分子系统生物学与细胞发生动力学

系统生物学采用系统理论和实验生物技术、计算机数学模型等方法整合研究动态生物系统网络.生物系统的结构理论和生物系统技术,研究基因组——生物体复杂系统与细胞分子网络系统的动态结构发生与进化,分析基因组的逻辑程序和人工设计原理.细胞信号传导、基因调控网络、代谢反应链和基因反馈调控的自组织化人工设计和基因、基因链、基因组人工合成等系统生物工程开发,可用于复杂疾病机理分析、药物分子筛选和转基因表达系统的生物反应器、纳米生物计算机等.     

系统遗传学与合成生物学——21世纪的生物工程产业化

基因型-表现型复杂生物系统由多基因群调控,细胞发生的信号传导路径、多基因相互作用与细胞系谱定位形成生物系统的结构-图式发生遗传学,但分子、细胞和器官的结构、图式形成机理还不很清楚。复杂生物系统的图式演化是细胞的物种进化、细胞形态发育的细胞发生非线性动力学过程,包括：1）物种基因组结构内等位基因替代构成物种内基因多样性调控;2）物种间进化的基因组结构层次级别的自组织化。系统理论应用于系统生态学（Van Dyne GM．1966）、系统生理学（Sagawa K．1973）、系统心理学（Titchener EB．1992）、系统生物医学（Kamada T．1992）、系统生物学（zieglgansherger W,Tolle TR．1993）、系统生物工程与系统遗传学（Zengg：BJ.1994）的建立,以及遗传学机理的生物系统分析。细胞的基因组结构自组织化形成生物的系统发生,基因组的结构变化形成物种的适应变异,生物体结构的基因组复制与表达的细胞自组织化构成生物个体发生。基于系统遗传学的工程应用,合成生物学探索生物系统泛进化,包括人工生物体的遗传工程、基因调控和仿生智能的纳米生物机器,构成生物系统的人工引导进化。     

系统遗传学与生物技术-细胞分子生物系统的分析与合成

生物系统的科学与工程是整合系统论、实验、计算和工程方法的交叉学科研究与应用.系统生物学、系统医学,建立在系统科学和数学模型基础上,采用分子、组学生物技术和计算、生物信息技术,以及基因合成与转基因生物技术等研究生物系统原理和规律.系统遗传学与系统生物技术是研究天然与人工生物系统的基因系统与蛋白质系统构成细胞的软件信息与硬件运行系统的机理与方法.合成生物学、系统生物工程也是建立在系统科学和数学模型基础上,应用于生物系统原理设计虚拟计算机信息软件和仿生人工机器硬件、人造工程生物体和基因信息系统等.     

合成生物学及其在生物技术中的应用进展

合成生物学是一门21世纪生物学的新兴学科,它着眼生物科学与工程科学的结合,把生物系统当作工程系统"从下往上"进行处理,由"单元"(unit)到"部件"(device)再到"系统"(system)来设计,修改和组装细胞构件及生物系统.合成生物学是分子和细胞生物学、进化系统学、生物化学、信息学、数学、计算机和工程等多学科交叉的产物.目前研究应用包括两个主要方面:一是通过对现有的、天然存在的生物系统进行重新设计和改造,修改已存在的生物系统,使该系统增添新的功能.二是通过设计和构建新的生物零件、组件和系统,创造自然界中尚不存在的人工生命系统.合成生物学作为一门建立在基因组方法之上的学科,主要强调对创造人工生命形态的计算生物学与实验生物学的协同整合.必须强调的是,用来构建生命系统新结构、产生新功能所使用的组件单元既可以是基因、核酸等生物组件,也可以是化学的、机械的和物理的元件.本文跟踪合成生物学研究及应用,对其在DNA水平编程、分子修饰、代谢途径、调控网络和工业生物技术等方面的进展进行综述.     

面向工业生物技术的系统生物学

工业生物技术是以微生物细胞工厂利用可再生的生物原料来生产能源、材料与化学品等的生物技术,在解决资源、能源与环境等问题方面起着越来越重要的作用。系统生物学是全面解析微生物细胞工厂及其发酵过程从"黑箱"到"白箱"的重要研究方法。系统生物学借助基因组、转录组、蛋白质组、代谢组以及代谢流组等多组学数据,可解析微生物细胞工厂在RNA、蛋白与代谢物等不同水平上的变化规律与调控机制。目前,系统生物学在微生物细胞工厂的设计创建与发酵工艺优化中起着越来越重要的指导作用,许多成功应用实例不断涌现,推动着工业生物技术的快速发展。文中重点综述基因组、转录组、蛋白质组、代谢组与代谢流组以及基因组规模的网络模型等各组学技术的最新发展及其在工业生物技术尤其是菌株改造与发酵优化中的应用,并就工业生物技术中系统生物学的未来发展方向进行展望。     

现代系统生物技术与图式遗传学

基因组程序化表达调控与生物体形态结构发生的相互对应是图式遗传学和系统生物技术研究复杂生物系统的核心。基因-蛋白质表达与神经-内分泌信号,构成生物系统发生演变的双向调控过程是生物信息控制系统的结构、功能和演变的基础。细胞信号传导与基因差异表达调控是从基因、细胞到器官的细胞动力学转换系统,是基因、蛋白质、脂类等生物高分子相互作用与细胞再生、分化、迁移、凋亡的程序化调控节律,也就是基因定位图谱-细胞定位图谱的基因组-蛋白质组与生物体的细胞节律-形态的发生转换过程。     

合成生物学在生物基化学品上的应用趋势及展望

合成生物学(synthetic biology)将工程学和生物学相结合, 它不同于对自然基因模拟的基因工程和对代谢途径模拟的代谢工程,而是在以基因组解析技术和化学合成技术为核心的现代生物技术基础上,以系统生物学思想和知识为指导,综合生物化学、生物物理和生物信息技术,建立基于基因和基因组、蛋白质和蛋白质组的基本要素(模块)及其组合的工程化的资源库和技术平台,旨在设计、改造、重建或制造生物分子、生物部件、生物系统、代谢途径与发育分化过程,以及具有生命活动能力的细胞和生物个体.     

系统生物学的研究进展

系统生物学以系统的观点．运用工程和计算机技术及各种先进的生物学研究手段研究细胞中所有基因和蛋白质,来解释生命的奥秘。系统生物学是在基因组序列的基础上完成由生命密码到生命过程的研究,了解系统的结构和功能,揭示系统内部各组成成分的相互作用和运行规律。从系统生物学的产生背景、发展现状和研究目标、研究平台、研究动态等方面综述了系统生物学的研究。     

数字细胞模型的研究及应用

组学分析技术的发展推动生物学逐渐成为一门以数据分析为中心的科学。依托生物数据在细胞整体系统水平建立数字细胞模型,对于理解细胞系统组织原理和生命产生进化规律,预测各种环境和基因扰动对细胞功能的影响并指导设计人工生命具有重要意义,因此数字细胞的构建模拟设计已成为合成生物学的核心研究内容与底层支撑技术。本文重点对天津工业生物技术研究所创立十年来在数字细胞研究方面的进展进行回顾介绍,重点包括基因组尺度代谢网络模型的构建、质控以及其在途径设计和指导菌种代谢工程改造方面的应用,进一步结合近年来细胞模型研究的前沿趋势,对整合多种约束的模型的构建和分析研究方面的最新成果进行了介绍,最后对数字细胞研究的未来发展方向进行展望。数字细胞技术将与基因组测序、合成和编辑等合成生物学前沿技术一起提升人们对生命进行读写改创的能力。     

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。     

Yeast systems biotechnology for the production of heterologous proteins

Systems biotechnology has been established as a highly potent tool for bioprocess development in recent years. The applicability to complex metabolic processes such as protein synthesis and secretion, however, is still in its infancy. While yeasts are frequently applied for heterologous protein production, more progress in this field has been achieved for bacterial and mammalian cell culture systems than for yeasts. A critical comparison between different protein production systems, as provided in this review, can aid in assessing the potentials and pitfalls of applying systems biotechnology concepts to heterologous protein producing yeasts. Apart from modelling, the methodological basis of systems biology strongly relies on postgenomic methods. However, this methodology is rapidly moving so that more global data with much higher sensitivity will be achieved in near future. The development of next generation sequencing technology enables an unexpected revival of genomic approaches, providing new potential for evolutionary engineering and inverse metabolic engineering.     

2012酶工程专刊序言

酶工程是酶学与工程科学融合的综合性科学技术,是现代生物技术与未来生物经济的支柱。近年来,随着在合成生物学研究上的突破,作为合成生物学重要核心内容的酶工程研究受到重视与关注,为促进国内酶工程研究的发展,本期"酶工程专刊"介绍了我国酶工程专家与青年学者在新酶的发掘、酶的作用机制及酶的生产与应用方面所取得的最新进展。     

系统生物学——生命科学的新领域

系统生物学是继基因组学、蛋白质组学之后一门新兴的生物学交叉学科,代表21世纪生物学的未来.最近,系统生物学研究机构纷纷成立.在研究上,了解一个复杂的生物系统需要整合实验和计算方法.基因组学和蛋白质组学中的高通量方法为系统生物学发展提供了大量的数据.计算生物学通过数据处理、模型构建和理论分析,成为系统生物学发展的一个必不可缺、强有力的工具.在应用上,系统生物学代表新一代医药开发和疾病防治的方向.     

Systems biology in animal sciences

Systems biology is a rapidly expanding field of research and is applied in a number of biological disciplines. In animal sciences, omics approaches are increasingly used, yielding vast amounts of data, but systems biology approaches to extract understanding from these data of biological processes and animal traits are not yet frequently used. This paper aims to explain what systems biology is and which areas of animal sciences could benefit from systems biology approaches. Systems biology aims to understand whole biological systems working as a unit, rather than investigating their individual components. Therefore, systems biology can be considered a holistic approach, as opposed to reductionism. The recently developed 'omics' technologies enable biological sciences to characterize the molecular components of life with ever increasing speed, yielding vast amounts of data. However, biological functions do not follow from the simple addition of the properties of system components, but rather arise from the dynamic interactions of these components. Systems biology combines statistics, bioinformatics and mathematical modeling to integrate and analyze large amounts of data in order to extract a better understanding of the biology from these huge data sets and to predict the behavior of biological systems. A 'system' approach and mathematical modeling in biological sciences are not new in itself, as they were used in biochemistry, physiology and genetics long before the name systems biology was coined. However, the present combination of mass biological data and of computational and modeling tools is unprecedented and truly represents a major paradigm shift in biology. Significant advances have been made using systems biology approaches, especially in the field of bacterial and eukaryotic cells and in human medicine. Similarly, progress is being made with 'system approaches' in animal sciences, providing exciting opportunities to predict and modulate animal traits.     

Systems biology,emergence and antireductionism

This study explores the conceptual history of systems biology and its impact on philosophical and scientific conceptions of reductionism, antireductionism and emergence. Development of systems biology at the beginning of 21st century transformed biological science. Systems biology is a new holistic approach or strategy how to research biological organisms, developed through three phases. The first phase was completed when molecular biology transformed into systems molecular biology. Prior to the second phase, convergence between applied general systems theory and nonlinear dynamics took place, hence allowing the formation of systems mathematical biology. The second phase happened when systems molecular biology and systems mathematical biology, together, were applied for analysis of biological data. Finally, after successful application in science, medicine and biotechnology, the process of the formation of modern systems biology was completed.Systems and molecular reductionist views on organisms were completely opposed to each other. Implications of systems and molecular biology on reductionist–antireductionist debate were quite different. The analysis of reductionism, antireductionism and emergence issues, in the era of systems biology, revealed the hierarchy between methodological, epistemological and ontological antireductionism. Primarily, methodological antireductionism followed from the systems biology. Only after, epistemological and ontological antireductionism could be supported.     

Systems Biology-an interdisciplinary approach

System-level approaches in biology are not new but foundations of “Systems Biology” are achieved only now at the beginning of the 21st century [Kitano, H., 2001. Foundations of Systems Biology. MIT Press, Cambridge, MA]. The renewed interest for a system-level approach is linked to the progress in collecting experimental data and to the limits of the “reductionist” approach. System-level understanding of native biological and pathological systems is needed to provide potential therapeutic targets. Examples of interdisciplinary approach in Systems Biology are described in U.S., Japan and Europe. Robustness in biology, metabolic engineering and idiotypic networks are discussed in the framework of Systems Biology.     

Calculating life? Duelling discourses in interdisciplinary systems biology

A high profile context in which physics and biology meet today is in the new field of systems biology. Systems biology is a fascinating subject for sociological investigation because the demands of interdisciplinary collaboration have brought epistemological issues and debates front and centre in discussions amongst systems biologists in conference settings, in publications, and in laboratory coffee rooms. One could argue that systems biologists are conducting their own philosophy of science. This paper explores the epistemic aspirations of the field by drawing on interviews with scientists working in systems biology, attendance at systems biology conferences and workshops, and visits to systems biology laboratories. It examines the discourses of systems biologists, looking at how they position their work in relation to previous types of biological inquiry, particularly molecular biology. For example, they raise the issue of reductionism to distinguish systems biology from molecular biology. This comparison with molecular biology leads to discussions about the goals and aspirations of systems biology, including epistemic commitments to quantification, rigor and predictability. Some systems biologists aspire to make biology more similar to physics and engineering by making living systems calculable, modelable and ultimately predictable-a research programme that is perhaps taken to its most extreme form in systems biology's sister discipline: synthetic biology. Other systems biologists, however, do not think that the standards of the physical sciences are the standards by which we should measure the achievements of systems biology, and doubt whether such standards will ever be applicable to 'dirty, unruly living systems'. This paper explores these epistemic tensions and reflects on their sociological dimensions and their consequences for future work in the life sciences.     

Fostering Systems Thinking in Biological Education Using the Example of Plant Hormones

Systems thinking is an increasingly recognized paradigm in education in both natural and social sciences, a particular focus being, naturally, in biology. This article argues that plant biology, and in particular, plant hormonal signaling, provides highly illustrative models for learning and teaching in a systems paradigm, because it offers examples of highly complex networks, ranging from the molecular‐ to ecosystem‐scale, and in addition lends itself to the use of real‐life biological objects.