合成基因线路规模化设计面临的挑战

随着合成基因线路规模的增加,传统的合成基因线路设计思路的瓶颈逐渐凸显,许多之前被忽略的因素对大规模基因线路的性能可能造成显著影响,这对合成基因线路的设计带来了新的挑战。本文重点梳理了基因表达噪声和竞争效应两方面对基因线路性能的影响,阐释了二者间的紧密联系,并基于理性设计的思路,从模拟-数字运算设计、网络拓扑设计、基因线路中的信息传递理论和动态信号等方面,归纳总结了解决这些问题的潜在方案,并展望了规模化合成基因线路理性设计的未来发展方向。     

Perspectives on the automatic design of regulatory systems for synthetic biology

Automatic design is based on computational modeling and optimization methods to provide prototype designs to targeted problems in an unsupervised manner. For biological circuits, we need to produce quantitative predictions of cell behavior for a given genotype as consequence of the different molecular interactions. Automatic design techniques aim at solving the inverse problem of finding the sequences of nucleotides that better fit a targeted behavior. In the post-genomic era, our molecular knowledge and modeling capabilities have allowed to start using such methodologies with success. Herein, we describe how the emergence of this new type of tools could enable novel synthetic biology applications. We highlight the essential elements to develop automatic design procedures for synthetic biology pointing out their advantages and bottlenecks. We discuss in detail the experimental difficulties to overcome in the in vivo implementation of designed networks. The use of automatic design to engineer biological networks is starting to emerge as a new technique to perform synthetic biology, which should not be neglected in the future.     

Circuit-Host Coupling Induces Multifaceted Behavioral Modulations of a Gene Switch

Quantitative modeling of gene circuits is fundamentally important to synthetic biology, as it offers the potential to transform circuit engineering from trial-and-error construction to rational design and, hence, facilitates the advance of the field. Currently, typical models regard gene circuits as isolated entities and focus only on the biochemical processes within the circuits. However, such a standard paradigm is getting challenged by increasing experimental evidence suggesting that circuits and their host are intimately connected, and their interactions can potentially impact circuit behaviors. Here we systematically examined the roles of circuit-host coupling in shaping circuit dynamics by using a self-activating gene switch as a model circuit. Through a combination of deterministic modeling, stochastic simulation, and Fokker-Planck equation formalism, we found that circuit-host coupling alters switch behaviors across multiple scales. At the single-cell level, it slows the switch dynamics in the high protein production regime and enlarges the difference between stable steady-state values. At the population level, it favors cells with low protein production through differential growth amplification. Together, the two-level coupling effects induce both quantitative and qualitative modulations of the switch, with the primary component of the effects determined by the circuit’s architectural parameters. This study illustrates the complexity and importance of circuit-host coupling in modulating circuit behaviors, demonstrating the need for a new paradigm—integrated modeling of the circuit-host system—for quantitative understanding of engineered gene networks.     

Computational design of synthetic regulatory networks from a genetic library to characterize the designability of dynamical behaviors

The engineering of synthetic gene networks has mostly relied on the assembly of few characterized regulatory elements using rational design principles. It is of outmost importance to analyze the scalability and limits of such a design workflow. To analyze the design capabilities of libraries of regulatory elements, we have developed the first automated design approach that combines such elements to search the genotype space associated to a given phenotypic behavior. Herein, we calculated the designability of dynamical functions obtained from circuits assembled with a given genetic library. By designing circuits working as amplitude filters, pulse counters and oscillators, we could infer new mechanisms for such behaviors. We also highlighted the hierarchical design and the optimization of the interface between devices. We dissected the functional diversity of a constrained library and we found that even such libraries can provide a rich variety of behaviors. We also found that intrinsic noise slightly reduces the designability of digital circuits, but it increases the designability of oscillators. Finally, we analyzed the robust design as a strategy to counteract the evolvability and noise in gene expression of the engineered circuits within a cellular background, obtaining mechanisms for robustness through non-linear negative feedback loops.     

A revolutionary tool: CRISPR technology plays an important role in construction of intelligentized gene circuits

With the development of synthetic biology, synthetic gene circuits have shown great applied potential in medicine, biology, and as commodity chemicals. An ultimate challenge in the construction of gene circuits is the lack of effective, programmable, secure and sequence‐specific gene editing tools. The clustered regularly interspaced short palindromic repeat (CRISPR) system, a CRISPR‐associated RNA‐guided endonuclease Cas9 (CRISPR‐associated protein 9)‐targeted genome editing tool, has recently been applied in engineering gene circuits for its unique properties‐operability, high efficiency and programmability. The traditional single‐targeted therapy cannot effectively distinguish tumour cells from normal cells, and gene therapy for single targets has poor anti‐tumour effects, which severely limits the application of gene therapy. Currently, the design of gene circuits using tumour‐specific targets based on CRISPR/Cas systems provides a new way for precision cancer therapy. Hence, the application of intelligentized gene circuits based on CRISPR technology effectively guarantees the safety, efficiency and specificity of cancer therapy. Here, we assessed the use of synthetic gene circuits and if the CRISPR system could be used, especially artificial switch‐inducible Cas9, to more effectively target and treat tumour cells. Moreover, we also discussed recent advances, prospectives and underlying challenges in CRISPR‐based gene circuit development.     

Designing and engineering evolutionary robust genetic circuits

Background  

One problem with engineered genetic circuits in synthetic microbes is their stability over evolutionary time in the absence of selective pressure. Since design of a selective environment for maintaining function of a circuit will be unique to every circuit, general design principles are needed for engineering evolutionary robust circuits that permit the long-term study or applied use of synthetic circuits.     

A modular positive feedback-based gene amplifier

Background  

Positive feedback is a common mechanism used in the regulation of many gene circuits as it can amplify the response to inducers and also generate binary outputs and hysteresis. In the context of electrical circuit design, positive feedback is often considered in the design of amplifiers. Similar approaches, therefore, may be used for the design of amplifiers in synthetic gene circuits with applications, for example, in cell-based sensors.     

Synthetic genetic circuits for programmable biological functionalities

Living organisms evolve complex genetic networks to interact with the environment. Due to the rapid development of synthetic biology, various modularized genetic parts and units have been identified from these networks. They have been employed to construct synthetic genetic circuits, including toggle switches, oscillators, feedback loops and Boolean logic gates. Building on these circuits, complex genetic machines with capabilities in programmable decision-making could be created. Consequently, these accomplishments have led to novel applications, such as dynamic and autonomous modulation of metabolic networks, directed evolution of biological units, remote and targeted diagnostics and therapies, as well as biological containment methods to prevent release of engineered microorganisms and genetic materials. Herein, we outline the principles in genetic circuit design that have initiated a new chapter in transforming concepts to realistic applications. The features of modularized building blocks and circuit architecture that facilitate realization of circuits for a variety of novel applications are discussed. Furthermore, recent advances and challenges in employing genetic circuits to impart microorganisms with distinct and programmable functionalities are highlighted. We envision that this review gives new insights into the design of synthetic genetic circuits and offers a guideline for the implementation of different circuits in various aspects of biotechnology and bioengineering.     

Rewiring host activities for synthetic circuit production: a translation view

The expression of synthetic circuits in host organisms, or chassis, is a key aspect of synthetic biology. Design adjustments made for maximal production may negatively affect the central metabolism and biosynthetic activities of the chassis host. Here, we review recent attempts to modulate synthetic circuit design for optimal production and present models that precisely capture the trade-off between circuit production and chassis growth. We also present emerging concepts for full orthogonalization of synthetic productivity and its decoupling from the endogenous biosynthetic activities of the cell, opening new routes towards robust synthetic circuit expression.     

哺乳动物合成生物学在生物医学领域的研究进展

虽然合成生物学还处于早期研究阶段,但最近十年,该领域取得了非常显著的研究进展。合成生物学是以工程学思想为基础,通过人工设计、改造基因线路,从而赋予细胞或生物体新的功能,现已广泛应用于各个领域。随着人们对基因线路设计的深入研究,使得合成生物学研究走向临床应用成为可能。本文将围绕哺乳动物合成生物学在疾病治疗方面的研究进展,介绍基因线路的设计思路和方法、不同诱导因子调控的开环式基因线路以及用于疾病诊疗的闭环式基因环路在生物医学领域的应用。最后对合成生物学走向临床治疗的应用前景和挑战进行展望。     

Regulatory dynamics of network architecture and function in tristable genetic circuit of Leishmania: a mathematical biology approach

The emerging field of synthetic biology has led to the design of tailor-made synthetic circuits for several therapeutic applications. Biological networks can be reprogramed by designing synthetic circuits that modulate the expression of target proteins. IPCS (inositol phosphorylceramide synthase) has been an attractive target in the sphingolipid metabolism of the parasite Leishmania. In this study, we have constructed a tristable circuit for the IPCS protein. The circuit has been validated and its long-term behavior has been assessed. The robustness and evolvability of the circuit has been estimated using evolutionary algorithms. The tristable synthetic circuit has been specifically designed to improve the rate of production of phosphatidylcholine: ceramide cholinephosphotransferase 4 (SLS4 protein). Site-specific delivery of the circuit into the parasite-infected macrophages could serve as a possible therapeutic intervention of the infectious disease ‘Leishmaniasis’.     

Promoters Architecture-Based Mechanism for Noise-Induced Oscillations in a Single-Gene Circuit

It is well known that single-gene circuits with negative feedback loop can lead to oscillatory gene expression when they operate with time delay. In order to generate these oscillations many processes can contribute to properly timing such delay. Here we show that the time delay coming from the transitions between internal states of the cis-regulatory system (CRS) can drive sustained oscillations in an auto-repressive single-gene circuit operating in a small volume like a cell. We found that the cooperative binding of repressor molecules is not mandatory for a oscillatory behavior if there are enough binding sites in the CRS. These oscillations depend on an adequate balance between the CRS kinetic, and the synthesis/degradation rates of repressor molecules. This finding suggest that the multi-site CRS architecture can play a key role for oscillatory behavior of gene expression. Finally, our results can also help to synthetic biologists on the design of the promoters architecture for new genetic oscillatory circuits.     

From Boolean Network Model to Continuous Model Helps in Design of Functional Circuits

Computational circuit design with desired functions in a living cell is a challenging task in synthetic biology. To achieve this task, numerous methods that either focus on small scale networks or use evolutionary algorithms have been developed. Here, we propose a two-step approach to facilitate the design of functional circuits. In the first step, the search space of possible topologies for target functions is reduced by reverse engineering using a Boolean network model. In the second step, continuous simulation is applied to evaluate the performance of these topologies. We demonstrate the usefulness of this method by designing an example biological function: the SOS response of E. coli. Our numerical results show that the desired function can be faithfully reproduced by candidate networks with different parameters and initial conditions. Possible circuits are ranked according to their robustness against perturbations in parameter and gene expressions. The biological network is among the candidate networks, yet novel designs can be generated. Our method provides a scalable way to design robust circuits that can achieve complex functions, and makes it possible to uncover design principles of biological networks.     

Toward predictive engineering of gene circuits

Many synthetic biology applications rely on programming living cells using gene circuits – the assembly and wiring of genetic elements to control cellular behaviors. Extensive progress has been made in constructing gene circuits with diverse functions and applications. For many circuit functions, however, it remains challenging to ensure that the circuits operate in a predictable manner. Although the notion of predictability may appear intuitive, close inspection suggests that it is not always clear what constitutes predictability. We dissect this concept and how it can be confounded by the complexity of a circuit, the complexity of the context, and the interplay between the two. We discuss circuit engineering strategies, in both computation and experiment, that have been used to improve the predictability of gene circuits.