代谢物生物传感器:微生物细胞工厂构建中的合成生物学工具

代谢物生物传感器作为重要的合成生物学工具,能够感应细胞内代谢物浓度的变化,转化为特定信号输出,在微生物细胞工厂的构建中显现出巨大的应用潜力。其主要组成部分通常包括生物识别元件和信号输出元件,前者来源于自然界中丰富的调控元件,如转录因子、核糖开关等,有着不同的响应机理,后者可以为荧光信号、生长优势、特定代谢通路的开闭等,取决于应用所需。着重介绍了近年来代谢物生物传感器在微生物细胞工厂构建中的应用实例,主要包括目标化合物菌株的高通量筛选、选择、胞内代谢动态调控和非遗传异质性选择,同时也着重讨论了代谢物生物传感器的性能对于应用的影响和在实际应用中可能面临的机遇与挑战。     

基因编码型生物传感器在微生物细胞工厂中的应用进展

合成生物学的迅猛发展推动了微生物细胞工厂中多种复杂化学品的生物合成,但仍存在产量低、生产效率不高等诸多问题。基因编码型生物传感器可以感知细胞内外代谢物浓度及外界环境的波动,产生可测量的信号输出或调控通路中的基因表达水平,具有成本低、操作简单、可再生等优点。目前,基因编码型生物传感器已经成为合成生物学和代谢工程的重要组成部分,是微生物细胞工厂中代谢动态调控及理想表型进化/筛选的强大工具。概述了基因编码型生物传感器的组成及工作原理,重点介绍了基因编码型生物传感器在微生物代谢动态调控及高通量筛选中的最新研究进展,就基因编码型生物传感器设计与构建过程中面临的挑战进行探讨,并展望了其今后的发展方向。     

微生物细胞工厂的代谢调控

代谢调控是构建微生物细胞工厂的重要技术手段.随着合成生物学技术的不断突破,挖掘和人工设计的高质量调控元件大幅度提升了对细胞代谢网络的改造能力;代谢调控研究也已从单基因的静态调控发展到系统水平上的智能精确动态调控.文中简要综述了近30年来代谢途径表达调控技术在代谢工程领域的研究进展.     

细菌信号传导调控元件的合成生物学研究进展

合成生物学的一个重要目标是设计、改造微生物(主要指细菌),使其能够自主执行复杂任务,如合成重要生物基产品(药物、生物燃料等)、疾病治疗以及环境修复等,造福人类社会.要完成这些任务,细菌必须依赖其信号传导系统,根据环境变化作出正确及时的应答.在长期进化过程中,细菌产生了众多不同的信号传导系统,给我们提供了大量宝贵的信号传导调控元件.通过对这些调控元件的合成生物学设计、改造,我们可以给细菌装备全新的信号传导系统,从而使其能够在工业生物技术及生物医学等应用中执行设定任务.     

形态工程在生物基化学品生产中的应用进展

合成生物学和代谢工程是构建微生物细胞工厂、实现化学品绿色生物制造的重要方法,目前主要集中在微生物代谢网络的改造及调控上,很少考虑到微生物细胞特性的影响.形态工程通过改造微生物细胞形态相关蛋白,有目的地对微生物细胞形态及分裂方式进行合理调控,从而优化微生物细胞的特性,是降低生物炼制成本的一种新兴生物工程技术.文中首先介绍...     

光遗传学技术在调控细菌生命活动中的应用

光遗传学技术利用光作为输入信号,能够精准地调控细胞的生理功能,同时具有高度的时间和空间特异性,使得构建高度动态的调控系统成为可能.近年来,随着新型光敏蛋白的发现和光照系统的创新,基于光遗传学技术的光控系统的效率得到了显著提高.通过合成生物学方法构造各种生物回路,光控系统在细菌中的应用也日益广泛.将光控系统作为输入模块,与其他生物功能模块相结合,能够实现对基因表达、蛋白质活性以及细菌生理功能的调控.本文主要介绍光遗传学技术的基本原理及其在合成生物学和调控细菌生命活动方面的应用.     

氨基酸生物传感器的开发及应用研究进展

氨基酸是蛋白质的基本组成单元,对人和动物的营养健康十分重要,广泛应用于饲料、食品、医药和日化等领域。目前,氨基酸主要通过微生物发酵可再生原料生产,氨基酸产业是我国生物制造的重要支柱产业之一。氨基酸菌株主要通过随机诱变和代谢工程改造结合筛选获得。菌株生产水平进一步提高的核心限制之一是缺乏高效、快速和准确的筛选方法,因此,发展氨基酸菌株的高通量筛选方法对关键功能元件挖掘及高产菌株的创制筛选至关重要。本文综述了氨基酸生物传感器的设计,及其在功能元件、高产菌株的高通量进化筛选和代谢途径动态调控中的应用研究进展,讨论了现有氨基酸生物传感器存在的问题和性能提升改造策略,并展望了开发氨基酸衍生物生物传感器的重要性。     

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。     

光遗传学在细菌生产调控中的应用进展

合成生物学的发展使得人们可以根据需求对微生物进行改造,作为“工厂”高效地合成催化所需物质,并通过添加化学诱导物的方式对生命过程进行调控。然而,化学诱导的潜在毒性以及不可逆性等限制其应用。光遗传学技术利用特定波长的光信号实现对细胞生命过程的调控,具有特异性、可逆性、高时空分辨率等特点。近年来,人们对不同来源的光敏蛋白进行改造,开发出各种不同波长、不同效应的光遗传元件用于基因回路的构建,进而实现对细菌蛋白合成、代谢过程的调控。光遗传技术在人与细菌之间搭起了实时的信号沟通桥梁,实现更为精准的物质生产调控:(1)通过光控治疗因子的合成分泌进行药物递送;(2)通过代谢通路的控制提高目的产物的催化效率;(3)通过光诱导控制生物活材料的形成。随着探索的深入,更小体积、更多波长、更高效率的光遗传元件将被开发出来,实现多输入的细菌生命活动调控。     

新型基因表达调控元件——人工核糖开关的构建及筛选

核糖开关作为一种新发现的RNA元件,可以高效、准确、快速地执行基因调控任务,且免疫原性低,有可能在将来以顺式模块的方式应用于未来的基因治疗。近年来已经成功构建了多种人造核糖开关,构建方法主要是利用人工适体元件与基因表达调控元件组装,或者是在天然核糖开关基础上进行改造。文中全面综述了涉及人工核糖开关设计及筛选的技术,讨论了可以用于哺乳细胞、响应非天然配体信号、调控特征为热力学和动力学控制的核糖开关的设计新策略,并对核糖开关的筛选构建策略及其在基因治疗及新型药物开发领域的应用前景进行了展望。尽管目前将核糖开关设计成为功能强大的新型基因调控系统还面临很大的困难,但通过构效关系的研究、计算机辅助设计、体外筛选及细胞内筛选技术、高通量优化筛选等技术的综合应用,核糖开关一定可以成为有力的基因调控工具,如能成功应用则可大大促进基因治疗临床化的进程。     

Dynamic control in metabolic engineering: Theories,tools, and applications

Metabolic engineering has allowed the production of a diverse number of valuable chemicals using microbial organisms. Many biological challenges for improving bio-production exist which limit performance and slow the commercialization of metabolically engineered systems. Dynamic metabolic engineering is a rapidly developing field that seeks to address these challenges through the design of genetically encoded metabolic control systems which allow cells to autonomously adjust their flux in response to their external and internal metabolic state. This review first discusses theoretical works which provide mechanistic insights and design choices for dynamic control systems including two-stage, continuous, and population behavior control strategies. Next, we summarize molecular mechanisms for various sensors and actuators which enable dynamic metabolic control in microbial systems. Finally, important applications of dynamic control to the production of several metabolite products are highlighted, including fatty acids, aromatics, and terpene compounds. Altogether, this review provides a comprehensive overview of the progress, advances, and prospects in the design of dynamic control systems for improved titer, rate, and yield metrics in metabolic engineering.     

Optimization of industrial microorganisms: recent advances in synthetic dynamic regulators

Production of biochemicals by industrial fermentation using microorganisms requires maintaining cellular production capacity, because maximal productivity is economically important. High-productivity microbial strains can be developed using static engineering, but these may not maintain maximal productivity throughout the culture period as culture conditions and cell states change dynamically. Additionally, economic reasons limit heterologous protein expression using inducible promoters to prevent metabolic burden for commodity chemical and biofuel production. Recently, synthetic and systems biology has been used to design genetic circuits, precisely controlling gene expression or influencing genetic behavior toward a desired phenotype. Development of dynamic regulators can maintain cellular phenotype in a maximum production state in response to factors including cell concentration, oxygen, temperature, pH, and metabolites. Herein, we introduce dynamic regulators of industrial microorganism optimization and discuss metabolic flux fine control by dynamic regulators in response to metabolites or extracellular stimuli, robust production systems, and auto-induction systems using quorum sensing.     

Parts plus pipes: synthetic biology approaches to metabolic engineering

Synthetic biologists combine modular biological "parts" to create higher-order devices. Metabolic engineers construct biological "pipes" by optimizing the microbial conversion of basic substrates to desired compounds. Many scientists work at the intersection of these two philosophies, employing synthetic devices to enhance metabolic engineering efforts. These integrated approaches promise to do more than simply improve product yields; they can expand the array of products that are tractable to produce biologically. In this review, we explore the application of synthetic biology techniques to next-generation metabolic engineering challenges, as well as the emerging engineering principles for biological design.     

历久弥新：进化中的代谢工程

20世纪90年代,Bailey及Stephanopoulos等提出了经典代谢工程的理念,旨在利用DNA重组技术对代谢网络进行改造,以达到细胞性能改善,目标产物增加的目的。自代谢工程诞生以来的30年,生命科学蓬勃发展,基因组学、系统生物学、合成生物学等新学科不断涌现,为代谢工程的发展注入了新的内涵与活力。经典代谢工程研究已进入到前所未有的系统代谢工程阶段。组学技术、基因组代谢模型、元件组装、回路设计、动态控制、基因组编辑等合成生物学工具与策略的应用,大大提升了复杂代谢的设计与合成能力;机器学习的介入以及进化工程与代谢工程的结合,为系统代谢工程的未来开辟了新的方向。文中对过去30年代谢工程的发展趋势作了梳理,介绍了代谢工程在发展中不断创新的理论与方法及其应用。     

Synthetic regulatory tools for microbial engineering

Microbial engineering requires accurate information about cellular metabolic networks and a set of molecular tools that can be predictably applied to the efficient redesign of such networks. Recent advances in the field of metabolic engineering and synthetic biology, particularly the development of molecular tools for synthetic regulation in the static and dynamic control of gene expression, have increased our ability to efficiently balance the expression of genes in various biological systems. It would accelerate the creation of synthetic pathways and genetic programs capable of adapting to environmental changes in real time to perform the programmed cellular behavior. In this paper, we review current developments in the field of synthetic regulatory tools for static and dynamic control of microbial gene expression.     

Adaptive rescaling maximizes information transmission

Adaptation is a widespread phenomenon in nervous systems, providing flexibility to function under varying external conditions. Here, we relate an adaptive property of a sensory system directly to its function as a carrier of information about input signals. We show that the input/output relation of a sensory system in a dynamic environment changes with the statistical properties of the environment. Specifically, when the dynamic range of inputs changes, the input/output relation rescales so as to match the dynamic range of responses to that of the inputs. We give direct evidence that the scaling of the input/output relation is set to maximize information transmission for each distribution of signals. This adaptive behavior should be particularly useful in dealing with the intermittent statistics of natural signals.     

Metabolic engineering for the utilization of carbohydrate portions of lignocellulosic biomass

The petrochemical industry has grown to meet the need for massive production of energy and commodities along with an explosive population growth; however, serious side effects such as greenhouse gas emissions and global warming have negatively impacted the environment. Lignocellulosic biomass with myriad quantities on Earth is an attractive resource for the production of carbon-neutral fuels and chemicals through environmentally friendly processes of microbial fermentation. This review discusses metabolic engineering efforts to achieve economically feasible industrial production of fuels and chemicals from microbial cell factories using the carbohydrate portion of lignocellulosic biomass as substrates. The combined knowledge of systems biology and metabolic engineering has been applied to construct robust platform microorganisms with maximum conversion of monomeric sugars, such as glucose and xylose, derived from lignocellulosic biomass. By comprehensively revisiting carbon conversion pathways, we provide a rationale for engineering strategies, as well as their features, feasibility, and recent representative studies. In addition, we briefly discuss how tools in systems biology can be applied in the field of metabolic engineering to accelerate the development of microbial cell factories that convert lignocellulosic biomass into carbon-neutral fuels and chemicals with economic feasibility.     

Predictive design of mRNA translation initiation region to control prokaryotic translation efficiency

Precise prediction of prokaryotic translation efficiency can provide valuable information for optimizing bacterial host for the production of biochemical compounds or recombinant proteins. However, dynamic changes in mRNA folding throughout translation make it difficult to assess translation efficiency. Here, we systematically determined the universal folding regions that significantly affect the efficiency of translation in Escherichia coli. By assessing the specific regions for mRNA folding, we could construct a predictive design method, UTR Designer, and demonstrate that proper codon optimization around the 5′-proximal coding sequence is necessary to achieve a broad range of expression levels. Finally, we applied our method to control the threshold value of input signals switching on a genetic circuit. This should increase our understanding of the processes underlying gene expression and provide an efficient design principle for optimizing various biological systems, thereby facilitating future efforts in metabolic engineering and synthetic biology.