Engineering Cell Fate with Adaptive Feedback Control

  • Frank Britto Bisso
  • , Giulia Giordano
  • , Christian Cuba Samaniego

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

1 Cita (Scopus)

Resumen

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.

Idioma originalInglés
Páginas (desde-hasta)3163-3176
Número de páginas14
PublicaciónACS synthetic biology
Volumen14
N.º8
DOI
EstadoPublicada - 15 ago. 2025
Publicado de forma externa

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