21ENGBIO Reprogramming bacterial cells using whole-cell models

最近越来越精确的基因组编辑技术的可用性为合成生物学家提供了在基因组水平上修改细胞和生物体的能力。在不久的将来，人们将有可能随意（重新）设计整个基因组，例如，建立能够产生有用化合物（例如胰岛素或生物燃料）的最小细胞。为了指导这一过程，合成生物学家通常利用数学模型来预测基因组工程的结果，并最终节省实验测试的时间和精力。到目前为止，缺乏数学模型，可以精确地代表所有功能的细胞是一个主要的瓶颈，在开发强大的循环之间的迭代设计和测试（所谓的“设计-构建-测试-学习周期”）再造活的organism. We的愿景是，全细胞模型可以彻底改变设计-构建-测试-学习周期。全细胞模型是细胞的最先进的计算表示，它解释了整个细胞生命周期中每个基因产物的功能和每个分子的动力学。我们在美国的国际合作伙伴最近开发了两种细菌细胞（生殖支原体和大肠杆菌）的全细胞模型，但迄今为止从未用于指导合成生物学实验。该计划将首次将全细胞模型预测和基因组编辑技术整合到设计-构建-测试-学习周期中，以合理地重新设计E。用于生产有用化合物的大肠杆菌细菌细胞。我们建立了一个跨学科团队，由英国系统和合成生物学专家组成，并包括全细胞模型开发和分析方面的世界专家。我们很高兴能够在基因组工程，系统和合成生物学以及现代计算机科学的界面上开创这个冒险和有前途的新研究计划。这项研究的成果可以通过显著降低实验成本、通过自动化加速发现以及促进全细胞模型对广泛的学术和工业界的影响来改变当前的合成生物学方法。从长远来看，随着全细胞模型可用于更高物种（例如人类细胞），我们的方法可能与合理设计患者量身定制的治疗方法相关。

The recent availability of increasingly precise genome-editing technologies provides synthetic biologists with the ability to modify cells and organisms at the genome-scale level. In the near future, it will be possible to (re-)engineer entire genomes at will, for example, to build minimal cells which can produce useful compounds (e.g. insulin or biofuels). To guide this process, synthetic biologists usually make use of mathematical models to predict the outcomes of genome engineering and, ultimately, save time and effort of experimental testing. To date, the lack of mathematical models which can represent precisely all functions within a cell is a major bottleneck in developing robust cycles of iterations between design and testing (the so-called "design-build-test-learn cycles") for reengineering living organisms.Our vision is that whole-cell models can revolutionise design-build-test-learn cycles. Whole-cell models are state-of-the-art computational representations of cells, which account for the function of every gene product and dynamics of every molecule over the entire cell lifecycle. Whole-cell models for two bacterial cells (Mycoplasma genitalium and Escherichia coli) have been developed very recently by our international partner in the US, but have never been used, to date, to guide experiments in synthetic biology. This programme will integrate, for the first time, whole-cell model predictions and genome-editing technologies within design-build-test-learn cycles to rationally redesign E. coli bacterial cells for the production of useful compounds. We set up an interdisciplinary team, composed of UK experts in systems and synthetic biology and encompassing the world experts in whole-cell model development and analysis. We are excited to pioneer this adventurous and promising new research programme at the interface of genome engineering, systems and synthetic biology and modern computer science. Outcomes of this research could transform current synthetic biology approaches by significantly reducing experimental costs, accelerating discovery through automation and promoting whole-cell model impact on broad academic and industrial communities.Longer-term, as whole-cell models become available for higher species (e.g. human cells), our approach could be relevant for the rational design of patient-tailored treatments.