Layered feedback control overcomes performance trade-off in synthetic biomolecular networks

Abstract

Layered feedback is an optimization strategy in feedback control designs widely used in engineering. Control theory suggests that layering multiple feedbacks could overcome the robustness-speed performance trade-off limit. In natural biological networks, genes are often regulated in layers to adapt to environmental perturbations. It is hypothesized layering architecture could also overcome the robustness-speed performance trade-off in genetic networks. In this work, we validate this hypothesis with a synthetic biomolecular network in living E. coli cells. We start with system dynamics analysis using models of various complexities to guide the design of a layered control architecture in living cells. Experimentally, we interrogate system dynamics under three groups of perturbations. We consistently observe that the layered control improves system performance in the robustness-speed domain. This work confirms that layered control could be adopted in synthetic biomolecular networks for performance optimization. It also provides insights into understanding genetic feedback control architectures in nature.

Combining positive and negative regulation for modular and robust biomolecular control architectures

“…For biological systems, external disturbances in this case include shifts in gene expression rates, cell growth rate fluctuations or changes in the cell culturing conditions [11], [12]. A major controller-associated disturbance is competition for the cellular resources required to exert control action, such as dCas9 proteins if feedback is implemented using CRISPR-mediated regulation [2], [3], [9].…”

“…due to a temporary shift in the chemical inducer’s concentration). Meanwhile, a simple cis feedback loop [12], where the controlled gene represses itself due to being co-expressed with an interfering sgRNA (Fig. 4b), can successfully combat transcriptional perturbations but not controllerassociated disturbances, especially for high g i production rates.…”

“…Trans feedback loops include an additional node which is regulated by – and in turn, regulates – the controlled node of interest (Fig. 4c) [12]. Exploring the design space of maximum sgRNA synthesis rates α i and α a shows that trans feedback occupies the middle between robustness only to external disturbances (strong cis feedback) and robustness to just controller-associated perturbations (open-loop system).…”

Improving Microbial Cell Factory Performance by Engineering SAM Availability

“…The demand for SdNPs has increased dramatically in recent years. , Traditional approaches to SdNPs include chemical synthesis and crude extraction, however, suffer from low chiral selectivity and yield. , Motivated by the great demand, the past decades have seen substantial advances in developing microbial cell factory (MCF) to produce SdNPs (Table ), which are believed to be promising alternatives to the traditional methods . Moreover, with the fast enrichment of synthetic biology toolboxes, more and more nonconventional microorganisms are being harnessed as producing chassis, − and delicate genetic circuits that can achieve accurate and dynamic regulation are being developed. − …”

A blueprint for a synthetic genetic feedback optimizer

“…To address this challenge, dynamic gene expression control 24 – 26 offers a promising solution, using a system-level approach that combines quantitative tools from a wide array of disciplines 27 – 30 . Recently, an especially fruitful direction has been to borrow ideas from control theory to analyze and design genetic feedback systems 31 , 32 . Notably, integral feedback has been proposed 33 to ensure perfect adaptation, that is, to return to a desired setpoint after a perturbation.…”