Atp6ap2 deletion causes extensive vacuolation that consumes the insulin content of pancreatic β cells.
Katrina Jean BingerMartin NeukamSudhir Gopal TattikotaFatimunnisa QadriDmytro PuchkovDiana M WillmesSabrina WurmseeSabrina GeisbergerRalf DechendKlemens RaileThomas KurthGenevieve NguyenMatthew N PoyMichele SolimenaDominik N MullerAndreas L BirkenfeldPublished in: Proceedings of the National Academy of Sciences of the United States of America (2019)
Pancreatic β cells store insulin within secretory granules which undergo exocytosis upon elevation of blood glucose levels. Crinophagy and autophagy are instead responsible to deliver damaged or old granules to acidic lysosomes for intracellular degradation. However, excessive consumption of insulin granules can impair β cell function and cause diabetes. Atp6ap2 is an essential accessory component of the vacuolar ATPase required for lysosomal degradative functions and autophagy. Here, we show that Cre recombinase-mediated conditional deletion of Atp6ap2 in mouse β cells causes a dramatic accumulation of large, multigranular vacuoles in the cytoplasm, with reduction of insulin content and compromised glucose homeostasis. Loss of insulin stores and gigantic vacuoles were also observed in cultured insulinoma INS-1 cells upon CRISPR/Cas9-mediated removal of Atp6ap2. Remarkably, these phenotypic alterations could not be attributed to a deficiency in autophagy or acidification of lysosomes. Together, these data indicate that Atp6ap2 is critical for regulating the stored insulin pool and that a balanced regulation of granule turnover is key to maintaining β cell function and diabetes prevention.
Keyphrases
- type diabetes
- glycemic control
- induced apoptosis
- blood glucose
- cell cycle arrest
- endoplasmic reticulum stress
- transcription factor
- cell death
- signaling pathway
- crispr cas
- oxidative stress
- cardiovascular disease
- body mass index
- blood pressure
- skeletal muscle
- endothelial cells
- pi k akt
- physical activity
- big data
- bone mineral density
- artificial intelligence
- weight gain
- room temperature
- deep learning