The field of synthetic biology has produced genetic circuits capable of emulating functional paradigms seen in digital electronic circuits. Examples are bistable switches, oscillators, and logic gates. The present work combines detailed mechanistic-kinetic models and stochastic simulation techniques as well as the techniques of in vivo molecular biology to study the potential of a synthetic, single promoter AND gate. This device is composed of elements of the tet, lac, and λ-phage promoters and is responsive to the commonly used inducers IPTG and aTc, producing GFP as an output signal. The quantitative behavior of the AND gate phenotype is studied both in numero and in vivo as a function of promoter topology. The model is constructed from kinetic data obtained from the literature and yields clearly defined ON/OFF logical behavior at realistic inducer concentrations. These behaviors are matched with observed in vivo data obtained through fluorescence-activated cell sorting. The effect of incomplete repression by weaker LacI repressor is also investigated and quantified. The simulation results, coupled with in vivo data, not only identify important design degrees of freedom, but also provide parameters that can be used to guide future synthetic designs using these common regulatory elements.
|Original language||English (US)|
|Number of pages||10|
|Journal||Biochemical Engineering Journal|
|State||Published - Dec 1 2009|
Bibliographical noteFunding Information:
This work was supported by a grant from the National Science Foundation (BES-0425882, CBET-0425882 and CBET-0644792) and the University of Minnesota Biotechnology Institute. Computational support from the Minnesota Supercomputing Institute (MSI) is gratefully acknowledged. This work was also supported by the National Computational Science Alliance under TG-MCA04N033. In addition, we would like to thank Jin Cui Tomshine for her preparation of the schematic diagrams in Fig. 1 .
- Computer-aided design
- Gene regulatory networks
- Logical AND gate
- Multiscale models
- Stochastic simulations
- Synthetic biology