Fine-tuning biosynthetic pathways is crucial for the development of economic feasible microbial cell factories. Therefore, the use of computational models able to predictably design regulatory sequences for pathway engineering proves to be a valuable tool, especially for modifying genes at the translational level. In this study we developed a computational approach for the de novo design of 5′-untranslated regions (5′UTRs) in Saccharomyces cerevisiae with a predictive outcome on translation initiation rate. On the basis of existing data, a partial least-squares (PLS) regression model was trained and showed good performance on predicting protein abundances of an independent test set. This model was further used for the construction of a “yUTR calculator” that can design 5′UTR sequences with a diverse range of desired translation efficiencies. The predictive power of our yUTR calculator was confirmed in vivo by different representative case studies. As such, these results show the great potential of data driven approaches for reliable pathway engineering in S. cerevisiae.

中文翻译：

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走向酿酒酵母中可预测的5'UTR ：yUTR计算器的开发

微调生物合成途径对于发展经济可行的微生物细胞工厂至关重要。因此，使用能够预测地设计用于途径工程的调控序列的计算模型被证明是有价值的工具，尤其是对于在翻译水平上修饰基因而言。在这项研究中，我们开发了一种用于酿酒酵母5'-非翻译区（5'UTR）从头设计的计算方法具有翻译起始率的预测结果。在现有数据的基础上，训练了偏最小二乘（PLS）回归模型，该模型在预测独立测试集的蛋白质丰度方面显示出良好的性能。该模型进一步用于构建“ yUTR计算器”，该计算器可以设计具有多种所需翻译效率范围的5'UTR序列。我们的yUTR计算器的预测能力已通过不同的代表性案例研究在体内得到证实。这样，这些结果显示了数据驱动方法对于酿酒酵母中可靠途径工程的巨大潜力。