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Automatic Design of Digital Synthetic Gene Circuits

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  • Mario A Marchisio
  • Jörg Stelling

Abstract

De novo computational design of synthetic gene circuits that achieve well-defined target functions is a hard task. Existing, brute-force approaches run optimization algorithms on the structure and on the kinetic parameter values of the network. However, more direct rational methods for automatic circuit design are lacking. Focusing on digital synthetic gene circuits, we developed a methodology and a corresponding tool for in silico automatic design. For a given truth table that specifies a circuit's input–output relations, our algorithm generates and ranks several possible circuit schemes without the need for any optimization. Logic behavior is reproduced by the action of regulatory factors and chemicals on the promoters and on the ribosome binding sites of biological Boolean gates. Simulations of circuits with up to four inputs show a faithful and unequivocal truth table representation, even under parametric perturbations and stochastic noise. A comparison with already implemented circuits, in addition, reveals the potential for simpler designs with the same function. Therefore, we expect the method to help both in devising new circuits and in simplifying existing solutions.Author Summary: Synthetic Biology is a novel discipline that aims at the construction of new biological systems able to perform specific tasks. Following the example of electrical engineering, most of the synthetic systems so far realized look like circuits where smaller DNA-encoded components are interconnected by the exchange of different kinds of molecules. According to this modular approach, we developed, in a previous work, a tool for the visual design of new genetic circuits whose components are displayed on the computer screen and connected through hypothetical wires where molecules flow. Here, we present an extension of this tool that automatically computes the structure of a digital gene circuit–where the inputs and the output take only 0/1 values–by applying procedures commonly used in electrical engineering to biology. In this way, our method generalizes and simplifies the design of genetic circuits far more complex than the ones so far realized. Moreover, different from other currently used methods, our approach limits the use of optimization procedures and drastically reduces the computational time necessary to derive the circuit structure. Future improvements can be achieved by exploiting some more biological mechanisms able to mimic Boolean behavior, without a substantial growth of the algorithmic complexity.

Suggested Citation

  • Mario A Marchisio & Jörg Stelling, 2011. "Automatic Design of Digital Synthetic Gene Circuits," PLOS Computational Biology, Public Library of Science, vol. 7(2), pages 1-13, February.
  • Handle: RePEc:plo:pcbi00:1001083
    DOI: 10.1371/journal.pcbi.1001083
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    References listed on IDEAS

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    Cited by:

    1. Zomorrodi, Ali R. & Maranas, Costas D., 2014. "Coarse-grained optimization-driven design and piecewise linear modeling of synthetic genetic circuits," European Journal of Operational Research, Elsevier, vol. 237(2), pages 665-676.
    2. Weiyue Ji & Handuo Shi & Haoqian Zhang & Rui Sun & Jingyi Xi & Dingqiao Wen & Jingchen Feng & Yiwei Chen & Xiao Qin & Yanrong Ma & Wenhan Luo & Linna Deng & Hanchi Lin & Ruofan Yu & Qi Ouyang, 2013. "A Formalized Design Process for Bacterial Consortia That Perform Logic Computing," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-9, February.
    3. Linh Huynh & John Kececioglu & Matthias Köppe & Ilias Tagkopoulos, 2012. "Automatic Design of Synthetic Gene Circuits through Mixed Integer Non-linear Programming," PLOS ONE, Public Library of Science, vol. 7(4), pages 1-9, April.
    4. Vedhas Pandit & Björn Schuller, 2017. "A Novel Graphical Technique for Combinational Logic Representation and Optimization," Complexity, Hindawi, vol. 2017, pages 1-12, December.

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