Background

State-of-the-art

Attempts to apply engineering principles to biological processes to understand and build new functions in cells have led to the growing research interdisciplinary community of Synthetic Biology. Currently synthetic circuits can perform only very basic functions thus having a limited impact in biotechnology and biomedicine.

Control engineering is a key discipline that provides the theoretical and methodological tools to engineer complex systems and make sure they behave in the desired way across a range of operating conditions. Application and adaption of established theories and techniques from conventional control engineering have been hampered by the peculiarities of biological systems, such as cell-to-cell variability, metabolic load, cross-talking and practical realizability.

It has been recently theoretically shown by consortium members (ETH) that a new motif implementing an integral action can be considered as a potential in vivo controller. These controllers have the advantage of being implementable in terms of chemical reactions, a property that we will call here “bio-realizability”. However, it remains unclear what classes of systems are bio-realizable. This problem has been partially solved for few classes of linear systems.

A first attempt has been made recently to map also nonlinear dynamics to kinetic systems based on a heuristic algorithm. Unfortunately, the scope of these approaches is limited and a sufficiently general framework to synthesize dynamical systems from biochemical primitives remains missing. Current biological control strategies are typically open-loop or built adhoc for the process being controlled using empirical rules, hence they are not generalisable. Moreover, to effectively control a biological circuit, a predictive dynamical model of the biomolecular network to be controlled is needed.

Despite recent progress, the identification of reliable dynamical input-output model of biological systems is still an empirical, time-consuming process.