Growth Versus Differentiation in Human Beta Cells

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PROVIDED. Many cell types exhibit an inverse relationship between growth and differentiation. This linkage is particularly strong in beta-cells. Beta-cells have a low mitotic index, and growth stimulation in vitro results in rapid shut off of insulin gene expression, However, the molecular mechanism by which this is controlled is poorly understood. During the past funding period, studies using cell lines developed from the human endocrine pancreas have led to the hypothesis that the balance between positively and negatively acting bHLH transcription factors plays a central role in controlling beta-cell proliferation and differentiation. Positively acting bHLH factors in the endocrine pancreas include Ngn3 and NeuroDI. Preliminary data presented here demonstrates that these factors induce two other positively acting bHLH factors, Hes6 and AtohS, neither of which had previously been identified in the endocrine pancreas. Hes6 is a bHLH factor that inhibits Notch signaling, which controls pancreatic morphogenesis and endocrine differentiation. Hes6 was found to be specifically expressed in islets, and Hes6 mutant mice developed diabetes, had an increased rate of endocrine cell proliferation, and perhaps most interestingly, spontaneously formed new pancreatic lobules. The role of Hes6 in the endocrine pancreas will be pursued using both cell line models and lineage analysis in transgenic mice. AtohS is a neurogenic bHLH factor that plays a role in the lineage decision between neuronal and glial cell fates. Like Hes6, it was induced by Ngn3 and NeuroDI. Although no antibody is available, RT-PCR demonstrated that it is expressed in islet but not in non-endocrine cells. Thus, it is a strong candidate for playing a role in endocrine cell differentiation. To pursue that finding, the downstream targets of AtohS will be ascertained. Finally, to understand better the pathways that control insulin gene expression in the beta-cell, small molecule libraries have been screened for compunds that modulate insulin promoter activity. To determine the mechanism by which those compounds act, biochemical and genetic data will be acquired and integrated using a bioinformatic approach to pathway analysis.