Noise-aided computation within a synthetic gene network through morphable and robust logic gates

School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona 85287-9709, USA.
Physical Review E (Impact Factor: 2.29). 04/2011; 83(4 Pt 1):041909. DOI: 10.1103/PhysRevE.83.041909
Source: PubMed


An important goal for synthetic biology is to build robust and tunable genetic regulatory networks that are capable of performing assigned operations, usually in the presence of noise. In this work, a synthetic gene network derived from the bacteriophage λ underpins a reconfigurable logic gate wherein we exploit noise and nonlinearity through the application of the logical stochastic resonance paradigm. This biological logic gate can emulate or "morph" the AND and OR operations through varying internal system parameters in a noisy background. Such genetic circuits can afford intriguing possibilities in the realization of engineered genetic networks in which the actual function of the gate can be changed after the network has been built, via an external control parameter. In this article, the full system characterization is reported, with the logic gate performance studied in the presence of external and internal noise. The robustness of the gate, to noise, is studied and illustrated through numerical simulations.

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    ABSTRACT: Computation underlies the genetic regulatory network activities. Previous studies have designed and engineered systems that can perform single logic gate functionalities, trying to avoid external and internal random fluctuations. In this work, we demonstrate the possibility to exploit noise when it cannot be eliminated. In particular, we adapt the LSR paradigm to a single-gene network derived from the bacteriophage λ and to a more robust two-gene network derived from the yeast S. cerevisiae. Our results demonstrate that in both cases there is an optimal amount of noise where the biological logic gate can be externally reprogrammed (i.e. switch from the AND to the OR gate) and perform well according to the truth table.
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    ABSTRACT: Following the advent of synthetic biology, several gene networks have been engineered to emulate digital devices, with the ability to program cells for different applications. In this work, we adapt the concept of logical stochastic resonance to a synthetic gene network derived from a bacteriophage λ. The intriguing results of this study show that it is possible to build a biological logic block that can emulate or switch from the AND to the OR gate functionalities through externally tuning the system parameters. Moreover, this behavior and the robustness of the logic gate are underpinned by the presence of an optimal amount of random fluctuations. We extend our earlier work in this field, by taking into account the effects of correlated external (additive) and internal (multiplicative or state-dependent) noise. Results obtained through analytical calculations as well as numerical simulations are presented.
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