Models of the Cell for Synthetic Gene Circuits Design

Premkumar Jayaraman, Chueh Loo Poh

School of Chemical and Biomedical Engineering, Nanyang Technological University, Singapore

Abstract
Synthetic Biology is an emerging and rapidly developing field that applies engineering principles to biology to systematically engineer biological systems with new functions that, for example, address important and challenging problems related to healthcare, energy and the environment. A challenge in Synthetic Biology is to achieve predictable and efficient engineering of the biological systems. This challenge is largely due to the complexity of biological systems. To engineer biological systems with new functions, foreign genetic circuits are often designed and introduced into microorganism (host) to achieve the desired functions. Consequently, this adds burden to the host as these foreign circuits would draw cellular resources and energy from the organism. This usually affects the growth of the host which will in turn affect the performance of the genetic circuits. It will be useful to be able to study this effect in silico before actual wet laboratory experiments. To this end, it is important to have models that are able to predict host-dependent circuit functions and burden on the host. The insights from those models could then be used to optimize the gene circuit and reduce the host-burden. In this talk, we will present models of Escherichia coli cell to interpret and predict the behaviour of synthetic gene circuits and its host-effect. We have verified the modelâ??s ability to mimic the wild-type cell state by estimating the growth reduction under different external glucose levels. We also validated that the model is able to predict the effects of transcription and translation inhibiting antibiotics on cellular growth under limiting nutrient conditions. After verifying the model without foreign gene circuits (i.e. wild-type), we carried out experiments to verify the models when foreign gene circuits were introduced. Our results show that our model can quantitatively account for the impact on cellular growth rates when simple constitutive and inducible devices are introduced.