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Title page for ETD etd-02202017-135410


Type of Document Dissertation
Author Clayton, Hannah Worchel
Author's Email Address hannah.worchel@vanderbilt.edu
URN etd-02202017-135410
Title Variables that influence transcription factor-mediated acinar to beta cell reprogramming
Degree PhD
Department Cell and Developmental Biology
Advisory Committee
Advisor Name Title
Gu Guoqiang Committee Chair
Luc Van Kaer Committee Member
Roland W. Stein Committee Member
William P. Tansey Committee Member
Keywords
  • acinar-to-ductal metaplasia
  • Reprogramming
  • inflammation
  • beta cells
  • acinar cells
  • diabetes
Date of Defense 2016-12-01
Availability unrestricted
Abstract
Reprogramming of pancreatic cells into new beta-like cells is a potential therapy for Type 1 diabetes. Pancreatic acinar cells are an appealing target for cellular reprogramming since they are abundant, derived from a common progenitor cell during pancreatic organogenesis, and exhibit significant transcriptional plasticity. Towards this end, it has been reported that adenoviral-mediated expression of three pancreas-specific transcription factors MafA, Pdx1 and Neurog3 (3TF) in immunocompromised Rag1-/- mice resulted in the conversion of pancreatic acinar cells into new, insulin-secreting, beta-like cells. Using a transgenic mouse model to express 3TF in a pancreatic acinar cell- and doxycycline-dependent manner, we discovered that the outcome of transcription factor-mediated acinar to beta-like cellular reprogramming is dependent on both the magnitude of 3TF expression and on reprogramming-induced inflammation. Overly robust 3TF expression causes acinar cell necrosis resulting in marked inflammation and acinar-to-ductal metaplasia. Generation of new beta-like cells requires limiting reprogramming-induced inflammation, either by reducing 3TF expression or by eliminating macrophages. The new beta-like cells were able to reverse streptozotocin-induced diabetes 6 days after inducing 3TF expression but failed to sustain their function after removal of the reprogramming factors.
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