iScience (Jan 2023)

Mapping transcriptional heterogeneity and metabolic networks in fatty livers at single-cell resolution

  • Laetitia Coassolo,
  • Tianyun Liu,
  • Yunshin Jung,
  • Nikki P. Taylor,
  • Meng Zhao,
  • Gregory W. Charville,
  • Silas Boye Nissen,
  • Hannele Yki-Jarvinen,
  • Russ B. Altman,
  • Katrin J. Svensson

Journal volume & issue
Vol. 26, no. 1
p. 105802

Abstract

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Summary: Non-alcoholic fatty liver disease is a heterogeneous disease with unclear underlying molecular mechanisms. Here, we perform single-cell RNA sequencing of hepatocytes and hepatic non-parenchymal cells to map the lipid signatures in mice with non-alcoholic fatty liver disease (NAFLD). We uncover previously unidentified clusters of hepatocytes characterized by either high or low srebp1 expression. Surprisingly, the canonical lipid synthesis driver Srebp1 is not predictive of hepatic lipid accumulation, suggestive of other drivers of lipid metabolism. By combining transcriptional data at single-cell resolution with computational network analyses, we find that NAFLD is associated with high constitutive androstane receptor (CAR) expression. Mechanistically, CAR interacts with four functional modules: cholesterol homeostasis, bile acid metabolism, fatty acid metabolism, and estrogen response. Nuclear expression of CAR positively correlates with steatohepatitis in human livers. These findings demonstrate significant cellular differences in lipid signatures and identify functional networks linked to hepatic steatosis in mice and humans.

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