Diversity-based, model-guided construction of synthetic gene networks with predicted functions.
Diversity-based, model-guided construction of synthetic gene networks with predicted functions.
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DOI：
10.1038/nbt.1536
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发表时间：
2009-05
影响因子：
46.9
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中科院分区：
文献类型：
--
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从模块化组件工程化人工基因网络是合成生物学的主要目标之一。然而，构建具有可预测功能的基因网络仍然受到缺乏合适组件的阻碍，并且组装的网络通常需要广泛的迭代改造才能按预期工作。在这里，我们提出了一种方法，耦合库的多样化的组件（合成与随机的非必需序列）与计算机建模，以指导可预测的基因网络的建设，而不需要事后调整。我们证明了我们的方法在S。通过合成调控启动子文库并使用它们构建具有不同预测输入-输出特征的前馈环网络，然后，我们扩展了我们的方法，以产生一个合成基因网络作为一个可预测的计时器，可通过组件选择进行修改。我们利用这个网络来控制酵母沉淀的时间，说明我们的设计的即插即用性质可以很容易地应用于生物技术。
Engineering artificial gene networks from modular components is one of the major goals of synthetic biology. However, the construction of gene networks with predictable functions remains hampered by a lack of suitable components and the fact that assembled networks often require extensive, iterative retrofitting to work as intended. Here we present an approach that couples libraries of diversified components (synthesized with randomized non-essential sequence) with in silico modeling to guide predictable gene network construction without the need for post-hoc tweaking. We demonstrate our approach in S. cerevisiae by synthesizing regulatory promoter libraries and using them to construct feedforward loop networks with different predicted input-output characteristics. We then expand our method to produce a synthetic gene network acting as a predictable timer, modifiable by component choice. We utilize this network to control the timing of yeast sedimentation, illustrating how the plug-and-play nature of our design can be readily applied to biotechnology.