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。     

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.     

Bottom-up approaches in synthetic biology and biomaterials for tissue engineering applications

Synthetic biologists use engineering principles to design and construct genetic circuits for programming cells with novel functions. A bottom-up approach is commonly used to design and construct genetic circuits by piecing together functional modules that are capable of reprogramming cells with novel behavior. While genetic circuits control cell operations through the tight regulation of gene expression, a diverse array of environmental factors within the extracellular space also has a significant impact on cell behavior. This extracellular space offers an addition route for synthetic biologists to apply their engineering principles to program cell-responsive modules within the extracellular space using biomaterials. In this review, we discuss how taking a bottom-up approach to build genetic circuits using DNA modules can be applied to biomaterials for controlling cell behavior from the extracellular milieu. We suggest that, by collectively controlling intrinsic and extrinsic signals in synthetic biology and biomaterials, tissue engineering outcomes can be improved.     

合成生物学技术在材料科学中的应用

材料是人类赖以生存与发展的物质基础,科技和社会的进步都离不开材料技术的发展,未来先进材料的合成和制备必然朝着绿色可持续、低耗高产出、精细可调控、高效多功能的方向发展。以"基因调控·工程设计"为核心的合成生物学技术从分子、细胞层面极大地推动了生命科学的发展,也已经并继续为材料科学的发展注入新的思路和活力。本文将围绕合成生物学技术在材料科学中的应用,以基因回路设计为核心,概念应用为线索,重点介绍合成生物学技术在高分子生物材料和无机纳米材料领域的开发和生产,细胞展示和蛋白定向进化战略对分子材料的筛选和优化,"活体"功能材料、工程菌调节的人工光合系统功能材料体系以及基因回路在材料科学中的应用。     

Engineering gene overlaps to sustain genetic constructs in vivo

Evolution is often an obstacle to the engineering of stable biological systems due to the selection of mutations inactivating costly gene circuits. Gene overlaps induce important constraints on sequences and their evolution. We show that these constraints can be harnessed to increase the stability of costly genes by purging loss-of-function mutations. We combine computational and synthetic biology approaches to rationally design an overlapping reading frame expressing an essential gene within an existing gene to protect. Our algorithm succeeded in creating overlapping reading frames in 80% of E. coli genes. Experimentally, scoring mutations in both genes of such overlapping construct, we found that a significant fraction of mutations impacting the gene to protect have a deleterious effect on the essential gene. Such an overlap thus protects a costly gene from removal by natural selection by associating the benefit of this removal with a larger or even lethal cost. In our synthetic constructs, the overlap converts many of the possible mutants into evolutionary dead-ends, reducing the evolutionary potential of the system and thus increasing its stability over time.     

噬菌体重组酶系统在合成生物学中的应用*

合成生物学技术采用工程化设计理念,对生物体进行有目标的设计、改造乃至重新合成,对重塑非自然功能的“人造生命”具有重要意义。噬菌体重组系统具有高效、精确和广谱适用性等特点,在基因工程、代谢工程以及生物治疗等合成生物学领域得到了广泛的应用。从基因电路、体内遗传改造和体外重组等方面全面阐述了噬菌体重组系统在合成生物学研究的现状及热点,对当前该系统的局限性进行了探讨,并就未来的研究和发展趋势进行了展望。     

The Constructor: a web application optimizing cloning strategies based on modules from the registry of standard biological parts

ABSTRACT: Synthetic biology is an emerging field that combines molecular biology with engineering principles, which requires abstraction levels applied to a modular biological componentry. The Registry of Standard Biological Parts harbours such a repository of standardized parts, and thereby facilitates the combination of complex molecular modules to novel genetic circuits and devices. However, since finding the best parts for a pre-determined genetic design can be time consuming, we devised the Constructor, a web tool that recommends the smallest number of cloning steps for pre-designed circuits, and implements user-defined quality checks.We present the Constructor (www.systemsbiology.nl/the_constructor) as a constructive web tool that simplifies the in silico assembly of pre-designed gene circuitries from standard parts, reducing both planning and subsequent cloning time.     

Engineering and applications of genetic circuits

In the field of synthetic biology, recent genetic engineering efforts have enabled the construction of novel genetic circuits with diverse functionalities and unique activation mechanisms. Because of these advances, artificial genetic networks are becoming increasingly complex, and are demonstrating more robust behaviors with reduced crosstalk between defined modules. These properties have allowed for the identification of a growing set of design principles that govern genetic networks, and led to an increased number of applications for genetic circuits in the fields of metabolic engineering and biomedical engineering. Such progress indicates that synthetic biology is rapidly evolving into an integrated engineering practice that uses rational and combinatorial design of synthetic gene networks to solve complex problems in biology, medicine, and human health.     

Modular design of artificial tissue homeostasis: robust control through synthetic cellular heterogeneity

Synthetic biology efforts have largely focused on small engineered gene networks, yet understanding how to integrate multiple synthetic modules and interface them with endogenous pathways remains a challenge. Here we present the design, system integration, and analysis of several large scale synthetic gene circuits for artificial tissue homeostasis. Diabetes therapy represents a possible application for engineered homeostasis, where genetically programmed stem cells maintain a steady population of β-cells despite continuous turnover. We develop a new iterative process that incorporates modular design principles with hierarchical performance optimization targeted for environments with uncertainty and incomplete information. We employ theoretical analysis and computational simulations of multicellular reaction/diffusion models to design and understand system behavior, and find that certain features often associated with robustness (e.g., multicellular synchronization and noise attenuation) are actually detrimental for tissue homeostasis. We overcome these problems by engineering a new class of genetic modules for 'synthetic cellular heterogeneity' that function to generate beneficial population diversity. We design two such modules (an asynchronous genetic oscillator and a signaling throttle mechanism), demonstrate their capacity for enhancing robust control, and provide guidance for experimental implementation with various computational techniques. We found that designing modules for synthetic heterogeneity can be complex, and in general requires a framework for non-linear and multifactorial analysis. Consequently, we adapt a 'phenotypic sensitivity analysis' method to determine how functional module behaviors combine to achieve optimal system performance. We ultimately combine this analysis with Bayesian network inference to extract critical, causal relationships between a module's biochemical rate-constants, its high level functional behavior in isolation, and its impact on overall system performance once integrated.     

合成生物学的医学应用

合成生物学旨在基于工程学原理,通过人工合成生物调控元件、模块和基因调控网络等对细胞进行设计和改造,以实现细胞和生命体的定向演化。在医学研究中,合成生物学主要采用人工设计合成治疗性的基因回路,制备工程化细胞植入体内,纠正机体已发生缺陷的生物调控元件,以达到治疗疾病的目的。本文对合成生物学的兴起、发展及其在医学中的应用和研究进展进行了综述。     

Synthetic therapeutic gene circuits in mammalian cells

In the emerging field of synthetic biology, scientists are focusing on designing and creating functional devices, systems, and organisms with novel functions by engineering and assembling standardised biological building blocks. The progress of synthetic biology has significantly advanced the design of functional gene networks that can reprogram metabolic activities in mammalian cells and provide new therapeutic opportunities for future gene- and cell-based therapies. In this review, we describe the most recent advances in synthetic mammalian gene networks designed for biomedical applications, including how these synthetic therapeutic gene circuits can be assembled to control signalling networks and applied to treat metabolic disorders, cancer, and immune diseases. We conclude by discussing the various challenges and future prospects of using synthetic mammalian gene networks for disease therapy.     

Synthetic circuits,devices and modules

The aim of synthetic biology is to design artificial biological systems for novel applications. From an engineering perspective, construction of biological systems of defined functionality in a hierarchical way is fundamental to this emerging field. Here, we highlight some current advances on design of several basic building blocks in synthetic biology including the artificial gene control elements, synthetic circuits and their assemblies into devices and modules. Such engineered basic building blocks largely expand the synthetic toolbox and contribute to our understanding of the underlying design principles of living cells.     

Engineering and control of biological systems: A new way to tackle complex diseases

The ongoing merge between engineering and biology has contributed to the emerging field of synthetic biology. The defining features of this new discipline are abstraction and standardisation of biological parts, decoupling between parts to prevent undesired cross-talking, and the application of quantitative modelling of synthetic genetic circuits in order to guide their design. Most of the efforts in the field of synthetic biology in the last decade have been devoted to the design and development of functional gene circuits in prokaryotes and unicellular eukaryotes. Researchers have used synthetic biology not only to engineer new functions in the cell, but also to build simpler models of endogenous gene regulatory networks to gain knowledge of the "rules" governing their wiring diagram. However, the need for innovative approaches to study and modify complex signalling and regulatory networks in mammalian cells and multicellular organisms has prompted advances of synthetic biology also in these species, thus contributing to develop innovative ways to tackle human diseases. In this work, we will review the latest progress in synthetic biology and the most significant developments achieved so far, both in unicellular and multicellular organisms, with emphasis on human health.     

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.     

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.     

A Formalized Design Process for Bacterial Consortia That Perform Logic Computing

The concept of microbial consortia is of great attractiveness in synthetic biology. Despite of all its benefits, however, there are still problems remaining for large-scaled multicellular gene circuits, for example, how to reliably design and distribute the circuits in microbial consortia with limited number of well-behaved genetic modules and wiring quorum-sensing molecules. To manage such problem, here we propose a formalized design process: (i) determine the basic logic units (AND, OR and NOT gates) based on mathematical and biological considerations; (ii) establish rules to search and distribute simplest logic design; (iii) assemble assigned basic logic units in each logic operating cell; and (iv) fine-tune the circuiting interface between logic operators. We in silico analyzed gene circuits with inputs ranging from two to four, comparing our method with the pre-existing ones. Results showed that this formalized design process is more feasible concerning numbers of cells required. Furthermore, as a proof of principle, an Escherichia coli consortium that performs XOR function, a typical complex computing operation, was designed. The construction and characterization of logic operators is independent of “wiring” and provides predictive information for fine-tuning. This formalized design process provides guidance for the design of microbial consortia that perform distributed biological computation.     

Programming microbial population dynamics by engineered cell-cell communication

A major aim of synthetic biology is to program novel cellular behavior using engineered gene circuits. Early endeavors focused on building simple circuits that fulfill simple functions, such as logic gates, bistable toggle switches, and oscillators. These gene circuits have primarily focused on single-cell behaviors since they operate intracellularly. Thus, they are often susceptible to cell-cell variations due to stochastic gene expression. Cell-cell communication offers an efficient strategy to coordinate cellular behavior at the population level. To this end, we review recent advances in engineering cell-cell communication to achieve reliable population dynamics, spanning from communication within single species to multispecies, from one-way sender-receiver communication to two-way communication in synthetic microbial ecosystems. These engineered systems serve as well-defined model systems to better understand design principles of their naturally occurring counterparts and to facilitate novel biotechnology applications.