Journal of Lipid ResearchMolecular BiologyPeer-reviewed journal article
Hepatic Deletion of X-box Binding Protein 1 in Farnesoid X Receptor Null Mice Leads to Enhanced Liver Injury
Xiaoying LiuiD, Mahmoud G. KhalafallaiD, Chuhan ChungiD, Yevgeniy GindiniD, Susan C. Hubchak, Brian E. LeCuyer, Alyssa A. KriegermeieriD, Danny Zhang, Wei QiuiD, Xianzhong DingiD, Deyu FangiD, Richard Green
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Abstract
Background & AimsFarnesoid X receptor (FXR) regulates bile acid metabolism and FXR null (Fxr-/-) mice have elevated bile acid levels and progressive liver injury. The inositol-requiring enzyme 1 (IRE1)/X-box binding protein 1 (XBP1) pathway is a protective pathway of the unfolded protein response (UPR) that is activated in response to ER stress. In this study we sought to determine the role of the UPR in Fxr-/- mice. Approach & ResultsWe examined hepatic UPR gene and protein expression in 10- and 24-week-old wild type (WT) and Fxr-/- mice. Hepatic XBP1 and other UPR pathways were activated in 24-week-old Fxr-/- mice, but not WT mice. To further determine the role of the liver UPR activation in Fxr-/- mice, we generated mice with FXR and liver-specific XBP1 double knockout (DKO, Fxr-/-Xbp1LKO) and Fxr-/- Xbp1fl/fl single knockout (SKO) mice and characterized their phenotypes at different ages. DKO mice demonstrated enhanced liver injury, apoptosis and fibrosis compared with SKO mice. RNA-seq revealed increased gene expression in apoptosis, inflammation and cell proliferation pathways in DKO mice. The proapoptotic C/EBP-homologous protein (CHOP) pathway was activated in DKO mice. At age 60 weeks, all DKO mice and no SKO mice spontaneously developed liver tumors. ConclusionsThe hepatic XBP1 pathway is activated in older Fxr-/- mice and has a protective role. The potential interaction between XBP1 and FXR signaling may be important in modulating the hepatocellular cholestatic stress responses.
- organism: mouse
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: cell type annotation
- approach: statistical model
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