Systematic Quantification of Sequence and Structural Determinants Controlling mRNA stability in Bacterial Operons
Systematic Quantification of Sequence and Structural Determinants Controlling mRNA stability in Bacterial Operons
复制标题
控制细菌操纵子mRNA稳定性的序列和结构决定因素的系统定量
DOI：
10.1021/acssynbio.0c00471
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发表时间：
2021-01-19
影响因子：
4.7
通讯作者：
Salis, Howard M.
中科院分区：
文献类型：
--
作者：
Cetnar, Daniel P.;Salis, Howard M.
mRNA降解是影响所有基因表达水平的核心过程，然而，控制mRNA降解率的决定因素仍然缺乏特征。在这里，我们应用了合成生物学，通过设计学习的方法来阐明在细菌操纵子中控制mRNA稳定性的序列和结构决定因素。我们设计、构建并表征了大肠杆菌中的82个操纵子，系统地改变了5'非翻译区（UTR）、基因间区和3' UTR区中的RNase结合位点特征、翻译起始速率和转录终止子效率，然后在指数生长期间使用逆转录定量聚合酶链反应（RT-qPCR）测定其mRNA水平。我们发现，将长单链RNA引入5'UTR使mRNA水平降低了9.4倍，降低翻译速率使mRNA水平降低了11.8倍。我们还发现基因间区域的RNase结合位点对mRNA水平的影响要小得多。令人惊讶的是，改变转录终止效率或将长单链RNA引入3'UTR对上游mRNA水平没有影响。通过这些测量，我们开发并验证了核糖体保护和RNA酶活性的生物物理模型，并且具有良好的定量一致性。我们还制定了合理控制mRNA稳定性的设计规则，促进了具有所需功能的工程遗传系统的自动化设计。
mRNA degradation is a central process that affects all gene expression levels, and yet, the determinants that control mRNA decay rates remain poorly characterized. Here, we applied a synthetic biology, learn-by-design approach to elucidate the sequence and structural determinants that control mRNA stability in bacterial operons. We designed, constructed, and characterized 82 operons in Escherichia coli, systematically varying RNase binding site characteristics, translation initiation rates, and transcriptional terminator efficiencies in the 5' untranslated region (UTR), intergenic, and 3' UTR regions, followed by measuring their mRNA levels using reverse transcription quantitative polymerase chain reaction (RT-qPCR) assays during exponential growth. We show that introducing long single-stranded RNA into 5' UTRs reduced mRNA levels by up to 9.4-fold and that lowering translation rates reduced mRNA levels by up to 11.8-fold. We also found that RNase binding sites in intergenic regions had much lower effects on mRNA levels. Surprisingly, changing the transcriptional termination efficiency or introducing long single-stranded RNA into 3' UTRs had no effect on upstream mRNA levels. From these measurements, we developed and validated biophysical models of ribosome protection and RNase activity with excellent quantitative agreement. We also formulated design rules to rationally control a mRNA's stability, facilitating the automated design of engineered genetic systems with desired functionalities.