常染色体显性多囊肾病
纤毛
多囊肾病
包装D1
肾
细胞生物学
医学
肾脏疾病
内科学
生物
作者
Dominique Douguet,Amanda Patel,Eric Honoré
标识
DOI:10.1038/s41581-019-0143-6
摘要
Mutations in the polycystins PC1 or PC2 cause autosomal dominant polycystic kidney disease (ADPKD), which is characterized by the formation of fluid-filled renal cysts that disrupt renal architecture and function, ultimately leading to kidney failure in the majority of patients. Although the genetic basis of ADPKD is now well established, the physiological function of polycystins remains obscure and a matter of intense debate. The structural determination of both the homomeric PC2 and heteromeric PC1–PC2 complexes, as well as the electrophysiological characterization of PC2 in the primary cilium of renal epithelial cells, provided new valuable insights into the mechanisms of ADPKD pathogenesis. Current findings indicate that PC2 can function independently of PC1 in the primary cilium of renal collecting duct epithelial cells to form a channel that is mainly permeant to monovalent cations and is activated by both membrane depolarization and an increase in intraciliary calcium. In addition, PC2 functions as a calcium-activated calcium release channel at the endoplasmic reticulum membrane. Structural studies indicate that the heteromeric PC1–PC2 complex comprises one PC1 and three PC2 channel subunits. Surprisingly, several positively charged residues from PC1 occlude the ionic pore of the PC1–PC2 complex, suggesting that pathogenic polycystin mutations might cause ADPKD independently of an effect on channel permeation. Emerging reports of novel structural and functional findings on polycystins will continue to elucidate the molecular basis of ADPKD. Autosomal dominant polycystic kidney disease (ADPKD) is caused by pathogenic mutations in the genes that encode polycystin 1 (PC1) and PC2. In this article, the authors discuss findings from structural and electrophysiological studies that give us insight into the function of polycystins and ADPKD pathogenesis.
科研通智能强力驱动
Strongly Powered by AbleSci AI