Identifying single cell response of synthetic networks to aid the | 7545
Current Synthetic and Systems Biology

Current Synthetic and Systems Biology
Open Access

ISSN: 2332-0737


Identifying single cell response of synthetic networks to aid their design: Application to a synthetic mammalian oscillator

2nd International Conference on Systems & Synthetic Biology

August 18-20, 2016 London, UK

Rob Krams

Imperial College London, UK

Posters & Accepted Abstracts: Curr Synthetic Sys Biol

Abstract :

Synthetic networks are becoming increasingly sophisticated and complex in their behavior. While rules to design simple networks are fairly known (orthogonally, matched promoter strength, matched plasmid replication rate), more complex networks need dynamical similarity next to static similarity. When one start using large, noise mammalian cells one also needs to obtain these parameters on a single cell level. This presentation describes a novel platform which integrates modeling features (convolution, parameter estimation) with single cell experiments of individual components of a three element negative feedback oscillator. The platform predicts dynamical behavior of the individual components of the oscillator and suggests which components need to be modified for a better behavior of the oscillator. We have developed a three plasmid gene network by modeling and measurement. We noticed that model predictions and measurements were not compatible and characterized each component in dynamical terms on a single cell level. The dynamical characterization is fed back into the model to predict oscillations and it could be predicted that only a few cells contained the right combination of synthesis rate and gene and protein half life to enable sustained oscillations. Predictions of adaptations of independent components enabled us to modify the network to increase the success rate of sustained oscillations in mammalian cells.

Biography :