RNANetMotif: Identifying sequence-structure RNA network motifs in RNA-protein binding sites

RNA molecules can adopt stable secondary and tertiary structures, which are essential in mediating physical interactions with other partners such as RNA binding proteins (RBPs) and in carrying out their cellular functions. In vivo and in vitro experiments such as RNAcompete and eCLIP have revealed in vitro binding preferences of RBPs to RNA oligomers and in vivo binding sites in cells. Analysis of these binding data showed that the structure properties of the RNAs in these binding sites are important determinants of the binding events; however, it has been a challenge to incorporate the structure information into an interpretable model. Here we describe a new approach, RNANetMotif, which takes predicted secondary structure of thousands of RNA sequences bound by an RBP as input and uses a graph theory approach to recognize enriched subgraphs. These enriched subgraphs are in essence shared sequence-structure elements that are important in RBP-RNA binding. To validate our approach, we performed RNA structure modeling via coarse-grained molecular dynamics folding simulations for selected 4 RBPs, and RNA-protein docking for LIN28B. The simulation results, e.g., solvent accessibility and energetics, further support the biological relevance of the discovered network subgraphs.     

Local RNA conformational dynamics revealed by 2-aminopurine solvent accessibility

Acrylamide quenching is widely used to monitor the solvent exposure of fluorescent probes in vitro. Here, we tested the utility of this technique to discriminate local RNA secondary structures using the fluorescent adenine analogue 2-aminopurine (2-AP). Under native conditions, the solvent accessibilities of most 2-AP-labeled RNA substrates were poorly resolved by classical single-population models; rather, a two-state quencher accessibility algorithm was required to model acrylamide-dependent changes in 2-AP fluorescence in structured RNA contexts. Comparing 2-AP quenching parameters between structured and unstructured RNA substrates permitted the effects of local RNA structure on 2-AP solvent exposure to be distinguished from nearest neighbor effects or environmental influences on intrinsic 2-AP photophysics. Using this strategy, the fractional accessibility of 2-AP for acrylamide ( f a) was found to be highly sensitive to local RNA structure. Base-paired 2-AP exhibited relatively poor accessibility, consistent with extensive shielding by adjacent bases. 2-AP in a single-base bulge was uniformly accessible to solvent, whereas the fractional accessibility of 2-AP in a hexanucleotide loop was indistinguishable from that of an unstructured RNA. However, these studies also provided evidence that the f a parameter reflects local conformational dynamics in base-paired RNA. Enhanced base pair dynamics at elevated temperatures were accompanied by increased f a values, while restricting local RNA breathing by adding a C-G base pair clamp or positioning 2-AP within extended RNA duplexes significantly decreased this parameter. Together, these studies show that 2-AP quenching studies can reveal local RNA structural and dynamic features beyond those that can be measured by conventional spectroscopic approaches.     

The role of RNA sequence and structure in RNA--protein interactions

We investigate the sequence and structural properties of RNA-protein interaction sites in 211 RNA-protein chain pairs, the largest set of RNA-protein complexes analyzed to date. Statistical analysis confirms and extends earlier analyses made on smaller data sets. There are 24.6% of hydrogen bonds between RNA and protein that are nucleobase specific, indicating the importance of both nucleobase-specific and -nonspecific interactions. While there is no significant difference between RNA base frequencies in protein-binding and non-binding regions, distinct preferences for RNA bases, RNA structural states, protein residues, and protein secondary structure emerge when nucleobase-specific and -nonspecific interactions are considered separately. Guanine nucleobase and unpaired RNA structural states are significantly preferred in nucleobase-specific interactions; however, nonspecific interactions disfavor guanine, while still favoring unpaired RNA structural states. The opposite preferences of nucleobase-specific and -nonspecific interactions for guanine may explain discrepancies between earlier studies with regard to base preferences in RNA-protein interaction regions. Preferences for amino acid residues differ significantly between nucleobase-specific and -nonspecific interactions, with nonspecific interactions showing the expected bias towards positively charged residues. Irregular protein structures are strongly favored in interactions with the protein backbone, whereas there is little preference for specific protein secondary structure in either nucleobase-specific interaction or -nonspecific interaction. Overall, this study shows strong preferences for both RNA bases and RNA structural states in protein-RNA interactions, indicating their mutual importance in protein recognition.     

Crystal structure of a brominated RNA helix with four mismatched base pairs: An investigation into RNA conformational variability.

The X-ray crystal structure of a brominated RNA helix with four mismatched base pairs and sequence r(UG(Br)C(Br)CAGUUCGCUGGC)(2) was determined to 2.1 A using the methods of multiwavelength anomalous diffraction (MAD) applied to the bromine K-absorption edge. There are three molecules in the asymmetric unit with unique crystal-packing environments, revealing true conformational variability at high resolution for this sequence. The structure shows that the sequence itself does not define a consistent pattern of solvent molecules, with the exception of the mismatched base pairs, implying that specific RNA-protein interactions would occur only with the nucleotides. There are a number of significant tertiary interactions, some of which are a result of the brominated base pairs and others that are directly mediated by the RNA 2' hydroxyl groups. The mismatched base pairs exhibit a solvent network as well as a stacking pattern with their nearest neighbors that validate previous thermodynamic analysis.     

Molecular dynamics simulations of RNA: an in silico single molecule approach

RNA molecules are now known to be involved in the processing of genetic information at all levels, taking on a wide variety of central roles in the cell. Understanding how RNA molecules carry out their biological functions will require an understanding of structure and dynamics at the atomistic level, which can be significantly improved by combining computational simulation with experiment. This review provides a critical survey of the state of molecular dynamics (MD) simulations of RNA, including a discussion of important current limitations of the technique and examples of its successful application. Several types of simulations are discussed in detail, including those of structured RNA molecules and their interactions with the surrounding solvent and ions, catalytic RNAs, and RNA-small molecule and RNA-protein complexes. Increased cooperation between theorists and experimentalists will allow expanded judicious use of MD simulations to complement conceptually related single molecule experiments. Such cooperation will open the door to a fundamental understanding of the structure-function relationships in diverse and complex RNA molecules. .     

Consensus folding of unaligned RNA sequences revisited.

As one of the earliest problems in computational biology, RNA secondary structure prediction (sometimes referred to as "RNA folding") problem has attracted attention again, thanks to the recent discoveries of many novel non-coding RNA molecules. The two common approaches to this problem are de novo prediction of RNA secondary structure based on energy minimization and the consensus folding approach (computing the common secondary structure for a set of unaligned RNA sequences). Consensus folding algorithms work well when the correct seed alignment is part of the input to the problem. However, seed alignment itself is a challenging problem for diverged RNA families. In this paper, we propose a novel framework to predict the common secondary structure for unaligned RNA sequences. By matching putative stacks in RNA sequences, we make use of both primary sequence information and thermodynamic stability for prediction at the same time. We show that our method can predict the correct common RNA secondary structures even when we are given only a limited number of unaligned RNA sequences, and it outperforms current algorithms in sensitivity and accuracy.     

Quantitative profiling of in vivo-assembled RNA-protein complexes using a novel integrated proteomic approach

Identification of proteins in RNA-protein complexes is an important step toward understanding regulation of RNA-based processes. Because of the lack of appropriate methodologies, many studies have relied on the creation of in vitro assembled RNA-protein complexes using synthetic RNA and cell extracts. Such complexes may not represent authentic RNPs as they exist in living cells as synthetic RNA may not fold properly and nonspecific RNA-protein interactions can form during cell lysis and purification processes. To circumvent limitations in current approaches, we have developed a novel integrated strategy namely MS2 in vivo biotin tagged RNA affinity purification (MS2-BioTRAP) to capture bona fide in vivo-assembled RNA-protein complexes. In this method, HB-tagged bacteriophage protein MS2 and stem-loop tagged target or control RNAs are co-expressed in cells. The tight association between MS2 and the RNA stem-loop tags allows efficient HB-tag based affinity purification of authentic RNA-protein complexes. Proteins associated with target RNAs are subsequently identified and quantified using SILAC-based quantitative mass spectrometry. Here the 1.2 kb internal ribosome entry site (IRES) from lymphoid enhancer factor-1 mRNA has been used as a proof-of-principle target RNA. An IRES target was chosen because of its importance in protein translation and our limited knowledge of proteins associated with IRES function. With a conventionally translated target RNA as control, 36 IRES binding proteins have been quantitatively identified including known IRES binding factors, novel interacting proteins, translation initiation factors (eIF4A-1, eIF-2A, and eIF3g), and ribosomal subunits with known noncanonical actions (RPS19, RPS7, and RPL26). Validation studies with the small molecule eIF4A-1 inhibitor Hippuristanol shows that translation of endogenous lymphoid enhancer factor-1 mRNA is especially sensitive to eIF4A-1 activity. Our work demonstrates that MS2 in vivo biotin tagged RNA affinity purification is an effective and versatile approach that is generally applicable for other RNA-protein complexes.     

Three-dimensional RNA structure refinement by hydroxyl radical probing

Molecular modeling guided by experimentally derived structural information is an attractive approach for three-dimensional structure determination of complex RNAs that are not amenable to study by high-resolution methods. Hydroxyl radical probing (HRP), which is performed routinely in many laboratories, provides a measure of solvent accessibility at individual nucleotides. HRP measurements have, to date, only been used to evaluate RNA models qualitatively. Here we report the development of a quantitative structure refinement approach using HRP measurements to drive discrete molecular dynamics simulations for RNAs ranging in size from 80 to 230 nucleotides. We first used HRP reactivities to identify RNAs that form extensive helical packing interactions. For these RNAs, we achieved highly significant structure predictions given the inputs of RNA sequence and base pairing. This HRP-directed tertiary structure refinement approach generates robust structural hypotheses that are useful for guiding explorations of structure-function inter-relationships in RNA.     

Tertiary core rearrangements in a tight binding transfer RNA aptamer

Guided by an in vitro selection experiment designed to obtain tight binding aptamers of Escherichia coli glutamine specific tRNA (tRNAGln) for glutaminyl-tRNA synthetase (GlnRS), we have engineered a tRNA mutant in which the five-nucleotide variable loop sequence 5'-44CAUUC48-3' is replaced by 5'-44AGGU48-3'. This mutant tRNA binds to GlnRS with 30-fold improved affinity compared to the wild type. The 2.7 A cocrystal structure of the RNA aptamer-GlnRS complex reveals major rearrangements in the central tertiary core of the tRNA, while maintaining an RNA-protein interface identical to the wild type. The repacked RNA core features a novel hydrogen bonding arrangement of the trans Levitt pair G15-U48, a new sulfate binding pocket in the major groove, and increased hydrophobic stacking interactions among the bases. These data suggest that enhanced protein binding to a mutant globular RNA can arise from stabilization of RNA tertiary interactions rather than optimization of RNA-protein contacts.     

RNA structure: Merging chemistry and genomics for a holistic perspective

The advent of deep sequencing technology has unexpectedly advanced our structural understanding of molecules composed of nucleic acids. A significant amount of progress has been made recently extrapolating the chemical methods to probe RNA structure into sequencing methods. Herein we review some of the canonical methods to analyze RNA structure, and then we outline how these have been used to probe the structure of many RNAs in parallel. The key is the transformation of structural biology problems into sequencing problems, whereby sequencing power can be interpreted to understand nucleic acid proximity, nucleic acid conformation, or nucleic acid‐protein interactions. Utilizing such technologies in this way has the promise to provide novel structural insights into the mechanisms that control normal cellular physiology and provide insight into how structure could be perturbed in disease.     

Quantifying sequence and structural features of protein–RNA interactions

Increasing awareness of the importance of protein–RNA interactions has motivated many approaches to predict residue-level RNA binding sites in proteins based on sequence or structural characteristics. Sequence-based predictors are usually high in sensitivity but low in specificity; conversely structure-based predictors tend to have high specificity, but lower sensitivity. Here we quantified the contribution of both sequence- and structure-based features as indicators of RNA-binding propensity using a machine-learning approach. In order to capture structural information for proteins without a known structure, we used homology modeling to extract the relevant structural features. Several novel and modified features enhanced the accuracy of residue-level RNA-binding propensity beyond what has been reported previously, including by meta-prediction servers. These features include: hidden Markov model-based evolutionary conservation, surface deformations based on the Laplacian norm formalism, and relative solvent accessibility partitioned into backbone and side chain contributions. We constructed a web server called aaRNA that implements the proposed method and demonstrate its use in identifying putative RNA binding sites.     

Rational siRNA design for RNA interference

Short-interfering RNAs suppress gene expression through a highly regulated enzyme-mediated process called RNA interference (RNAi). RNAi involves multiple RNA-protein interactions characterized by four major steps: assembly of siRNA with the RNA-induced silencing complex (RISC), activation of the RISC, target recognition and target cleavage. These interactions may bias strand selection during siRNA-RISC assembly and activation, and contribute to the overall efficiency of RNAi. To identify siRNA-specific features likely to contribute to efficient processing at each step, we performed a systematic analysis of 180 siRNAs targeting the mRNA of two genes. Eight characteristics associated with siRNA functionality were identified: low G/C content, a bias towards low internal stability at the sense strand 3'-terminus, lack of inverted repeats, and sense strand base preferences (positions 3, 10, 13 and 19). Further analyses revealed that application of an algorithm incorporating all eight criteria significantly improves potent siRNA selection. This highlights the utility of rational design for selecting potent siRNAs and facilitating functional gene knockdown studies.     

RNA Whole-Mount In situ Hybridisation Proximity Ligation Assay (rISH-PLA), an Assay for Detecting RNA-Protein Complexes in Intact Cells

Techniques for studying RNA-protein interactions have lagged behind those for DNA-protein complexes as a consequence of the complexities associated with working with RNA. Here we present a method for the modification of the existing In Situ Hybridisation–Proximity Ligation Assay (ISH-PLA) protocol to adapt it to the study of RNA regulation (rISH-PLA). As proof of principle we used the well-characterised interaction of the Xenopus laevis Staufen RNA binding protein with Vg1 mRNA, the complex of which co-localises to the vegetal pole of Xenopus oocytes. The applicability of both the Stau1 antibody and the Locked Nucleic Acid probe (LNA) recognising Vg1 mRNA were independently validated by whole-mount Immunohistochemistry and whole-mount in situ hybridisation assays respectively prior to combining them in the rISH-PLA assay. The rISH-PLA assay allows the identification of a given RNA-protein complex at subcellular and single cell resolution, thus avoiding the lack of spatial resolution and sensitivity associated with assaying heterogenous cell populations from which conventional RNA-protein interaction detection techniques suffer. This technique will be particularly usefully for studying the activity of RNA binding proteins (RBPs) in complex mixtures of cells, for example tissue sections or whole embryos.     

Genome-wide Mapping of Cellular Protein–RNA Interactions Enabled by Chemical Crosslinking

RNA–protein interactions influence many biological processes. Identifying the binding sites of RNA-binding proteins（RBPs） remains one of the most fundamental and important challenges to the studies of such interactions. Capturing RNA and RBPs via chemical crosslinking allows stringent purification procedures that significantly remove the non-specific RNA and protein interactions. Two major types of chemical crosslinking strategies have been developed to date, i.e., UV-enabled crosslinking and enzymatic mechanism-based covalent capture. In this review, we compare such strategies and their current applications, with an emphasis on the technologies themselves rather than the biology that has been revealed. We hope such methods could benefit broader audience and also urge for the development of new methods to study RNA RBP interactions.