Wyss Institute for Biologically Inspired Engineering, Boston, MA 02115, USA.
Proc Natl Acad Sci U S A. 2013 Aug 20;110(34):14024-9. doi: 10.1073/pnas.1301301110. Epub 2013 Aug 7.
The inability to predict heterologous gene expression levels precisely hinders our ability to engineer biological systems. Using well-characterized regulatory elements offers a potential solution only if such elements behave predictably when combined. We synthesized 12,563 combinations of common promoters and ribosome binding sites and simultaneously measured DNA, RNA, and protein levels from the entire library. Using a simple model, we found that RNA and protein expression were within twofold of expected levels 80% and 64% of the time, respectively. The large dataset allowed quantitation of global effects, such as translation rate on mRNA stability and mRNA secondary structure on translation rate. However, the worst 5% of constructs deviated from prediction by 13-fold on average, which could hinder large-scale genetic engineering projects. The ease and scale this of approach indicates that rather than relying on prediction or standardization, we can screen synthetic libraries for desired behavior.
无法准确预测异源基因表达水平，这极大地限制了我们对生物系统进行工程设计的能力。如果这些调控元件在组合时能表现出可预测的行为，那么使用特征明确的调控元件可能是一个可行的解决方法。我们合成了 12563 种常见启动子和核糖体结合位点的组合，并同时测量了整个文库的 DNA、RNA 和蛋白质水平。通过一个简单的模型，我们发现 RNA 和蛋白质的表达水平分别有 80%和 64%的时间在预期水平的两倍以内。这个大型数据集还允许对全局效应进行定量分析，例如翻译效率对 mRNA 稳定性的影响，以及 mRNA 二级结构对翻译效率的影响。然而，最差的 5%的构建体的偏离度平均达到了 13 倍，这可能会阻碍大规模的基因工程项目。这种方法的简便性和规模表明，我们可以直接从合成文库中筛选出所需的行为，而不必依赖于预测或标准化。
