10. Chelsea Hu: Dual-Scale Dynamical Models of Gene Expression Across Growth Stages

Abstract. Synthetic biology holds the potential to transform medicine and sustainability by enabling the precise reprogramming of biological systems. However, this promise remains largely unmet due to the unpredictable behavior of engineered organisms in real-world environments, where living systems are inherently noisy and continuously exposed to environmental fluctuations. To address this challenge, feedback control has emerged as a critical strategy for ensuring the robust and reliable performance of synthetic biological systems. The design of effective feedback control relies on accurate dynamical models that can predict system behavior and inform control strategies. Most current models are mono-scale, focusing exclusively on gene expression dynamics and assuming constant log-phase growth. Although these models have been successful in guiding feedback control in highly controlled environments, such as chemostats, they do not account for growth dynamics. As a result, when growth conditions are not kept constant, these models lose their fidelity.
In this talk, I will introduce the Gene Expression Across Growth Stages (GEAGS) model, which captures gene expression dynamics in batch cultures, where bacterial cells transition through the lag, log, and stationary phases. Using this model, we were able to explain previously unresolved dynamics, particularly when reporter proteins are tagged for fast degradation. In parallel, we explored whether integrating electronics and biology into a closed-loop system could improve the robustness of biological systems by developing an LED-embedded microplate for optogenetic studies (LEMOS). This platform enables seamless communication between electronics and living cells, providing real-time optical feedback to regulate gene expression. By combining the GEAGs model with LEMOS, we identified key limitations in feedback control due to system dead time, which introduces offsets and complicates precise regulation. Together, these tools offer valuable insights into the challenges and opportunities of applying feedback control in biological systems, paving the way for reliable applications of synthetic biology in the real world.
Bio. Dr. Chelsea Hu is an Assistant Professor in the Artie McFerrin Department of Chemical Engineering at Texas A&M University. She received her B.S. in Chemical Engineering from UCLA in 2013 and her Ph.D. from Cornell University in 2018. Following her doctoral work, she joined the Richard Murray Group at the California Institute of Technology as a postdoctoral scholar, where she studied layered feedback control in synthetic biology. In January 2024, Dr. Hu joined Texas A&M as tenure-track faculty. Dr. Hu currently leads the Synbio Systems Lab, which specializes in system dynamics and feedback control in biomolecular networks, combining systems modeling with experimental methods. Her lab’s research focuses on dynamical model development, system identification, and the application of feedback control to biomolecular networks. The Synbio Systems Lab is currently funded by ARPA-H to develop populational control and containment strategies for live bacteria-based cancer immunotherapy