Engineered burden-based feedback for robust and optimised synthetic biology

工程化的基于负荷的反馈，用于稳健和优化的合成生物学

• 批准号: EP/J021849/1
• 负责人: Thomas Ellis
• 金额: $ 55.68万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2013
• 资助国家: 英国
• 起止时间: 2013 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FJ021849%2F1
• 关键词: Engineered; burden; based; feedback; robust

Synthetic biology is an exciting new subject that is accelerating the research and development of new biotechnologies by rigorously applying engineering design principles to the way we work with biological systems. The most prominent application of synthetic biology is the rational modification and redesign of living organisms like microbes for new efficient use in sectors such as energy production, biomedicine, drug production and food technology. Crucial to developing and applying synthetic biology is the rigorous quantification, modelling, analysis and control of the synthetic biology designs. By using this engineering framework we aim to be able to reliably predict and robustly control how engineered biological systems will operate.Although synthetic biology has had numerous successes in research, it is still difficult to predict how engineered cells behave when new synthetic genetic information is added to these host cells. One of the major reasons for this is that new synthetic genes add an as-yet unquantified burden to cells, particularly to commonly used microbes like E. coli. This burden effect is due to the new genes requiring resources to be maintained and function. This means that the introduced genes take resources away from those needed by their host cell in order to grow and survive. Usually the result of this is the unpredictable failure of the synthetic biology design to behave as expected or the creation of designs that only function in a narrow set of ideal conditions.The work proposed in this project seeks to address and make use of the understudied effect of synthetic biology we know as burden. To achieve this goal, we will use novel genetic tools to quantify the effect of burden for several typical synthetic biology devices and do this work in the well-characterised microbe E. coli so that our results are useful to the many researchers who work with this model organism. To see how the cell naturally reacts to burden we will use the high-resolution tool of RNA sequencing to quantify the gene expression changes that a cell triggers when it is burdened. Quantified burden combined with the quantified gene expression changes in response to burden will together give us crucial data that can be used to build a mathematical model of how a cell reacts to new synthetic genes being added and used. This model will allow future applications of synthetic biology to predict how synthetic systems will interact with their host cells and therefore open the door for rigorous optimisation of the robustness/performance compromise inherent to any control engineering design. It will also allow for a new generation of synthetic biology devices that automatically account for the burden effect. To demonstrate this final point, this project will use our quantified understanding of burden to engineer novel synthetic plasmid vectors that are designed to auto-regulate their copy number via feedback mechanisms that take into account burden, thereby serving as general purpose burden-based controllers. We will show how these plasmid systems work by building and testing a self-regulating biological nightlight that emits bioluminescence in the dark without any significant loss in growth. The new plasmid systems we generate will be extremely valuable for synthetic biology as they will allow synthetic devices and systems to respond directly to cell health thereby endowing them with the robust and predictable behaviours needed for future applications in health, energy and biosensing.

合成生物学是一个令人兴奋的新主题，正在通过严格将工程设计原理应用于我们与生物系统的方式中，从而加速了新生物技术的研究和开发。合成生物学的最突出的应用是，在能源生产，生物医学，药物生产和食品技术等领域的新有效利用中，像微生物（如微生物）的合理修饰和重新设计。对于合成生物学设计的严格定量，建模，分析和控制，对于发展和应用合成生物学至关重要。通过使用该工程框架，我们旨在能够可靠地预测和稳健地控制工程生物学系统的运作方式。尽管合成生物学在研究方面取得了许多成功，但仍然很难预测何时将新的合成遗传信息添加到这些宿主细胞中。造成这种情况的主要原因之一是，新的合成基因为细胞增加了尚未量化的负担，尤其是对大肠杆菌等常用微生物。这种负担效应是由于新基因需要维护资源和运作。这意味着引入的基因将资源从其宿主细胞所需的资源中夺走，以生长和生存。通常，结果是合成生物学设计的不可预测的失败，其表现为预期，或者创建仅在狭窄的理想条件下运作的设计。该项目提出的工作旨在解决和利用合成生物学的被忽视效应，我们知道我们称为负担。为了实现这一目标，我们将使用新颖的遗传工具来量化对几种典型合成生物学设备的负担的效果，并在特征良好的微生物大肠杆菌中进行这项工作，以使我们的结果对许多与该模型生物体一起工作的研究人员有用。为了了解细胞对负担的自然反应，我们将使用RNA测序的高分辨率工具来量化细胞在负担时触发的基因表达变化。量化的负担与量化的基因表达对负担的响应相结合将为我们提供重要的数据，可用于构建细胞对新合成基因的反应和使用的新合成基因的反应。该模型将允许合成生物学的将来的应用预测合成系统将如何与宿主细胞相互作用，因此为任何控制工程设计固有的稳健性/性能折衷打开了大门。它还将允许新一代的合成生物学设备自动解释负担效果。为了证明这一点，该项目将利用我们对负担的量化理解来工程师新颖的合成质粒向量，这些质粒载体旨在通过考虑负担的反馈机制自动调节其拷贝数，从而充当基于通用负担的控制器。我们将通过构建和测试自我调节的生物夜灯来展示这些质粒系统如何工作，该夜灯在黑暗中发出生物发光而没有任何显着的生长损失。我们生成的新质粒系统对于合成生物学将非常有价值，因为它们将允许合成设备和系统直接对细胞健康做出反应，从而赋予它们在健康，能源和生物效率上的未来应用所需的强大和可预测的行为。

项目成果

Overloaded and stressed: whole-cell considerations for bacterial synthetic biology

• DOI: 10.1016/j.mib.2016.07.009
• 发表时间: 2016-10-01
• 期刊: CURRENT OPINION IN MICROBIOLOGY
• 影响因子: 5.4
• 作者: Borkowski, Olivier;Ceroni, Francesca;Ellis, Tom
• 通讯作者: Ellis, Tom

Burden-driven feedback control of gene expression

• DOI: 10.1101/177030
• 发表时间: 2017-08
• 期刊: Nature Methods
• 影响因子: 48
• 作者: Francesca Ceroni;Alice Boo;Simone Furini;T. Gorochowski;Olivier Borkowski;Y. Ladak;A. Awan;Charlie Gilbert;G. Stan;T. Ellis

Modelling the burden caused by gene expression: an in silico investigation into the interactions between synthetic gene circuits and their chassis cell

模拟基因表达引起的负担：对合成基因电路与其底盘细胞之间相互作用的计算机研究

• 发表时间: 2013
• 作者: Algar R Algar

Modelling essential interactions between synthetic genes and their chassis cell

• DOI: 10.1109/cdc.2014.7040239
• 发表时间: 2014-01-01
• 期刊: 2014 IEEE 53RD ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC)
• 作者: Algar, R. J. R.;Ellis, T.;Stan, G. -B.
• 通讯作者: Stan, G. -B.