Adipocyte-specific disruption of ATPase copper transporting α in mice accelerates lipoatrophy

ATPase copper transporting α (ATP7A), also known as Menkes disease protein, is a P-type ATPase that transports copper across cell membranes. The critical role of ATP7A-mediated copper homeostasis has been well recognised in various organs, such as the intestine, macrophages and the nervous system. However, the importance of adipocyte ATP7A-mediated copper homeostasis on fat metabolism is not well understood. Here, we sought to reveal the contribution of adipose ATP7A to whole-body fat metabolism in mice.

We generated adipocyte-specific Atp7a-knockout (ASKO) mice using the Cre/loxP system, with Cre expression driven by the adiponectin promoter. ASKO mice and littermate control mice were aged on a chow diet or fed with a high-fat diet (HFD); body weight, fat mass, and glucose and insulin metabolism were analysed. Histological analysis, transmission electron microscopy and RNA-sequencing (RNA-Seq) analysis of white adipose tissue (WAT) were used to understand the physiological and molecular changes associated with loss of copper homeostasis in adipocytes.

Significantly increased copper concentrations were observed in adipose tissues of ASKO mice compared with control mice. Aged or HFD-fed ASKO mice manifested a lipoatrophic phenotype characterised by a progressive generalised loss of WAT. Dysfunction of adipose tissues in these ASKO mice was confirmed by decreased levels of both serum leptin and adiponectin and increased levels of triacylglycerol and insulin. Systemic metabolism was also impaired in these mice, as evidenced by a pronounced glucose intolerance, insulin resistance and hepatic steatosis. Moreover, we demonstrate a significant induction of lipolysis and DNA-damage signalling pathways in gonadal WAT from aged and HFD-fed ASKO mice. In vitro studies suggest that copper overload is responsible for increased lipolysis and DNA damage.

Our results show a previously unappreciated role of adipocyte Atp7a in the regulation of ageing-related metabolic disease and identify new metallophysiologies in whole-body fat metabolism.

The datasets generated during the current study are available in the Genome Sequence Archive in BIG Data Center, Beijing Institute of Genomics (BIG), Chinese Academy of Sciences, under accession number CRA001769 (http://bigd.big.ac.cn/gsa).