Queuing Networks for the Optimization of Cell Factories

View all posters

Haseong Kim, Haseong Kim, Bong Hyun Sung, Daehee Lee, Jien Lee, and Seung-Goo Lee

Korea Research Institute of Bioscience and Biotechnology, South Korea

The development of synthetic biology enables genetically modified microbes to produce useful biochemicals especially for the cost-effective and sustainable green chemistry. Currently one of the essential tasks of the cell factory research is to optimize the bioprocess of the target chemicals for maximizing the production efficiency. To this end, we have applied the G-network which is a type of queuing networks that have had a broad range of applications ranging from the evaluation of production efficiency in a factory to the performance analysis of computer systems and network routing. Although molecule based modeling is limited by the nature the queuing system (e.g. merging and spiriting of a molecule), we show that a latent molecule containing the expression information of related chemical species successfully describes the chemical reaction processes by modeling the flows of the latent molecule. As an example, a genetic circuit consisting of two AND gates, one Input and one GFP output is modeled along with the single cell based GFP fluorescence level from a high-throughput flow cytometry technique. Thanks to the analytical steady-state solution of the G-networks, we can evaluate the circuit performance and its dynamics without time demanding computational simulations. Although the G-network approach still has limitations for describing a non-steady-state system such as oscillatory expressions, it will be beneficial for optimizing the complex cell factory involving tens of hundreds of molecules by detecting bottle necks in a target chemical production pathway.