Visualization and characterization of RNA–protein interactions in living cells

RNA–protein interactions are the structural and functional basis of significant numbers of RNA molecules. RNA–protein interaction assays though, still mainly depend on biochemical tests in vitro. Here, we establish a convenient and reliable RNA fluorescent three-hybrid (rF3H) method to detect/interrogate the interactions between RNAs and proteins in cells. A GFP tagged highly specific RNA trap is constructed to anchor the RNA of interest to an artificial or natural subcellular structure, and RNA–protein interactions can be detected and visualized by the enrichment of RNA binding proteins (RBPs) at these structures. Different RNA trapping systems are developed and detection of RNA–protein complexes at multiple subcellular structures are assayed. With this new toolset, interactions between proteins and mRNA or noncoding RNAs are characterized, including the interaction between a long noncoding RNA and an epigenetic modulator. Our approach provides a flexible and reliable method for the characterization of RNA–protein interactions in living cells.     

Evidence that avian reovirus σNS is an RNA chaperone: implications for genome segment assortment

Reoviruses are important human, animal and plant pathogens having 10–12 segments of double-stranded genomic RNA. The mechanisms controlling the assortment and packaging of genomic segments in these viruses, remain poorly understood. RNA–protein and RNA–RNA interactions between viral genomic segment precursors have been implicated in the process. While non-structural viral RNA-binding proteins, such as avian reovirus σNS, are essential for virus replication, the mechanism by which they assist packaging is unclear. Here we demonstrate that σNS assembles into stable elongated hexamers in vitro, which bind single-stranded nucleic acids with high affinity, but little sequence specificity. Using ensemble and single molecule fluorescence spectroscopy, we show that σNS also binds to a partially double-stranded RNA, resulting in gradual helix unwinding. The hexamer can bind multiple RNA molecules and exhibits strand-annealing activity, thus mediating conversion of metastable, intramolecular stem-loops into more stable heteroduplexes. We demonstrate that the ARV σNS acts as an RNA chaperone facilitating specific RNA–RNA interactions between genomic precursors during segment assortment and packaging.     

Directed evolution of orthogonal RNA–RBP pairs through library-vs-library in vitro selection

RNA-binding proteins (RBPs) and their RNA ligands play many critical roles in gene regulation and RNA processing in cells. They are also useful for various applications in cell biology and synthetic biology. However, re-engineering novel and orthogonal RNA–RBP pairs from natural components remains challenging while such synthetic RNA–RBP pairs could significantly expand the RNA–RBP toolbox for various applications. Here, we report a novel library-vs-library in vitro selection strategy based on Phage Display coupled with Systematic Evolution of Ligands by EXponential enrichment (PD-SELEX). Starting with pools of 1.1 × 10¹² unique RNA sequences and 4.0 × 10⁸ unique phage-displayed L7Ae-scaffold (LS) proteins, we selected RNA–RBP complexes through a two-step affinity purification process. After six rounds of library-vs-library selection, the selected RNAs and LS proteins were analyzed by next-generation sequencing (NGS). Further deconvolution of the enriched RNA and LS protein sequences revealed two synthetic and orthogonal RNA–RBP pairs that exhibit picomolar affinity and >4000-fold selectivity.     

Amino acid–base interactions: a three-dimensional analysis of protein–DNA interactions at an atomic level

To assess whether there are universal rules that govern amino acid–base recognition, we investigate hydrogen bonds, van der Waals contacts and water-mediated bonds in 129 protein–DNA complex structures. DNA–backbone interactions are the most numerous, providing stability rather than specificity. For base interactions, there are significant base–amino acid type correlations, which can be rationalised by considering the stereochemistry of protein side chains and the base edges exposed in the DNA structure. Nearly two-thirds of the direct read-out of DNA sequences involves complex networks of hydrogen bonds, which enhance specificity. Two-thirds of all protein–DNA interactions comprise van der Waals contacts, compared to about one-sixth each of hydrogen and water-mediated bonds. This highlights the central importance of these contacts for complex formation, which have previously been relegated to a secondary role. Although common, water-mediated bonds are usually non-specific, acting as space-fillers at the protein–DNA interface. In conclusion, the majority of amino acid–base interactions observed follow general principles that apply across all protein–DNA complexes, although there are individual exceptions. Therefore, we distinguish between interactions whose specificities are ‘universal’ and ‘context-dependent’. An interactive Web-based atlas of side chain–base contacts provides access to the collected data, including analyses and visualisation of the three-dimensional geometry of the interactions.     

From Nonspecific DNA–Protein Encounter Complexes to the Prediction of DNA–Protein Interactions

DNA–protein interactions are involved in many essential biological activities. Because there is no simple mapping code between DNA base pairs and protein amino acids, the prediction of DNA–protein interactions is a challenging problem. Here, we present a novel computational approach for predicting DNA-binding protein residues and DNA–protein interaction modes without knowing its specific DNA target sequence. Given the structure of a DNA-binding protein, the method first generates an ensemble of complex structures obtained by rigid-body docking with a nonspecific canonical B-DNA. Representative models are subsequently selected through clustering and ranking by their DNA–protein interfacial energy. Analysis of these encounter complex models suggests that the recognition sites for specific DNA binding are usually favorable interaction sites for the nonspecific DNA probe and that nonspecific DNA–protein interaction modes exhibit some similarity to specific DNA–protein binding modes. Although the method requires as input the knowledge that the protein binds DNA, in benchmark tests, it achieves better performance in identifying DNA-binding sites than three previously established methods, which are based on sophisticated machine-learning techniques. We further apply our method to protein structures predicted through modeling and demonstrate that our method performs satisfactorily on protein models whose root-mean-square Cα deviation from native is up to 5 Å from their native structures. This study provides valuable structural insights into how a specific DNA-binding protein interacts with a nonspecific DNA sequence. The similarity between the specific DNA–protein interaction mode and nonspecific interaction modes may reflect an important sampling step in search of its specific DNA targets by a DNA-binding protein.     

Nano-sandwich composite by kinetic trapping assembly from protein and nucleic acid

Design and preparation of layered composite materials alternating between nucleic acids and proteins has been elusive due to limitations in occurrence and geometry of interaction sites in natural biomolecules. We report the design and kinetically controlled stepwise synthesis of a nano-sandwich composite by programmed noncovalent association of protein, DNA and RNA modules. A homo-tetramer protein core was introduced to control the self-assembly and precise positioning of two RNA–DNA hybrid nanotriangles in a co-parallel sandwich arrangement. Kinetically favored self-assembly of the circularly closed nanostructures at the protein was driven by the intrinsic fast folding ability of RNA corner modules which were added to precursor complex of DNA bound to the protein. The 3D architecture of this first synthetic protein–RNA–DNA complex was confirmed by fluorescence labeling and cryo-electron microscopy studies. The synthesis strategy for the nano-sandwich composite provides a general blueprint for controlled noncovalent assembly of complex supramolecular architectures from protein, DNA and RNA components, which expand the design repertoire for bottom-up preparation of layered biomaterials.     

Statistical prediction of single-stranded regions in RNA secondary structure and application to predicting effective antisense target sites and beyond

Single-stranded regions in RNA secondary structure are important for RNA–RNA and RNA–protein interactions. We present a probability profile approach for the prediction of these regions based on a statistical algorithm for sampling RNA secondary structures. For the prediction of phylogenetically-determined single-stranded regions in secondary structures of representative RNA sequences, the probability profile offers substantial improvement over the minimum free energy structure. In designing antisense oligonucleotides, a practical problem is how to select a secondary structure for the target mRNA from the optimal structure(s) and many suboptimal structures with similar free energies. By summarizing the information from a statistical sample of probable secondary structures in a single plot, the probability profile not only presents a solution to this dilemma, but also reveals ‘well-determined’ single-stranded regions through the assignment of probabilities as measures of confidence in predictions. In antisense application to the rabbit β-globin mRNA, a significant correlation between hybridization potential predicted by the probability profile and the degree of inhibition of in vitro translation suggests that the probability profile approach is valuable for the identification of effective antisense target sites. Coupling computational design with DNA–RNA array technique provides a rational, efficient framework for antisense oligonucleotide screening. This framework has the potential for high-throughput applications to functional genomics and drug target validation.     

RNA pull-down confocal nanoscanning (RP-CONA) detects quercetin as pri-miR-7/HuR interaction inhibitor that decreases α-synuclein levels

RNA–protein interactions are central to all gene expression processes and contribute to a variety of human diseases. Therapeutic approaches targeting RNA–protein interactions have shown promising effects on some diseases that are previously regarded as ‘incurable’. Here, we developed a fluorescent on-bead screening platform, RNA Pull-Down COnfocal NAnoscanning (RP-CONA), to identify RNA–protein interaction modulators in eukaryotic cell extracts. Using RP-CONA, we identified small molecules that disrupt the interaction between HuR, an inhibitor of brain-enriched miR-7 biogenesis, and the conserved terminal loop of pri-miR-7–1. Importantly, miR-7′s primary target is an mRNA of α-synuclein, which contributes to the aetiology of Parkinson’s disease. Our method identified a natural product quercetin as a molecule able to upregulate cellular miR-7 levels and downregulate the expression of α-synuclein. This opens up new therapeutic avenues towards treatment of Parkinson’s disease as well as provides a novel methodology to search for modulators of RNA–protein interaction.     

DNA phosphate crowding correlates with protein cationic side chain density and helical curvature in protein/DNA crystal structures

Sequence-specific binding of proteins to their DNA targets involves a complex spectrum of processes that often induce DNA conformational variation in the bound complex. The forces imposed by protein binding that cause the helical deformations are intimately interrelated and difficult to parse or rank in importance. To investigate the role of electrostatics in helical deformation, we quantified the relationship between protein cationic residue density (Cpc) and DNA phosphate crowding (Cpp). The correlation between Cpc and Cpp was then calculated for a subset of 58 high resolution protein–DNA crystal structures. Those structures containing strong Cpc/Cpp correlation (>±0.25) were likely to contain DNA helical curvature. Further, the correlation factor sign predicted the direction of helical curvature with positive (16 structures) and negative (seven structures) correlation containing concave (DNA curved toward protein) and convex (DNA curved away from protein) curvature, respectively. Protein–DNA complexes without significant Cpc/Cpp (36 structures) correlation (-0.25<0<0.25) tended to contain DNA without significant curvature. Interestingly, concave and convex complexes also include more arginine and lysine phosphate contacts, respectively, whereas linear complexes included essentially equivalent numbers of Lys/Arg phosphate contacts. Together, these findings suggest an important role for electrostatic interactions in protein–DNA complexes involving helical curvature.     

Protein and drug interactions in the minor groove of DNA

Interactions between proteins, drugs, water and B-DNA minor groove have been analyzed in crystal structures of 60 protein–DNA and 14 drug–DNA complexes. It was found that only purine N3, pyrimidine O2, guanine N2 and deoxyribose O4′ are involved in the interactions, and that contacts to N3 and O2 are most frequent and more polar than contacts to O4′. Many protein contacts are mediated by water, possibly to increase the DNA effective surface. Fewer water-mediated contacts are observed in drug complexes. The distributions of ligands around N3 are significantly more compact than around O2, and distributions of water molecules are the most compact. Distributions around O4′ are more diffuse than for the base atoms but most distributions still have just one binding site. Ligands bind to N3 and O2 atoms in analogous positions, and simultaneous binding to N3 and N2 in guanines is extremely rare. Contacts with two consecutive nucleotides are much more frequent than base–sugar contacts within one nucleotide. The probable reason for this is the large energy of deformation of hydrogen bonds for the one nucleotide motif. Contacts of Arg, the most frequent amino acid ligand, are stereochemically indistinguishable from the binding of the remaining amino acids except asparagine (Asn) and phenylalanine (Phe). Asn and Phe bind in distinct ways, mostly to a deformed DNA, as in the complexes of TATA-box binding proteins. DNA deformation concentrates on dinucleotide regions with a distinct deformation of the δ and backbone torsion angles for the Asn and δ, , ζ and χ for the Phe-contacted regions.     

Genome-Wide Double-Stranded RNA Sequencing Reveals the Functional Significance of Base-Paired RNAs in Arabidopsis

The functional structure of all biologically active molecules is dependent on intra- and inter-molecular interactions. This is especially evident for RNA molecules whose functionality, maturation, and regulation require formation of correct secondary structure through encoded base-pairing interactions. Unfortunately, intra- and inter-molecular base-pairing information is lacking for most RNAs. Here, we marry classical nuclease-based structure mapping techniques with high-throughput sequencing technology to interrogate all base-paired RNA in Arabidopsis thaliana and identify ∼200 new small (sm)RNA–producing substrates of RNA–DEPENDENT RNA POLYMERASE6. Our comprehensive analysis of paired RNAs reveals conserved functionality within introns and both 5′ and 3′ untranslated regions (UTRs) of mRNAs, as well as a novel population of functional RNAs, many of which are the precursors of smRNAs. Finally, we identify intra-molecular base-pairing interactions to produce a genome-wide collection of RNA secondary structure models. Although our methodology reveals the pairing status of RNA molecules in the absence of cellular proteins, previous studies have demonstrated that structural information obtained for RNAs in solution accurately reflects their structure in ribonucleoprotein complexes. Furthermore, our identification of RNA–DEPENDENT RNA POLYMERASE6 substrates and conserved functional RNA domains within introns and both 5′ and 3′ untranslated regions (UTRs) of mRNAs using this approach strongly suggests that RNA molecules are correctly folded into their secondary structure in solution. Overall, our findings highlight the importance of base-paired RNAs in eukaryotes and present an approach that should be widely applicable for the analysis of this key structural feature of RNA.     

Inferring primase-DNA specific recognition using a data driven approach

DNA–protein interactions play essential roles in all living cells. Understanding of how features embedded in the DNA sequence affect specific interactions with proteins is both challenging and important, since it may contribute to finding the means to regulate metabolic pathways involving DNA–protein interactions. Using a massive experimental benchmark dataset of binding scores for DNA sequences and a machine learning workflow, we describe the binding to DNA of T7 primase, as a model system for specific DNA–protein interactions. Effective binding of T7 primase to its specific DNA recognition sequences triggers the formation of RNA primers that serve as Okazaki fragment start sites during DNA replication.     

Incorporation of thio-pseudoisocytosine into triplex-forming peptide nucleic acids for enhanced recognition of RNA duplexes

Peptide nucleic acids (PNAs) have been developed for applications in biotechnology and therapeutics. There is great potential in the development of chemically modified PNAs or other triplex-forming ligands that selectively bind to RNA duplexes, but not single-stranded regions, at near-physiological conditions. Here, we report on a convenient synthesis route to a modified PNA monomer, thio-pseudoisocytosine (L), and binding studies of PNAs incorporating the monomer L. Thermal melting and gel electrophoresis studies reveal that L-incorporated 8-mer PNAs have superior affinity and specificity in recognizing the duplex region of a model RNA hairpin to form a pyrimidine motif major-groove RNA₂–PNA triplex, without appreciable binding to single-stranded regions to form an RNA–PNA duplex or, via strand invasion, forming an RNA–PNA₂ triplex at near-physiological buffer condition. In addition, an L-incorporated 8-mer PNA shows essentially no binding to single-stranded or double-stranded DNA. Furthermore, an L-modified 6-mer PNA, but not pseudoisocytosine (J) modified or unmodified PNA, binds to the HIV-1 programmed −1 ribosomal frameshift stimulatory RNA hairpin at near-physiological buffer conditions. The stabilization of an RNA₂–PNA triplex by L modification is facilitated by enhanced van der Waals contacts, base stacking, hydrogen bonding and reduced dehydration energy. The destabilization of RNA–PNA and DNA–PNA duplexes by L modification is due to the steric clash and loss of two hydrogen bonds in a Watson–Crick-like G–L pair. An RNA₂–PNA triplex is significantly more stable than a DNA₂–PNA triplex, probably because the RNA duplex major groove provides geometry compatibility and favorable backbone–backbone interactions with PNA. Thus, L-modified triplex-forming PNAs may be utilized for sequence-specifically targeting duplex regions in RNAs for biological and therapeutic applications.     

Dimeric assembly of human Suv3 helicase promotes its RNA unwinding function in mitochondrial RNA degradosome for RNA decay

Human Suv3 is a unique homodimeric helicase that constitutes the major component of the mitochondrial degradosome to work cooperatively with exoribonuclease PNPase for efficient RNA decay. However, the molecular mechanism of how Suv3 is assembled into a homodimer to unwind RNA remains elusive. Here, we show that dimeric Suv3 preferentially binds to and unwinds DNA–DNA, DNA–RNA, and RNA–RNA duplexes with a long 3′ overhang (≥10 nucleotides). The C‐terminal tail (CTT)‐truncated Suv3 (Suv3ΔC) becomes a monomeric protein that binds to and unwinds duplex substrates with ~six to sevenfold lower activities relative to dimeric Suv3. Only dimeric Suv3, but not monomeric Suv3ΔC, binds RNA independently of ATP or ADP, and is capable of interacting with PNPase, indicating that dimeric Suv3 assembly ensures its continuous association with RNA and PNPase during ATP hydrolysis cycles for efficient RNA degradation. We further determined the crystal structure of the apo‐form of Suv3ΔC, and SAXS structures of dimeric Suv3 and PNPase–Suv3 complex, showing that dimeric Suv3 caps on the top of PNPase via interactions with S1 domains, and forms a dumbbell‐shaped degradosome complex with PNPase. Overall, this study reveals that Suv3 is assembled into a dimeric helicase by its CTT for efficient and persistent RNA binding and unwinding to facilitate interactions with PNPase, promote RNA degradation, and maintain mitochondrial genome integrity and homeostasis.     

Identification of antisense RNA stem–loops that inhibit RNA–protein interactions using a bacterial reporter system

Many well-characterized examples of antisense RNAs from prokaryotic systems involve hybridization of the looped regions of stem–loop RNAs, presumably due to the high thermodynamic stability of the resulting loop–loop and loop–linear interactions. In this study, the identification of RNA stem–loops that inhibit U1A protein binding to the hpII RNA through RNA–RNA interactions was attempted using a bacterial reporter system based on phage λ N-mediated antitermination. As a result, loop sequences possessing 7–8 base complementarity to the 5′ region of the boxA element important for functional antitermination complex formation, but not the U1 hpII loop, were identified. In vitro and in vivo mutational analysis strongly suggested that the selected loop sequences were binding to the boxA region, and that the structure of the antisense stem–loop was important for optimal inhibitory activity. Next, in an attempt to demonstrate the ability to inhibit the interaction between the U1A protein and the hpII RNA, the rational design of an RNA stem–loop that inhibits U1A-binding to a modified hpII was carried out. Moderate inhibitory activity was observed, showing that it is possible to design and select antisense RNA stem–loops that disrupt various types of RNA–protein interactions.     

Fragment-based modelling of single stranded RNA bound to RNA recognition motif containing proteins

Protein-RNA complexes are important for many biological processes. However, structural modeling of such complexes is hampered by the high flexibility of RNA. Particularly challenging is the docking of single-stranded RNA (ssRNA). We have developed a fragment-based approach to model the structure of ssRNA bound to a protein, based on only the protein structure, the RNA sequence and conserved contacts. The conformational diversity of each RNA fragment is sampled by an exhaustive library of trinucleotides extracted from all known experimental protein–RNA complexes. The method was applied to ssRNA with up to 12 nucleotides which bind to dimers of the RNA recognition motifs (RRMs), a highly abundant eukaryotic RNA-binding domain. The fragment based docking allows a precise de novo atomic modeling of protein-bound ssRNA chains. On a benchmark of seven experimental ssRNA–RRM complexes, near-native models (with a mean heavy-atom deviation of <3 Å from experiment) were generated for six out of seven bound RNA chains, and even more precise models (deviation < 2 Å) were obtained for five out of seven cases, a significant improvement compared to the state of the art. The method is not restricted to RRMs but was also successfully applied to Pumilio RNA binding proteins.