After inserting inducible promoters in our violacein pathway, our system now has inbuilt switches. This means we can automate the pathway with computers and control the production of all four metabolites in the violacein pathway by applying control theory. We have come up with the idea/plan behind the implementation of this idea. Our ultimate objective is to control the concentration of all four metabolic products in solution, in real-time automated fashion.
To achieve our objective, we have planned the theory, schema and designed models of two different systems: a culture management system and an image processing & response system. We believe that this will be a step forward for future projects involving the violacein pathway as well as a proof-of-concept for the automation of metabolic pathways in general. Our pages for drylab include:
- Design: An explanation of the motivation and scientific theory, as well as our implementation of our design.
- Hardware: Technical explanation of our setup parts.
- Demonstration: Preliminary Explanation of current undertakings and progress.
To achieve our objective, we have planned the theory, schema and designed models of two different systems: a culture management system and an image processing & response system.The setup that our team developed so far will be able to determine the relationship between RGB values and metabolite concentration. By first elucidating this relationship and creating the physical chemostat and Raspberry Pi setup, we believe our work can already be translatable in many different situations and experiments for other teams in the future. The machine learning aspect of our plans would be the most time-intensive and difficult part to master. But, with more time, we would like to develop our plans and put them to fruition, eventually building a proof-of-concept system for the automation of metabolic pathways in general.