Dr Angel Goni-Moreno has won an EPSRC First Grant for SynBio3D, a project that will change engineers' understanding of synthetic biological systems.
The high-tech world of synthetic biology draws on expertise across biology, cytology, computer science and electronics to engineer, design and build biological systems and living organisms. By creating new combinations of DNA and placing them in to existing living cells, engineers are able to create new materials and sensors.
Unlike most other engineering processes, however, there is little need to consider the spatial dimensions of the system being designed.
Dr Goni-Moreno explained: "In the case of building an aeroplane, we need all the parts to be in the right position and connected the right way. In a synthetic biological system, traditionally engineers have only been concerned with whether something was taking place inside or outside of the cell that we are working with."
Dr Goni-Moreno's SynBio3D will upgrade synthetic biology by adding spatial information to the design process.
Speaking about how the project will achieve this, Dr Goni-Moreno said: "When we design a genetic circuit for a synthetic biology system, we generally use time as the only reference point for controlling the system. This project will add spatial constraints such as distances and molecular crowding to improve our ability to deign and model circuits."
Although this will improve the modelling and design of synthetic biological systems, Dr Goni-Moreno will also investigate how we can improve how well we can see what actually happens once the circuits are placed in to cells.
"We will use super-resolution microscopy to obtain three dimensional, real-time measurements of genetic circuits. For the first time, we will be able to see how a genetic circuit operates and changes in the space in which it is operating. This will allow us to formalise spatial engineering fundamentals for future synthetic biology works."
This three-dimensional approach to synthetic biology will lead the way in turning molecular networks into programmable systems - traditional time-based approaches to this challenge have not yet been successful.
Follow Dr Goni-Moreno on Twitter: @AngelGMoreno
published on: 19 October 2017