Analog and Digital Approaches for Engineering Large-Scale Gene Networks

To date, the dominant computational paradigm in synthetic biology has been mainly digital. However, the digital paradigm has failed to scale up synthetic logic functions beyond a few gates or to the level needed for complex computations in living cells.

Given that cellular signals are often graded and stochastic in their nature, it is not surprising that the digital paradigm is limited in the complexity of computations that can be achieved in living cells. Furthermore, there is often a trade-off between the complexity of synthetic devices and cellular resource limitation which prevents digital circuits from functioning properly in large-scale-networks.

While hybrid analog-digital design is widely used in nature, it was never implemented in biological engineering. In this study, we offer a novel synthetic framework that combines analog and digital design together to engineer large-scale gene networks. Our design takes advantages of the complex operations already naturally present in cells, termed analog computation, executing sophisticated computational functions in concert with decision-making digital circuits.

We have shown that P_BAD promoter is a universal logic gate. It can act as a high-pass filter (implementing AND logic gate), band-pass filter (implementing XOR logic gate) or a low-pass filter (implementing NOR logic gate) and is determined by a combination of our wide input dynamic range circuit based-graded positive feedback and decision making behavior of Arabionse ,yielding analog-to-digital convertors.