Department of Chemistry , The University of North Carolina , Chapel Hill , North Carolina 27599-3290 , United States.
Biochemistry. 2019 Aug 6;58(31):3377-3385. doi: 10.1021/acs.biochem.9b00076. Epub 2019 Jul 26.
Chemical probing experiments, coupled with empirically determined free energy change relationships, can enable accurate modeling of the secondary structures of diverse and complex RNAs. A current frontier lies in modeling large and structurally heterogeneous transcripts, including complex eukaryotic RNAs. To validate and improve on experimentally driven approaches for modeling large transcripts, we obtained high-quality SHAPE data for the protein-free human 18S and 28S ribosomal RNAs (rRNAs). To our surprise, SHAPE-directed structure models for the human rRNAs poorly matched accepted structures. Analysis of predicted rRNA structures based on low-SHAPE and low-entropy (lowSS) metrics revealed that, whereas ∼75% of rRNA sequences form well-determined lowSS secondary structure, only ∼40% of the human rRNAs do. Critically, regions of the human rRNAs that specifically fold into well-determined lowSS structures were modeled to high accuracy using SHAPE data. This work reveals that eukaryotic rRNAs are more unfolded than are those of prokaryotic rRNAs and indeed are largely unfolded overall, likely reflecting increased protein dependence for eukaryotic ribosome structure. In addition, those regions and substructures that are well-determined can be identified and successfully modeled by SHAPE-directed folding.
化学探测实验,结合经验确定的自由能变化关系,可以实现对不同和复杂 RNA 的二级结构的准确建模。当前的前沿领域在于对大型和结构异质的转录物进行建模,包括复杂的真核 RNA。为了验证和改进基于实验驱动的建模大型转录物的方法,我们获得了无蛋白质的人 18S 和 28S 核糖体 RNA(rRNA)的高质量 SHAPE 数据。令我们惊讶的是,SHAPE 指导的人 rRNA 结构模型与公认的结构模型不匹配。基于低 SHAPE 和低熵(lowSS)指标的预测 rRNA 结构分析表明,虽然约 75%的 rRNA 序列形成了确定的低 SS 二级结构,但只有约 40%的人 rRNA 是这样。至关重要的是,使用 SHAPE 数据对人 rRNA 中具体折叠成确定的低 SS 结构的区域进行了高精度建模。这项工作表明,真核 rRNA 比原核 rRNA 更展开,实际上总体上大部分是展开的,这可能反映了真核核糖体结构对蛋白质的依赖增加。此外,那些确定的区域和亚结构可以通过 SHAPE 指导的折叠来识别和成功建模。