Retrovirus Biology

Division Of Basic Sciences - Nci

Investigators

Linked publications, trials & patents

Abstract

In collaboration with Dr. Yun-Xing Wang of the Protein-Nucleic Acid Interaction Section, Center for Structural Biology, CCR, we have analyzed the 3-dimensional structure of the Rev Response Element (RRE), a functional element in HIV-1 RNA that is required for the export of unspliced and singly spliced viral RNAs from the nucleus. Using small-angle X-ray scattering (SAXS), we reported several years ago that the 351-base RRE forms an "A" shape in solution (Fang et al., Cell, 2013). This structure was completely unanticipated and was of great interest, particularly since the distance between the "legs" of the A seemed to correspond well with the dimensions of the viral Rev protein dimer that is known to interact with the RRE. We highlighted the significance of this distance in further detailed studies of RRE structure and function (O'Carroll et al., J. Virol., 2017). More recently, Dr. Wang has developed the use of Atomic Force Microscopy (AFM) as a tool for the determination of 3-dimensional RNA structures. The special virtue of AFM for these studies is that information can be obtained from images of single RNA molecules; this is unlike the great majority of structure-determination techniques in which information from numerous molecules is pooled or averaged before analysis. This feature is especially important for RNA as RNA is so flexible that a population of identical RNA molecules will inevitably contain a mixture of different conformations. Dr. Wang has devised computational methods for the sorting of images into groups of related structures and the refinement of structural models from these images (Ding et al., Nature Comm. 2023; Degenhardt et al., 2025). Results using these new methodologies provide striking confirmation of the "A" shape of the RRE. It is hoped that the high-resolution information expected with these techniques could enable the design of new antiviral reagents targeting the RRE. We report holistic RNA structure determination method using atomic force microscopy, unsupervised machine learning and deep neural networks (HORNET), a novel method for determining three-dimensional topological structures of RNA using atomic force microscopy images of individual molecules in solution. Owing to the high signal-to-noise ratio of atomic force microscopy, this method is ideal for capturing structures of large RNA molecules in distinct conformations. In addition to six benchmark cases, we demonstrate the utility of HORNET by determining multiple heterogeneous structures of RNase P RNA and the HIV-1 Rev response element (RRE) RNA. Thus, our method addresses one of the major challenges in determining heterogeneous structures of large and flexible RNA molecules, and contributes to the fundamental understanding of RNA structural biology.