Synthetic negative feedback circuits using engineered small RNAs. Synthetic negative feedback circuits using engineered small RNAs

Small RNA (sRNA) are non-coding RNA molecules which can post-transcriptionally regulate gene expression through interaction with messenger RNA (mRNA). Many natural bacterial sRNAs have been identified to date, and a small number of synthetic sRNAs have been designed that can regulate gene expression predictably. The use of sRNAs in synthetic biology has so far focussed on characterising their properties or to silence specific mRNAs for metabolic engineering purposes; they have not been used extensively in circuits. A particular use of sRNA could be in the implementation of feedback control architectures, which are known to endow natural and man-made systems with robust performance in the face of uncertainties. In this paper, we design, model and build two new negative feedback architectures that use translation-inhibiting sRNA modules. The first circuit builds upon the well characterised tet-based autorepressor, allowing fine tuning of the circuit output through the use of an external input molecule that modulates sRNA expression. The second circuit involves an sRNA module that responds to the level of the circuit output - a protein - by regulating the mRNA that encodes for this protein. We use mathematical modelling to predict the output response of both circuits to the external inputs and to predict the noise characteristics of each. Synthetic sRNAs were rationally designed and strong translation-inhibition against each mRNA target validated. The best performing sRNAs were integrated into each negative feedback circuit and qualitatively tested in vivo in Escherichia coli. The properties of both feedback circuits were compared to the autorepressor and found to be in good agreement with those predicted by modelling and found to have many beneficial effects on overall circuit performance. Finally mathematical modelling predicted important increases in noise would occur if these sRNA circuits were split across more than one plasmid, which correlated with our experimental results; this has wider implications for the construction of robust synthetic genetic circuits.

小分子RNA（small RNA，sRNA）是一类非编码RNA（non-coding RNA）分子，可通过与信使RNA（messenger RNA，mRNA）结合在转录后（post-transcriptionally）水平调控基因表达。迄今已鉴定出多种天然细菌sRNA，且已设计出少量可预测地调控基因表达的合成sRNA。目前，sRNA在合成生物学（synthetic biology）中的应用多聚焦于表征其自身特性，或为代谢工程（metabolic engineering）目的沉默特定mRNA，尚未在基因回路（genetic circuits）中得到广泛应用。sRNA的一类潜在应用是实现反馈控制架构（feedback control architectures），此类架构已被证实可赋予天然与人工系统在不确定性条件下的稳健性能。本文中，我们设计、建模并构建了两种基于翻译抑制（translation-inhibiting）型sRNA模块的新型负反馈回路。第一种回路以已被充分表征的基于tet的自动阻遏系统为基础，可通过调节sRNA表达的外部输入分子实现对回路输出的精细调控。第二种回路包含一个sRNA模块，该模块可通过调控编码该回路输出蛋白的mRNA，响应回路输出蛋白的水平变化。我们通过数学建模预测了两种回路对外部输入的输出响应，并分别分析了各自的噪声特性。我们通过理性设计合成了sRNA，并验证了其对各mRNA靶点的强效翻译抑制效果。将性能最优的sRNA整合至各负反馈回路后，我们在大肠杆菌（Escherichia coli）体内完成了定性测试。将两种反馈回路的性能与tet自动阻遏系统进行对比后发现，实验结果与建模预测的吻合度良好，且两类回路对整体性能有多方面的积极影响。最后，数学建模预测，若将这些sRNA回路拆分至多个质粒（plasmid）中，会出现噪声显著升高的情况，该结论与我们的实验结果一致；这一发现对构建稳健的合成基因回路（synthetic genetic circuits）具有更广泛的指导意义。