Model-driven design and in vivo implementation of a multi-level dynamic pathway regulation combining transcriptional and post-transcriptional regulation (FWOTM1305)

Biomanufacturing using microbial cell factories is often limited by static gene expression, leading to
metabolic imbalances and suboptimal productivity under industrial conditions. Inspired by natural
gene regulation, biosensors can enable dynamic pathway regulation, but current strategies are
limited to either transcriptional or post-transcriptional regulation. This project aims to develop a
model-driven framework that integrates both levels of regulation in synthetic gene circuits to
optimise microbial production. Using Escherichia coli as a host and the β-alanine pathway for 3-
hydroxypropionic acid production as a proof-of-concept, I will develop β-alanine-responsive
riboswitches and combine them with transcription factor-based biosensors to achieve multi-level
regulation. Mathematical modelling, Bayesian optimisation and stochastic simulation will be used to
identify optimal control architectures. In parallel, Capture-SELEX and high-throughput screening will
be used to design and characterise synthetic riboswitches. The most promising circuits will be
implemented in vivo to assess their impact on bioproduction. By integrating multiple levels of
regulation, this project will establish a generalisable strategy for adaptive metabolic engineering.

Keywords:Microbial cell factories, Dynamic regulation of metabolic pathways, Biosensors

Disciplines:Synthetic biology, Bioprocessing, bioproduction and bioproducts, Modelling, simulation and optimisation, Regulation of metabolism