Control systems for synthetic biology and a case-study in cell fate reprogramming

TL;DR

The paper addresses the challenge of precisely controlling intracellular regulatory-factor levels under environmental and cellular perturbations for applications like regenerative medicine. It surveys biomolecular control strategies, covering integral/quasi-integral feedback and incoherent feedforward loops, and demonstrates how these can be realized within cellular chemistry. The case study on hiPSC reprogramming uses a high-gain feedback plus feedforward architecture to stabilize Oct4 levels, with experimental validation showing reduced output variability and improved reprogramming efficiency. The work highlights both the promise of biomolecular control for cell fate decisions and the need for context-aware designs and broader field testing to translate these controllers to real-world applications.

Abstract

This paper gives an overview of the use of control systems engineering in synthetic biology, motivated by applications such as cell therapy and cell fate reprogramming for regenerative medicine. A ubiquitous problem in these and other applications is the ability to control the concentration of specific regulatory factors in the cell accurately despite environmental uncertainty and perturbations. The paper describes the origin of these perturbations and how they affect the dynamics of the biomolecular ``plant'' to be controlled. A variety of biomolecular control implementations are then introduced to achieve robustness of the plant's output to perturbations and are grouped into feedback and feedforward control architectures. Although sophisticated control laws can be implemented in a computer today, they cannot be necessarily implemented inside the cell via biomolecular processes. This fact constraints the set of feasible control laws to those realizable through biomolecular processes that can be engineered with synthetic biology. After reviewing biomolecular feedback and feedforward control implementations, mostly focusing on the author's own work, the paper illustrates the application of such control strategies to cell fate reprogramming. Within this context, a master regulatory factor needs to be controlled at a specific level inside the cell in order to reprogram skin cells to pluripotent stem cells. The article closes by highlighting on-going challenges and directions of future research for biomolecular control design.

Figures (12)

• Figure 1: Synthetic genetic device and its environment. (a) A synthetic genetic device is an input/output module constituted by the process of gene expression where a gene produces an output protein X through the process of transcription and translation BFS. When X is a copy of an endogenous protein, the overall production of mRNA is influenced by the endogenous GRN including gene x. Transcription and translation are affected by perturbations to cellular resources. (b) Perturbations to cellular resources arise due to changes in the cellular or extra-cellular context and to the sequestration of these resources by other genetic devices TCONQian. The figure has been adapted from Shakiba2021.
• Figure 2: Biomolecular controller architectures for a synthetic genetic device. (a) Unregulated genetic device with disturbances acting either on transcription or on translation. (b) Regulated genetic device through a feedback controller. (c) Regulated genetic device through a feedforward controller. (d) Output temporal response to a disturbance input. Red shows the response of the unregulated device while blue is the response of the regulated device.
• Figure 3: Biomolecular implementation of an integral feedback cotnroller. (a) Biomolecular circuit diagram. Gene x co-expresses both the output protein and a phosphatase w that dephosphorylates protein u. Only when phosphorylated, this protein can bind to the gene x promoter to activate transcription. Kinase v converts unphosphorylated protein u$_0$ to its phosphorylated version. The open loop system is obtained when phosphotase w is substituted with an inert protein incapable of dephosphorylating u. In the experimental realization published in Jones2022, u$_0$ is protein OmpR, z in the EnvZ kinase, and w is EnvZ mutated to be a pure phosphotase. All these proteins are taken from bacterial cells. OmpR, only when phosphorylated can bind to its cognate promoter cloned in front of gene x. To activate transcription in mammalian cells, OmpR was fused to an activation domain. (b) Expected behavior of open loop and closed loop systems when the disturbance $d$ in the form of a perturbation to transcription is added. (c) Experimental data showing the output protein level, measured via fluorescence in arbitrary units of fluorescence (AUF), for open loop and closed loop systems when an activator protein (Gal4) is added to the system, which sequesters transcriptional resources, thereby lowering transcription rate. Open loop and closed loop system output levels were made comparable by increasing the DNA copy number in the closed loop compared to the open loop. (d) Distribution of the output $y$ across a cell population for different values of the input for open loop (left) and closed loop (right) systems. Figures c and d were adapted from Jones2022.
• Figure 4: Feedforward biomolecular controllers to attenuate transcriptional and translational perturbations. (a) Incoherent feedforward loop. The disturbance enhances the output $y$ through a direct path and inhibits the output $y$ through an indirect path where $d$ first activates an intermediate variable $w$, which then inhibits $y$. The T-like arrow represents inhibition or repression. If well tuned, the effects of the two branches on the output can cancel each other. (b) Feedforward genetic controller implementing an incoherent feedforward loop from disturbance inputs $d_i$ to output $y$. The inhibition of y by w is achieved through transcriptional repression. (c) Feedforward genetic controller where the inhibition of y by w is achieved by w catalyzing the degradation of y as a protease. (d) Feedforward genetic controller where the inhibition of y by w is achieved by w catalyzing the degradation of the mRNA m as an endoribonuclease (ERN). Here, $d_1$ represents a perturbation of the transcription rate while $d_2$ represents a perturbation of the translation rate.
• Figure 5: Implementation of a feedforward controller and its experimental validation. (a) Synthetic genetic circuit implementation of an unregulated genetic device and of its corresponding regulated device via a feedforward controller. The disturbance to the transcription rate is applied by expressing a transcriptional activator (Gal4-VPR), which sequesters transcriptional co-factors from the genetic module, thereby lowering its transcription rate Jones2020. (b) Expected behavior of the feedforward controller (in blue). (c) Experimental data showing the output of the genetic module, unregulated or regulated, as the amount of transcriptional activator is increased, thereby lowering the availability of transcriptional resources to the module. The regulated module achieves the same output level as the unregulated one (with no Gal4-VPR) despite the ERN-based repression by increasing the DNA copy number of the genetic module. (d) Performance of the regulated module with respect to attenuating the effect of variable transcription rate constant due to variability in DNA copy number. (e) Different cell lines have different levels of resources and hence will have different levels of output of the genetic module (unregulated). The regulated device quenches the differences in output due to global changes to resources required for gene expression. Data plots are taken from Jones2020.