系统生物学和合成生物学研究在生物燃料生产菌株改造中的应用

基于生物质资源生产环境友好的生物燃料,对经济和社会的可持续发展具有重要意义,但其生产成本高的问题十分突出,而高效生产菌株的获得是解决这一问题的根本出路。以下综述了利用系统生物学研究所获得的信息进行菌种改造的过程,重点论述了生产菌株胁迫耐受性方面的研究进展,并讨论了系统生物学、合成生物学和代谢工程技术在改造生物燃料生产菌株中的应用,展望了合成生物学在构建高效生物能源生产菌株方面应用的前景。     

A day of systems and synthetic biology for non‐experts

From understanding ageing to the creation of artificial membrane‐bounded ‘organisms’, systems biology and synthetic biology are seen as the latest revolutions in the life sciences. They certainly represent a major change of gear, but paradigm shifts? This is open to debate, to say the least. For scientists they open up exciting ways of studying living systems, of formulating the ‘laws of life’, and the relationship between the origin of life, evolution and artificial biological systems. However, the ethical and societal considerations are probably indistinguishable from those of human genetics and genetically modified organisms. There are some tangible developments just around the corner for society, and as ever, our ability to understand the consequences of, and manage, our own progress lags far behind our technological abilities. Furthermore our educational systems are doing a bad job of preparing the next generation of scientists and non‐scientists.     

Towards one sample per second for mass spectrometric screening of engineered microbial strains

1. Download : Download high-res image (155KB)
2. Download : Download full-size image

     

系统生物学与细胞发生系统动力学

系统生物学是系统理论和实验生物技术、计算机数学模型等方法整合的生物系统研究,系统遗传学研究基因组的稳态与进化、功能基因组和生物性状等复杂系统的结构、动态与发生演变等。合成生物学是系统生物学的工程应用,采用工程学方法、基因工程和计算机辅助设计等研究人工生物系统的生物技术。系统与合成生物学的结构理论,序列标志片段显示分析与微流控生物芯片,广泛用于研究细胞代谢、繁殖和应激的自组织进化、生物体形态发生等细胞分子生物系统原理等。     

合成生物学时代基于非模式细菌的工业底盘细胞研究现状与展望

工业微生物底盘细胞的开发将为工业生物技术的发展提供优良的细胞工厂,有利于实现环境保护及经济可持续发展.基于合成生物学"设计-构建-测试-学习"(Design-Build-Test-Learn,DBTL)策略,对底盘细胞进行多维度的理性或半理性改造是实现"建物致知"以及"建物致用"目标的重要手段.文中简述了合成生物学DB...     

Evolving cell models for systems and synthetic biology

This paper proposes a new methodology for the automated design of cell models for systems and synthetic biology. Our modelling framework is based on P systems, a discrete, stochastic and modular formal modelling language. The automated design of biological models comprising the optimization of the model structure and its stochastic kinetic constants is performed using an evolutionary algorithm. The evolutionary algorithm evolves model structures by combining different modules taken from a predefined module library and then it fine-tunes the associated stochastic kinetic constants. We investigate four alternative objective functions for the fitness calculation within the evolutionary algorithm: (1) equally weighted sum method, (2) normalization method, (3) randomly weighted sum method, and (4) equally weighted product method. The effectiveness of the methodology is tested on four case studies of increasing complexity including negative and positive autoregulation as well as two gene networks implementing a pulse generator and a bandwidth detector. We provide a systematic analysis of the evolutionary algorithm’s results as well as of the resulting evolved cell models.     

植物来源药用天然产物的合成生物学研究进展

大多数药用天然产物在植物中含量低微,提取分离困难;而且这些化合物一般结构复杂,化学合成难度大,还容易造成环境污染.基于合成生物学技术获得药用天然产物具有绿色环保和可持续发展等优点.文中以药用萜类化合物人参皂苷、紫杉醇、青蒿素、丹参酮,生物碱类化合物长春新碱、吗啡以及黄酮类化合物灯盏花素为例,总结了植物来源药用萜类、生物...     

Designing synthetic microbial communities for effectual bioremediation: A review

Abstract

Bioremediation is a better alternative and widely accepted approach used for efficient degradation of environmental pollutants released from industries, urban and agricultural activities due to its eco-friendly nature. Systems biology helps in the identification of new genes, proteins, metabolites, and metabolic pathways involved in bioremediation. Such information can be used for designing synthetic microbial communities that can degrade multiple recalcitrant pollutants simultaneously. This review gives a brief insight into various systems biology tools towards providing a greater understanding of microbial behaviour and improving the way of bioremediation. These techniques alone or in combination, provide a way to understand and improve the genetic potential of microorganisms to remediate various environmental contaminants efficiently. Further, this review also describes the successful employment of synthetic microbial consortium in the bioremediation. Moreover, In-silico tools are also described to analyse the data obtained through different laboratory experiments as well to predict the behaviour of microbial consortium towards the pollutants using different databases.     

微生物胞外电子传递效率的合成生物学强化

电活性微生物(产电微生物和亲电微生物)通过与外界环境进行双向电子和能量传递来实现多种微生物电催化过程(包括微生物燃料电池、微生物电解电池、微生物电催化等),从而实现在环境、能源领域的广泛应用,并为开发有效且可持续性生产新能源或大宗精细化学品的工艺提供了新机会。但是,电活性微生物的胞外电子传递效率比较低,这已经成为限制微生物电催化系统在工业应用中的主要瓶颈。以下综述了近年来利用合成生物学改造电活性微生物的相关研究成果,阐明了合成生物学如何用于打破电活性微生物胞外电子传递途径低效率的瓶颈,从而实现电活性微生物与环境的高效电子传递和能量交换,推动电活性微生物电催化系统的实用化进程。     

Impact of systems biology on metabolic engineering of Saccharomyces cerevisiae

Industrial biotechnology is a rapidly growing field. With the increasing shift towards a bio-based economy, there is rising demand for developing efficient cell factories that can produce fuels, chemicals, pharmaceuticals, materials, nutraceuticals, and even food ingredients. The yeast Saccharomyces cerevisiae is extremely well suited for this objective. As one of the most intensely studied eukaryotic model organisms, a rich density of knowledge detailing its genetics, biochemistry, physiology, and large-scale fermentation performance can be capitalized upon to enable a substantial increase in the industrial application of this yeast. Developments in genomics and high-throughput systems biology tools are enhancing one's ability to rapidly characterize cellular behaviour, which is valuable in the field of metabolic engineering where strain characterization is often the bottleneck in strain development programmes. Here, the impact of systems biology on metabolic engineering is reviewed and perspectives on the role of systems biology in the design of cell factories are given.     

合成未来：从大肠杆菌的重构看合成生物学的发展

合成生物学（synthetic biology）是伴随着基因工程、系统生物学以及生物信息学的发展而出现的一个新的交叉学科。大肠杆菌（Escherichia coli）作为一种宿主在合成生物学的发展中功不可没。从某种意义上讲,合成生物学的每一次进展都离不开大肠杆菌。从大肠杆菌的角度出发,对合成生物学的发展进行深入分析,并提出了合成生物学在中圉发展的重点。     

蛋白质预算：合成生物学的成本标尺

合成生物学以创建人工生命体系为目的.实践中人们希望人工生命体系具有更强的生产能力、转化能力、环境适应与监测能力,从而获得更优质的生产方式.生命体系的优化涉及到多层次的调控网络,而根本上还是对细胞中蛋白质的含量、定位、活性的控制.在蛋白质表达水平上进行控制是合成生物学元件设计、模块组装以及适配性研究最核心的手段.类似于工厂中的成本计算,合成生物学创建的人工生命体系(人工细胞工厂)以蛋白质预算为依据.优化蛋白质预算的研究策略已经成功应用于合成生物学研究实践中.     

Engineering of microorganisms for the production of biofuels and perspectives based on systems metabolic engineering approaches

The increasing oil price and environmental concerns caused by the use of fossil fuel have renewed our interest in utilizing biomass as a sustainable resource for the production of biofuel. It is however essential to develop high performance microbes that are capable of producing biofuels with very high efficiency in order to compete with the fossil fuel. Recently, the strategies for developing microbial strains by systems metabolic engineering, which can be considered as metabolic engineering integrated with systems biology and synthetic biology, have been developed. Systems metabolic engineering allows successful development of microbes that are capable of producing several different biofuels including bioethanol, biobutanol, alkane, and biodiesel, and even hydrogen. In this review, the approaches employed to develop efficient biofuel producers by metabolic engineering and systems metabolic engineering approaches are reviewed with relevant example cases. It is expected that systems metabolic engineering will be employed as an essential strategy for the development of microbial strains for industrial applications.     

Building momentum for systems and synthetic biology in India

Biological systems are inherently noisy. Predicting the outcome of a perturbation is extremely challenging. Traditional reductionist approach of describing properties of parts, vis-a-vis higher level behaviour has led to enormous understanding of fundamental molecular level biology. This approach typically consists of converting genes into junk (knock-down) and garbage (knock-out) and observe how a system responds. To enable broader understanding of biological dynamics, an integrated computational and experimental strategy was formally proposed in mid 1990s leading to the re-emergence of Systems Biology. However, soon it became clear that natural systems were far more complex than expected. A new strategy to address biological complexity was proposed at MIT (Massachusetts Institute of Technology) in June 2004, when the first meeting of synthetic biology was held. Though the term ‘synthetic biology’ was proposed during 1970s (Szybalski in Control of gene expression, Plenum Press, New York, 1974), the usage of the original concept found an experimental proof in 2000 with the demonstration of a three-gene circuit called repressilator (Elowitz and Leibler in Nature, 403:335–338, 2000). This encouraged people to think of forward engineering biology from a set of well described parts.     

Improved understanding of gene expression regulation using systems biology

This article reviews the current state of systems biology approaches, including the experimental tools used to generate ‘omic’ data and computational frameworks to interpret this data. Through illustrative examples, systems biology approaches to understand gene expression and gene expression regulation are discussed. Some of the challenges facing this field and the future opportunities in the systems biology era are highlighted.