Design of a Synthetic Integral Feedback Circuit: Dynamic Analysis and DNA Implementation

Abstract

The design and implementation of regulation motifs ensuring robust perfect adaptation are challenging problems in synthetic biology. Indeed, the design of high-yield robust metabolic pathways producing, for instance, drug precursors and biofuels, could be easily imagined to rely on such a control strategy in order to optimize production levels and reduce production costs, despite the presence of environmental disturbance and model uncertainty. We propose here a motif that ensures tracking and robust perfect adaptation for the controlled reaction network through integral feedback. Its metabolic load on the host is fully tunable and can be made arbitrarily close to the constitutive limit, the universal minimal metabolic load of all possible controllers. A DNA implementation of the controller network is finally provided. Computer simulations using realistic parameters demonstrate the good agreement between the DNA implementation and the ideal controller dynamics.

A Blueprint for a Synthetic Genetic Feedback Controller to Reprogram Cell Fate

“…Other options include integral feedback, as proposed in Briat et al (2016a) for certain classes of systems. However, such integral feedback designs assume that species do not dilute (i.e., no cell growth), making them better suited for reconstituted cell-free systems (an elegant realization of this has been proposed in Briat et al, [2016b]). Interestingly, the mathematical formulation of integral control of Briat et al (2016a) requires that the “control input” on the target’s equation is an additive positive perturbation, leading to the same shortcomings as preset overexpression for the gene regulatory network reprogramming problem of this paper.…”

Design of an embedded inverse-feedforward biomolecular tracking controller for enzymatic reaction processes

“…The complexity of the control problem considered here is significantly higher than in previous studies – almost all previous studies consider either a static or a very simple first order process that avoids the possibility of the reference value being larger than the output value (Cosentino et al, 2016) or employing control strategies that can reduce the duration of the reference value being smaller than the output value (Briat et al, 2016) or consider only a very simple static process with no dynamics (Yordanov et al, 2014). Using the existing standard realisation of one-sided subtraction, our approach of using inverse feedforward combined with feedback control produces highly accurate and robust reference tracking.…”

In vitro implementation of robust gene regulation in a synthetic biomolecular integral controller

“…S9). 14 Encouraged by these results, we experimentally tested the same conditions in TXTL reactions.…”

“…Motivated by this analogy, various possible designs of such controllers have been discussed substantially in the context of biological systems. [13][14][15][16]26 The present work is inspired by our previous work, 26 in which we introduced a computational design based on RNA based controllers; no experimental validation was provided. Here, we start from that design, modifying it to allow for direct genetic regulation and provide an experimental validation.…”

“…The "internal model principle" in control theory states, in essence, that the existence of an integrator in the control loop is necessary for the tight regulation of the concentration of an output species in the presence of disturbances or stimuli. 12 Inspired by these ideas from engineering and control theory, there have been several recent designs [13][14][15][16] and implementations [17][18] of biomolecular integral feedback controllers. These implementations are not completely satisfactory in that it is very difficult to make quantitative predictive models of their behaviors, in large part due to the biological noise which is found in cellular systems, which makes it hard to achieve precise control over model parameters, thereby complicating the design and feasibility of the system.…”