The core mammalian pluripotency network in induced pluripotent stem cell (iPSC) formation : models for genetic and epigenetic reprogramming
Author(s)Abdallah, Hussein(Hussein M.)
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Domitilla Del Vecchio.
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In 2006, history was made in a seminal experiment that converted mouse fibroblasts to a pluripotent phenotype coined the 'induced pluripotent stem cell' (iPSC) state. Unhindered by ethical or immunogenic constraints, iPSCs potentially hold the keys to tremendous applications in therapeutic and regenerative medicine. Furthermore, on-demand iPSC generation has the capacity to revolutionize basic research in disease modeling and drug discovery. These promises notwithstanding, the economics of iPSC formation--which remains a slow, inefficient, expensive, and laborious process--still stand in the way of fully making use of this extraordinary technology. In this thesis, I present mathematical models aimed at understanding the theoretical reprogrammability of the core pluripotency gene regulatory network being awakened in iPSC reprogramming. Using these modeling insights, I discuss the merits of current reprogramming strategies, which can be viewed as open-loop perturbations in control theoretic terms. I then discuss an alternative paradigm of closed-loop reprogramming, which is theoretically shown to be far superior when it comes to the reprogrammability of the pluripotency network. Finally, I propose a reprogramming model that incorporates the eæect of DNA demethylation on the activation of the network, with attention given to the relationship between this epigenetic transformation and the cell proliferation barrier that somatic cells seemingly face on the road to pluripotency.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018Cataloged from student-submitted PDF version of thesis. "February 2018."Includes bibliographical references (pages 23-37).
DepartmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology
Electrical Engineering and Computer Science.