREBPβ mediated de novo lipogenesis in mice

Author:

Tsujimoto Kazutaka1,Takeuchi Akira1,Ikeda Kenji1,Aoki Jun1,Niitsu Yoshihiro1,Horino Masato1,Hara Kazunari1,Okazaki Rei1,Kaneda Ryo1,Murakami Masanori1,Shiba Kumiko1,Komiya Chikara1,Yamada Tetsuya1

Affiliation:

1. Tokyo Medical and Dental University

Abstract

Abstract Brown adipose tissue (BAT), a thermogenic tissue that plays an important role in systemic energy expenditure, has histological and functional sex differences. BAT thermogenic activity is higher in female mice than in male mice. However, the molecular mechanism underlying this functional sex difference has not been fully elucidated. Herein, we demonstrate the role and mechanism of PGC-1α in this sex difference. Inducible adipocyte-specific PGC-1α knockout (KO) mice displayed decreased BAT thermogenesis only in females. Expression of carbohydrate response-element binding protein beta (Chrebpβ) and downstream de novo lipogenesis (DNL) related genes were both reduced only in female KO mice. BAT-specific knockdown of Chrebpβ reduced the DNL-related gene expression and BAT thermogenesis in female wild-type mice. Furthermore, PGC-1α enhanced the sensitivity of female BAT estrogen signaling, thereby increasing Chrebpβ and its downstream DNL-related gene expression. These findings demonstrate that PGC-1α-ChREBPβ mediated DNL plays a pivotal role in BAT thermogenesis in a sex-dependent manner.

Publisher

Research Square Platform LLC

Reference51 articles.

1. 1. Oelkrug, R. & Mittag, J. An improved method for the precise unravelment of non-shivering brown fat thermokinetics. Sci Rep 11, 4799 (2021). https://doi.org/10.1038/s41598-021-84200-1 NE-Induced oxygen consumption Oxygen consumption was measured using a metabolic chamber (Shin Factory, JAPAN) coupled to a mass spectrometer (ARCO-2000; Arco system, Tokyo, JAPAN). Mice were anesthetized, and measurements were performed for 30 min at 33℃ to obtain basal values. Each mouse was then briefly removed from the chamber, treated with norepinephrine (1 mg norepinephrine/kgBW), and returned to the chamber, and oxygen consumption was measured for another 30–40 min. Glucose tolerance test The glucose tolerance test was performed via an intraperitoneal injection of glucose at 2.0 g/kg body weight, and blood glucose levels were measured before and 15, 30, 60, 90, and 120 min after the injection. Blood glucose was measured using a glucometer (Stat Strip Xpress; Nova biomedical, USA). Western blotting Protein lysates were extracted from Brown adipose tissue using RIPA buffer (nacalai) supplemented with a protease inhibitor cocktail (cOmpletetm, Sigma-Aldrich). Immunoblotting was performed with Anti-PGC-1α Mouse mAb (Sigma-Aldrich, ST1202, 1:1000) and total OXPHOS rodent WB antibody cocktail (Abcam, ab110413, 1:1000). α-tublin (Cell Signaling, #2144, 1:1000) was used as the loading control. Immunoblots were detected and analyzed using ECL Prime Western Blotting Detection Reagent and ImageQuant LAS 4000 mini (GE Healthcare). HE staining BAT was fixed with 4% paraformaldehyde and embedded in paraffin. Sections were stained with hematoxylin and eosin (HE). Electron microscopy The BAT were fixed in 4% PFA and 2.5% GA in 0.1M phosphate buffer (PB) for 2 h, washed with 0.1 M PB, post-fixed in 1% OsO4 buffered with 0.1 M PB for 2 h, dehydrated in a graded series of ethanol, and embedded in Epon 812. Ultrathin sections (70 nm) were collected on copper grids, double-stained with uranyl acetate and lead citrate, and then examined by transmission electron microscopy (JEM-1400Flash, JEOL, Japan). Quantification of mitochondrial size and content was performed using ImageJ software. RNA isolation and quantitative RT-PCR Total RNA was isolated using the RNeasy Plus Universal Mini Kit (Qiagen). cDNA was synthesized using Random Primer (Thermo Fisher Scientific Inc.) and ReverTra Ace (Toyobo Co., Ltd.). Quantitative PCR was performed using the QuantStudio 6 Flex Real-Time PCR System with Fast SYBR Green Master Mix Reagent. The primer sequences are presented in (Supplemental Table 1). RNA sequencing RNA-seq experiments were performed by Novogene (Beijing, China) using RNA extracted from BAT. Sequencing libraries were built using the NEBNext UltraTM RNA Library Prep Kit (Illumina, USA). The library preparations were sequenced on an Illumina Novaseq 6000 platform, and 150-bp paired-end reads were generated. Differentially expressed genes were determined by fold change (> 1.5), and gene ontology analysis was conducted using Metasape 3.5. Metabolomics BAT samples for metabolomics were obtained from mice 30 min after NE administration at 33°C to evaluate the metabolic dynamics of BAT exhibiting maximal oxygen consumption. Approximately 25–30 mg of frozen BAT tissue was placed in a homogenization tube along with zirconia beads (5mmφ and 3mmφ). Next, 1,500 µL of 50% acetonitrile/Milli-Q water containing internal standards (H3304-1002, Human Metabolome Technologies, Inc. (HMT), Tsuruoka, Yamagata, Japan) was added to the tube, after which the tissue was completely homogenized at 1,500 rpm, 4°C for 60 s using a bead shaker (Shake Master NEO, Bio Medical Science, Tokyo, Japan). The homogenate was then centrifuged at 2,300 × g, 4°C for 5 min. Subsequently, 800 µL of upper aqueous layer was centrifugally filtered through a Millipore 5-kDa cutoff filter (UltrafreeMC-PLHCC, HMT) at 9,100 ×g, 4°C for 180 min to remove macromolecules. The filtrate was evaporated to dryness under vacuum and reconstituted in 50 µL of Milli-Q water for metabolome analysis at HMT. Metabolome analysis was conducted according to HMT’s C-SCOPE package, using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS) for cation analysis and CE-tandem mass spectrometry (CE-MS/MS) for anion analysis based on the methods described previously (1, 2). Briefly, CE-TOFMS and CE-MS/MS analyses were performed using an Agilent CE capillary electrophoresis system equipped with an Agilent 6210 time-of-flight mass spectrometer (Agilent Technologies, Inc., Santa Clara, CA, USA) and Agilent 6460 Triple Quadrupole LC/MS (Agilent Technologies), respectively. The systems were controlled using Agilent G2201AA ChemStation software version B.03.01 for CE (Agilent Technologies) and connected by a fused silica capillary (50 ∝m i. d. × 80 cm total length) with commercial electrophoresis buffer (H3301-1001 and I3302-1023 for cation and anion analyses, respectively, HMT) as the electrolyte. The time-of-flight mass spectrometer was scanned from m/z 50 to 1,000 (1), and the triple quadrupole mass spectrometer was used to detect compounds in dynamic MRM mode. Peaks were extracted using MasterHands, automatic integration software (Keio University, Tsuruoka, Yamagata, Japan) (3) and MassHunter Quantitative Analysis B.04.00 (Agilent Technologies) to obtain peak information, including m/z, peak area, and migration time (MT). Signal peaks were annotated according to the HMT metabolite database based on their m/z values and MTs. The peak area of each metabolite was normalized to internal standards, and the metabolite concentration was evaluated by standard curves with three-point calibrations using each standard compound. Hierarchical cluster analysis and principal component analysis (PCA) (4) were performed using HMT’s proprietary MATLAB and R programs, respectively. Detected metabolites were plotted on metabolic pathway maps using the VANTED software (5). References

2. 1. Ohashi, Y. et al. Depiction of metabolome changes in histidine-starved Escherichia coli by CE-TOFMS. Mol. Biosyst. 4, 135–147, 2008.

3. 2. Ooga, T. et al. Metabolomic anatomy of an animal model revealing homeostatic imbalances in dyslipidaemia. Mol. Biosyst. 7, 1217–1223 (2011).

4. 3. Sugimoto, M., Wong, D. T., Hirayama, A., Soga, T. & Tomita, M. Capillary electrophoresis mass spectrometry-based saliva metabolomics identified oral, breast and pancreatic cancer–specific profiles. Metabolomics 6, 78–95 (2009).

5. 4. Yamamoto, H., Fujimori, T., Sato, H., Ishikawa, G., Kami, K. & Ohashi, Y: Statistical hypothesis testing of factor loading in principal component analysis and its application to metabolite set enrichment analysis. BMC Bioinform. 15, 51 (2014).

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