High-resolution mapping of bifurcations in nonlinear biochemical circuits

Abstract : Analog molecular circuits can exploit the nonlinear nature of biochemical reaction networks to compute low-precision outputs with fewer resources than digital circuits. This analog computation is similar to that employed by gene-regulation networks. Although digital systems have a tractable link between structure and function, the nonlinear and continuous nature of analog circuits yields an intricate functional landscape, which makes their design counter-intuitive, their characterization laborious and their analysis delicate. Here, using droplet-based microfluidics, we map with high resolution and dimensionality the bifurcation diagrams of two synthetic, out-of-equilibrium and nonlinear programs: a bistable DNA switch and a predator-prey DNA oscillator. The diagrams delineate where function is optimal, dynamics bifurcates and models fail. Inverse problem solving on these large-scale data sets indicates interference from enzymatic coupling. Additionally, data mining exposes the presence of rare, stochastically bursting oscillators near deterministic bifurcations.
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Anthony Genot, A. Baccouche, R. Sieskind, N. Aubert-Kato, N. Bredeche, et al.. High-resolution mapping of bifurcations in nonlinear biochemical circuits. Nature Chemistry, Nature Publishing Group, 2016, 8 (8), pp.760-767. ⟨10.1038/nchem.2544⟩. ⟨inserm-02299554⟩

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