Article | Published:

Characterizing bacterial gene circuit dynamics with optically programmed gene expression signals

Nature Methods volume 11, pages 449455 (2014) | Download Citation

Abstract

Gene circuits are dynamical systems that regulate cellular behaviors, often using protein signals as inputs and outputs. Here we have developed an optogenetic 'function generator' method for programming tailor-made gene expression signals in live bacterial cells. We designed precomputed light sequences based on experimentally calibrated mathematical models of light-switchable two-component systems and used them to drive intracellular protein levels to match user-defined reference time courses. We used this approach to generate accelerated and linearized dynamics, sinusoidal oscillations with desired amplitudes and periods, and a complex waveform, all with unprecedented accuracy and precision. We also combined the function generator with a dual fluorescent protein reporter system, analogous to a dual-channel oscilloscope, to reveal that a synthetic repressible promoter linearly transforms repressor signals with an approximate 7-min delay. Our approach will enable a new generation of dynamical analyses of synthetic and natural gene circuits, providing an essential step toward the predictive design and rigorous understanding of biological systems.

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Acknowledgements

This research was supported by the US National Science Foundation Biotechnology, Biochemical, and Biomass Engineering (BBBE) program (EFRI–1137266) and the Office of Naval Research MURI programs (N000141310074). L.A.H. was supported by the US National Aeronautics and Space Administration Office of the Chief Technologist's Space Technology Research Fellowship (NSTRF) (NNX11AN39H). We thank S. Schmidl (Rice University) for his contribution of the pPCBSE plasmid.

Author information

Affiliations

  1. Graduate Program in Applied Physics, Rice University, Houston, Texas, USA.

    • Evan J Olson
  2. Department of Bioengineering, Rice University, Houston, Texas, USA.

    • Lucas A Hartsough
    • , Brian P Landry
    • , Raghav Shroff
    •  & Jeffrey J Tabor
  3. Department of Biochemistry and Cell Biology, Rice University, Houston, Texas, USA.

    • Jeffrey J Tabor

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Contributions

J.J.T. and E.J.O. conceived of the project, and J.J.T. supervised the project. E.J.O., L.A.H., B.P.L. and R.S. designed and performed experiments. E.J.O. and B.P.L. designed and constructed plasmids. E.J.O. designed and constructed the LTA, analyzed data, constructed the model and developed the light program sequence optimization algorithm. J.J.T. and E.J.O. wrote the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Jeffrey J Tabor.

Supplementary information

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    Supplementary Text and Figures

    Supplementary Figures 1–18, Supplementary Tables 1–7 and Supplementary Notes 1–12

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    Supplementary Software

    Python scripts to perform flow cytometry file extraction and analysis, produce model simulations of gene expression output, fit models to gene expression data and compute light inputs that drive gene expression output to follow a reference signal.

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DOI

https://doi.org/10.1038/nmeth.2884

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