Dramatic improvement of crystals of large RNAs by cation replacement and dehydration

RNAvigate: efficient exploration of RNA chemical probing datasets

Chemical probing technologies enable high-throughput examination of diverse structural features of RNA, including local nucleotide flexibility, RNA secondary structure, protein and ligand binding, through-space interaction networks, and multistate structural ensembles. Deep understanding of RNA structure-function relationships typically requires evaluating a system under structure- and function-altering conditions, linking these data with additional information, and visualizing multilayered relationships. Current platforms lack the broad accessibility, flexibility and efficiency needed to iterate on integrative analyses of these diverse, complex data. Here, we share the RNA visualization and graphical analysis toolset RNAvigate, a straightforward and flexible Python library that automatically parses 21 standard file formats (primary sequence annotations, per- and internucleotide data, and secondary and tertiary structures) and outputs 18 plot types. RNAvigate enables efficient exploration of nuanced relationships between multiple layers of RNA structure information and across multiple experimental conditions. Compatibility with Jupyter notebooks enables nonburdensome, reproducible, transparent and organized sharing of multistep analyses and data visualization strategies. RNAvigate simplifies and accelerates discovery and characterization of RNA-centric functions in biology.

Geometric deep learning for the prediction of magnesium-binding sites in RNA structures

Magnesium ions (Mg2+) are essential for the folding, functional expression, and structural stability of RNA molecules. However, predicting Mg2+-binding sites in RNA molecules based solely on RNA structures is still challenging. The molecular surface, characterized by a continuous shape with geometric and chemical properties, is important for RNA modelling and carries essential information for understanding the interactions between RNAs and Mg2+ ions. Here, we propose an approach named RNA-magnesium ion surface interaction fingerprinting (RMSIF), a geometric deep learning-based conceptual framework to predict magnesium ion binding sites in RNA structures. To evaluate the performance of RMSIF, we systematically enumerated decoy Mg2+ ions across a full-space grid within the range of 2 to 10 Å from the RNA molecule and made predictions accordingly. Visualization techniques were used to validate the prediction results and calculate success rates. Comparative assessments against state-of-the-art methods like MetalionRNA, MgNet, and Metal3DRNA revealed that RMSIF achieved superior success rates and accuracy in predicting Mg2+-binding sites. Additionally, in terms of the spatial distribution of Mg2+ ions within the RNA structures, a majority were situated in the deep grooves, while a minority occupied the shallow grooves. Collectively, the conceptual framework developed in this study holds promise for advancing insights into drug design, RNA co-transcriptional folding, and structure prediction.

RNAvigate: Efficient exploration of RNA chemical probing datasets

Chemical probing technologies enable high-throughput examination of diverse structural features of RNA including local nucleotide flexibility, RNA secondary structure, protein- and ligand-binding, through-space interaction networks, and multi-state structural ensembles. Performing these experiments, by themselves, does not directly lead to biological insight. Instead, deep understanding of RNA structure-function relationships typically requires evaluating a system under structure- and function-altering conditions, linking these data with additional information, and visualizing multi-layered relationships. Current platforms lack the broad accessibility, flexibility, and efficiency needed to iterate on integrative analyses of these diverse, complex data. Here, we share the RNA visualization and graphical analysis toolset RNAvigate, a straightforward and flexible Python library. RNAvigate currently automatically parses twenty-one standard file formats (primary sequence annotations, per- and internucleotide data, and secondary and tertiary structures) and outputs eighteen plot types. These features enable efficient exploration of nuanced relationships between chemical probing data, RNA structure, and motif annotations across multiple experimental samples. Compatibility with Jupyter Notebooks enables non-burdensome, reproducible, transparent and organized sharing of multi-step analyses and data visualization strategies. RNAvigate simplifies examination of multi-layered RNA structure information and accelerates discovery and characterization of RNA-centric functions in biology.

Advances in chaperone-assisted RNA crystallography using synthetic antibodies

RNA molecules play essential roles in many biological functions, from gene expression regulation, cellular growth, and metabolism to catalysis. They frequently fold into three-dimensional structures to perform their functions. Therefore, determining RNA structure represents a key step for understanding the structure-function relationships and developing RNA-targeted therapeutics. X-ray crystallography remains a method of choice for determining high-resolution RNA structures, but it has been challenging due to difficulties associated with RNA crystallization and phasing. Several natural and synthetic RNA binding proteins have been used to facilitate RNA crystallography. Having unique properties to help crystal packing and phasing, synthetic antibody fragments, specifically the Fabs, have emerged as promising RNA crystallization chaperones, and so far, over a dozen of RNA structures have been solved using this strategy. Nevertheless, multiple steps in this approach need to be improved, including the recombinant expression of these anti-RNA Fabs, to warrant the full potential of these synthetic Fabs as RNA crystallization chaperones. This review highlights the nuts and bolts and recent advances in the chaperone-assisted RNA crystallography approach, specifically emphasizing the Fab antibody fragments as RNA crystallization chaperones.

Single-Molecule Correlated Chemical Probing: A Revolution in RNA Structure Analysis

RNA molecules convey biological information both in their linear sequence and in their base-paired secondary and tertiary structures. Chemical probing experiments, which involve treating an RNA with a reagent that modifies conformationally dynamic nucleotides, have broadly enabled examination of short- and long-range RNA structure in diverse contexts, including in living cells. For decades, chemical probing experiments have been interpreted in a per-nucleotide way, such that the reactivity measured at each nucleotide reports the average structure at a position over all RNA molecules within a sample. However, there are numerous important cases where per-nucleotide chemical probing falls short, including for RNAs that are bound by proteins, RNAs that form complex higher order structures, and RNAs that sample multiple conformations.Recent experimental and computational innovations have started a revolution in RNA structure analysis by transforming chemical probing into a massively parallel, single-molecule experiment. Enabled by a specialized reverse transcription strategy called mutational profiling (MaP), multiple chemical modification events can be measured within individual RNA molecules. Nucleotides that communicate structurally through direct base pairing or large-scale folding-unfolding transitions will react with chemical probes in a correlated manner, thereby revealing structural complexity hidden to conventional approaches. These single-molecule correlated chemical probing (smCCP) experiments can be interpreted to directly identify nucleotides that base pair (the PAIR-MaP strategy) and to reveal long-range, through-space structural communication (RING-MaP). Correlated probing can also define the thermodynamic populations of complex RNA ensembles (DANCE-MaP). Complex RNA-protein networks can be interrogated by cross-linking proteins to RNA and measuring correlations between cross-linked positions (RNP-MaP).smCCP thus visualizes RNA secondary and higher-order structure with unprecedented accuracy, defining novel structures, RNA-protein interaction networks, time-resolved dynamics, and allosteric structural switches. These strategies are not mutually exclusive; in favorable cases, multiple levels of RNA structure ─ base pairing, through-space structural communication, and equilibrium ensembles ─ can be resolved concurrently. The physical experimentation required for smCCP is profoundly simple, and experiments are readily performed in cells on RNAs of any size, including large noncoding RNAs and mRNAs. Single-molecule correlated chemical probing is paving the way for a new generation of biophysical studies on RNA in living systems.

Cotranscriptional Assembly and Native Purification of Large RNA-RNA Complexes for Structural Analyses

Recent technological developments such as cryogenic electron microscopy (Cryo-EM) and X-ray free electron lasers (XFEL) have significantly expanded the available toolkit to visualize large, complex noncoding RNAs and their complexes. Consequently, the quality of the RNA sample, as measured by its chemical monodispersity and conformational homogeneity, has become the bottleneck that frequently precludes effective structural analyses. Here we describe a general RNA sample preparation protocol that combines cotranscriptional RNA folding and RNA-RNA complex assembly, followed by native purification of stoichiometric complexes. We illustrate and discuss the utility of this versatile method in overcoming RNA misfolding and enabling the structural and mechanistic elucidations of the T-box riboswitch-tRNA complexes.

Potential effects of metal ion induced two-state allostery on the regulatory mechanism of add adenine riboswitch

Riboswitches normally regulate gene expression through structural changes in response to the specific binding of cellular metabolites or metal ions. Taking add adenine riboswitch as an example, we explore the influences of metal ions (especially for K⁺ and Mg²⁺ ions) on the structure and dynamics of riboswitch aptamer (with and without ligand) by using molecular dynamic (MD) simulations. Our results show that a two-state transition marked by the structural deformation at the connection of J12 and P1 (C_J12-P1) is not only related to the binding of cognate ligands, but also strongly coupled with the change of metal ion environments. Moreover, the deformation of the structure at C_J12-P1 can be transmitted to P1 directly connected to the expression platform in multiple ways, which will affect the structure and stability of P1 to varying degrees, and finally change the regulation state of this riboswitch.

Molecular dynamic simulations are employed to assess the influence of metal ions on riboswitch structure and dynamics, suggesting a conformational control of riboswitch aptamers by metal ions before ligand binding.

tRNA Fusion to Streamline RNA Structure Determination: Case Studies in Probing Aminoacyl-tRNA Sensing Mechanisms by the T-Box Riboswitch

RNAs are prone to misfolding and are often more challenging to crystallize and phase than proteins. Here, we demonstrate that tRNA fusion can streamline the crystallization and structure determination of target RNA molecules. This strategy was applied to the T-box riboswitch system to capture a dynamic interaction between the tRNA 3′-UCCA tail and the T-box antiterminator, which senses aminoacylation. We fused the T-box antiterminator domain to the tRNA anticodon arm to capture the intended interaction through crystal packing. This approach drastically improved the probability of crystallization and successful phasing. Multiple structure snapshots captured the antiterminator loop in an open conformation with some resemblance to that observed in the recent co-crystal structures of the full-length T box riboswitch–tRNA complex, which contrasts the resting, closed conformation antiterminator observed in an earlier NMR study. The anticipated tRNA acceptor–antiterminator interaction was captured in a low-resolution crystal structure. These structures combined with our previous success using prohead RNA–tRNA fusions demonstrates tRNA fusion is a powerful method in RNA structure determination.

Discovery of a large-scale, cell-state-responsive allosteric switch in the 7SK RNA using DANCE-MaP

7SK is a conserved noncoding RNA that regulates transcription by sequestering the transcription factor P-TEFb. 7SK function entails complex changes in RNA structure, but characterizing RNA dynamics in cells remains an unsolved challenge. We developed a single-molecule chemical probing strategy, DANCE-MaP (deconvolution and annotation of ribonucleic conformational ensembles), that defines per-nucleotide reactivity, direct base pairing interactions, tertiary interactions, and thermodynamic populations for each state in RNA structural ensembles from a single experiment. DANCE-MaP reveals that 7SK RNA encodes a large-scale structural switch that couples dissolution of the P-TEFb binding site to structural remodeling at distal release factor binding sites. The 7SK structural equilibrium shifts in response to cell growth and stress and can be targeted to modulate expression of P-TEFbresponsive genes. Our study reveals that RNA structural dynamics underlie 7SK function as an integrator of diverse cellular signals to control transcription and establishes the power of DANCE-MaP to define RNA dynamics in cells.

Rational engineering enables co-crystallization and structural determination of the HIV-1 matrix-tRNA complex

Host tRNAs specifically interact with the matrix domain (MA) of HIV-1 major structural polyprotein, Gag, to control its membrane localization and virion assembly. In this protocol, we describe the purification and engineering of HIV-1 MA and tRNA, and the co-crystallization and structure determination of the complex using X-ray crystallography. Rational engineering of the tRNA surface created tRNA-tRNA packing contacts that drove the formation of diffraction-quality co-crystals. This protocol can be adapted to solve other ribonucleoprotein complex structures containing structured RNAs. For complete details on the use and execution of this protocol, please refer to Bou-Nader et al. (2021).

CoCoNet-boosting RNA contact prediction by convolutional neural networks

Co-evolutionary models such as direct coupling analysis (DCA) in combination with machine learning (ML) techniques based on deep neural networks are able to predict accurate protein contact or distance maps. Such information can be used as constraints in structure prediction and massively increase prediction accuracy. Unfortunately, the same ML methods cannot readily be applied to RNA as they rely on large structural datasets only available for proteins. Here, we demonstrate how the available smaller data for RNA can be used to improve prediction of RNA contact maps. We introduce an algorithm called CoCoNet that is based on a combination of a Coevolutionary model and a shallow Convolutional Neural Network. Despite its simplicity and the small number of trained parameters, the method boosts the positive predictive value (PPV) of predicted contacts by about 70% with respect to DCA as tested by cross-validation of about eighty RNA structures. However, the direct inclusion of the CoCoNet contacts in 3D modeling tools does not result in a proportional increase of the 3D RNA structure prediction accuracy. Therefore, we suggest that the field develops, in addition to contact PPV, metrics which estimate the expected impact for 3D structure modeling tools better. CoCoNet is freely available and can be found at https://github.com/KIT-MBS/coconet.

Predicting RNA Secondary Structure Using In Vitro and In Vivo Data

The new flow of high-throughput RNA secondary structure data coming from different techniques allowed the further development of machine learning approaches. We developed CROSS and CROSSalive, two algorithms trained on experimental data able to predict the RNA secondary structure propensity both in vitro and in vivo. Since the in vivo folding of RNA molecules depends on multiple factors due to the cellular crowded environment, prediction is a complex problem that needs additional calculations for the interaction with proteins and other molecules. In the following chapter, we will describe the differences in predicting RNA secondary structure propensity using experimental data as input for an Artificial Neural Network (ANN) in vitro and in vivo.

Structures of artificially designed discrete RNA nanoarchitectures at near-atomic resolution

Although advances in nanotechnology have enabled the construction of complex and functional synthetic nucleic acid–based nanoarchitectures, high-resolution discrete structures are lacking because of the difficulty in obtaining good diffracting crystals. Here, we report the design and construction of RNA nanostructures based on homooligomerizable one-stranded tiles for x-ray crystallographic determination. We solved three structures to near-atomic resolution: a 2D parallelogram, a 3D nanobracelet unexpectedly formed from an RNA designed for a nanocage, and, eventually, a bona fide 3D nanocage designed with the guidance of the two previous structures. Structural details of their constituent motifs, such as kissing loops, branched kissing loops, and T-junctions, that resemble natural RNA motifs and resisted x-ray determination are revealed, providing insights into those natural motifs. This work unveils the largely unexplored potential of crystallography in gaining high-resolution feedback for nanoarchitectural design and suggests a route to investigate RNA motif structures by configuring them into nanoarchitectures.

Effect of Sequence on the Interactions of Divalent Cations with M-Box Riboswitches from Mycobacterium tuberculosis and Bacillus subtilis

RNA is highly negatively charged and often acquires complex structures that require the presence of divalent cations. Subtle changes in conformation resulting from changes in sequence can affect the way ions associate with RNA. Riboswitches are RNA molecules that are involved in the control of gene expression in bacteria and are excellent systems for testing the effects of sequence variations on the conformation of RNA because they contain a highly conserved binding pocket but present sequence variability among different organisms. In this work, we have compared the aptamer domain of a proposed M-box riboswitch from Mycobacterium tuberculosis with the aptamer domain of a validated M-box riboswitch from Bacillus subtilis. We have in vitro transcribed and purified wild-type (WT) M-box riboswitches from M. tuberculosis and B. subtilis as well as a variety of mutated aptamers in which regions from one riboswitch have been replaced with regions from the other riboswitch. We have used ultraviolet unfolding experiments and circular dichroism to characterize the interactions of WT and related M-box riboswitches with divalent cations. Our results show that M-box from M. tuberculosis associates with Mg²⁺ and Sr²⁺ in a similar fashion while M-box from B. subtilis discriminates between these two ions and appears to associate better with Mg²⁺. Our overall results show that M-box from M. tuberculosis interacts differently with cations than M-box from B. subtilis and suggest conformational differences between these two riboswitches.

Engineering Crystal Packing in RNA Structures I: Past and Future Strategies for Engineering RNA Packing in Crystals

X-ray crystallography remains a powerful method to gain atomistic insights into the catalytic and regulatory functions of RNA molecules. However, the technique requires the preparation of diffraction-quality crystals. This is often a resource- and time-consuming venture because RNA crystallization is hindered by the conformational heterogeneity of RNA, as well as the limited opportunities for stereospecific intermolecular interactions between RNA molecules. The limited success at crystallization explains in part the smaller number of RNA-only structures in the Protein Data Bank. Several approaches have been developed to aid the formation of well-ordered RNA crystals. The majority of these are construct-engineering techniques that aim to introduce crystal contacts to favor the formation of well-diffracting crystals. A typical example is the insertion of tetraloop-tetraloop receptor pairs into non-essential RNA segments to promote intermolecular association. Other methods of promoting crystallization involve chaperones and crystallization-friendly molecules that increase RNA stability and improve crystal packing. In this review, we discuss the various techniques that have been successfully used to facilitate crystal packing of RNA molecules, recent advances in construct engineering, and directions for future research in this vital aspect of RNA crystallography.

The mechanism driving a solid-solid phase transition in a biomacromolecular crystal

Solid-solid phase transitions (SSPTs) occur between distinguishable crystalline forms. Because of their importance in application and theory in materials science and condensed-matter physics, SSPTs have been studied most extensively in metallic alloys, inorganic salts and small organic molecular crystals, but much less so in biomacromolecular crystals. In general, the mechanisms of SSPTs at the atomic and molecular levels are not well understood. Here, the ordered molecular rearrangements in biomacromolecular crystals of the adenine riboswitch aptamer are described using real-time serial crystallography and solution atomic force microscopy. Large, ligand-induced conformational changes drive the initial phase transition from the apo unit cell (AUC) to the trans unit cell 1 (TUC1). During this transition, coaxial stacking of P1 duplexes becomes the dominant packing interface, whereas P2-P2 interactions are almost completely disrupted, resulting in 'floating' layers of molecules. The coupling points in TUC1 and their local conformational flexibility allow the molecules to reorganize to achieve the more densely packed and energetically favorable bound unit cell (BUC). This study thus reveals the interplay between the conformational changes and the crystal phases - the underlying mechanism that drives the phase transition. Using polarized video microscopy to monitor SSPTs in small crystals at high ligand concentration, the time window during which the major conformational changes take place was identified, and the in crystallo kinetics have been simulated. Together, these results provide the spatiotemporal information necessary for informing time-resolved crystallography experiments. Moreover, this study illustrates a practical approach to characterization of SSPTs in transparent crystals.

Thermostability, Tunability, and Tenacity of RNA as Rubbery Anionic Polymeric Materials in Nanotechnology and Nanomedicine-Specific Cancer Targeting with Undetectable Toxicity

RNA nanotechnology is the bottom-up self-assembly of nanometer-scale architectures, resembling LEGOs, composed mainly of RNA. The ideal building material should be (1) versatile and controllable in shape and stoichiometry, (2) spontaneously self-assemble, and (3) thermodynamically, chemically, and enzymatically stable with a long shelf life. RNA building blocks exhibit each of the above. RNA is a polynucleic acid, making it a polymer, and its negative-charge prevents nonspecific binding to negatively charged cell membranes. The thermostability makes it suitable for logic gates, resistive memory, sensor set-ups, and NEM devices. RNA can be designed and manipulated with a level of simplicity of DNA while displaying versatile structure and enzyme activity of proteins. RNA can fold into single-stranded loops or bulges to serve as mounting dovetails for intermolecular or domain interactions without external linking dowels. RNA nanoparticles display rubber- and amoeba-like properties and are stretchable and shrinkable through multiple repeats, leading to enhanced tumor targeting and fast renal excretion to reduce toxicities. It was predicted in 2014 that RNA would be the third milestone in pharmaceutical drug development. The recent approval of several RNA drugs and COVID-19 mRNA vaccines by FDA suggests that this milestone is being realized. Here, we review the unique properties of RNA nanotechnology, summarize its recent advancements, describe its distinct attributes inside or outside the body and discuss potential applications in nanotechnology, medicine, and material science.

Optimized Magnesium Force Field Parameters for Biomolecular Simulations with Accurate Solvation, Ion-Binding, and Water-Exchange Properties

Magnesium ions play an essential role in many vital processes. To correctly describe their interactions in molecular dynamics simulations, an accurate parametrization is crucial. Despite the importance and considerable scientific effort, current force fields based on the commonly used 12-6 Lennard-Jones interaction potential fail to reproduce a variety of experimental solution properties. In particular, no parametrization exists so far that simultaneously reproduces the solvation free energy and the distance to the water oxygens in the first hydration shell. Moreover, current Mg2+ force fields significantly underestimate the rate of water exchange leading to unrealistically slow exchange kinetics. In order to make progress in the development of improved models, we systematically optimize the Mg2+ parameters in combination with the TIP3P water model in a much larger parameter space than previously done. The results show that a long-ranged interaction potential and modified Lorentz-Berthelot combination rules allow us to accurately reproduce multiple experimental properties including the solvation free energy, the distances to the oxygens of the first hydration shell, the hydration number, the activity coefficient derivative in MgCl2 solutions, the self-diffusion coefficient, and the binding affinity to the phosphate oxygen of RNA. Matching this broad range of thermodynamic properties, we present two sets of optimal parameters: MicroMg yields water exchange on the microsecond timescale in agreement with experiments. NanoMg yields water exchange on the nanosecond timescale facilitating the direct observation of ion-binding events. As shown for the example of the add A-riboswitch, the optimized parameters correctly reproduce the structure of specifically bound ions and permit the de novo prediction of Mg2+-binding sites in biomolecular simulations.

Improving RNA Crystal Diffraction Quality by Postcrystallization Treatment

The crystallization and structural determination of large RNAs and their complexes remain major bottlenecks in the mechanistic analysis of cellular and viral RNAs. Here, we describe a protocol that combines postcrystallization dehydration and ion replacement that dramatically improved the diffraction quality of crystals of a large gene-regulatory tRNA-mRNA complex. Through this method, the resolution limit of X-ray data extended from 8.5 to 3.2 Å, enabling structure determination. Although this protocol was developed for a particular RNA complex, the general importance of solvent and counterions in nucleic acid structure may render it generally useful for crystallographic analysis of other RNAs.

19 F NMR-Based Fragment Screening for 14 Different Biologically Active RNAs and 10 DNA and Protein Counter-Screens

We report here the nuclear magnetic resonance ¹⁹F screening of 14 RNA targets with different secondary and tertiary structure to systematically assess the druggability of RNAs. Our RNA targets include representative bacterial riboswitches that naturally bind with nanomolar affinity and high specificity to cellular metabolites of low molecular weight. Based on counter‐screens against five DNAs and five proteins, we can show that RNA can be specifically targeted. To demonstrate the quality of the initial fragment library that has been designed for easy follow‐up chemistry, we further show how to increase binding affinity from an initial fragment hit by chemistry that links the identified fragment to the intercalator acridine. Thus, we achieve low‐micromolar binding affinity without losing binding specificity between two different terminator structures.

Evaluating DCA-based method performances for RNA contact prediction by a well-curated data set

RNA molecules play many pivotal roles in a cell that are still not fully understood. Any detailed understanding of RNA function requires knowledge of its three-dimensional structure, yet experimental RNA structure resolution remains demanding. Recent advances in sequencing provide unprecedented amounts of sequence data that can be statistically analyzed by methods such as direct coupling analysis (DCA) to determine spatial proximity or contacts of specific nucleic acid pairs, which improve the quality of structure prediction. To quantify this structure prediction improvement, we here present a well curated data set of about 70 RNA structures of high resolution and compare different nucleotide-nucleotide contact prediction methods available in the literature. We observe only minor differences between the performances of the different methods. Moreover, we discuss how robust these predictions are for different contact definitions and how strongly they depend on procedures used to curate and align the families of homologous RNA sequences.

Using Rosetta for RNA homology modeling

The three-dimensional structures of RNA molecules provide rich and often critical information for understanding their functions, including how they recognize small molecule and protein partners. Computational modeling of RNA 3D structure is becoming increasingly accurate, particularly with the availability of growing numbers of template structures already solved experimentally and the development of sequence alignment and 3D modeling tools to take advantage of this database. For several recent "RNA puzzle" blind modeling challenges, we have successfully identified useful template structures and achieved accurate structure predictions through homology modeling tools developed in the Rosetta software suite. We describe our semi-automated methodology here and walk through two illustrative examples: an adenine riboswitch aptamer, modeled from a template guanine riboswitch structure, and a SAM I/IV riboswitch aptamer, modeled from a template SAM I riboswitch structure.

Heavy-atom labeling of RNA by PLOR for de novo crystallographic phasing

Due to the paucity of known RNA structures, experimental phasing is crucial for obtaining three-dimensional structures of RNAs by X-ray crystallography. Covalent attachment of heavy atoms to RNAs is one of the most useful strategies to facilitate phase determination. However, this approach is limited by the inefficiency or inability to synthesize large RNAs (>60 nucleotides) site-specifically labeled with heavy atoms using traditional methods. Here, we applied our recently reported method, PLOR (position-selective labeling of RNA) to incorporate 5-iodouridine at specific positions in the adenine riboswitch RNA aptamer domain, which was then used for crystallization and subsequent de novo SAD phasing. PLOR is a powerful tool to improve the efficiency of obtaining RNA structures de novo by X-ray crystallography.

Predicting RNA-Metal Ion Binding with Ion Dehydration Effects

Metal ions play essential roles in nucleic acids folding and stability. The interaction between metal ions and nucleic acids can be highly complicated because of the interplay between various effects such as ion correlation, fluctuation, and dehydration. These effects may be particularly important for multivalent ions such as Mg²⁺ ions. Previous efforts to model ion correlation and fluctuation effects led to the development of the Monte Carlo tightly bound ion model. Here, by incorporating ion hydration/dehydration effects into the Monte Carlo tightly bound ion model, we develop a, to our knowledge, new approach to predict ion binding. The new model enables predictions for not only the number of bound ions but also the three-dimensional spatial distribution of the bound ions. Furthermore, the new model reveals several intriguing features for the bound ions such as the mutual enhancement/inhibition in ion binding between the fully hydrated (diffuse) ions, the outer-shell dehydrated ions, and the inner-shell dehydrated ions and novel features for the monovalent-divalent ion interplay due to the hydration effect.

omiXcore: a web server for prediction of protein interactions with large RNA

Summary

Here we introduce omiXcore, a server for calculations of protein binding to large RNAs (> 500 nucleotides). Our webserver allows (i) use of both protein and RNA sequences without size restriction, (ii) pre-compiled library for exploration of human long intergenic RNAs interactions and (iii) prediction of binding sites.

Results

omiXcore was trained and tested on enhanced UV Cross-Linking and ImmunoPrecipitation data. The method discriminates interacting and non-interacting protein-RNA pairs and identifies RNA binding sites with Areas under the ROC curve > 0.80, which suggests that the tool is particularly useful to prioritize candidates for further experimental validation.

Availability and implementation

omiXcore is freely accessed on the web at http://service.tartaglialab.com/grant_submission/omixcore.

Supplementary information

Supplementary data are available at Bioinformatics online.

Incorporation of isotopic, fluorescent, and heavy-atom-modified nucleotides into RNAs by position-selective labeling of RNA

Site-specific incorporation of labeled nucleotides is an extremely useful synthetic tool for many structural studies (e.g., NMR, electron paramagnetic resonance (EPR), fluorescence resonance energy transfer (FRET), and X-ray crystallography) of RNA. However, specific-position-labeled RNAs >60 nt are not commercially available on a milligram scale. Position-selective labeling of RNA (PLOR) has been applied to prepare large RNAs labeled at desired positions, and all the required reagents are commercially available. Here, we present a step-by-step protocol for the solid-liquid hybrid phase method PLOR to synthesize 71-nt RNA samples with three different modification applications, containing (i) a ¹³C¹⁵N-labeled segment; (ii) discrete residues modified with Cy3, Cy5, or biotin; or (iii) two iodo-U residues. The flexible procedure enables a wide range of downstream biophysical analyses using precisely localized functionalized nucleotides. All three RNAs were obtained in <2 d, excluding time for preparing reagents and optimizing experimental conditions. With optimization, the protocol can be applied to other RNAs with various labeling schemes, such as ligation of segmentally labeled fragments.

Allosteric mechanism of the V. vulnificus adenine riboswitch resolved by four-dimensional chemical mapping

The structural interconversions that mediate the gene regulatory functions of RNA molecules may be different from classic models of allostery, but the relevant structural correlations have remained elusive in even intensively studied systems. Here, we present a four-dimensional expansion of chemical mapping called lock-mutate-map-rescue (LM²R), which integrates multiple layers of mutation with nucleotide-resolution chemical mapping. This technique resolves the core mechanism of the adenine-responsive V. vulnificus add riboswitch, a paradigmatic system for which both Monod-Wyman-Changeux (MWC) conformational selection models and non-MWC alternatives have been proposed. To discriminate amongst these models, we locked each functionally important helix through designed mutations and assessed formation or depletion of other helices via compensatory rescue evaluated by chemical mapping. These LM²R measurements give strong support to the pre-existing correlations predicted by MWC models, disfavor alternative models, and suggest additional structural heterogeneities that may be general across ligand-free riboswitches.

Divalent ion competition reveals reorganization of an RNA ion atmosphere upon folding

Although RNA interactions with K+ and Mg2+ have been studied extensively, much less is known about the third most abundant cation in bacterial cells, putrescine2+, and how RNA folding might be influenced by the three ions in combination. In a new approach, we have observed the competition between Mg2+ and putrescine2+ (in a background of K+) with native, partially unfolded and highly extended conformations of an adenine riboswitch aptamer. With the native state, putrescine2+ is a weak competitor when the ratio of the excess Mg2+ (which neutralizes phosphate charge) to RNA is very low, but becomes much more effective at replacing Mg2+ as the excess Mg2+ in the RNA ion atmosphere increases. Putrescine2+ is even more effective in competing Mg2+ from the extended conformation, independent of the Mg2+ excess. To account for these and other results, we propose that both ions closely approach the surface of RNA secondary structure, but the completely folded RNA tertiary structure develops small pockets of very negative electrostatic potential that are more accessible to the compact charge of Mg2+. The sensitivity of RNA folding to the combination of Mg2+ and putrescine2+ found in vivo depends on the architectures of both the unfolded and native conformations.

Predicting Ion Effects in an RNA Conformational Equilibrium

We develop a partial charge-based tightly bound ion (PCTBI) model for the ion effects in RNA folding. On the basis of the Monte Carlo tightly bound ion (MCTBI) approach, the model can account for ion fluctuation and correlation effects, and can predict the ion distribution around the RNA. Furthermore, unlike the previous coarse-grained RNA charge models, where negative charges are placed on the phosphates only, the current new model considers the detailed all-atom partial charge distribution on the RNA. Thus, the model not only keeps the advantage of the MCTBI model, but also has the potential to provide important detailed information unattainable by the previous MCTBI models. For example, the model predicts the reduction in ion binding upon protein binding and ion-induced conformational switches. For hepatitis C virus genomic RNA, the model predicts a Mg²⁺-induced stabilization of a kissing motif for a cis-acting regulatory element in the genomic RNA. Extensive theory-experiment comparisons support the reliability of the theoretical predictions. Therefore, the model may serve as a robust starting point for further development of an accurate method for ion effects in an RNA conformational equilibrium and RNA-cofactor interactions.

Real-time crystallographic studies of the adenine riboswitch using an X-ray free-electron laser

Structures of the four reaction states of the adenine riboswitch aptamer domain, including a transient intermediate state were solved by serial femtosecond crystallography. The structures not only demonstrate the use of X-ray free-electron lasers for RNA crystallography but have also proven that transient states can be determined in real time by mix-and-inject crystallography. These results illustrate the structural basis for the ligand-induced conformational changes associated with the molecular 'switch'.

MCTBI: a web server for predicting metal ion effects in RNA structures

Metal ions play critical roles in RNA structure and function. However, web servers and software packages for predicting ion effects in RNA structures are notably scarce. Furthermore, the existing web servers and software packages mainly neglect ion correlation and fluctuation effects, which are potentially important for RNAs. We here report a new web server, the MCTBI server (http://rna.physics.missouri.edu/MCTBI), for the prediction of ion effects for RNA structures. This server is based on the recently developed MCTBI, a model that can account for ion correlation and fluctuation effects for nucleic acid structures and can provide improved predictions for the effects of metal ions, especially for multivalent ions such as Mg²⁺ effects, as shown by extensive theory-experiment test results. The MCTBI web server predicts metal ion binding fractions, the most probable bound ion distribution, the electrostatic free energy of the system, and the free energy components. The results provide mechanistic insights into the role of metal ions in RNA structure formation and folding stability, which is important for understanding RNA functions and the rational design of RNA structures.

Theory and Modeling of RNA Structure and Interactions with Metal Ions and Small Molecules

In addition to continuous rapid progress in RNA structure determination, probing, and biophysical studies, the past decade has seen remarkable advances in the development of a new generation of RNA folding theories and models. In this article, we review RNA structure prediction models and models for ion-RNA and ligand-RNA interactions. These new models are becoming increasingly important for a mechanistic understanding of RNA function and quantitative design of RNA nanotechnology. We focus on new methods for physics-based, knowledge-based, and experimental data-directed modeling for RNA structures and explore the new theories for the predictions of metal ion and ligand binding sites and metal ion-dependent RNA stabilities. The integration of these new methods with theories about the cellular environment effects in RNA folding, such as molecular crowding and cotranscriptional kinetic effects, may ultimately lead to an all-encompassing RNA folding model.

Mg2+ ions: do they bind to nucleobase nitrogens?

Given the many roles proposed for Mg2+ in nucleic acids, it is essential to accurately determine their binding modes. Here, we surveyed the PDB to classify Mg2+ inner-sphere binding patterns to nucleobase imine N1/N3/N7 atoms. Among those, purine N7 atoms are considered to be the best nucleobase binding sites for divalent metals. Further, Mg2+ coordination to N7 has been implied in several ribozyme catalytic mechanisms. We report that Mg2+ assigned near imine nitrogens derive mostly from poor interpretations of electron density patterns and are most often misidentified Na+, K+, NH4+ ions, water molecules or spurious density peaks. Consequently, apart from few documented exceptions, Mg2+ ions do not bind to N7 atoms. Without much of a surprise, Mn2+, Zn2+ and Cd2+, which have a higher affinity for nitrogens, may contact N7 atoms when present in crystallization buffers. In this respect, we describe for the first time a potential Zn2+ ribosomal binding site involving two purine N7 atoms. Further, we provide a set of guidelines to help in the assignment of Mg2+ in crystallographic, cryo-EM, NMR and model building practices and discuss implications of our findings related to ion substitution experiments.

Structures of riboswitch RNA reaction states by mix-and-inject XFEL serial crystallography

Riboswitches are structural RNA elements that are generally located in the 5' untranslated region of messenger RNA. During regulation of gene expression, ligand binding to the aptamer domain of a riboswitch triggers a signal to the downstream expression platform. A complete understanding of the structural basis of this mechanism requires the ability to study structural changes over time. Here we use femtosecond X-ray free electron laser (XFEL) pulses to obtain structural measurements from crystals so small that diffusion of a ligand can be timed to initiate a reaction before diffraction. We demonstrate this approach by determining four structures of the adenine riboswitch aptamer domain during the course of a reaction, involving two unbound apo structures, one ligand-bound intermediate, and the final ligand-bound conformation. These structures support a reaction mechanism model with at least four states and illustrate the structural basis of signal transmission. The three-way junction and the P1 switch helix of the two apo conformers are notably different from those in the ligand-bound conformation. Our time-resolved crystallographic measurements with a 10-second delay captured the structure of an intermediate with changes in the binding pocket that accommodate the ligand. With at least a 10-minute delay, the RNA molecules were fully converted to the ligand-bound state, in which the substantial conformational changes resulted in conversion of the space group. Such notable changes in crystallo highlight the important opportunities that micro- and nanocrystals may offer in these and similar time-resolved diffraction studies. Together, these results demonstrate the potential of 'mix-and-inject' time-resolved serial crystallography to study biochemically important interactions between biomacromolecules and ligands, including those that involve large conformational changes.

Controlled dehydration improves the diffraction quality of two RNA crystals

BACKGROUND

Post-crystallization dehydration methods, applying either vapor diffusion or humidity control devices, have been widely used to improve the diffraction quality of protein crystals. Despite the fact that RNA crystals tend to diffract poorly, there is a dearth of reports on the application of dehydration methods to improve the diffraction quality of RNA crystals.

RESULTS

We use dehydration techniques with a Free Mounting System (FMS, a humidity control device) to recover the poor diffraction quality of RNA crystals. These approaches were applied to RNA constructs that model various RNA-mediated repeat expansion disorders.

CONCLUSION

The method we describe herein could serve as a general tool to improve diffraction quality of RNA crystals to facilitate structure determinations.

Applications of PLOR in labeling large RNAs at specific sites

Incorporation of modified or labeled nucleotides at specific sites in RNAs is critical for gaining insights into the structure and function of RNAs. Preparation of site-specifically labeled large RNAs in amounts suitable for structural or functional studies is extremely difficult using current methodologies. The position-selective labeling of RNA, PLOR, is a recently developed method that makes such syntheses possible. PLOR allows incorporation of various probes, including (2)D/(13)C/(15)N-isotopic labels, Cy3/Cy5/Alexa488/Alexa555 fluorescent dyes, biotin and other chemical groups, into specific positions in long RNAs. Here, we describe in detail the use of PLOR to label RNAs at specific segment(s) or discrete sites.

Post-crystallization Improvement of RNA Crystal Diffraction Quality

The crystallization and structural determination of large RNAs and their complexes remain major bottlenecks in the mechanistic analysis of cellular and viral RNAs. Here, we describe a protocol that combines post-crystallization dehydration and ion replacement that dramatically improved the diffraction quality of crystals of a large gene-regulatory tRNA-mRNA complex. Through this method, the resolution limit of X-ray data extended from 8.5 to 3.2 Å, enabling structure determination. Although this protocol was developed for a particular RNA complex, the general importance of solvent and counterions in nucleic acid structure may render it generally useful for crystallographic analysis of other RNAs.

Nuclear Magnetic Resonance-Assisted Prediction of Secondary Structure for RNA: Incorporation of Direction-Dependent Chemical Shift Constraints

Knowledge of RNA structure is necessary to determine structure–function relationships and to facilitate design of potential therapeutics. RNA secondary structure prediction can be improved by applying constraints from nuclear magnetic resonance (NMR) experiments to a dynamic programming algorithm. Imino proton walks from NOESY spectra reveal double-stranded regions. Chemical shifts of protons in GH1, UH3, and UH5 of GU pairs, UH3, UH5, and AH2 of AU pairs, and GH1 of GC pairs were analyzed to identify constraints for the 5′ to 3′ directionality of base pairs in helices. The 5′ to 3′ directionality constraints were incorporated into an NMR-assisted prediction of secondary structure (NAPSS-CS) program. When it was tested on 18 structures, including nine pseudoknots, the sensitivity and positive predictive value were improved relative to those of three unrestrained programs. The prediction accuracy for the pseudoknots improved the most. The program also facilitates assignment of chemical shifts to individual nucleotides, a necessary step for determining three-dimensional structure.

Post-crystallization Improvement of RNA Crystals by Synergistic Ion Exchange and Dehydration

Compared to the recent dramatic growth in the numbers of genome-wide and functional studies of complex non-coding RNAs, mechanistic and structural analyses have lagged behind. A major technical bottleneck in the structural determination of large RNAs and their complexes is preparation of diffracting crystals. Empirically, a vast majority of such RNA crystals fail to diffract X-rays to usable resolution (~4 Å) due to their inherent disorder and non-specific packing within the crystals. Here, we present a protocol that combines post-crystallization cation replacement and dehydration that dramatically improved the diffraction quality of crystals of a large gene-regulatory mRNA-tRNA complex. This procedure not only extended the resolution limit of X-ray data from 8.5 to 3.2 Å, but also significantly improved the quality of the data, enabling de novo phasing and structure determination. Because it exploits the general importance of counterions and solvation in RNA structure, this procedure may prove broadly useful in the crystallographic analyses of other large non-coding RNAs.

Synthesis and applications of RNAs with position-selective labelling and mosaic composition

Knowledge of the structure and dynamics of RNA molecules is critical to understanding their many biological functions. Furthermore, synthetic RNAs have applications as therapeutics and molecular sensors. Both research and technological applications of RNA would be dramatically enhanced by methods that enable incorporation of modified or labelled nucleotides into specifically designated positions or regions of RNA. However, the synthesis of tens of milligrams of such RNAs using existing methods has been impossible. Here we develop a hybrid solid-liquid phase transcription method and automated robotic platform for the synthesis of RNAs with position-selective labelling. We demonstrate its use by successfully preparing various isotope- or fluorescently labelled versions of the 71-nucleotide aptamer domain of an adenine riboswitch for nuclear magnetic resonance spectroscopy or single-molecule Förster resonance energy transfer, respectively. Those RNAs include molecules that were selectively isotope-labelled in specific loops, linkers, a helix, several discrete positions, or a single internal position, as well as RNA molecules that were fluorescently labelled in and near kissing loops. These selectively labelled RNAs have the same fold as those transcribed using conventional methods, but they greatly simplify the interpretation of NMR spectra. The single-position isotope- and fluorescently labelled RNA samples reveal multiple conformational states of the adenine riboswitch. Lastly, we describe a robotic platform and the operation that automates this technology. Our selective labelling method may be useful for studying RNA structure and dynamics and for making RNA sensors for a variety of applications including cell-biological studies, substance detection, and disease diagnostics.

Structure and mechanism of the T-box riboswitches

In most Gram-positive bacteria, including many clinically devastating pathogens from genera such as Bacillus, Clostridium, Listeria, and Staphylococcus, T-box riboswitches sense and regulate intracellular availability of amino acids through a multipartite messenger RNA (mRNA)-transfer RNA (tRNA) interaction. The T-box mRNA leaders respond to nutrient starvation by specifically binding cognate tRNAs and sensing whether the bound tRNA is aminoacylated, as a proxy for amino acid availability. Based on this readout, T-boxes direct a transcriptional or translational switch to control the expression of downstream genes involved in various aspects of amino acid metabolism: biosynthesis, transport, aminoacylation, transamidation, and so forth. Two decades after its discovery, the structural and mechanistic underpinnings of the T-box riboswitch were recently elucidated, producing a wealth of insights into how two structured RNAs can recognize each other with robust affinity and exquisite selectivity. The T-box paradigm exemplifies how natural noncoding RNAs can interact not just through sequence complementarity but can add molecular specificity by precisely juxtaposing RNA structural motifs, exploiting inherently flexible elements and the biophysical properties of post-transcriptional modifications, ultimately achieving a high degree of shape complementarity through mutually induced fit. The T-box also provides a proof-of-principle that compact RNA domains can recognize minute chemical changes (such as tRNA aminoacylation) on another RNA. The unveiling of the structure and mechanism of the T-box system thus expands our appreciation of the range of capabilities and modes of action of structured noncoding RNAs, and hints at the existence of networks of noncoding RNAs that communicate through both, structural and sequence specificity.