SynBioNT: A Synthetic Biology Network for Modelling and Programming Cell-Chell Interactions

SynBioNT：用于建模和编程细胞-细胞相互作用的合成生物学网络

• 批准号: BB/F01855X/1
• 负责人: Natalio Krasnogor
• 金额: $ 9.5万
• 依托单位: University of Nottingham
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2008
• 资助国家: 英国
• 起止时间: 2008 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FF01855X%2F1
• 关键词: SynBioNT; Synthetic; Biology; Network; Modelling

The field of synthetic biology holds a great promise for the design, construction and development of artificial (i.e. man-made) biological (sub)systems thus offering viable new routes to 'genetically modified' organisms, smart drugs as well as model systems to examine artificial genomes and proteomes. The informed manipulation of such biological (sub)systems could have an enormous positive impact on our societies, with its effects being felt across a range of activities such as the provision of healthcare, environmental protection and remediation, etc. The basic premise of synthetic biology is that methods commonly used to design and construct non-biological systems, such as those employed in the computational sciences and the engineering disciplines, could also be used to model and program novel synthetic biosystems. Synthetic biology thus lies at the interface of a variety of disciplines ranging from biology through chemistry, physics, computer science, mathematics and engineering. The overarching aim of this network will be to generate new vigorous interactions between the disciplines that impinge (and contribute to) Synthetic Biology by supporting a range of community building activities. These activities will be centred on the specific technical goal of achieving programmable interactions between biological and artificial cells. By focusing on this specific technical challenge we hope to contribute to mending the rift that is appearing in the synthetic biology community between those who argue that synthetic biology should be done in a top-down fashion (i.e. knocking out or modifying functions of existing cells) and those that argue that it should follow a bottom-up approach that starts from first principles. We believe that both approaches are important and will have a role to play in the future of synthetic biology, hence a challenge that calls for the interaction between top-down systems (modified cells) and bottom-up systems (chells, protocells) provides the ideal background against which a new research community can be built and sustained. Rebecca Morell's article 'Creating Life in the Laboratory' that apeared in the BBC NEWS science section on the 19th of October 2007, not only illustrate *perfectly* the growing dichotomy in SB between those who approach it top down and those who do it bottom up but also ends up on a cautionary notice by citing George Attard from Southampton University as saying 'The biggest challenge is not necessarily creating life, but knowing that you have created life - doing the experiment that unambiguously tells you that you've got it..That's because you are going to be looking at a 'soup' that contains several hundred, possibly several thousand, chemical species. How on Earth can you tell that what you have isn't just a chemical waste bottle but something that is exhibiting the signs of life?' SynBioNT will focus *precisely* on shedding light into this question by fostering research on the so call 'cellular imitation game' as we have recently propose in our ground breaking paper 'The imitation game/a computational chemical approach to recognizing life' in Nature Biotechnology, 24:1203-1206, 2006.

合成生物学领域为人工(即人造)生物(亚)系统的设计、建造和发展带来了巨大的希望，从而为“转基因”生物、智能药物以及检验人工基因组和蛋白质组的模型系统提供了可行的新途径。对这种生物(亚)系统的知情操纵可能会对我们的社会产生巨大的积极影响，其影响可以通过提供医疗保健、环境保护和补救等一系列活动感受到。合成生物学的基本前提是，通常用于设计和构建非生物系统的方法，如计算科学和工程学科中使用的方法，也可以用于对新型合成生物系统进行建模和编程。因此，合成生物学处于从生物学到化学、物理、计算机科学、数学和工程学等多个学科的交界处。这个网络的首要目标将是通过支持一系列社区建设活动，在影响(并促进)合成生物学的学科之间产生新的强有力的互动。这些活动将围绕实现生物细胞和人造细胞之间可编程的相互作用这一具体技术目标展开。通过关注这一具体的技术挑战，我们希望有助于修补合成生物学领域出现的裂痕，前者认为合成生物学应该以自上而下的方式进行(即敲除或修改现有细胞的功能)，后者认为合成生物学应该遵循从基本原则开始的自下而上的方法。我们认为，这两种方法都很重要，并将在合成生物学的未来发挥作用，因此，要求自上而下系统(改良细胞)和自下而上系统(细胞、原细胞)之间相互作用的挑战提供了理想的背景，在此基础上可以建立和维持一个新的研究社区。2007年10月19日，英国广播公司新闻科学栏目刊登了丽贝卡·莫雷尔的文章《在实验室里创造生命》，这篇文章不仅完美地说明了自上而下和自下而上对待生命的人之间日益增长的二分法，而且还发出了警告，引用南安普顿大学的乔治·阿塔德的话说，最大的挑战不一定是创造生命，但要知道你已经创造了生命--做实验，毫不含糊地告诉你你已经得到了……因为你将看到的是一道含有数百种、可能数千种化学物质的汤。你怎么知道你所拥有的不只是一个化学废瓶，而是一些显示出生命迹象的东西？SynBioNT将“准确地”通过促进所谓的“细胞模拟游戏”的研究来关注这个问题，正如我们最近在“自然生物技术”杂志上发表的开创性论文“模拟游戏/识别生命的计算化学方法”，2006年24：1203-1206中提出的那样。

项目成果

Deterministic and stochastic P systems for modelling cellular processes

• DOI: 10.1007/s11047-009-9158-4
• 发表时间: 2010-06
• 期刊: Natural Computing
• 影响因子: 2.1
• 作者: M. Gheorghe;V. Manca;F. Romero-Campero

vrmlgen: An R Package for 3D Data Visualization on the Web

• DOI: 10.18637/jss.v036.i08
• 发表时间: 2010-08
• 期刊: Journal of Statistical Software
• 影响因子: 5.8
• 作者: E. Glaab;J. Garibaldi;N. Krasnogor

Learning Classifier Systems

学习分类器系统

• DOI: 10.1007/978-3-540-88138-4_15
• 发表时间: 2008
• 作者: Bacardit J

Photochromic molecular implementations of universal computation.

通用计算的光致变色分子实现。

• DOI: 10.1016/j.biosystems.2014.09.004
• 发表时间: 2014
• 期刊: Bio Systems
• 作者: Chaplin JC

EnrichNet: network-based gene set enrichment analysis.

• DOI: 10.1093/bioinformatics/bts389
• 发表时间: 2012-09-15
• 期刊: Bioinformatics (Oxford, England)
• 作者: Glaab E;Baudot A;Krasnogor N;Schneider R;Valencia A
• 通讯作者: Valencia A