Computational modeling of programmable bacteria

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Daniel Machado

The Novo Nordisk Foundation Center for Biosustainability, Denmark

The idea of programming cells to perform specific tasks has become an active research topic with applications in biomedical research and industrial biotechnology. This is promoted by synthetic biology through the development of a variety of artificial biological parts. However, computational simulation of a programmable cell is currently not possible due to the lack of integrated modeling of the synthetic parts within the cellular chassis. The goal of this work is the development of a computational modeling framework for a programmable E. coli cell. It begins with an extensive search of biological parts that have been built and experimentally validated. These will be modeled in silico to create a small library of plug-and-play model components. They will then be integrated into recent large-scale regulatory and metabolic model reconstructions of E. coli. The development of methods for integrated simulation of the synthetic parts within the cellular metabolism is one of the novel aspects of this work. The advantages of this framework are two-fold. First, it can save time and money in the laboratory by predicting ahead which combinations of the parts and the host metabolism will not work as expected. On the other hand, it will facilitate the computational design of new potential applications by combining and fine-tuning different parts. This framework will be tested in a practical case study for optimal biochemical production in E. coli from a feedstock containing multiple carbon sources.