The Cellular Computing team aims to engineer synthetic genetic circuits with increasing levels of complexity: going from the molecular-level in cell-free systems to the multicellular level in co-cultures, with intercellular exchange. By integrating experimental data with mathematical modelling, we strive to understand and predict the behaviour of these circuits, facilitating optimisation and scaling up. Finally, we will use the knowledge generated to improve computer-aided design and automate the process of designing new genetic circuits with diverse functionalities, and across diverse organisms. Our long-term vision is to advance the field of synthetic biology and pave the way for transformative applications in bioengineering and biotechnology.
For details, see: https://www.cellularcomputing.team/
As synthetic genetic circuits grow in scale, they become increasingly difficult for the host cells to maintain and run. The cellular resources required for these circuits impose cellular burden and make the circuits susceptible to negative selection that results in their loss. In this research theme, we build experimental and theoretical methods for quantifying and reducing the expenses/ burden associated with circuit maintenance and execution, as well as mitigating circuit burden using resource-aware dynamic feedback control. Using these methods, we aim to identify the most efficient design architectures that enable the implementation of genetic circuits with defined functions, while minimising expression costs.
To circumvent the size-limit on scaling up of genetic circuits inside single cells, multicellular approaches for building distributed biological circuits have recently emerged. In this research theme, we develop approaches to enable synthetic cell-to-cell communication within bacterial communities, including the accompanying computational logic. These engineered communication signals will enable scaling up of multicellular circuits for complex computational tasks, using a combination of small molecules and DNA-based high bandwidth signals for intercellular communication, implemented in several different environments.
The lack of genetic tools in useful non-model organisms currently prevents leveraging the full potential of the biotechnological process. Considerable effort is required to identify and characterise new genetic parts before they are for engineering in a new chassis organism. In this research theme, we develop cross-system compatible genetic tools and expression systems that are “portable” between different types of cellular and cell-free systems. We use these portable parts for rapid prototyping of genetic circuits and metabolic pathways in a cross-system manner. The aim is to expand the genetic circuits from a single species at-a-time to systems with cells from multiple species: including those from different kingdoms of life.
This theme focusses on the modelling and simulation of biological systems across various levels of biological organisation. We utilise experimental data to construct realistic models of biological circuits that can be simulated using both deterministic and stochastic methods. Starting from molecular-level modelling, we aim to develop computer-aided-design (CAD) tools for the automated design of biological circuits. These circuits will serve various applications, including information-processing circuits within individual cells or in cellular consortia of multiple cells. By integrating experimental data, mathematical modelling, and computational tools, our long-term goal is to achieve predictable computer-aided design of biological circuits for user-defined applications.
All the team publications are available in the CellComp-MICALIS HAL collection.
