TY - JOUR
T1 - Engineering Cell Fate with Adaptive Feedback Control
AU - Britto Bisso, Frank
AU - Giordano, Giulia
AU - Cuba Samaniego, Christian
N1 - Publisher Copyright:
© 2025 The Authors. Published by American Chemical Society
PY - 2025/8/15
Y1 - 2025/8/15
N2 - Engineering cell fate is fundamental to optimizing therapies based on stem cells, which are aimed at replacing cells in patients suffering from trauma or disease. By timely administering molecular regulators (e.g., transcription factors, RNAs, or small molecules) in a process that mimics in vivo embryonic development, stem cell differentiation can be guided toward a specific cell fate. However, scaling up these therapies is extremely challenging because such differentiation strategies often result in mixed cellular populations. While synthetic biology approaches have been proposed to increase the yield of desired cell types, designing gene circuits that effectively redirect cell fate decisions requires mechanistic insight into the dynamics of the endogenous regulatory networks that govern this type of decision-making. In this work, we present a biomolecular adaptive controller designed to favor a specific cell fate. The controller, whose topology is akin to that of an Incoherent Feedforward Loop (IFFL), requires minimal knowledge of the endogenous network as it exhibits adaptive, non-reference-based behavior. The synthetic circuit operates through a sequestration mechanism and a delay introduced by an intermediate species, producing an output that asymptotically approximates a discrete temporal derivative of its input if the sequestration rate is sufficiently fast. Allowing the controller to actuate over a target species involved in the decision-making process creates a tunable synthetic bias that favors the production of the desired species with minimal alteration to the overall equilibrium landscape of the endogenous network. Through theoretical and computational analysis, we provide design guidelines for the controller’s optimal operation, evaluate its performance under parametric perturbations, and extend its applicability to various examples of common multistable systems in biology.
AB - Engineering cell fate is fundamental to optimizing therapies based on stem cells, which are aimed at replacing cells in patients suffering from trauma or disease. By timely administering molecular regulators (e.g., transcription factors, RNAs, or small molecules) in a process that mimics in vivo embryonic development, stem cell differentiation can be guided toward a specific cell fate. However, scaling up these therapies is extremely challenging because such differentiation strategies often result in mixed cellular populations. While synthetic biology approaches have been proposed to increase the yield of desired cell types, designing gene circuits that effectively redirect cell fate decisions requires mechanistic insight into the dynamics of the endogenous regulatory networks that govern this type of decision-making. In this work, we present a biomolecular adaptive controller designed to favor a specific cell fate. The controller, whose topology is akin to that of an Incoherent Feedforward Loop (IFFL), requires minimal knowledge of the endogenous network as it exhibits adaptive, non-reference-based behavior. The synthetic circuit operates through a sequestration mechanism and a delay introduced by an intermediate species, producing an output that asymptotically approximates a discrete temporal derivative of its input if the sequestration rate is sufficiently fast. Allowing the controller to actuate over a target species involved in the decision-making process creates a tunable synthetic bias that favors the production of the desired species with minimal alteration to the overall equilibrium landscape of the endogenous network. Through theoretical and computational analysis, we provide design guidelines for the controller’s optimal operation, evaluate its performance under parametric perturbations, and extend its applicability to various examples of common multistable systems in biology.
KW - adaptive control
KW - cell fate
KW - feedback control
KW - genetic circuits
KW - incoherent feedforward loop
KW - multistability
UR - https://www.scopus.com/pages/publications/105013588228
U2 - 10.1021/acssynbio.5c00299
DO - 10.1021/acssynbio.5c00299
M3 - Article
C2 - 40698642
AN - SCOPUS:105013588228
SN - 2161-5063
VL - 14
SP - 3163
EP - 3176
JO - ACS synthetic biology
JF - ACS synthetic biology
IS - 8
ER -