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Diversity-based, model-guided construction of synthetic gene networks with predicted functions

Nature Biotechnology volume 27, pages 465–471 (2009)Cite this article

Abstract

Engineering artificial gene networks from modular components is a major goal of synthetic biology. However, the construction of gene networks with predictable functions remains hampered by a lack of suitable components and the fact that assembled networks often require extensive, iterative retrofitting to work as intended. Here we present an approach that couples libraries of diversified components (synthesized with randomized nonessential sequence) with in silico modeling to guide predictable gene network construction without the need for post hoc tweaking. We demonstrate our approach in Saccharomyces cerevisiae by synthesizing regulatory promoter libraries and using them to construct feed-forward loop networks with different predicted input-output characteristics. We then expand our method to produce a synthetic gene network acting as a predictable timer, modifiable by component choice. We use this network to control the timing of yeast sedimentation, illustrating how the plug-and-play nature of our design can be readily applied to biotechnology.

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Figure 1: Regulatory promoter library synthesis, screening and characterization.
Figure 2: Modeling and synthesis of feed-forward loop networks using a promoter library.
Figure 3: Predictable genetic timer networks constructed from two promoter libraries.
Figure 4: Controlling the timing of yeast sedimentation using a predictable gene network.

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Acknowledgements

We thank P.R. Jensen for advice on promoter library synthesis methods, K. Verstrepen for guidance and materials relating to yeast flocculation and H.H. Lee for valuable ideas in genetic device construction. This work was supported by the National Institutes of Health (NIH) through the NIH Director's Pioneer Award Program, grant number DP1 OD003644, the National Science Foundation Frontiers in Integrative Biological Research program and the Howard Hughes Medical Institute.

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  1. Tom Ellis and Xiao Wang: These authors contributed equally to this work.

Authors and Affiliations

  1. Howard Hughes Medical Institute and the Department of Biomedical Engineering, Center for BioDynamics and Center for Advanced Biotechnology, Boston University, Boston, Massachusetts, USA

    Tom Ellis, Xiao Wang & James J Collins

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  1. Tom Ellis
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Contributions

T.E., X.W. and J.J.C. designed the study; T.E. performed the experiments; X.W. conducted the modeling work; T.E., X.W. and J.J.C. analyzed the data and wrote the paper.

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Correspondence to James J Collins.

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Ellis, T., Wang, X. & Collins, J. Diversity-based, model-guided construction of synthetic gene networks with predicted functions. Nat Biotechnol 27, 465–471 (2009). https://doi.org/10.1038/nbt.1536

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