Characterizing bacterial gene circuit dynamics with optically programmed gene expression signals

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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Figure 1: Light-switchable two-component systems (TCSs) and light tube array (LTA).
Figure 2: Experimentally characterized TCS models predict input-output dynamics.
Figure 3: Programming protein transition dynamics with a biological function generator.
Figure 4: Programming custom protein-expression signals with a biological function generator.
Figure 5: Analysis of gene circuit signal processing using the biological function generator and dual-reporter oscilloscope system.

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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.

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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.

Corresponding author

Correspondence to Jeffrey J Tabor.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–18, Supplementary Tables 1–7 and Supplementary Notes 1–12 (PDF 3922 kb)

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. (ZIP 1580 kb)

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Olson, E., Hartsough, L., Landry, B. et al. Characterizing bacterial gene circuit dynamics with optically programmed gene expression signals. Nat Methods 11, 449–455 (2014). https://doi.org/10.1038/nmeth.2884

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