Engineering, Analysis and Control of Biomolecular Circuits Under Uncertainty

Introduction

Synthetic Biology is one of the pillars of the bioeconomy. However, a number of fundamental issues need to be resolved before its full potential can be realized.

Challenges in Synthetic Biology

First, the design of dynamic biomolecular circuits faces high 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 the demands arising from cutting-edge applications and scientific challenges such as the synthetic cell, including those related to cell cognition.

Objectives of CellWise

CellWise aims to make a major contribution to the field by developing theoretical tools, and mathematical and computational methods to achieve enhanced predictability in Synthetic Biology. The objectives are:

1. Harnessing noise from different sources, uncertainty, and context dependency for the precise engineering of complex biological functions.
2. Fundamentally advancing the bifurcation analysis of biomolecular circuits under noise and uncertainty.
3. Achieving precise control of cell function, both at the single cell and population levels.

Focus Areas

The project has a special focus on the engineering and control of cell cognition capabilities such as memory and cell decision-making.

Proposed Methodology

To accomplish this, we propose an innovative mathematical modeling framework for dynamic biomolecular circuits under noise and uncertainty, combined with state-of-the-art optimization methods, our recent insights on the automated design and bifurcation behavior of stochastic systems, and experimental work.

Expected Outcomes

Through the realization of these objectives, CellWise will unlock innovative synthetic biology applications and improve our understanding of fundamental questions in biology. This will illuminate mechanisms by which cells achieve robust function in the presence of noise and elucidate how cellular decisions can be precisely controlled.