Li Minglun, Muthukumar Murugappan
Department of Polymer Science and Engineering, University of Massachusetts, Amherst, Massachusetts 01003, United States.
J Am Chem Soc. 2025 Jan 15;147(2):1553-1562. doi: 10.1021/jacs.4c10640. Epub 2024 Dec 31.
Direct translocation of RNA with secondary structures using single-molecule electrophoresis through protein nanopores shows significant fluctuations in the measured ionic current, in contrast to unstructured single-stranded RNA or DNA. We developed a multiscale model combining the oxRNA model for RNA with the 3-dimensional Poisson-Nernst-Planck formalism for electric fields within protein pores, aiming to map RNA conformations to ionic currents as RNA translocates through three protein nanopores: α-hemolysin, CsgG, and MspA. Our findings reveal three distinct stages of translocation (pseudoknot, melting, and molten globule) based on contact maps and current values. Two translocation modes emerge: fast and slow. In the fast mode, the speed is determined by the electric field, independent of pore geometry. In the slow mode, the molten globule stage is the rate-determining factor in slowing the translocation, instead of the previous paradigm of melting of the base pairs. Using these insights, we propose a neural network framework to identify and reconstruct RNA secondary structures from ionic current windows. We find that the electric field distribution, not the nanopore geometry, drives the molten globule stage. Our results explain the large current fluctuations. These results provide a fundamental understanding of the role of secondary and tertiary structures in the translocation of RNA in direct RNA translocation platforms based on single-molecule electrophoresis. This work offers design rules for new protein pores and real-time imaging of the secondary structures of RNA.
与无结构的单链RNA或DNA不同,利用单分子电泳通过蛋白质纳米孔对具有二级结构的RNA进行直接转位时,测量的离子电流会出现显著波动。我们开发了一种多尺度模型,将用于RNA的oxRNA模型与蛋白质孔内电场的三维泊松-能斯特-普朗克形式体系相结合,旨在在RNA通过三种蛋白质纳米孔(α-溶血素、CsgG和MspA)转位时,将RNA构象映射为离子电流。我们的研究结果基于接触图和电流值揭示了转位的三个不同阶段(假结、解链和熔球)。出现了两种转位模式:快速和慢速。在快速模式下,速度由电场决定,与孔的几何形状无关。在慢速模式下,熔球阶段是减缓转位的速率决定因素,而不是之前碱基对解链的范式。利用这些见解,我们提出了一个神经网络框架,用于从离子电流窗口识别和重建RNA二级结构。我们发现电场分布而非纳米孔几何形状驱动熔球阶段。我们的结果解释了较大的电流波动。这些结果为基于单分子电泳的直接RNA转位平台中二级和三级结构在RNA转位中的作用提供了基本理解。这项工作为新的蛋白质孔提供了设计规则以及RNA二级结构的实时成像方法。