Back

Myelin transcription factors 1 and 3 have overlapping but distinct roles in insulin secretion and survival of human β cells

Hu, R.; Yagan, M.; Wang, Y.; Tong, X.; Doss, T.; Liu, J.-H.; Xu, Y.; Simmons, A.; Lau, K.; stein, r.; Liu, Q.; Gu, G.

2025-02-25 cell biology
10.1101/2025.02.24.639737 bioRxiv
Show abstract

Aims/hypothesisGenetic and environmental factors work together to cause islet beta-cell failure, leading to type 2 diabetes (T2D). How these factors are integrated to regulate beta cells remains largely unclear. Based on our previous findings that the family of Myelin transcription factors (MYT1, MYT1L, and ST18) prevents mouse beta-cell failure by repressing the overactivation of stress response, their regulation by obesity-related nutrition signals in human beta cells, and their association with T2D, we postulate that these factors prevent human beta-cell failure under normal physiology and obesity-related stress. MethodsMYT1 or ST18 were knocked down in primary human beta cells using shRNA. Beta-cell survival, secretory function, and gene expression were examined after islet cells were cultured in vitro or xenotransplanted into mice under normal or obesity-related stress. ResultsIn culture, MYT1-knockdown (KD) caused beta-cell death, while ST18-KD compromised glucose-stimulated insulin secretion. Under obesity-induced stress as xenotransplants, ST18-KD also caused beta-cell death. Accordingly, MYT1-KD deregulated several genes and genesets in cell death and cellular stress response, while ST18-KD deregulated those regulating stress response, mitochondria, and ion channels. Corresponding to these gene expression changes, ST18-KD reduces glucose-stimulated Ca2+ influx in beta cells. In addition, the MYT1- and ST18-regulated genes are enriched for T2D-associated loci, with an enrichment of 2.05-fold relative to random distribution. Conclusions/interpretationThe MYT TFs complement each other to integrate genetic and environmental factors to prevent beta-cell failure and T2D, with their major effects exerted on beta-cell viability and/or Ca2+ influx. Graphical AbstractNutrient-responsive transcription factors MYT1 and ST18 regulate human beta-cell survival and secretory functions. Under low metabolic stress, MYT1 regulates cell survival while ST18 regulates insulin secretion. Under high metabolic stress, ST18 also regulates beta-cell survival. MYT1, at least partly, regulates cell survival through stress-related apoptotic processes, while ST18 regulates insulin secretion via Ca2+ influx. Research in context summaryO_ST_ABSBackgroundC_ST_ABSO_LIThe myelin transcription factors (MYT TFs, including MYT1, MYT1l, and ST18) prevent mouse beta-cell failure by depressing the overactivation of stress-response genes. C_LIO_LISNPs in all three MYT loci are associated with human type 2 diabetes. C_LIO_LIThe expression and nuclear localization of MYT1 and ST18 were increased in primary human beta cells under acute metabolic stress but downregulated in type 2 diabetes. C_LIO_LIThe co-knockdown of MYT1, MYT1L, and ST18 in a human beta-cell line resulted in apoptosis. C_LI Key questionO_LIHow does MYT1 or ST18 regulate human beta-cell function and survival? C_LI New findingsO_LIMYT1 prevents human beta-cell death under normal and metabolic stress conditions, corresponding to deregulation of a few genes involved in cell death under cellular stress. C_LIO_LIST18 promotes insulin secretion under normal physiological conditions by regulating Ca2+ influx and prevents beta-cell death under metabolic stress. C_LIO_LIThe MYT1- and ST18-regulated genes are enriched for type 2 diabetes-risk loci. C_LI Clinical impactO_LIRegulators of the MYT-TF activities could be explored to delay/prevent beta-cell failure and the development of type 2 diabetes. C_LI

Published in Diabetologia (predicted rank #1) · training set

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.