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。     

基于合成基因线路的智能药物

合成生物学自诞生以来对生物学领域的研究产生了重要的影响。利用工程学思维与方法,合成生物学揭开了生命系统许多调控机制,改造并扩展了一系列生物元件,同时带来了广泛的生物医学应用,为疾病诊断与治疗提供了新的思路。本文综述了适用于哺乳动物细胞或者细菌的合成基因线路并用于疾病诊断与治疗领域的最新进展,为未来智能药物设计提供新的思路。     

通过合成基因线路实现细胞分类

合成生物学是生物学与工程学结合的新兴学科,通过人工将生物元器件组合成线路引入细胞,使细胞获得对信息进行处理并做特定输出的新功能。近年来,针对疾病治疗的合成生物学研究发展迅猛,基因线路的工程化特性使通过它对疾病进行更精确、灵活的干预成为可能,在基因治疗中有广泛的应用前景。精确干预的前提是综合多种输入信号并识别出特定种类的细胞,如特异性识别出癌细胞的溶瘤病毒。疾病的发生往往伴随着细胞内多种调控网络的改变,从中提取出关键信号分子作为基因线路的输入至关重要。现综述哺乳动物细胞中对不同的信号输入进行感知的基因线路细胞分类器,为未来模块化整合信号输入、设计基因线路提供新的思路。     

合成功能菌群的构建及其工程化应用

自然界中存在着大量的天然微生物群落,不同种群的微生物通过通信及分工拓展了单菌的性能边界,降低了整体的代谢负担并增加了对环境的适应性。合成生物学依据工程设计原理构建或改造基本功能元件、基因线路和底盘细胞,从而对生命的运行过程进行具有目的性的重新编程,获得丰富及可控的生物学功能。将这种工程设计的原理引入菌群,获得结构明确及功能可调的合成群落,可以为合成功能菌群的理论研究到应用提供思路及方法。本文回顾了近年来合成功能菌群领域的相关工作,对合成功能菌群的设计原则、构建方法以及应用进行详细介绍,并对未来的发展进行了展望。     

合成生物系统的组合优化

合成生物学所面临的一项重要挑战是构建具有全新功能的生物系统.由于生物系统固有的复杂性,仅通过理性设计,通常难以使合成基因线路发挥出最优的功能.组合工程的兴起和发展为获得组合优化性状提供了有利条件,并大大促进了具有全新功能的生物系统的构建.文中主要从单个元件的微调、代谢通路的优化以及基因组范围内靶点的识别和组合修饰三个方面入手,总结和评述了近些年表现突出的合成生物系统的组合优化方法.     

合成生物学设计技术

合成生物学以工程化思想为指导,通过多学科交叉,设计改造生命系统,以加深对生命的认识和创造新功能,为应对人类面临的诸多挑战提供支撑。合成生物学的精髓在于借助精妙的设计实现对生物系统的构建和模拟,从而更好地了解生命现象。该文主要集中介绍合成生物学研究中的设计技术,包括生物元件设计、人工基因线路设计和代谢线路设计、人工基因组设计,归纳总结目前已有的设计技术手段和策略。     

合成生物学基因设计软件:iGEM设计综述

随着基因回路规模的扩大,和应用范围的拓展,传统的合成基因回路的设计思路面临着新的挑战。新合成基因回路构建的试验周期长,试错成本大,单纯依靠经验进行设计构建,难以迅速得到满意的结果。iGEM中软件设计比赛旨在帮助合成生物学家,更高效地完成基因回路的设计与预测。为了更好地研究iGEM软件的设计与研究方向,寻找新的设计思路和理念,综述了最近几年iGEM软件队的项目,仔细总结了每一个项目的背景、目的,设计和应用。通过对比和总结,发现这几年的iGEM软件项目从功能上可以分为以下四类:①辅助设计;②资料共享;③合作交流;④数据分析。该综述可以为今后iGEM软件设计提供思考方向,也为合成生物学的发展提供新的思路。     

CRISPR-Cas9技术在构建基因线路中的应用

随着合成生物学的发展,基因线路在临床医学、生物制剂和化学品生产等多个领域展现出巨大的应用潜力。既往在构建基因线路的过程中往往面临着一个难题——缺乏一个有效的、可编辑的、靶向性高的转录调控因子。原核规律性重复短回文序列簇(CRISPR)基因编辑/修饰系统——一种由向导RNA诱导Cas9蛋白靶向目的基因的基因编辑工具,具有高效、简单、可编辑等特性,契合了构建基因线路的需要,近来被广泛应用。现对合成基因线路的发展历程以及CRISPR系统如何改造构建基因线路作一回顾,同时讨论了CRISPR介导的基因线路的最新进展、潜能和存在的挑战。     

基于代谢网络预测菌种基因改造靶点方法的研究进展

高产特定产品的人工细胞工厂的构建需要对野生菌株进行大量的基因工程改造,近年来随着大量基因组尺度代谢网络模型的构建,人们提出了多种基于代谢网络分析预测基因改造靶点以使某一目标化合物合成最优的方法。这些方法利用基因组尺度代谢网络模型中的反应计量关系约束和反应不可逆性约束等,通过约束优化的方法预测可使产物合成最大化的改造靶点,避免了传统的通过相关途径的直观分析确定靶点的方法的局限性和主观性,为细胞工厂的理性设计提供了新的思路。以下结合作者的实际研究经验,对这些菌种优化方法的原理、优缺点及适用性等进行详细介绍,并讨论了目前存在的主要问题和未来的研究方向,为人们针对不同目标产品选择合适的方法及预测结果的可靠性评估提供了指导。     

基因组工程在医学合成生物学中的应用

合成生物学旨在建立一套完整的工程理论和方法,通过设计和组装基本生物学元件,更为有效地实现复杂生物系统的设计,并使其完成可编程的生物学功能。近年来随着可编程基因组元件的出现,特别是CRISPR和CRISPRi技术平台的建立和完善,使得合成生物学进入了一个全新发展的时期。本文重点综述CRISPR等基因组编辑和调控技术,其在构建可编程生物学元件和复杂基因线路的应用以及合成生物学在医学中(称为医学合成生物学)的发展前景。     

Automatic design of digital synthetic gene circuits

De novo computational design of synthetic gene circuits that achieve well-defined target functions is a hard task. Existing, brute-force approaches run optimization algorithms on the structure and on the kinetic parameter values of the network. However, more direct rational methods for automatic circuit design are lacking. Focusing on digital synthetic gene circuits, we developed a methodology and a corresponding tool for in silico automatic design. For a given truth table that specifies a circuit's input-output relations, our algorithm generates and ranks several possible circuit schemes without the need for any optimization. Logic behavior is reproduced by the action of regulatory factors and chemicals on the promoters and on the ribosome binding sites of biological Boolean gates. Simulations of circuits with up to four inputs show a faithful and unequivocal truth table representation, even under parametric perturbations and stochastic noise. A comparison with already implemented circuits, in addition, reveals the potential for simpler designs with the same function. Therefore, we expect the method to help both in devising new circuits and in simplifying existing solutions.     

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.     

Therapeutic synthetic gene networks

The field of synthetic biology is rapidly expanding and has over the past years evolved from the development of simple gene networks to complex treatment-oriented circuits. The reprogramming of cell fate with open-loop or closed-loop synthetic control circuits along with biologically implemented logical functions have fostered applications spanning over a wide range of disciplines, including artificial insemination, personalized medicine and the treatment of cancer and metabolic disorders. In this review we describe several applications of interactive gene networks, a synthetic biology-based approach for future gene therapy, as well as the utilization of synthetic gene circuits as blueprints for the design of stimuli-responsive biohybrid materials. The recent progress in synthetic biology, including the rewiring of biosensing devices with the body's endogenous network as well as novel therapeutic approaches originating from interdisciplinary work, generates numerous opportunities for future biomedical applications.     

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.     

Computational methods in synthetic biology: towards computer-aided part design

A number of computational tools have been developed for composing synthetic gene circuits, managing workflows, and simulating their behavior. Less attention has been directed towards the underlying parts that go into these designs. New computational approaches nonetheless are being developed for engineering these parts and relating their underlying DNA or amino-acid sequences to functional parameters. These approaches range from detailed mechanistic models to simple ones based on statistical correlations. The challenges will be to integrate the disparate tools into a common framework for the computer-aided design of synthetic gene circuits.     

Dual selection of a genetic switch by a single selection marker

Forward engineering of synthetic genetic circuits in living cells is expected to deliver various applications in biotechnology and medicine and to provide valuable insights into the design principles of natural gene networks. However, lack of biochemical data and complexity of biological environment complicate rational design of such circuits based on quantitative simulation. Previously, we have shown that directed evolution can complement our weakness in designing genetic circuits by screening or selecting functional circuits from a large pool of nonfunctional ones. Here we describe a dual selection strategy that allows selection of both ON and OFF states of genetic circuits using tetA as a single selection marker. We also describe a successful demonstration of a genetic switch selection from a 2000-fold excess background of nonfunctional switches in three rounds of iterative selection. The dual selection system is more robust than the previously reported selection system employing three genes, with no observed false positive mutants during the simulated selections.