Accelerated cryo-EM-guided determination of three-dimensional RNA-only structures

Nexus between RNA conformational dynamics and functional versatility

RNA conformational dynamics is pivotal for functional regulations in biology. RNA can function as versatile as protein but adopts multiple distinct structures. In this review, we provide a focused review of the recent advances in studies of RNA conformational dynamics and address some of the misconceptions about RNA structure and its conformational dynamics. We discuss why the traditional methods for structure determination come up short in describing RNA conformational space. The examples discussed provide illustrations of the structure-based mechanisms of RNAs with diverse roles, including viral, long noncoding, and catalytic RNAs, one of which focuses on the debated area of conformational heterogeneity of an RNA structural element in the HIV-1 genome.

Cryo-EM Structure of raiA ncRNA From Clostridium Reveals a New RNA 3D Fold

Advancements in genome-wide sequence analysis have led to the discovery of numerous novel bacterial non-coding RNAs (ncRNAs). These ncRNAs have been categorized into various RNA families and classes based on their size, structure, function, and evolutionary relationships. One such ncRNA family, raiA, is notably abundant in the bacterial phyla Firmicutes and Actinobacteria and is remarkably well-conserved across many Gram-positive bacteria. In this study, we integrated cryo-electron microscopy single-particle analysis with computational modeling and biochemical techniques to elucidate the structural characteristics of raiA from Clostridium sp. CAG 138. Our findings reveal the globular 3D fold of raiA, providing valuable structural insights. This analysis paves the way for future investigations into the functional properties of raiA, potentially uncovering new regulatory mechanisms in bacterial ncRNAs.

RNA sample optimization for cryo-EM analysis

RNAs play critical roles in most biological processes. Although the three-dimensional (3D) structures of RNAs primarily determine their functions, it remains challenging to experimentally determine these 3D structures due to their conformational heterogeneity and intrinsic dynamics. Cryogenic electron microscopy (cryo-EM) has recently played an emerging role in resolving dynamic conformational changes and understanding structure-function relationships of RNAs including ribozymes, riboswitches and bacterial and viral noncoding RNAs. A variety of methods and pipelines have been developed to facilitate cryo-EM structure determination of challenging RNA targets with small molecular weights at subnanometer to near-atomic resolutions. While a wide range of conditions have been used to prepare RNAs for cryo-EM analysis, correlations between the variables in these conditions and cryo-EM visualizations and reconstructions remain underexplored, which continue to hinder optimizations of RNA samples for high-resolution cryo-EM structure determination. Here we present a protocol that describes rigorous screenings and iterative optimizations of RNA preparation conditions that facilitate cryo-EM structure determination, supplemented by cryo-EM data processing pipelines that resolve RNA dynamics and conformational changes and RNA modeling algorithms that generate atomic coordinates based on moderate- to high-resolution cryo-EM density maps. The current protocol is designed for users with basic skills and experience in RNA biochemistry, cryo-EM and RNA modeling. The expected time to carry out this protocol may range from 3 days to more than 3 weeks, depending on the many variables described in the protocol. For particularly challenging RNA targets, this protocol could also serve as a starting point for further optimizations.

Comparison of Three Computational Tools for the Prediction of RNA Tertiary Structures

Understanding the structures of noncoding RNAs (ncRNAs) is important for the development of RNA-based therapeutics. There are inherent challenges in employing current experimental techniques to determine the tertiary (3D) structures of RNAs with high complexity and flexibility in folding, which makes computational methods indispensable. In this study, we compared the utilities of three advanced computational tools, namely RNAComposer, Rosetta FARFAR2, and the latest AlphaFold 3, to predict the 3D structures of various forms of RNAs, including the small interfering RNA drug, nedosiran, and the novel bioengineered RNA (BioRNA) molecule showing therapeutic potential. Our results showed that, while RNAComposer offered a malachite green aptamer 3D structure closer to its crystal structure, the performances of RNAComposer and Rosetta FARFAR2 largely depend upon the secondary structures inputted, and Rosetta FARFAR2 predictions might not even recapitulate the typical, inverted "L" shape tRNA 3D structure. Overall, AlphaFold 3, integrating molecular dynamics principles into its deep learning framework, directly predicted RNA 3D structures from RNA primary sequence inputs, even accepting several common post-transcriptional modifications, which closely aligned with the experimentally determined structures. However, there were significant discrepancies among three computational tools in predicting the distal loop of human pre-microRNA and larger BioRNA (tRNA fused pre-miRNA) molecules whose 3D structures have not been characterized experimentally. While computational predictions show considerable promise, their notable strengths and limitations emphasize the needs for experimental validation of predictions besides characterization of more RNA 3D structures.

Advances in the field of RNA 3D structure prediction and modeling, with purely theoretical approaches, and with the use of experimental data

Recent advancements in RNA three-dimensional (3D) structure prediction have provided significant insights into RNA biology, highlighting the essential role of RNA in cellular functions and its therapeutic potential. This review summarizes the latest developments in computational methods, particularly the incorporation of artificial intelligence and machine learning, which have improved the efficiency and accuracy of RNA structure predictions. We also discuss the integration of new experimental data types, including cryoelectron microscopy (cryo-EM) techniques and high-throughput sequencing, which have transformed RNA structure modeling. The combination of experimental advances with computational methods represents a significant leap in RNA structure determination. We review the outcomes of RNA-Puzzles and critical assessment of structure prediction (CASP) challenges, which assess the state of the field and limitations of existing methods. Future perspectives are discussed, focusing on the impact of RNA 3D structure prediction on understanding RNA mechanisms and its implications for drug discovery and RNA-targeted therapies, opening new avenues in molecular biology.

Targeting RNA with small molecules, from RNA structures to precision medicines: IUPHAR review: 40

RNA plays important roles in regulating both health and disease biology in all kingdoms of life. Notably, RNA can form intricate three-dimensional structures, and their biological functions are dependent on these structures. Targeting the structured regions of RNA with small molecules has gained increasing attention over the past decade, because it provides both chemical probes to study fundamental biology processes and lead medicines for diseases with unmet medical needs. Recent advances in RNA structure prediction and determination and RNA biology have accelerated the rational design and development of RNA-targeted small molecules to modulate disease pathology. However, challenges remain in advancing RNA-targeted small molecules towards clinical applications. This review summarizes strategies to study RNA structures, to identify small molecules recognizing these structures, and to augment the functionality of RNA-binding small molecules. We focus on recent advances in developing RNA-targeted small molecules as potential therapeutics in a variety of diseases, encompassing different modes of actions and targeting strategies. Furthermore, we present the current gaps between early-stage discovery of RNA-binding small molecules and their clinical applications, as well as a roadmap to overcome these challenges in the near future.

Automated detection and de novo structure modeling of nucleic acids from cryo-EM maps

Cryo-electron microscopy (cryo-EM) is one of the most powerful experimental methods for macromolecular structure determination. However, accurate DNA/RNA structure modeling from cryo-EM maps is still challenging especially for protein-DNA/RNA or multi-chain DNA/RNA complexes. Here we propose a deep learning-based method for accurate de novo structure determination of DNA/RNA from cryo-EM maps at  <5 Å resolutions, which is referred to as EM2NA. EM2NA is extensively evaluated on a diverse test set of 50 experimental maps at 2.0-5.0 Å resolutions, and compared with state-of-the-art methods including CryoREAD, ModelAngelo, and phenix.map_to_model. On average, EM2NA achieves a residue coverage of 83.15%, C4' RMSD of 1.06 Å, and sequence recall of 46.86%, which outperforms the existing methods. Moreover, EM2NA is applied to build the DNA/RNA structures with 10 to 5347 nt from an EMDB-wide data set of 263 unmodeled raw maps, demonstrating its ability in the blind model building of DNA/RNA from cryo-EM maps. EM2NA is fast and can normally build a DNA/RNA structure of  <500 nt within 10 minutes.

Linker-Mediated Inactivation of the SAM-II Domain in the Tandem SAM-II/SAM-V Riboswitch

Tandem SAM-II/SAM-V riboswitch belongs to a class of riboswitches found in the marine bacterium 'Candidatus Pelagibacter ubique'. Previous studies have demonstrated that these riboswitches have the potential for digital modulation of gene expression at both the transcriptional and translational levels. In this study, we investigate the conformational changes in the tandem SAM-II/SAM-V riboswitch binding to S-adenosylmethionine (SAM) using selective 2'-hydroxyl acylation analyzed by the primer extension (SHAPE) assay, small-angle X-ray scattering (SAXS), and oligos depressing probing. Our findings reveal that the linker between SAM-II/SAM-V aptamers blocks the SAM response of the SAM-II domain. This result proposes a new mechanism for gene expression regulation, where the ligand-binding functions of tandem riboswitches can be selectively masked or released through a linker.

Riboswitch Mechanisms for Regulation of P1 Helix Stability

Riboswitches are highly structured RNA regulators of gene expression. Although found in all three domains of life, they are particularly abundant and widespread in bacteria, including many human pathogens, thus making them an attractive target for antimicrobial development. Moreover, the functional versatility of riboswitches to recognize a myriad of ligands, including ions, amino acids, and diverse small-molecule metabolites, has enabled the generation of synthetic aptamers that have been used as molecular probes, sensors, and regulatory RNA devices. Generally speaking, a riboswitch consists of a ligand-sensing aptamer domain and an expression platform, whose genetic control is achieved through the formation of mutually exclusive secondary structures in a ligand-dependent manner. For most riboswitches, this involves formation of the aptamer's P1 helix and the regulation of its stability, whose competing structure turns gene expression ON/OFF at the level of transcription or translation. Structural knowledge of the conformational changes involving the P1 regulatory helix, therefore, is essential in understanding the structural basis for ligand-induced conformational switching. This review provides a summary of riboswitch cases for which ligand-free and ligand-bound structures have been determined. Comparative analyses of these structures illustrate the uniqueness of these riboswitches, not only in ligand sensing but also in the various structural mechanisms used to achieve the same end of regulating switch helix stability. In all cases, the ligand stabilizes the P1 helix primarily through coaxial stacking interactions that promote helical continuity.

An RNA-centric view of transcription and genome organization

Foundational models of transcriptional regulation involve the assembly of protein complexes at DNA elements associated with specific genes. These assemblies, which can include transcription factors, cofactors, RNA polymerase, and various chromatin regulators, form dynamic spatial compartments that contribute to both gene regulation and local genome architecture. This DNA-protein-centric view has been modified with recent evidence that RNA molecules have important roles to play in gene regulation and genome structure. Here, we discuss evidence that gene regulation by RNA occurs at multiple levels that include assembly of transcriptional complexes and genome compartments, feedback regulation of active genes, silencing of genes, and control of protein kinases. We thus provide an RNA-centric view of transcriptional regulation that must reside alongside the more traditional DNA-protein-centric perspectives on gene regulation and genome architecture.

Challenges, advances, and opportunities in RNA structural biology by Cryo-EM

RNAs are remarkably versatile molecules that can fold into intricate three-dimensional (3D) structures to perform diverse cellular and viral functions. Despite their biological importance, relatively few RNA 3D structures have been solved, and our understanding of RNA structure-function relationships remains in its infancy. This limitation partly arises from challenges posed by RNA's complex conformational landscape, characterized by structural flexibility, formation of multiple states, and a propensity to misfold. Recently, cryo-electron microscopy (cryo-EM) has emerged as a powerful tool for the visualization of conformationally dynamic RNA-only 3D structures. However, RNA's characteristics continue to pose challenges. We discuss experimental methods developed to overcome these hurdles, including the engineering of modular modifications that facilitate the visualization of small RNAs, improve particle alignment, and validate structural models.

Identification of RNA structures and their roles in RNA functions

The development of high-throughput RNA structure profiling methods in the past decade has greatly facilitated our ability to map and characterize different aspects of RNA structures transcriptome-wide in cell populations, single cells and single molecules. The resulting high-resolution data have provided insights into the static and dynamic nature of RNA structures, revealing their complexity as they perform their respective functions in the cell. In this Review, we discuss recent technical advances in the determination of RNA structures, and the roles of RNA structures in RNA biogenesis and functions, including in transcription, processing, translation, degradation, localization and RNA structure-dependent condensates. We also discuss the current understanding of how RNA structures could guide drug design for treating genetic diseases and battling pathogenic viruses, and highlight existing challenges and future directions in RNA structure research.

Structural and biophysical dissection of RNA conformational ensembles

RNA's ability to form and interconvert between multiple secondary and tertiary structures is critical to its functional versatility and the traditional view of RNA structures as static entities has shifted towards understanding them as dynamic conformational ensembles. In this review we discuss RNA structural ensembles and their dynamics, highlighting the concept of conformational energy landscapes as a unifying framework for understanding RNA processes such as folding, misfolding, conformational changes, and complex formation. Ongoing advancements in cryo-electron microscopy and chemical probing techniques are significantly enhancing our ability to investigate multiple structures adopted by conformationally dynamic RNAs, while traditional methods such as nuclear magnetic resonance spectroscopy continue to play a crucial role in providing high-resolution, quantitative spatial and temporal information. We discuss how these methods, when used synergistically, can provide a comprehensive understanding of RNA conformational ensembles, offering new insights into their regulatory functions.

A systematic search for RNA structural switches across the human transcriptome

RNA structural switches are key regulators of gene expression in bacteria, but their characterization in Metazoa remains limited. Here, we present SwitchSeeker, a comprehensive computational and experimental approach for systematic identification of functional RNA structural switches. We applied SwitchSeeker to the human transcriptome and identified 245 putative RNA switches. To validate our approach, we characterized a previously unknown RNA switch in the 3' untranslated region of the RORC (RAR-related orphan receptor C) transcript. In vivo dimethyl sulfate (DMS) mutational profiling with sequencing (DMS-MaPseq), coupled with cryogenic electron microscopy, confirmed its existence as two alternative structural conformations. Furthermore, we used genome-scale CRISPR screens to identify trans factors that regulate gene expression through this RNA structural switch. We found that nonsense-mediated messenger RNA decay acts on this element in a conformation-specific manner. SwitchSeeker provides an unbiased, experimentally driven method for discovering RNA structural switches that shape the eukaryotic gene expression landscape.

Discovery and Quantification of Long-Range RNA Base Pairs in Coronavirus Genomes with SEARCH-MaP and SEISMIC-RNA

RNA molecules perform a diversity of essential functions for which their linear sequences must fold into higher-order structures. Techniques including crystallography and cryogenic electron microscopy have revealed 3D structures of ribosomal, transfer, and other well-structured RNAs; while chemical probing with sequencing facilitates secondary structure modeling of any RNAs of interest, even within cells. Ongoing efforts continue increasing the accuracy, resolution, and ability to distinguish coexisting alternative structures. However, no method can discover and quantify alternative structures with base pairs spanning arbitrarily long distances - an obstacle for studying viral, messenger, and long noncoding RNAs, which may form long-range base pairs. Here, we introduce the method of Structure Ensemble Ablation by Reverse Complement Hybridization with Mutational Profiling (SEARCH-MaP) and software for Structure Ensemble Inference by Sequencing, Mutation Identification, and Clustering of RNA (SEISMIC-RNA). We use SEARCH-MaP and SEISMIC-RNA to discover that the frameshift stimulating element of SARS coronavirus 2 base-pairs with another element 1 kilobase downstream in nearly half of RNA molecules, and that this structure competes with a pseudoknot that stimulates ribosomal frameshifting. Moreover, we identify long-range base pairs involving the frameshift stimulating element in other coronaviruses including SARS coronavirus 1 and transmissible gastroenteritis virus, and model the full genomic secondary structure of the latter. These findings suggest that long-range base pairs are common in coronaviruses and may regulate ribosomal frameshifting, which is essential for viral RNA synthesis. We anticipate that SEARCH-MaP will enable solving many RNA structure ensembles that have eluded characterization, thereby enhancing our general understanding of RNA structures and their functions. SEISMIC-RNA, software for analyzing mutational profiling data at any scale, could power future studies on RNA structure and is available on GitHub and the Python Package Index.

Discovery and Quantification of Long-Range RNA Base Pairs in Coronavirus Genomes with SEARCH-MaP and SEISMIC-RNA

RNA molecules perform a diversity of essential functions for which their linear sequences must fold into higher-order structures. Techniques including crystallography and cryogenic electron microscopy have revealed 3D structures of ribosomal, transfer, and other well-structured RNAs; while chemical probing with sequencing facilitates secondary structure modeling of any RNAs of interest, even within cells. Ongoing efforts continue increasing the accuracy, resolution, and ability to distinguish coexisting alternative structures. However, no method can discover and quantify alternative structures with base pairs spanning arbitrarily long distances - an obstacle for studying viral, messenger, and long noncoding RNAs, which may form long-range base pairs. Here, we introduce the method of Structure Ensemble Ablation by Reverse Complement Hybridization with Mutational Profiling (SEARCH-MaP) and software for Structure Ensemble Inference by Sequencing, Mutation Identification, and Clustering of RNA (SEISMIC-RNA). We use SEARCH-MaP and SEISMIC-RNA to discover that the frameshift stimulating element of SARS coronavirus 2 base-pairs with another element 1 kilobase downstream in nearly half of RNA molecules, and that this structure competes with a pseudoknot that stimulates ribosomal frameshifting. Moreover, we identify long-range base pairs involving the frameshift stimulating element in other coronaviruses including SARS coronavirus 1 and transmissible gastroenteritis virus, and model the full genomic secondary structure of the latter. These findings suggest that long-range base pairs are common in coronaviruses and may regulate ribosomal frameshifting, which is essential for viral RNA synthesis. We anticipate that SEARCH-MaP will enable solving many RNA structure ensembles that have eluded characterization, thereby enhancing our general understanding of RNA structures and their functions. SEISMIC-RNA, software for analyzing mutational profiling data at any scale, could power future studies on RNA structure and is available on GitHub and the Python Package Index.

FRET-guided modeling of nucleic acids

The functional diversity of RNAs is encoded in their innate conformational heterogeneity. The combination of single-molecule spectroscopy and computational modeling offers new attractive opportunities to map structural transitions within nucleic acid ensembles. Here, we describe a framework to harmonize single-molecule Förster resonance energy transfer (FRET) measurements with molecular dynamics simulations and de novo structure prediction. Using either all-atom or implicit fluorophore modeling, we recreate FRET experiments in silico, visualize the underlying structural dynamics and quantify the reaction coordinates. Using multiple accessible-contact volumes as a post hoc scoring method for fragment assembly in Rosetta, we demonstrate that FRET can be used to filter a de novo RNA structure prediction ensemble by refuting models that are not compatible with in vitro FRET measurement. We benchmark our FRET-assisted modeling approach on double-labeled DNA strands and validate it against an intrinsically dynamic manganese(II)-binding riboswitch. We show that a FRET coordinate describing the assembly of a four-way junction allows our pipeline to recapitulate the global fold of the riboswitch displayed by the crystal structure. We conclude that computational fluorescence spectroscopy facilitates the interpretability of dynamic structural ensembles and improves the mechanistic understanding of nucleic acid interactions.

Determining Protein Secondary Structures in Heterogeneous Medium-Resolution Cryo-EM Images Using CryoSSESeg

While the acquisition of cryo-electron microscopy (cryo-EM) at near-atomic resolution is becoming more prevalent, a considerable number of density maps are still resolved only at intermediate resolutions (5-10 Å). Due to the large variation in quality among these medium-resolution density maps, extracting structural information from them remains a challenging task. This study introduces a convolutional neural network (CNN)-based framework, cryoSSESeg, to determine the organization of protein secondary structure elements in medium-resolution cryo-EM images. CryoSSESeg is trained on approximately 1300 protein chains derived from around 500 experimental cryo-EM density maps of varied quality. It demonstrates strong performance with residue-level F 1 scores of 0.76 for helix detection and 0.60 for β-sheet detection on average across a set of testing chains. In comparison to traditional image processing tools like SSETracer, which demand significant manual intervention and preprocessing steps, cryoSSESeg demonstrates comparable or superior performance. Additionally, it demonstrates competitive performance alongside another deep learning-based model, Emap2sec. Furthermore, this study underscores the importance of secondary structure quality, particularly adherence to expected shapes, in detection performance, emphasizing the necessity for careful evaluation of the data quality.

Scaffold-enabled high-resolution cryo-EM structure determination of RNA

Cryo-EM structure determination of protein-free RNAs has remained difficult with most attempts yielding low to moderate resolution and lacking nucleotide-level detail. These difficulties are compounded for small RNAs as cryo-EM is inherently more difficult for lower molecular weight macromolecules. Here we present a strategy for fusing small RNAs to a group II intron that yields high resolution structures of the appended RNA, which we demonstrate with the 86-nucleotide thiamine pyrophosphate (TPP) riboswitch, and visualizing the riboswitch ligand binding pocket at 2.5 Å resolution. We also determined the structure of the ligand-free apo state and observe that the aptamer domain of the riboswitch undergoes a large-scale conformational change upon ligand binding, illustrating how small molecule binding to an RNA can induce large effects on gene expression. This study both sets a new standard for cryo-EM riboswitch visualization and offers a versatile strategy applicable to a broad range of small to moderate-sized RNAs, which were previously intractable for high-resolution cryo-EM studies.

Decoding the Structural Diversity: A New Horizon in Antimicrobial Prospecting and Mechanistic Investigation

The escalating crisis of antimicrobial resistance (AMR) underscores the urgent need for novel antimicrobials. One promising strategy is the exploration of structural diversity, as diverse structures can lead to diverse biological activities and mechanisms of action. This review delves into the role of structural diversity in antimicrobial discovery, highlighting its influence on factors such as target selectivity, binding affinity, pharmacokinetic properties, and the ability to overcome resistance mechanisms. We discuss various approaches for exploring structural diversity, including combinatorial chemistry, diversity-oriented synthesis, and natural product screening, and provide an overview of the common mechanisms of action of antimicrobials. We also describe techniques for investigating these mechanisms, such as genomics, proteomics, and structural biology. Despite significant progress, several challenges remain, including the synthesis of diverse compound libraries, the identification of active compounds, the elucidation of complex mechanisms of action, the emergence of AMR, and the translation of laboratory discoveries to clinical applications. However, emerging trends and technologies, such as artificial intelligence, high-throughput screening, next-generation sequencing, and open-source drug discovery, offer new avenues to overcome these challenges. Looking ahead, we envisage an exciting future for structural diversity-oriented antimicrobial discovery, with opportunities for expanding the chemical space, harnessing the power of nature, deepening our understanding of mechanisms of action, and moving toward personalized medicine and collaborative drug discovery. As we face the continued challenge of AMR, the exploration of structural diversity will be crucial in our search for new and effective antimicrobials.

Structure of the SARS-CoV-2 Frameshift Stimulatory Element with an Upstream Multibranch Loop

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) frameshift stimulatory element (FSE) is necessary for programmed -1 ribosomal frameshifting (-1 PRF) and optimized viral efficacy. The FSE has an abundance of context-dependent alternate conformations, but two of the structures most crucial to -1 PRF are an attenuator hairpin and a three-stem H-type pseudoknot structure. A crystal structure of the pseudoknot alone features three RNA stems in a helically stacked linear structure, whereas a 6.9 Å cryo-EM structure including the upstream heptameric slippery site resulted in a bend between two stems. Our previous research alluded to an extended upstream multibranch loop that includes both the attenuator hairpin and the slippery site-a conformation not previously modeled. We aim to provide further context to the SARS-CoV-2 FSE via computational and medium resolution cryo-EM approaches, by presenting a 6.1 Å cryo-EM structure featuring a linear pseudoknot structure and a dynamic upstream multibranch loop.

Conserved structures and dynamics in 5'-proximal regions of Betacoronavirus RNA genomes

Betacoronaviruses are a genus within the Coronaviridae family of RNA viruses. They are capable of infecting vertebrates and causing epidemics as well as global pandemics in humans. Mitigating the threat posed by Betacoronaviruses requires an understanding of their molecular diversity. The development of novel antivirals hinges on understanding the key regulatory elements within the viral RNA genomes, in particular the 5'-proximal region, which is pivotal for viral protein synthesis. Using a combination of cryo-electron microscopy, atomic force microscopy, chemical probing, and computational modeling, we determined the structures of 5'-proximal regions in RNA genomes of Betacoronaviruses from four subgenera: OC43-CoV, SARS-CoV-2, MERS-CoV, and Rousettus bat-CoV. We obtained cryo-electron microscopy maps and determined atomic-resolution models for the stem-loop-5 (SL5) region at the translation start site and found that despite low sequence similarity and variable length of the helical elements it exhibits a remarkable structural conservation. Atomic force microscopy imaging revealed a common domain organization and a dynamic arrangement of structural elements connected with flexible linkers across all four Betacoronavirus subgenera. Together, these results reveal common features of a critical regulatory region shared between different Betacoronavirus RNA genomes, which may allow targeting of these RNAs by broad-spectrum antiviral therapeutics.

Tertiary folds of the SL5 RNA from the 5' proximal region of SARS-CoV-2 and related coronaviruses

Coronavirus genomes sequester their start codons within stem-loop 5 (SL5), a structured, 5' genomic RNA element. In most alpha- and betacoronaviruses, the secondary structure of SL5 is predicted to contain a four-way junction of helical stems, some of which are capped with UUYYGU hexaloops. Here, using cryogenic electron microscopy (cryo-EM) and computational modeling with biochemically determined secondary structures, we present three-dimensional structures of SL5 from six coronaviruses. The SL5 domain of betacoronavirus severe-acute-respiratory-syndrome-related coronavirus 2 (SARS-CoV-2), resolved at 4.7 Å resolution, exhibits a T-shaped structure, with its UUYYGU hexaloops at opposing ends of a coaxial stack, the T's "arms." Further analysis of SL5 domains from SARS-CoV-1 and MERS (7.1 and 6.4 to 6.9 Å resolution, respectively) indicate that the junction geometry and inter-hexaloop distances are conserved features across these human-infecting betacoronaviruses. The MERS SL5 domain displays an additional tertiary interaction, which is also observed in the non-human-infecting betacoronavirus BtCoV-HKU5 (5.9 to 8.0 Å resolution). SL5s from human-infecting alphacoronaviruses, HCoV-229E and HCoV-NL63 (6.5 and 8.4 to 9.0 Å resolution, respectively), exhibit the same coaxial stacks, including the UUYYGU-capped arms, but with a phylogenetically distinct crossing angle, an X-shape. As such, all SL5 domains studied herein fold into stable tertiary structures with cross-genus similarities and notable differences, with implications for potential protein-binding modes and therapeutic targets.

Flipping the script: Understanding riboswitches from an alternative perspective

Riboswitches are broadly distributed regulatory elements most frequently found in the 5'-leader sequence of bacterial mRNAs that regulate gene expression in response to the binding of a small molecule effector. The occupancy status of the ligand-binding aptamer domain manipulates downstream information in the message that instructs the expression machinery. Currently, there are over 55 validated riboswitch classes, where each class is defined based on the identity of the ligand it binds and/or sequence and structure conservation patterns within the aptamer domain. This classification reflects an "aptamer-centric" perspective that dominates our understanding of riboswitches. In this review, we propose a conceptual framework that groups riboswitches based on the mechanism by which RNA manipulates information directly instructing the expression machinery. This scheme does not replace the established aptamer domain-based classification of riboswitches but rather serves to facilitate hypothesis-driven investigation of riboswitch regulatory mechanisms. Based on current bioinformatic, structural, and biochemical studies of a broad spectrum of riboswitches, we propose three major mechanistic groups: (1) "direct occlusion", (2) "interdomain docking", and (3) "strand exchange". We discuss the defining features of each group, present representative examples of riboswitches from each group, and illustrate how these RNAs couple small molecule binding to gene regulation. While mechanistic studies of the occlusion and docking groups have yielded compelling models for how these riboswitches function, much less is known about strand exchange processes. To conclude, we outline the limitations of our mechanism-based conceptual framework and discuss how critical information within riboswitch expression platforms can inform gene regulation.

All-atom RNA structure determination from cryo-EM maps

Many methods exist for determining protein structures from cryogenic electron microscopy maps, but this remains challenging for RNA structures. Here we developed EMRNA, a method for accurate, automated determination of full-length all-atom RNA structures from cryogenic electron microscopy maps. EMRNA integrates deep learning-based detection of nucleotides, three-dimensional backbone tracing and scoring with consideration of sequence and secondary structure information, and full-atom construction of the RNA structure. We validated EMRNA on 140 diverse RNA maps ranging from 37 to 423 nt at 2.0-6.0 Å resolutions, and compared EMRNA with auto-DRRAFTER, phenix.map_to_model and CryoREAD on a set of 71 cases. EMRNA achieves a median accuracy of 2.36 Å root mean square deviation and 0.86 TM-score for full-length RNA structures, compared with 6.66 Å and 0.58 for auto-DRRAFTER. EMRNA also obtains a high residue coverage and sequence match of 93.30% and 95.30% in the built models, compared with 58.20% and 42.20% for phenix.map_to_model and 56.45% and 52.3% for CryoREAD. EMRNA is fast and can build an RNA structure of 100 nt within 3 min.

Minimization of the E. coli ribosome, aided and optimized by community science

The ribosome is a ribonucleoprotein complex found in all domains of life. Its role is to catalyze protein synthesis, the messenger RNA (mRNA)-templated formation of amide bonds between α-amino acid monomers. Amide bond formation occurs within a highly conserved region of the large ribosomal subunit known as the peptidyl transferase center (PTC). Here we describe the step-wise design and characterization of mini-PTC 1.1, a 284-nucleotide RNA that recapitulates many essential features of the Escherichia coli PTC. Mini-PTC 1.1 folds into a PTC-like structure under physiological conditions, even in the absence of r-proteins, and engages small molecule analogs of A- and P-site tRNAs. The sequence of mini-PTC 1.1 differs from the wild type E. coli ribosome at 12 nucleotides that were installed by a cohort of citizen scientists using the on-line video game Eterna. These base changes improve both the secondary structure and tertiary folding of mini-PTC 1.1 as well as its ability to bind small molecule substrate analogs. Here, the combined input from Eterna citizen-scientists and RNA structural analysis provides a robust workflow for the design of a minimal PTC that recapitulates many features of an intact ribosome.

Cryo-EM structure and functional landscape of an RNA polymerase ribozyme

The emergence of an RNA replicase capable of self-replication is considered an important stage in the origin of life. RNA polymerase ribozymes (PR) - including a variant that uses trinucleotide triphosphates (triplets) as substrates - have been created by in vitro evolution and are the closest functional analogues of the replicase, but the structural basis for their function is poorly understood. Here we use single-particle cryogenic electron microscopy (cryo-EM) and high-throughput mutation analysis to obtain the structure of a triplet polymerase ribozyme (TPR) apoenzyme and map its functional landscape. The cryo-EM structure at 5-Å resolution reveals the TPR as an RNA heterodimer comprising a catalytic subunit and a noncatalytic, auxiliary subunit, resembling the shape of a left hand with thumb and fingers at a 70° angle. The two subunits are connected by two distinct kissing-loop (KL) interactions that are essential for polymerase function. Our combined structural and functional data suggest a model for templated RNA synthesis by the TPR holoenzyme, whereby heterodimer formation and KL interactions preorganize the TPR for optimal primer-template duplex binding, triplet substrate discrimination, and templated RNA synthesis. These results provide a better understanding of TPR structure and function and should aid the engineering of more efficient PRs.

RNA target highlights in CASP15: Evaluation of predicted models by structure providers

The first RNA category of the Critical Assessment of Techniques for Structure Prediction competition was only made possible because of the scientists who provided experimental structures to challenge the predictors. In this article, these scientists offer a unique and valuable analysis of both the successes and areas for improvement in the predicted models. All 10 RNA-only targets yielded predictions topologically similar to experimentally determined structures. For one target, experimentalists were able to phase their x-ray diffraction data by molecular replacement, showing a potential application of structure predictions for RNA structural biologists. Recommended areas for improvement include: enhancing the accuracy in local interaction predictions and increased consideration of the experimental conditions such as multimerization, structure determination method, and time along folding pathways. The prediction of RNA-protein complexes remains the most significant challenge. Finally, given the intrinsic flexibility of many RNAs, we propose the consideration of ensemble models.

Tertiary folds of the SL5 RNA from the 5' proximal region of SARS-CoV-2 and related coronaviruses

Coronavirus genomes sequester their start codons within stem-loop 5 (SL5), a structured, 5' genomic RNA element. In most alpha- and betacoronaviruses, the secondary structure of SL5 is predicted to contain a four-way junction of helical stems, some of which are capped with UUYYGU hexaloops. Here, using cryogenic electron microscopy (cryo-EM) and computational modeling with biochemically-determined secondary structures, we present three-dimensional structures of SL5 from six coronaviruses. The SL5 domain of betacoronavirus SARS-CoV-2, resolved at 4.7 Å resolution, exhibits a T-shaped structure, with its UUYYGU hexaloops at opposing ends of a coaxial stack, the T's "arms." Further analysis of SL5 domains from SARS-CoV-1 and MERS (7.1 and 6.4-6.9 Å resolution, respectively) indicate that the junction geometry and inter-hexaloop distances are conserved features across the studied human-infecting betacoronaviruses. The MERS SL5 domain displays an additional tertiary interaction, which is also observed in the non-human-infecting betacoronavirus BtCoV-HKU5 (5.9-8.0 Å resolution). SL5s from human-infecting alphacoronaviruses, HCoV-229E and HCoV-NL63 (6.5 and 8.4-9.0 Å resolution, respectively), exhibit the same coaxial stacks, including the UUYYGU-capped arms, but with a phylogenetically distinct crossing angle, an X-shape. As such, all SL5 domains studied herein fold into stable tertiary structures with cross-genus similarities, with implications for potential protein-binding modes and therapeutic targets.

A generalizable scaffold-based approach for structure determination of RNAs by cryo-EM

Single-particle cryo-electron microscopy (cryo-EM) can reveal the structures of large and often dynamic molecules, but smaller biomolecules (≤50 kDa) remain challenging targets due to their intrinsic low signal to noise ratio. Methods to help resolve small proteins have been applied but development of similar approaches to aid in structural determination of small, structured RNA elements have lagged. Here, we present a scaffold-based approach that we used to recover maps of sub-25 kDa RNA domains to 4.5-5.0 Å. While lacking the detail of true high-resolution maps, these maps are suitable for model building and preliminary structure determination. We demonstrate this method helped faithfully recover the structure of several RNA elements of known structure, and that it promises to be generalized to other RNAs without disturbing their native fold. This approach may streamline the sample preparation process and reduce the optimization required for data collection. This first-generation scaffold approach provides a robust system to aid in RNA structure determination by cryo-EM and lays the groundwork for further scaffold optimization to achieve higher resolution.

CryoREAD: de novo structure modeling for nucleic acids in cryo-EM maps using deep learning

DNA and RNA play fundamental roles in various cellular processes, where their three-dimensional structures provide information critical to understanding the molecular mechanisms of their functions. Although an increasing number of nucleic acid structures and their complexes with proteins are determined by cryogenic electron microscopy (cryo-EM), structure modeling for DNA and RNA remains challenging particularly when the map is determined at a resolution coarser than atomic level. Moreover, computational methods for nucleic acid structure modeling are relatively scarce. Here, we present CryoREAD, a fully automated de novo DNA/RNA atomic structure modeling method using deep learning. CryoREAD identifies phosphate, sugar and base positions in a cryo-EM map using deep learning, which are traced and modeled into a three-dimensional structure. When tested on cryo-EM maps determined at 2.0 to 5.0 Å resolution, CryoREAD built substantially more accurate models than existing methods. We also applied the method to cryo-EM maps of biomolecular complexes in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

Capturing heterogeneous conformers of cobalamin riboswitch by cryo-EM

RNA conformational heterogeneity often hampers its high-resolution structure determination, especially for large and flexible RNAs devoid of stabilizing proteins or ligands. The adenosylcobalamin riboswitch exhibits heterogeneous conformations under 1 mM Mg2+ concentration and ligand binding reduces conformational flexibility. Among all conformers, we determined one apo (5.3 Å) and four holo cryo-electron microscopy structures (overall 3.0-3.5 Å, binding pocket 2.9-3.2 Å). The holo dimers exhibit global motions of helical twisting and bending around the dimer interface. A backbone comparison of the apo and holo states reveals a large structural difference in the P6 extension position. The central strand of the binding pocket, junction 6/3, changes from an 'S'- to a 'U'-shaped conformation to accommodate ligand. Furthermore, the binding pocket can partially form under 1 mM Mg2+ and fully form under 10 mM Mg2+ within the bound-like structure in the absence of ligand. Our results not only demonstrate the stabilizing ligand-induced conformational changes in and around the binding pocket but may also provide further insight into the role of the P6 extension in ligand binding and selectivity.

Hepatitis B Virus Epsilon (ε) RNA Element: Dynamic Regulator of Viral Replication and Attractive Therapeutic Target

Hepatitis B virus (HBV) chronically infects millions of people worldwide, which underscores the importance of discovering and designing novel anti-HBV therapeutics to complement current treatment strategies. An underexploited but attractive therapeutic target is ε, a cis-acting regulatory stem-loop RNA situated within the HBV pregenomic RNA (pgRNA). The binding of ε to the viral polymerase protein (P) is pivotal, as it triggers the packaging of pgRNA and P, as well as the reverse transcription of the viral genome. Consequently, small molecules capable of disrupting this interaction hold the potential to inhibit the early stages of HBV replication. The rational design of such ligands necessitates high-resolution structural information for the ε-P complex or its individual components. While these data are currently unavailable for P, our recent structural elucidation of ε through solution nuclear magnetic resonance spectroscopy marks a significant advancement in this area. In this review, we provide a brief overview of HBV replication and some of the therapeutic strategies to combat chronic HBV infection. These descriptions are intended to contextualize our recent experimental efforts to characterize ε and identify ε-targeting ligands, with the ultimate goal of developing novel anti-HBV therapeutics.

Advances, Applications, and Perspectives in Small-Angle X-ray Scattering of RNA

RNAs exhibit a plethora of functions far beyond transmitting genetic information. Often, RNA functions are entailed in their structure, be it as a regulatory switch, protein binding site, or providing catalytic activity. Structural information is a prerequisite for a full understanding of RNA-regulatory mechanisms. Owing to the inherent dynamics, size, and instability of RNA, its structure determination remains challenging. Methods such as NMR spectroscopy, X-ray crystallography, and cryo-electron microscopy can provide high-resolution structures; however, their limitations make structure determination, even for small RNAs, cumbersome, if at all possible. Although at a low resolution, small-angle X-ray scattering (SAXS) has proven valuable in advancing structure determination of RNAs as a complementary method, which is also applicable to large-sized RNAs. Here, we review the technological and methodological advancements of RNA SAXS. We provide examples of the powerful inclusion of SAXS in structural biology and discuss possible future applications to large RNAs.

RNA structure determination: From 2D to 3D

RNA molecules serve a wide range of functions that are closely linked to their structures. The basic structural units of RNA consist of single- and double-stranded regions. In order to carry out advanced functions such as catalysis and ligand binding, certain types of RNAs can adopt higher-order structures. The analysis of RNA structures has progressed alongside advancements in structural biology techniques, but it comes with its own set of challenges and corresponding solutions. In this review, we will discuss recent advances in RNA structure analysis techniques, including structural probing methods, X-ray crystallography, nuclear magnetic resonance, cryo-electron microscopy, and small-angle X-ray scattering. Often, a combination of multiple techniques is employed for the integrated analysis of RNA structures. We also survey important RNA structures that have been recently determined using various techniques.

The diverse structural modes of tRNA binding and recognition

tRNAs are short noncoding RNAs responsible for decoding mRNA codon triplets, delivering correct amino acids to the ribosome, and mediating polypeptide chain formation. Due to their key roles during translation, tRNAs have a highly conserved shape and large sets of tRNAs are present in all living organisms. Regardless of sequence variability, all tRNAs fold into a relatively rigid three-dimensional L-shaped structure. The conserved tertiary organization of canonical tRNA arises through the formation of two orthogonal helices, consisting of the acceptor and anticodon domains. Both elements fold independently to stabilize the overall structure of tRNAs through intramolecular interactions between the D- and T-arm. During tRNA maturation, different modifying enzymes posttranscriptionally attach chemical groups to specific nucleotides, which not only affect translation elongation rates but also restrict local folding processes and confer local flexibility when required. The characteristic structural features of tRNAs are also employed by various maturation factors and modification enzymes to assure the selection, recognition, and positioning of specific sites within the substrate tRNAs. The cellular functional repertoire of tRNAs continues to extend well beyond their role in translation, partly, due to the expanding pool of tRNA-derived fragments. Here, we aim to summarize the most recent developments in the field to understand how three-dimensional structure affects the canonical and noncanonical functions of tRNA.

A Generalizable Scaffold-Based Approach for Structure Determination of RNAs by Cryo-EM

Single-particle cryo-electron microscopy (cryo-EM) can reveal the structures of large and often dynamic molecules, but smaller biomolecules remain challenging targets due to their intrinsic low signal to noise ratio. Methods to resolve small proteins have been applied but development of similar approaches for small structured RNA elements have lagged. Here, we present a scaffold-based approach that we used to recover maps of sub-25 kDa RNA domains to 4.5 - 5.0 Å. While lacking the detail of true high-resolution maps, these are suitable for model building and preliminary structure determination. We demonstrate this method faithfully recovers the structure of several RNA elements of known structure, and it promises to be generalized to other RNAs without disturbing their native fold. This approach may streamline the sample preparation process and reduce the optimization required for data collection. This first-generation scaffold approach provides a system for RNA structure determination by cryo-EM and lays the groundwork for further scaffold optimization to achieve higher resolution.

Crystal structure of Escherichia coli thiamine pyrophosphate-sensing riboswitch in the apo state

The thiamine pyrophosphate (TPP)-sensing riboswitch is one of the earliest discovered and most widespread riboswitches. Numerous structural studies have been reported for this riboswitch bound with various ligands. However, the ligand-free (apo) structure remains unknown. Here, we report a 3.1 Å resolution crystal structure of Escherichia coli TPP riboswitch in the apo state, which exhibits an extended, Y-shaped conformation further supported by small-angle X-ray scattering data and driven molecular dynamics simulations. The loss of ligand interactions results in helical uncoiling of P5 and disruption of the key tertiary interaction between the sensory domains. Opening of the aptamer propagates to the gene-regulatory P1 helix and generates the key conformational flexibility needed for the switching behavior. Much of the ligand-binding site at the three-way junction is unaltered, thereby maintaining a partially preformed pocket. Together, these results paint a dynamic picture of the ligand-induced conformational changes in TPP riboswitches that confer conditional gene regulation.

Structure, folding and flexibility of co-transcriptional RNA origami

RNA origami is a method for designing RNA nanostructures that can self-assemble through co-transcriptional folding with applications in nanomedicine and synthetic biology. However, to advance the method further, an improved understanding of RNA structural properties and folding principles is required. Here we use cryogenic electron microscopy to study RNA origami sheets and bundles at sub-nanometre resolution revealing structural parameters of kissing-loop and crossover motifs, which are used to improve designs. In RNA bundle designs, we discover a kinetic folding trap that forms during folding and is only released after 10 h. Exploration of the conformational landscape of several RNA designs reveal the flexibility of helices and structural motifs. Finally, sheets and bundles are combined to construct a multidomain satellite shape, which is characterized by individual-particle cryo-electron tomography to reveal the domain flexibility. Together, the study provides a structural basis for future improvements to the design cycle of genetically encoded RNA nanodevices.

Structure-Guided Development of Bivalent Aptamers Blocking SARS-CoV-2 Infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused devastation to human society through its high virulence, infectivity, and genomic mutations, which reduced the efficacy of vaccines. Here, we report the development of aptamers that effectively interfere with SARS-CoV-2 infection by targeting its spike protein, which plays a pivotal role in host cell entry of the virus through interaction with the viral receptor angiotensin-converting enzyme 2 (ACE2). To develop highly effective aptamers and to understand their mechanism in inhibiting viral infection, we determined the three-dimensional (3D) structures of aptamer/receptor-binding domain (RBD) complexes using cryogenic electron microscopy (cryo-EM). Moreover, we developed bivalent aptamers targeting two distinct regions of the RBD in the spike protein that directly interact with ACE2. One aptamer interferes with the binding of ACE2 by blocking the ACE2-binding site in RBD, and the other aptamer allosterically inhibits ACE2 by binding to a distinct face of RBD. Using the 3D structures of aptamer-RBD complexes, we minimized and optimized these aptamers. By combining the optimized aptamers, we developed a bivalent aptamer that showed a stronger inhibitory effect on virus infection than the component aptamers. This study confirms that the structure-based aptamer-design approach has a high potential in developing antiviral drugs against SARS-CoV-2 and other viruses.

Intricate 3D architecture of a DNA mimic of GFP

Numerous studies have shown how RNA molecules can adopt elaborate three-dimensional (3D) architectures1-3. By contrast, whether DNA can self-assemble into complex 3D folds capable of sophisticated biochemistry, independent of protein or RNA partners, has remained mysterious. Lettuce is an in vitro-evolved DNA molecule that binds and activates4 conditional fluorophores derived from GFP. To extend previous structural studies5,6 of fluorogenic RNAs, GFP and other fluorescent proteins7 to DNA, we characterize Lettuce-fluorophore complexes by X-ray crystallography and cryogenic electron microscopy. The results reveal that the 53-nucleotide DNA adopts a four-way junction (4WJ) fold. Instead of the canonical L-shaped or H-shaped structures commonly seen8 in 4WJ RNAs, the four stems of Lettuce form two coaxial stacks that pack co-linearly to form a central G-quadruplex in which the fluorophore binds. This fold is stabilized by stacking, extensive nucleobase hydrogen bonding-including through unusual diagonally stacked bases that bridge successive tiers of the main coaxial stacks of the DNA-and coordination of monovalent and divalent cations. Overall, the structure is more compact than many RNAs of comparable size. Lettuce demonstrates how DNA can form elaborate 3D structures without using RNA-like tertiary interactions and suggests that new principles of nucleic acid organization will be forthcoming from the analysis of complex DNAs.

Nano-DMS-MaP allows isoform-specific RNA structure determination

Genome-wide measurements of RNA structure can be obtained using reagents that react with unpaired bases, leading to adducts that can be identified by mutational profiling on next-generation sequencing machines. One drawback of these experiments is that short sequencing reads can rarely be mapped to specific transcript isoforms. Consequently, information is acquired as a population average in regions that are shared between transcripts, thus blurring the underlying structural landscape. Here, we present nanopore dimethylsulfate mutational profiling (Nano-DMS-MaP)-a method that exploits long-read sequencing to provide isoform-resolved structural information of highly similar RNA molecules. We demonstrate the value of Nano-DMS-MaP by resolving the complex structural landscape of human immunodeficiency virus-1 transcripts in infected cells. We show that unspliced and spliced transcripts have distinct structures at the packaging site within the common 5' untranslated region, likely explaining why spliced viral RNAs are excluded from viral particles. Thus, Nano-DMS-MaP is a straightforward method to resolve biologically important transcript-specific RNA structures that were previously hidden in short-read ensemble analyses.

Rock, scissors, paper: How RNA structure informs function

RNA can fold back on itself to adopt a wide range of structures. These range from relatively simple hairpins to intricate 3D folds and can be accompanied by regulatory interactions with both metabolites and macromolecules. The last 50 yr have witnessed elucidation of an astonishing array of RNA structures including transfer RNAs, ribozymes, riboswitches, the ribosome, the spliceosome, and most recently entire RNA structuromes. These advances in RNA structural biology have deepened insight into fundamental biological processes including gene editing, transcription, translation, and structure-based detection and response to temperature and other environmental signals. These discoveries reveal that RNA can be relatively static, like a rock; that it can have catalytic functions of cutting bonds, like scissors; and that it can adopt myriad functional shapes, like paper. We relate these extraordinary discoveries in the biology of RNA structure to the plant way of life. We trace plant-specific discovery of ribozymes and riboswitches, alternative splicing, organellar ribosomes, thermometers, whole-transcriptome structuromes and pan-structuromes, and conclude that plants have a special set of RNA structures that confer unique types of gene regulation. We finish with a consideration of future directions for the RNA structure-function field.

Recognizing the power of machine learning and other computational methods to accelerate progress in small molecule targeting of RNA

RNA structures regulate a wide range of processes in biology and disease, yet small molecule chemical probes or drugs that can modulate these functions are rare. Machine learning and other computational methods are well poised to fill gaps in knowledge and overcome the inherent challenges in RNA targeting, such as the dynamic nature of RNA and the difficulty of obtaining RNA high-resolution structures. Successful tools to date include principal component analysis, linear discriminate analysis, k-nearest neighbor, artificial neural networks, multiple linear regression, and many others. Employment of these tools has revealed critical factors for selective recognition in RNA:small molecule complexes, predictable differences in RNA- and protein-binding ligands, and quantitative structure activity relationships that allow the rational design of small molecules for a given RNA target. Herein we present our perspective on the value of using machine learning and other computation methods to advance RNA:small molecule targeting, including select examples and their validation as well as necessary and promising future directions that will be key to accelerate discoveries in this important field.

RNA levers and switches controlling viral gene expression

RNA viruses are diverse and abundant pathogens that are responsible for numerous human diseases. RNA viruses possess relatively compact genomes and have therefore evolved multiple mechanisms to maximize their coding capacities, often by encoding overlapping reading frames. These reading frames are then decoded by mechanisms such as alternative splicing and ribosomal frameshifting to produce multiple distinct proteins. These solutions are enabled by the ability of the RNA genome to fold into 3D structures that can mimic cellular RNAs, hijack host proteins, and expose or occlude regulatory protein-binding motifs to ultimately control key process in the viral life cycle. We highlight recent findings focusing on less conventional mechanisms of gene expression and new discoveries on the role of RNA structures.

Snapshots of the second-step self-splicing of Tetrahymena ribozyme revealed by cryo-EM

Group I introns are catalytic RNAs that coordinate two consecutive transesterification reactions for self-splicing. To understand how the group I intron promotes catalysis and coordinates self-splicing reactions, we determine the structures of L-16 Tetrahymena ribozyme in complex with a 5'-splice site analog product and a 3'-splice site analog substrate using cryo-EM. We solve six conformations from a single specimen, corresponding to different splicing intermediates after the first ester-transfer reaction. The structures reveal dynamics during self-splicing, including large conformational changes of the internal guide sequence and the J5/4 junction as well as subtle rearrangements of active-site metals and the hydrogen bond formed between the 2'-OH group of A261 and the N2 group of guanosine substrate. These results help complete a detailed structural and mechanistic view of this paradigmatic group I intron undergoing the second step of self-splicing.

Cryo-EM-guided engineering of T-box-tRNA modules with enhanced selectivity and sensitivity in translational regulation

Riboswitches are non-coding RNA elements that play vital roles in regulating gene expression. Their specific ligand-dependent structural reorganization facilitates their use as templates for design of engineered RNA switches for therapeutics, nanotechnology and synthetic biology. T-box riboswitches bind tRNAs to sense aminoacylation and control gene expression via transcription attenuation or translation inhibition. Here we determine the cryo-EM structure of the wild-type Mycobacterium smegmatis ileS T-box in complex with its cognate tRNA ^Ile . This structure shows a very flexible antisequestrator region that tolerates both 3'-OH and 2',3'-cyclic phosphate modification at the 3' end of tRNA ^Ile . Elongation of one helical turn (11-base pair) in both the tRNA acceptor arm and T-box Stem III maintains T-box-tRNA complex formation and increases the selectivity for tRNA 3' end modification. Moreover, elongation of Stem III results in ∼6-fold tighter binding to tRNA, which leads to increased sensitivity of downstream translational regulation indicated by precedent translation. Our results demonstrate that cryo-EM can guide RNA engineering to design improved riboswitch modules for translational regulation, and potentially a variety of additional functions.

Characterization of structures and molecular interactions of RNA and lipid carriers using atomic force microscopy

Ribonucleic acid (RNA) and lipid are essential biomolecules in many biological processes, and hold a great prospect for biomedical applications, such as gene therapy, vaccines and therapeutic drug delivery. The characterization of morphology and intra-/inter-molecular interactions of RNA and lipid molecules is critical for understanding their functioning mechanisms. Atomic force microscopy (AFM) is a sophisticated technique for characterizing biomolecules featured by its piconewton force sensitivity, sub-nanometer spatial resolution, and flexible operation conditions in both air and liquid. The goal of this review is to highlight the representative and outstanding discoveries of the characterization of RNA and lipid molecules through morphology identification, physicochemical property determination and intermolecular force measurements by AFM. The first section introduces the AFM imaging of RNA molecules to obtain high-resolution morphologies and nanostructures in air and liquid, followed by the discussion of employing AFM force spectroscopy in understanding the nanomechanical properties and intra-/inter-molecular interactions of RNA molecules, including RNA-RNA and RNA-biomolecule interactions. The second section focuses on the studies of lipid and RNA encapsulated in lipid carrier (RNA-lipid) by AFM as well as the sample preparation and factors influencing the morphology and structure of lipid/RNA-lipid complexes. Particularly, the nanomechanical properties of lipid and RNA-lipid characterized by nanomechanical imaging and force measurements are discussed. The future perspectives and remaining challenges on the characterization of RNA and lipid offered by the versatile AFM techniques are also discussed. This review provides useful insights on the characterization of RNA and lipids nanostructures along with their molecular interactions, and also enlightens the application of AFM techniques in investigating a broad variety of biomolecules.