Identification of Beta-Cell-Inducing Small RNAs by Random shRNA Selection

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DESCRIPTION (provided by applicant): The finding that insulin-secreting, endocrine beta cells can be derived from exocrine cells of the mouse pancreas by expressing Ngn3, Pdx1, and MafA could revolutionize diabetes therapeutics. The primary problem - which this proposal seeks to address - is that the viral vectors used to deliver the genes integrate permanently into the genome, which could interfere with the function of derived cells, or cause tumors. In the induced-stem-cell field, several methods have been tested to obviate the need for vector integration, or the introduction of genes. However, none of these methods is entirely satisfactory. We recently developed a novel technology that has the potential to address the problems described above. This technology is an shRNA-expressing library that is completely random at the nucleotide level. Herein, we propose to use this library to identify shRNA sequences that can reprogram, or increase the efficiency of reprogramming of, endocrine beta cells from exocrine cells of the pancreas. Modulation of gene expression by small RNAs can be accomplished by expression of shRNAs from DNA vectors, or by adding pre-synthesized siRNAs to cells exogenously. The advantage of exogenous siRNAs is that their effects are easy to sustain by repeated addition, and are easily reversible - because there is no vector integration, one can simply stop adding them and allow them to degrade. Thus, effective sequences identified from our random shRNA- encoding library, and optimized by random mutagenesis and re-screening, could be used as pre-synthesized siRNAs, thereby obviating the risks associated with vector integration. In addition, siRNAs are easy to synthesize, and easy to introduce into cells using well-established transfection protocols. PUBLIC HEALTH RELEVANCE: This proposal describes an approach to develop novel therapeutics and biologic tools using an shRNA- expressing library that is completely random at the nucleotide level. This approach has implications for the development of diabetes therapeutics and stem-cell-based therapeutics, and is highly relevant to public health.