Designing Biological Circuits: From Principles to Applications.

Rational engineering of biological systems is often complicated by the complex but unwanted interactions between cellular components at multiple levels. Here we address this issue at the level of prokaryotic transcription by insulating minimal promoters and operators to prevent their interaction and enable the biophysical modeling of synthetic transcription without free parameters. This approach allows genetic circuit design with extraordinary precision and diversity, and consequently simplifies the design-build-test-learn cycle of circuit engineering to a mix-and-match workflow. As a demonstration, combinatorial promoters encoding NOT-gate functions were designed from scratch with mean errors of <1.5-fold and a success rate of >96% using our insulated transcription elements. Furthermore, four-node transcriptional networks with incoherent feed-forward loops that execute stripe-forming functions were obtained without any trial-and-error work. This insulation-based engineering strategy improves the resolution of genetic circuit technology and provides a simple approach for designing genetic circuits for systems and synthetic biology.

Two recent papers report the de novo design of a functioning biological circuit using well-characterized genetic elements.(1,2) Gardner et al. designed and constructed a genetic toggle switch while Elowitz and Leibler built an oscillating genetic circuit. Both circuits were designed with the aid of mathematical models. These papers demonstrate progress towards the unification of theory and experiment in the study of genetic circuits. Comparison of the predicted and observed behavior of the circuits, however, shows that the models explain only some of the circuits' properties. Further study of the observed behaviors not predicted by the model would lead to new insight into the properties of genetic networks. BioEssays 22:507-509, 2000.

Recent developments demonstrate that the combination of microbiology with micro- and nanoelectronics is a successful approach to develop new miniaturized sensing devices and other technologies. In the last decade, there has been a shift from the optimization of the abiotic components, for example, the chip, to the improvement of the processing capabilities of cells through genetic engineering. The synthetic biology approach will not only give rise to systems with new functionalities, but will also improve the robustness and speed of their response towards applied signals. To this end, the development of new genetic circuits has to be guided by computational design methods that enable to tune and optimize the circuit response. As the successful design of genetic circuits is highly dependent on the quality and reliability of its composing elements, intense characterization of standard biological parts will be crucial for an efficient rational design process in the development of new genetic circuits. Microengineered devices can thereby offer a new analytical approach for the study of complex biological parts and systems. By summarizing the recent techniques in creating new synthetic circuits and in integrating biology with microdevices, this review aims at emphasizing the power of combining synthetic biology with microfluidics and microelectronics.

Quorum quenching (QQ) enzymes, which degrade signaling molecules so as to disrupt the quorum sensing signaling process, have drawn much attention as alternative antimicrobial agents. However, the screening methods for evolution of such enzymes through constructing genetic circuits remain a challenge for its relatively high false positive rates caused by the higher basal expression level of the naturally acquired promoter. Thus, we presented an improved genetic circuit by introducing an artificial hybrid promoter PluxI-lacO combining PlacO originated from lactose promoter with QS regulatory promoter PluxI to control the expression of reporter gene rfp. Herein, we investigated the effect of various expression strengths of suppressive protein LacI and signaling molecule AHL on the expression of rfp. We found that the effect AHL exerted on the expression of rfp outweighed that from IPTG. The results also demonstrated that our genetic circuit could achieve the lower basal expression level of reporter gene and could respond to the expression of AiiA. The resulting circuits show the potential for screening the evolved AiiA more efficiently by virtue of inherent low basal expression level.

A recurring challenge in the design of genetic circuits is context dependence, the fact that the behavior of a functional module is influenced by the state of the wider cellular milieu with which it interacts. One key player in context dependence is the scarcity of shared cellular resources, especially those required for transcription and translation during gene expression. Because of competition for these limited resources, the behavior of modules becomes coupled in subtle ways, preventing circuits from working as expected. This paper proposes a classical feedback control approach to mitigate the steady state effects of the competition for resources necessary for gene expression. In particular, we analyze and compare the ability of several inhibitory feedback regulation architectures to reduce the interdependence between different gene expression processes due to resource limitations.

Design of genetic circuits that are robust to resource competition

Synthetic genetic circuits are examined from an electronic circuit design perspective. The design of an amplifier is used to explore interactions between genetic elements used as circuit components. A stochastic simulation is developed. This is used to analyze performance in terms of elementary notions of feedback, gain and noise. Degradation reactions, analogous to leakage off circuit capacitors, are found to have considerable impact on circuit response. For the non-linear gain element used in our exemplary circuit, the selection of bias level plays an important role in determining circuit behavior.

Biological systems are inherently stochastic, a fact which is often ignored when simulating genetic circuits. Synthetic biology aims to design genetic circuits de novo, and cannot therefore afford to ignore the effects of stochastic behavior. Since computational design tools will be essential for large-scale synthetic biology, it is important to develop an understanding of the role of stochasticity in molecular biology, and incorporate this understanding into computational tools for genetic circuit design. We report upon an investigation into the combination of evolutionary algorithms and stochastic simulation for genetic circuit design, to design regulatory systems based on the Bacillus subtilis sin operon.

Optimization-Based Eukaryotic Genetic Circuit Design (EuGeneCiD) and Modeling (EuGeneCiM) Tools: Computational Approach to Synthetic Biology

Synthetic Biology is an interdisciplinary field that utilizes well-established engineering principles, ranging from electrical, control and computer systems, for analyzing the biological systems, such as biological circuits, enzymes, pathways and controllers. Traditionally, these biological systems, i.e., the genetic circuits are analyzed using paper-and-pencil proofs and computer-based simulations techniques. However, these methods cannot provide accurate results due to their inherent limitations such as human error-proneness, round-off errors and the unverified algorithms present in the core of the tools, providing such analyses. In this paper, we propose to use higher-order-logic theorem proving as a complementary technique for analyzing these systems and thus overcome the above-mentioned issues. In particular, we propose a higher-order-logic theorem proving based framework to formally reason about the genetic circuits used in synthetic biology. The main idea is to, first, model the continuous dynamics of the genetic circuits using differential equations. The next step is to obtain the systems' transfer function from their corresponding block diagram representations. Finally, the transfer function based analysis of these differential equation based models is performed using the Laplace transform. To illustrate the practical utilization of our proposed framework, we formally analyze the genetic circuits of activated and repressed expressions of protein.

In the field of synthetic biology, genetic networks are designed by combining well-characterized genetic parts, similar to electronic circuits. Such gene networks are called synthetic genetic circuits. The design approach for synthetic genetic circuits is based on mathematical modeling and numerical simulation. The approach allows the realization of various cellular functions. However, unavoidable differences in the initial states or fluctuations of the gene expression in cells have prevented the precise prediction and control of cellular behavior. Therefore, the design of synthetic genetic circuits is not sufficient, and the dynamic control of the circuits is also required. In this report, we provide examples of synthetic circuit designs and the control of synthetic biological systems, as well as perspectives on design and control.KeywordsSynthetic biologyControl engineeringSynthetic genetic circuits

Sense and sensibility: of synthetic biology and the redesign of bioreporter circuits.

Synthetic genetic circuits are the core research objects in synthetic biology, and the programming of cell behavior is achieved through the combination of engineered gene elements. Mathematical modeling provides crucial support for understanding and designing synthetic genetic circuits, enabling researchers to predict the dynamic behavior of the circuits and guide experimental optimization. This study reviews the categories of synthetic genetic circuits (such as gene switches, oscillators, feedback circuits, etc.) and their biological mechanisms, with a focus on the application of ordinary differential equation (ODE) models, stochastic modeling, and network topology dynamics models in circuit modeling. We expounded on the estimation of model parameters, sensitivity analysis, and the integration methods of experimental data and models, and compared the characteristics of numerical simulation algorithms and commonly used software tools (such as MATLAB, COPASI, BioNetGen, etc.). Through the discussion of the steady-state, oscillation behavior, multiple steady-state and bifurcation analysis of system dynamics, the understanding of the influence of positive and negative feedback mechanisms on system stability is deepened. In addition, we took the classic synthetic gene oscillator Repressilator as a case to conduct modeling and simulation analysis, and compared the model predictions with the experimental data. Finally, the application prospects of synthetic genetic circuits in the fields of bioengineering and medicine were summarized, and the future directions of promoting the design of synthetic circuits with the help of model optimization and artificial intelligence-assisted design were prospected. Research shows that mathematical modeling and computational simulation have become key tools for the study and design of synthetic genetic circuits, providing a theoretical basis and practical guidance for the engineering transformation of complex biological systems.

E. coli is a model platform for engineering microbes, so genetic circuit design and analysis will be greatly facilitated by simple and effective approaches to introduce genetic constructs into the E. coli chromosome at well-characterised loci. We combined the Red recombinase system of bacteriophage λ and Isothermal Gibson Assembly for rapid integration of novel DNA constructs into the E. coli chromosome. We identified the flagellar region as a promising region for integration and expression of genetic circuits. We characterised integration and expression at four candidate loci, fliD, fliS, fliT, and fliY, of the E. coli flagellar region 3a. The integration efficiency and expression from the four integrations varied considerably. Integration into fliD and fliS significantly decreased motility, while integration into fliT and fliY had only a minor effect on the motility. None of the integrations had negative effects on the growth of the bacteria. Overall, we found that fliT was the most suitable integration site.

In recent years, synthetic biology develops rapidly, the purpose of which is to create beneficial products or organisms with special functions. Genetic circuits are dynamic regulating systems of organisms controlling their own life processes. According to specific rules and grammar, synthetic biologists try to design artificial genetic circuits to achieve their goals. In our research, we designed grammar rules on basis of the context-free grammar, imported a part library which we acquired from IGEM database and then we processed, and constructed a genetic circuit for expressing TetR in GenoCAD, which is a free web-based application for synthetic biology. Finally, we generated a plasmid map on the PlasMapper, and we can see the concrete information of the plasmid. We creatively designed the genetic circuit to express the TetR. The work provides a new dynamic regulating system for synthetic biology. We think the genetic circuit will help us predict the biological regulator process.