Britto Bisso Frank, Giordano Giulia, Cuba Samaniego Christian
Computational Biology Department, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, United States.
Department of Industrial Engineering, University of Trento, Trento 38123, Italy.
ACS Synth Biol. 2025 Aug 15;14(8):3163-3176. doi: 10.1021/acssynbio.5c00299. Epub 2025 Jul 23.
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.
工程化细胞命运对于优化基于干细胞的疗法至关重要，这些疗法旨在替换遭受创伤或疾病的患者体内的细胞。通过在模拟体内胚胎发育的过程中及时施用分子调节剂（例如转录因子、RNA或小分子），可以将干细胞分化引导至特定的细胞命运。然而，扩大这些疗法的规模极具挑战性，因为这种分化策略往往会导致细胞群体混合。虽然已经提出了合成生物学方法来提高所需细胞类型的产量，但设计能够有效重定向细胞命运决定的基因回路需要对控制此类决策的内源性调节网络的动态有深入的机制理解。在这项工作中，我们提出了一种旨在促进特定细胞命运的生物分子自适应控制器。该控制器的拓扑结构类似于非相干前馈环（IFFL），由于其表现出自适应的、基于非参考的行为，因此对内源性网络的了解要求最低。合成回路通过一种隔离机制和由中间物种引入的延迟来运行，如果隔离速率足够快，会产生一个渐近近似其输入的离散时间导数的输出。允许控制器对参与决策过程的目标物种起作用会产生一个可调的合成偏差，有利于所需物种的产生，同时对内源性网络的整体平衡格局的改变最小。通过理论和计算分析，我们为控制器的最佳运行提供了设计指南，评估了其在参数扰动下的性能，并将其适用性扩展到生物学中常见的多稳态系统的各种示例。
