Related Experiment Video
Updated: Sep 14, 2025

Reliably Engineering and Controlling Stable Optogenetic Gene Circuits in Mammalian Cells
Published on: July 6, 2021
Engineering Cell Fate with Adaptive Feedback Control
Frank Britto Bisso1, Giulia Giordano2, Christian Cuba Samaniego1
1Computational Biology Department, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, United States.
None:
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.
Related Concept Videos
Cell Signaling Feedback Loops
Negative feedback loops
Most signaling systems have negative feedback loops that can perform different functions such as output limiter, and adaptation.
Output limiter
Upon receiving an input signal, the cellular response rapidly increases until a threshold is reached. Beyond this threshold, a negative feedback loop...
Feedback control systems
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
Determination
Effects of feedback
Feedback significantly modifies the gain of a control system. The gain of a system without feedback is altered by a factor of one plus GH, where G represents...
Maintenance of the ES Cell State
The Cell Cycle Control System
Cyclins and cyclin-dependent kinases (Cdks) are the primary cell cycle regulators and...

