Given the depletion of fossil resources and climate change concerns, we are transitioning towards a bio-based industry in which microbes are considered to be the chemical factories of the future. 3
-hydroxypropionic acid is a major target chemical to be produced in a sustainable microbial bioconversion process using organic feedstocks, as it can be used for various applications, ranging from bioplastics to additives and resins. The most attractive production pathway to be engineered uses β-alanine as a precursor, however, this pathway is not yet applied for large-scale commercialization due to productivities being too low. Here, I will contribute to lifting this bottleneck by engineering dynamic pathway regulation using a biosensor strategy in the model bacterium Escherichia coli. Starting from the exploration of natural transcription factors that are responsive to the metabolic precursor β-alanine, biosensor modules will be built and functionally analyzed. Mathematical modeling of response curves will enable a thorough understanding and finetuning of the biosensor performance to optimally fit the targeted application, which consists of a production strain with a bifunctional control network. This bifunctional control enables the cell
to optimally balance production and growth leading to higher productivities. This project will not only result in a more performant strain, but will also advance the state-of-the-art of dynamic pathway control for a variety of hosts and products.