An unbiased drug screen approach to reverse beta cell dedifferentiation in diabetes

The aim of this proposal is to identify driver networks of pancreatic β-cell failure in humans, and perform an unbiased drug screen to test whether it is reversible by pharmacological treatment. In preliminary data, using a combinatorial approach of single-cell RNA sequencing (scRNA-Seq) with human T2D islets and computational regulatory network analysis, the PI identified potential master regulatory networks associated with diabetes-unique b-cell sub-populations. Using this information, the PI proposes to functionally test the effects of candidate master regulators using a candidate gene perturbation screen in primary islets. This information will be used to carry out an unbiased screen of a limited subset of FDA-approved drugs in primary islets, using an integrated high-throughput screening (HTS)/RNA-seq platform (PlateSeq) for the high-multiplex, low-cost RNA-seq profiling of compound perturbations in cellular systems. The findings will increase our understanding of cellular heterogeneity in human T2D islets, determine driver networks that control cell fate transition, and begin to define actionable therapeutic pathways to intervene on the disease process.