Abstract

The circadian clock component NR1D1 (REVERBα) is considered a dominant regulator of lipid metabolism, with global Nr1d1 deletion driving dysregulation of white adipose tissue (WAT) lipogenesis and obesity. However, a similar phenotype is not observed under adipocyte-selective deletion (Nr1d1Flox2-6:AdipoqCre), and transcriptional pro1ling demonstrates that, under basal conditions, direct targets of NR1D1 regulation are limited, and include the circadian clock and collagen dynamics. Under high-fat diet (HFD) feeding, Nr1d1Flox2-6:AdipoqCre mice do manifest profound obesity, yet without the accompanying WAT in2ammation and 1brosis exhibited by controls. Integration of the WAT NR1D1 cistrome with differential gene expression reveals broad control of metabolic processes by NR1D1 which is unmasked in the obese state. Adipocyte NR1D1 does not drive an anticipatory daily rhythm in WAT lipogenesis, but rather modulates WAT activity in response to alterations in metabolic state. Importantly, NR1D1 action in adipocytes is critical to the development of obesity-related WAT pathology and insulin resistance.

Data availability

RNA-seq data generated in the course of this study has been uploaded to ArrayExpress and is available at http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-8840. For reviewer access, the following login details can be used: username "Reviewer_E-MTAB-8840", password "IGGB44Tx". ChIP-seq data generated in the course of this study has been uploaded to ArrayExpress and is available at http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-10573. For reviewer access, the follow690ing login details can be used: username "Reviewer_E-MTAB-10573", password "nncbrjdh". Access to these datasets will be opened to the public upon acceptance of themanuscript. Raw proteomics data has been uploaded to Mendeley Data . Output of 'omics analyses (proteomics, edgeR, stageR, ReactomePA outputs, peak calling) are provided in the Source Data Files.

The following data sets were generated

Article and author information

Author details

  1. Ann Louise Hunter

    Centre for Biological Timing, University of Manchester, Manchester, United Kingdom
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3874-4852
  2. Charlotte E Pelekanou

    Centre for Biological Timing, University of Manchester, Manchester, United Kingdom
    Competing interests
    No competing interests declared.
  3. Nichola J Barron

    Centre for Biological Timing, University of Manchester, Manchester, United Kingdom
    Competing interests
    No competing interests declared.
  4. Rebecca C Northeast

    Centre for Biological Timing, University of Manchester, Manchester, United Kingdom
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3121-2802
  5. Magdalena Grudzien

    Centre for Biological Timing, University of Manchester, Manchester, United Kingdom
    Competing interests
    No competing interests declared.
  6. Antony D Adamson

    Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
    Competing interests
    No competing interests declared.
  7. Polly Downton

    Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1617-6153
  8. Thomas Cornfield

    OCDEM, University of Oxford, Oxford Centre for Diabetes, Endocrinology and Metabolism, United Kingdom
    Competing interests
    No competing interests declared.
  9. Peter S Cunningham

    Centre for Biological Timing, University of Manchester, Manchester, United Kingdom
    Competing interests
    No competing interests declared.
  10. Jean-Noel Billaud

    QIAGEN Bioinformatics, Redwood City, United States
    Competing interests
    Jean-Noel Billaud, J-N.B. is an employee of Qiagen..
  11. Leanne Hodson

    OCDEM, University of Oxford, Oxford Centre for Diabetes, Endocrinology and Metabolism, United Kingdom
    Competing interests
    No competing interests declared.
  12. Andrew Loudon

    Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
    Competing interests
    No competing interests declared.
  13. Richard D Unwin

    Stoller Biomarker Discovery Centre, University of Manchester, Manchester, United Kingdom
    Competing interests
    No competing interests declared.
  14. Mudassar Iqbal

    Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
    Competing interests
    No competing interests declared.
  15. David Ray

    OCDEM, University of Oxford, Oxford Centre for Diabetes, Endocrinology and Metabolism, United Kingdom
    Competing interests
    No competing interests declared.
  16. David A Bechtold

    Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
    For correspondence
    david.bechtold@manchester.ac.uk
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8676-8704

Funding

Biotechnology and Biological Sciences Research Council (BB/I018654/1)

  • David A Bechtold

Medical Research Council (MR/N021479/1)

  • Ann Louise Hunter

Medical Research Council (MR/P00279X/1)

  • David A Bechtold

Medical Research Council (MR/P011853/1)

  • David Ray

Medical Research Council (MR/P023576/1)

  • David Ray

Wellcome Trust (107849/Z/15/Z)

  • David Ray

Wellcome Trust (107851/Z/15/Z)

  • David Ray

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Peter Tontonoz, University of California, Los Angeles, United States

Ethics

Animal experimentation: All experiments described here were conducted in accordance with local requirements and licenced under the UK Animals (Scientific Procedures) Act 1986, project licence number 70/8558 (licence holder Dr. David A Bechtold). Procedures were approved by the University of Manchester Animal Welfare and Ethical Review Body (AWERB).

Version history

  1. Received: September 22, 2020
  2. Preprint posted: September 25, 2020 (view preprint)
  3. Accepted: July 30, 2021
  4. Accepted Manuscript published: August 5, 2021 (version 1)
  5. Version of Record published: August 12, 2021 (version 2)

Copyright

© 2021, Hunter et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 3,873
    views
  • 490
    downloads
  • 26
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Ann Louise Hunter
  2. Charlotte E Pelekanou
  3. Nichola J Barron
  4. Rebecca C Northeast
  5. Magdalena Grudzien
  6. Antony D Adamson
  7. Polly Downton
  8. Thomas Cornfield
  9. Peter S Cunningham
  10. Jean-Noel Billaud
  11. Leanne Hodson
  12. Andrew Loudon
  13. Richard D Unwin
  14. Mudassar Iqbal
  15. David Ray
  16. David A Bechtold
(2021)
Adipocyte NR1D1 dictates adipose tissue expansion during obesity
eLife 10:e63324.
https://doi.org/10.7554/eLife.63324

Share this article

https://doi.org/10.7554/eLife.63324

Further reading

    1. Cell Biology
    2. Developmental Biology
    Corey D Holman, Alexander P Sakers ... Patrick Seale
    Research Article

    The energy-burning capability of beige adipose tissue is a potential therapeutic tool for reducing obesity and metabolic disease, but this capacity is decreased by aging. Here, we evaluate the impact of aging on the profile and activity of adipocyte stem and progenitor cells (ASPCs) and adipocytes during the beiging process in mice. We found that aging increases the expression of Cd9 and other fibro-inflammatory genes in fibroblastic ASPCs and blocks their differentiation into beige adipocytes. Fibroblastic ASPC populations from young and aged mice were equally competent for beige differentiation in vitro, suggesting that environmental factors suppress adipogenesis in vivo. Examination of adipocytes by single nucleus RNA-sequencing identified compositional and transcriptional differences in adipocyte populations with aging and cold exposure. Notably, cold exposure induced an adipocyte population expressing high levels of de novo lipogenesis (DNL) genes, and this response was severely blunted in aged animals. We further identified Npr3, which encodes the natriuretic peptide clearance receptor, as a marker gene for a subset of white adipocytes and an aging-upregulated gene in adipocytes. In summary, this study indicates that aging blocks beige adipogenesis and dysregulates adipocyte responses to cold exposure and provides a resource for identifying cold and aging-regulated pathways in adipose tissue.

    1. Cell Biology
    Tongtong Ma, Ruimin Ren ... Heng Wang
    Research Article

    Current studies on cultured meat mainly focus on the muscle tissue reconstruction in vitro, but lack the formation of intramuscular fat, which is a crucial factor in determining taste, texture, and nutritional contents. Therefore, incorporating fat into cultured meat is of superior value. In this study, we employed the myogenic/lipogenic transdifferentiation of chicken fibroblasts in 3D to produce muscle mass and deposit fat into the same cells without the co-culture or mixture of different cells or fat substances. The immortalized chicken embryonic fibroblasts were implanted into the hydrogel scaffold, and the cell proliferation and myogenic transdifferentiation were conducted in 3D to produce the whole-cut meat mimics. Compared to 2D, cells grown in 3D matrix showed elevated myogenesis and collagen production. We further induced fat deposition in the transdifferentiated muscle cells and the triglyceride content could be manipulated to match and exceed the levels of chicken meat. The gene expression analysis indicated that both lineage-specific and multifunctional signalings could contribute to the generation of muscle/fat matrix. Overall, we were able to precisely modulate muscle, fat, and extracellular matrix contents according to balanced or specialized meat preferences. These findings provide new avenues for customized cultured meat production with desired intramuscular fat contents that can be tailored to meet the diverse demands of consumers.