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Overcoming Contextual Effects On Cell Signaling: A Control Theoretic Approach

Speaker Name: 
Marcella Gomez
Speaker Title: 
Postdoctoral Fellow in Electrical Engineering and Computer Science
Speaker Organization: 
University of California Berkeley
Start Time: 
Friday, January 20, 2017 - 10:00am
End Time: 
Friday, January 20, 2017 - 11:00am
E2 180 Simularium
Professor Daniele Venturi


Gene regulatory networks lie at the crux of life, from regulating concentration of enzymes that propel metabolic pathways to regulating concentration of proteins involved in high-level cellular decision-making.  Despite rapidly evolving tools in synthetic biology, our ability to replicate these behaviors remains a challenge. This is in part because contextual effects are poorly understood. There is a need to extend control theory to automate effective network design in the presence of all adversarial facets of biological processes.  Such a challenge includes the development of predictive models. At the single cell level I find that the inclusion of delays and stochastic processes can result in varied dynamical responses. I show that with an understanding of the effects of delays and stochasticity on dynamics, one can design effective controllers for stability. Furthermore, to generate reliable heterogeneous responses, cell-to-cell communication can be used.  To this end, I show that spatial context and boundary conditions in a bistable system with diffusion can influence predicted dynamical behavior. I show that a bistable system in two-dimensional space can exhibit spatio-temporal patterns. Finally, I propose to optimize expression of an enzymatic pathway by overcoming inhibition from its host environment. More specifically, I showcase current work towards controlling expression rates in the mevalonate pathway to further advance production rates of biofuels in a way not currently doable.  Ultimately, these methods combined will bridge control and dynamical systems with synthetic biology to achieve robust regulation of heterologous networks independent of environmental context.


Marcella M. Gomez received her PhD in Mechanical Engineering from the California Institute of Technology in June 2015. She is currently a postdoctoral fellow at the University of California, Berkeley in Electrical Engineering and Computer Science.  Her research interests lie in developing synergistic methods combining applied mathematics and experimental work for the advancement in understanding and designing complex genetic networks. In particular, her efforts focus on uncovering the underpinnings of effective feedback control mechanisms within noisy biochemical processes and parallel cellular processes.