A mathematical model of cell fate reprogramming: From open loop to closed loop feedback control

Domitilla Del Vecchio
Massachusetts Institute of Technology

To artificially reprogram cell fate, experimentalists manipulate the gene regulatory networks (GRNs) that maintain a cell’s phenotype. In practice, reprogramming is often performed by constant overexpression of specific transcription factors (TFs). This process can be unreliable and inefficient. Here, we focus on induced pluripotent stem cell reprogramming (iPSC) as a case study. We propose a mathematical model demonstrating how constant overexpression may not succeed in general since it is reliant on the GRN's dynamics. In particular, because the core pluripotency GRN is
cooperative, certain state transitions are not possible with constant overexpression. We
therefore propose an alternative reprogramming strategy: a synthetic genetic feedback
controller that dynamically steers the concentration of a GRN’s key TFs to any desired
value. The controller works by adjusting TF expression based on the discrepancy
between desired and actual TF concentrations. Theory predicts that this reprogramming
strategy is guaranteed to succeed, and its performance is independent of the GRN’s
structure and parameters, provided that feedback gain is sufficiently high.

Paper: D. Del Vecchio, H. Abdallah, Y. Qian, and J. J. Collins. A blueprint for a
synthetic genetic controller to reprogram cell fate. Cell Systems, 4:1-12, January 2017.

Presentation (PDF File)

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