A Quantitative and Predictive Model for RNA Binding by Human Pumilio Proteins
A Quantitative and Predictive Model for RNA Binding by Human Pumilio Proteins
复制标题
DOI：
10.1016/j.molcel.2019.04.012
复制
发表时间：
2019-06-06
期刊：
影响因子：
16
通讯作者：
Herschlag, Daniel
中科院分区：
文献类型：
--
作者：
Jarmoskaite, Inga;Denny, Sarah K.;Herschlag, Daniel
高通量方法使RNA结合蛋白(RBPs)的RNA靶点集和序列基序的常规生成成为可能。然而，需要定量的方法来捕捉负责细胞调控的RNA-RBP相互作用的图景。我们使用RNA-MAP平台直接测量了数千个设计的RNA的平衡结合，并构建了人类PUM1和PUM2蛋白识别RNA的预测模型。尽管先前发现了线性序列基序，但我们的测量显示了广泛的残基翻转和位置耦合实例。将我们的热力学模型应用于已发表的体内交联数据，揭示了预测的亲和力与体内占有率之间的定量一致性。我们的分析表明，一种热力学驱动的、连续的浮石结合格局可以忽略不计地受到RNA结构或动力学因素的影响，例如核糖体的置换。这项工作为剖析限制性商业惯例的细胞行为和影响其占有率的细胞特征提供了量化基础。
High-throughput methodologies have enabled routine generation of RNA target sets and sequence motifs for RNA-binding proteins (RBPs). Nevertheless, quantitative approaches are needed to capture the landscape of RNA-RBP interactions responsible for cellular regulation. We have used the RNA-MaP platform to directly measure equilibrium binding for thousands of designed RNAs and to construct a predictive model for RNA recognition by the human Pumilio proteins PUM1 and PUM2. Despite prior findings of linear sequence motifs, our measurements revealed widespread residue flipping and instances of positional coupling. Application of our thermodynamic model to published in vivo crosslinking data reveals quantitative agreement between predicted affinities and in vivo occupancies. Our analyses suggest a thermodynamically driven, continuous Pumilio-binding landscape that is negligibly affected by RNA structure or kinetic factors, such as displacement by ribosomes. This work provides a quantitative foundation for dissecting the cellular behavior of RBPs and cellular features that impact their occupancies.