A fast, robust, and tunable synthetic gene oscillator

By J. Stricker, Scott Cookson, Matthew R. Bennett, William H. Mather, Lev S. Tsimring, Jeff Hasty. Nature, 2008

1,169 citations recorded by the source corpus.

One defining goal of synthetic biology is the development of engineering-based approaches that enable the construction of gene-regulatory networks according to ‘design specifications’ generated from computational modelling. This approach provides a systematic framework for exploring how a given regulatory network generates a particular phenotypic behaviour. Several fundamental gene circuits have been developed using this approach, including toggle switches and oscillators, and these have been applied in new contexts such as triggered biofilm development and cellular population control. Here we describe an engineered genetic oscillator in Escherichia coli that is fast, robust and persistent, with tunable oscillatory periods as fast as 13 min. The oscillator was designed using a previously modelled network architecture comprising linked positive and negative feedback loops. Using a microfluidic platform tailored for single-cell microscopy, we precisely control environmental conditions and monitor oscillations in individual cells through multiple cycles. Experiments reveal remarkable robustness and persistence of oscillations in the designed circuit; almost every cell exhibited large-amplitude fluorescence oscillations throughout observation runs. The oscillatory period can be tuned by altering inducer levels, temperature and the media source. Computational modelling demonstrates that the key design principle for constructing a robust oscillator is a time delay in the negative feedback loop, which can mechanistically arise from the cascade of cellular processes involved in forming a functional transcription factor. The positive feedback loop increases the robustness of the oscillations and allows for greater tunability. Examination of our refined model suggested the existence of a simplified oscillator design without positive feedback, and we construct an oscillator strain confirming this computational prediction.

Subfields: Biophysics, Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/f802c6d9d2d45ef261fd91517a484317686a3557

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Citations in the corpus

Biomolecular computing systems: principles, progress and potential (2012, background): “Biomolecular realizations of such circuits 26,27,131–133 may or may not behave as expected, depending on reaction parameters.”
Enzyme-free nucleic acid dynamical systems (2017, background): “…recently, the information-based chemistry underlying the central dogma of molecular biology has been used to create a variety of dynamical systems, such as bistable switches and oscillators in living cells ( 4–7 ) and in simpliﬁed cell-free systems ( 8–14 ) that involve a limited number of enzymes.”
Genetic circuit design automation (2016, positive): “This approach has led to digitallogic gates( 19 – 24 ),memorydevices( 25 – 29 ),analogcom-putation( 30 ),anddynamiccircuits(e.g.,timersand oscillators) ( 15 , 16 , 31 – 33 ).”
Nonequilibrium physics in biology (2019, background): “This difficulty was addressed by (Stricker et al., 2008) by creating a persistent genetic oscillator (Fig.”
Modeling the cell cycle: why do certain circuits oscillate? (2011, positive): “Delay differential equation models have been used to rationalize the robust oscillations seen in some synthetic biochemical oscillators based on negative feedback loops (Stricker et al., 2008) and have been proposed to model the embryonic cell cycle in Xenopus as well (Busenberg and Tang, 1994).”
A Synthetic Genetic Edge Detection Program (2009, background): “…2007; Guet et al., 2002; Rackham and Chin, 2005), memory (Ajo-Franklin et al., 2007; Gardner et al., 2000; Ham et al., 2006), pulse generators (Basu et al., 2004), and oscil- lators (Atkinson et al., 2003; Elowitz and Leibler, 2000; Fung et al., 2005; Stricker et al., 2008; Tigges et al., 2009).”