Synthesizing a novel genetic sequential logic circuit: a push-on push-off switch (original) (raw)
Design of Asynchronous Genetic Circuits
Proceedings of the IEEE, 2019
Most digital electronic circuits utilize a timing reference to synchronize the progression of signals and enable sequential memory elements. These designs may not be realizable in biological substrates due to the lack of a reliable high frequency clock signal. Asynchronous designs eliminate the need for a clock with data encodings and request/acknowledge handshake protocols. This paper proposes a workflow to automate the design of asynchronous genetic circuits. This workflow extends genetic design tools by leveraging asynchronous logic design methods customized for this technology. This workflow is demonstrated on a genetic sensor that uses filtering and cellular communication to improve its reliability.
Genetic regulatory circuits: Advances toward a genetic circuit engineering
Genetic circuits can now be engineered that perform moderately complicated switching functions or exhibit predictable dynamical behavior. These "forward engineering" techniques may have to be combined with directed evolution techniques to produce robustness comparable with naturally occurring circuits or to meet perfo rmance specifications.
Engineering Gene Circuits: Foundations and Applications
Nanotechnology in Biology and Medicine, 2007
Synthetic biology has emerged as a useful approach to decoding fundamental laws underlying biological control. Recent efforts have produced many exciting systems and generated substantial insights. These progresses highlight the potential of synthetic biology to impact diverse areas including biology, computation, engineering, and medicine. 20.1 Introduction Biological systems often function reliably in diverse environments despite internal or external perturbations. This behavior is often characterized as ''robustness.'' Based on extensive studies over the last several decades, much of this robustness can be attributed to the control of gene expression through complex cellular networks [1-4]. These networks are known to consist of various regulatory modules, including feedback [5] and feed-forward [6] regulation and cell-cell communication [7]. With these basic regulatory modules and motifs, researchers are now constructing artificial networks that mimic nature to gain fundamental biological insight and understanding [8]. In addition, other artificial networks that are engineered with novel functions will serve as building blocks for future practical applications. These efforts form the foundation of the recent emergence of synthetic biology [3,9,10]. These artificial networks are interchangeably called ''synthetic gene circuits'' or ''engineered gene circuits.'' Recent accomplishments in synthetic biology include engineered switches [11-14], oscillators [15,16], logic gates [17-19], metabolic control [20], reengineered translational machinery [21], population control [22] and pattern formation [23] using natural or synthetic [24] cell-cell communication, reengineered viral genome [25], and hierarchically complex circuits built upon smaller, well-characterized
Design principles of transcriptional logic circuits
Using a set of genetic logic gates (AND, OR and XOR), we constructed a binary full-adder. The optimality analysis of the full-adder showed that, based on the position of the regulation threshold, the system displays different optimal configurations for speed and accuracy under fixed metabolic cost. In addition, the analysis identified an optimal trade-off curve bounded by these two optimal configurations. Any configuration outside this optimal trade-off curve is sub-optimal in both speed and accuracy. This type of analysis represents a useful tool for synthetic biologists to engineer faster, more accurate and cheaper genes.
Building blocks of a biochemical CPU based on DNA transcription logic
2004
In this paper we study the design of transcriptional logic based on quantitative models of cis-regulatory networks. Recent efforts in the area of synthetic biology have shown that logic gates can be implemented using the DNA transcriptional machinery of the cell. We show how to extend these previous results to the design of combinational and sequential circuits. The extension of our method to the design of sequential circuits is particularly attractive because they represent the most general class of circuits. As representative examples here we demonstrate the construction of a memory element and of a 1-bit ALU, two basic building blocks of a transcription-based biochemical CPU.
2011
Building biological devices to perform computational and signal processing tasks is one of the main research issues in synthetic biology. Herein, two modular biological systems that could mimic multiplexing and demultiplexing logic functions are proposed and discussed. These devices, called multiplexer (mux) and demultiplexer (demux), respectively, have a remarkable importance in electronic, telecommunication, and signal processing systems and, similarly, they could play a crucial role if implemented in a living organism, such as Escherichia coli. BioBrick standard parts were used to design mux and demux and to construct two genetic circuits that could carry out the desired tasks. A modular approach, mimicking basic logic gates (AND, OR, and NOT) with protein/autoinducer or protein/DNA interactions and interconnecting them to create the final circuits, was adopted. A mathematical model of the designed gene networks was defined and simulations performed to validate the expected behavior of the systems. In addition, circuit subparts were tested in vivo and the results used to determine some of the parameters of the mathematical model. According to both the experimental and simulated results, guidelines for future finalization of mux and demux are provided.
Genetic circuit building blocks for cellular computation, communications, and signal processing
2003
In this paper, we review an emerging engineering discipline to program cell behaviors by embedding synthetic gene networks that perform computation, communications, and signal processing. To accomplish this goal, we begin with a genetic component library and a biocircuit design methodology for assembling these components into compound circuits. The main challenge in biocircuit design lies in selecting well-matched genetic components that when coupled, reliably produce the desired behavior. We use simulation tools to guide circuit design, a process that consists of selecting the appropriate components and genetically modifying existing components until the desired behavior is achieved. In addition to such rational design, we also employ directed evolution to optimize genetic circuit behavior. Building on Nature's fundamental principle of evolution, this unique process directs cells to mutate their own DNA until they find gene network configurations that exhibit the desired system characteristics. The integration of all the above capabilities in future synthetic gene networks will enable cells to perform sophisticated digital and analog computation, both as individual entities and as part of larger cell communities. This engineering discipline and its associated tools will advance the capabilities of genetic engineering, and allow us to harness cells for a myriad of applications not previously achievable.
Electronic Design of Synthetic Genetic Networks
International Journal of Bifurcation and Chaos, 2007
We propose the use of nonlinear electronic circuits to study synthetic gene regulation networks. Specifically, we have designed two electronic versions of a synthetic genetic clock, known as the "repressilator," making use of appropriate electronic elements linked in the same way as the original biochemical system. We study the effects of coupling in a population of electronic repressilators, with the aim of observing coherent oscillations of the whole population. With these results, we show that this kind of nonlinear circuits can be helpful in the design and understanding of synthetic genetic networks.
Computational design of digital and memory biological devices
2007
The use of combinatorial optimization techniques with computational design allows the development of automated methods to design biological systems. Automatic design integrates design principles in an unsupervised algorithm to sample a larger region of the biological network space, at the topology and parameter levels. The design of novel synthetic transcriptional networks with targeted behaviors will be key to understand the design principles underlying biological networks. In this work, we evolve transcriptional networks towards a targeted dynamics, by using a library of promoters and coding sequences, to design a complex biological memory device. The designed sequential transcription network implements a JK-Latch, which is fully predictable and richer than other memory devices. Furthermore, we present designs of transcriptional devices behaving as logic gates, and we show how to create digital behavior from analog promoters. Our procedure allows us to propose a scenario for the evolution of multifunctional genetic networks. In addition, we discuss the decomposability of regulatory networks in terms of genetic modules to develop a given cellular function. Summary. We show how to use an automated procedure to design logic and sequential transcription circuits. This methodology will allow advancing the rational design of biological devices to more complex systems, and we propose the first design of a biological JK-latch memory device.