Engineering, Analysis and Control of Biomolecular Circuits Under Uncertainty

Synthetic Biology is one of the pillars of the bioeconomy. However, a number of fundamental issues need tobe resolved before its full potential can be realized. First, the design of dynamic biomolecular circuits faceshigh levels of uncertainty from different sources leading to poor predictability of Synthetic Biology designs.Furthermore, there is an urgent need for more sophisticated biomolecular circuit functionalities to meet thedemands arising from cutting-edge applications and scientific challenges such as the synthetic cell, includingthose related with cell cognition.CellWise aims to make a major contribution to the field by developing theoretical tools, and mathematical andcomputational methods to achieve enhanced predictability in Synthetic Biology. The objectives are: i)harnessing noise of different sources, uncertainty and context dependency for the precise engineering ofcomplex biological functions, ii) fundamentally advancing the bifurcation analysis of biomolecular circuitsunder noise and uncertainty, and iii) achieving precise control of cell function, both at the single cell andpopulation levels. The project has a special focus on the engineering and control of cell cognition capabilitiessuch as memory and cell decision-making. To accomplish this, we propose an innovative mathematicalmodelling framework for dynamic biomolecular circuits under noise and uncertainty, combined with state-ofthe-art optimization methods, our recent insights on the automated design and bifurcation behaviour ofstochastic systems, and experimental work.Through the realization of these objectives, CellWise will unlock innovative synthetic biology applicationsand improve our understanding of fundamental questions in biology, illuminating mechanisms by which cellsachieve robust function in presence of noise, and elucidating how cellular decisions can be precisely controlled.