Analyzing mRNA-protein complexes using a yeast three-hybrid system

RNA-protein interactions are essential for the proper execution and regulation of every step in the life of a eukaryotic mRNA. Here we describe a three-hybrid system in which RNA-protein interactions can be analyzed using simple phenotypic or enzymatic assays in Saccharomyces cerevisiae. The system can be used to detect or confirm an RNA-protein interaction, to analyze RNA-protein interactions genetically, and to discover new protein or RNA partners when only one is known. Multicomponent complexes containing more than one protein can be detected, identified, and analyzed. We describe the method and how to use it, and discuss applications that bear particularly on eukaryotic mRNAs.     

Stacking interactions in PUF-RNA complexes

Stacking interactions between amino acids and bases are common in RNA-protein interactions. Many proteins that regulate mRNAs interact with single-stranded RNA elements in the 3' UTR (3'-untranslated region) of their targets. PUF proteins are exemplary. Here we focus on complexes formed between a Caenorhabditis elegans PUF protein, FBF, and its cognate RNAs. Stacking interactions are particularly prominent and involve every RNA base in the recognition element. To assess the contribution of stacking interactions to formation of the RNA-protein complex, we combine in vivo selection experiments with site-directed mutagenesis, biochemistry, and structural analysis. Our results reveal that the identities of stacking amino acids in FBF affect both the affinity and specificity of the RNA-protein interaction. Substitutions in amino acid side chains can restrict or broaden RNA specificity. We conclude that the identities of stacking residues are important in achieving the natural specificities of PUF proteins. Similarly, in PUF proteins engineered to bind new RNA sequences, the identity of stacking residues may contribute to "target" versus "off-target" interactions, and thus be an important consideration in the design of proteins with new specificities.     

A microbead-based system for identifying and characterizing RNA-protein interactions by flow cytometry

We present a high throughput, versatile approach to identify RNA-protein interactions and to determine nucleotides important for specific protein binding. In this approach, oligonucleotides are coupled to microbeads and hybridized to RNA-protein complexes. The presence or absence of RNA and/or protein fluorescence indicates the formation of an oligo-RNA-protein complex on each bead. The observed fluorescence is specific for both the hybridization and the RNA-protein interaction. We find that the method can discriminate noncomplementary and mismatch sequences. The observed fluorescence reflects the affinity and specificity of the RNA-protein interaction. In addition, the fluorescence patterns footprint the protein recognition site to determine nucleotides important for protein binding. The system was developed with the human protein U1A binding to RNAs derived from U1 snRNA but can also detect RNA-protein interactions in total RNA backgrounds. We propose that this strategy, in combination with emerging coded bead systems, can identify RNAs and RNA sequences important for interacting with RNA-binding proteins on genomic scales.     

A liquid synchronized-growth culture assay for the identification of true positive and negative yeast three-hybrid transformants

AIMS: To develop a simple and easy-to-use assay for detection of truely positive transformants from a yeast three-hybrid assay. METHODS AND RESULTS: The yeast three-hybrid system is a new powerful system for studying RNA-protein interactions in vivo. There are, however, many reports from investigators about the difficulty in distinguishing a positive from a negative result due to the hard-to-detect differences between truely positive transformants and the negative ones. A liquid synchronous-growth culture approach has been described for all positive and negative transformants and their growth densities have been compared to each other at fixed intervals of incubation times. We have designed a simple yet effective procedure to assay for positive and negative RNA-protein interactions based on liquid culture analysis of synchronously growing yeast cells. Results obtained from this new procedure clearly show differences in positive and negative transformants after a 24-h incubation of synchronously growing transformants in liquid culture. CONCLUSIONS: The procedure mentioned in this report shows clearly the differences between positive and negative results from a three-hybrid system. SIGNIFICANCE AND IMPACT OF THE STUDY: The method proposed here is a clear advantage over existing methods based on measuring growth on restrictive growth medium plates by the naked eye. This method will have substantial usage with investigators using the yeast three-hybrid studies for RNA-protein interactions.     

RNA as a drug target: methods for biophysical characterization and screening

RNA folds into complex structures that can interact specifically with effector proteins. These interactions are essential for various biological functions. In order to discover small molecules that can affect important RNA-protein complexes, a thorough analysis of the thermodynamics and kinetics of RNA-protein binding is required. This can facilitate the formulation of high-throughput screening strategies and the development of structure-activity relationships for compound leads. In addition to traditional methods, such as filter binding, gel mobility shift assay and various fluorescence techniques, newer methods such as surface plasmon resonance and mass spectrometry are being used for the study of RNA-protein interactions.     

RNA和蛋白质的相互作用

RNA与蛋白质的相互作用是许多基本的细胞生理过程得以实现的决定性因素.近年来,随着技术的改进和新方法的建立,RNA和蛋白质的相互作用研究取得了长足进步.目前科研人员已经鉴定了许多RNA上的蛋白质结合位点,也发现了许多蛋白质中的RNA结合结构域,并对它们的结构特征进行了比较详细的研究.这些都为最终探明RNA和蛋白质相互作用的分子机制,从而从本质上认识相关的细胞生理过程打下了坚实的基础.     

Detection of double-stranded RNA-protein interactions by methylene blue-mediated photo-crosslinking.

Double-stranded(ds) RNA-binding proteins have diverse functions in the cell. An obstacle to investigating the interactions between these proteins and dsRNA is the relative inefficiency of traditional UV-crosslinking methods for extended regions of dsRNA. We have therefore developed an alternative procedure for RNA-protein photo-crosslinking that efficiently induces RNA-protein crosslinks in double-stranded regions of RNA. We show that dsRNA-protein crosslinks can be induced by visible light in the presence of the dye methylene blue, which most likely mediates crosslinking by intercalating in the dsRNA helix. A recombinant dsRNA binding domain from the Drosophila staufen protein and human protein kinase R were crosslinked by UV or methylene blue to a series of dsRNAs. In each case, the degree of crosslinking was greater with methylene blue, particularly with RNAs with few single-stranded loops. Methylene blue-mediated crosslinking therefore complements and extends the existing repertoire of crosslinking methods for detecting RNA-protein interactions.     

Methods for comprehensive experimental identification of RNA-protein interactions

The importance of RNA-protein interactions in controlling mRNA regulation and non-coding RNA function is increasingly appreciated. A variety of methods exist to comprehensively define RNA-protein interactions. We describe these methods and the considerations required for designing and interpreting these experiments.     

Kinetic studies of RNA-protein interactions using surface plasmon resonance

Although structural, biochemical, and genetic studies have provided much insight into the determinants of specificity and affinity of proteins for RNA, little is currently known about the kinetics that underlie RNA-protein interactions. Protein-RNA complexes are dynamic, and the kinetics of binding and release could influence many processes, such as the ability of RNA-binding proteins to compete for binding sites, the sequential assembly of ribonucleoprotein complexes, and the ability of bound RNA to move between cellular compartments. Therefore, to attain a complete and biologically relevant understanding of RNA-protein interactions, complex formation must be studied not only in equilibrated reactions, but also as a dynamic process. BIACORE, a surface plasmon resonance-based biosensor technology, allows intermolecular interactions to be measured in real time, and can provide both equilibrium and kinetic information about complex formation. This technology is a powerful tool with which to study the dynamics of RNA-protein interactions. We have used BIACORE extensively to obtain detailed insight into the interaction between RNA and proteins carrying RNA recognition motif domains. Here we discuss the physical principles on which BIACORE is based, and the required instrumentation. We describe how to design well-controlled RNA-protein interaction experiments aimed at yielding high-quality data, and outline the steps required for data analysis. In addition, we present examples to illustrate how kinetic studies have provided us with unique insights into the interaction of the spliceosomal U1A protein and the neuronal HuD protein with their respective RNA targets.     

Prediction of RNA binding sites in proteins from amino acid sequence

RNA-protein interactions are vitally important in a wide range of biological processes, including regulation of gene expression, protein synthesis, and replication and assembly of many viruses. We have developed a computational tool for predicting which amino acids of an RNA binding protein participate in RNA-protein interactions, using only the protein sequence as input. RNABindR was developed using machine learning on a validated nonredundant data set of interfaces from known RNA-protein complexes in the Protein Data Bank. It generates a classifier that captures primary sequence signals sufficient for predicting which amino acids in a given protein are located in the RNA-protein interface. In leave-one-out cross-validation experiments, RNABindR identifies interface residues with >85% overall accuracy. It can be calibrated by the user to obtain either high specificity or high sensitivity for interface residues. RNABindR, implementing a Naive Bayes classifier, performs as well as a more complex neural network classifier (to our knowledge, the only previously published sequence-based method for RNA binding site prediction) and offers the advantages of speed, simplicity and interpretability of results. RNABindR predictions on the human telomerase protein hTERT are in good agreement with experimental data. The availability of computational tools for predicting which residues in an RNA binding protein are likely to contact RNA should facilitate design of experiments to directly test RNA binding function and contribute to our understanding of the diversity, mechanisms, and regulation of RNA-protein complexes in biological systems. (RNABindR is available as a Web tool from http://bindr.gdcb.iastate.edu.).     

Assembly of ribonucleoparticle complexes

RNA-proteins interactions are involved in numerous cellular functions. These interactions are found in most cases within complex macromolecular assemblies. The recent development of tools and techniques to study RNA-protein complexes has significantly increased our knowledge in the nature of these specific interactions. The aim of this article is to present the different techniques used to study RNA-protein complexes, as well as recent data concerning the application of RNA as therapeutic molecules.     

Selection of TAR RNA-binding chameleon peptides by using a retroviral replication system

The interaction between the arginine-rich motif (ARM) of the human immunodeficiency virus (HIV) Tat protein and TAR RNA is essential for Tat activation and viral replication. Two related lentiviruses, bovine immunodeficiency virus (BIV) and Jembrana disease virus (JDV), also require Tat ARM-TAR interactions to mediate activation, but the viruses have evolved different RNA-binding strategies. Interestingly, the JDV ARM can act as a "chameleon," adopting both the HIV and BIV TAR binding modes. To examine how RNA-protein interactions may evolve in a viral context and possibly to identify peptides that recognize HIV TAR in novel ways, we devised a retroviral system based on HIV replication to amplify and select for RNA binders. We constructed a combinatorial peptide library based on the BIV Tat ARM and identified peptides that, like the JDV Tat ARM, also function through HIV TAR, revealing unexpected sequence characteristics of an RNA-binding chameleon. The results suggest that a retroviral screening approach may help identify high-affinity TAR binders and may provide new insights into the evolution of RNA-protein interactions.     

A Novel Strategy for Analyzing RNA-Protein Interactions by Surface Plasmon Resonance Biosensor

Surface plasmon resonance (SPR) biosensor is a promising technology for its various advantages including the real-time measurement of biomolecular interactions without labeling. A method of hybridizing RNAs on the surface of the streptavidin-coated (SA) sensor chip to study RNA-protein interactions was described in this paper. In our study, it has been shown that the nucleocapsid (N) protein of severe acute respiratory syndrome coronavirus (SARS-CoV) has a high binding affinity for the leader sequence of SARS-CoV genome. Effect of temperature on the RNA-DNA hybridization was also examined. This method can provide the affinity of interactions with high sensitivity. Therefore, it will be useful in screening binding candidates for a given RNA target motif with one chip.     

Genome-wide identification of protein binding sites on RNAs in mammalian cells

RNA-binding proteins (RBPs) are proteins that bind to the RNA and participate in forming ribonucleoprotein complexes. They have crucial roles in various biological processes such as RNA splicing, editing, transport, maintenance, degradation, intracellular localization and translation. The RBPs bind RNA with different RNA-sequence specificities and affinities, thus, identification of protein binding sites on RNAs (R-PBSs) will deeper our understanding of RNA-protein interactions. Currently, high-throughput sequencing of RNA isolated by crosslinking immunoprecipitation (HITS-CLIP, also known as CLIP-Seq) is one of the most powerful methods to map RNA-protein binding sites or RNA modification sites. However, this method is only used for identification of single known RBPs and antibodies for RBPs are required. Here we developed a novel method, called capture of protein binding sites on RNAs (RPBS-Cap) to identify genome-wide protein binding sites on RNAs without using antibodies. Double click strategy is used for the RPBS-Cap assay. Proteins and RNAs are UV-crosslinked in vivo first, then the proteins are crosslinked to the magnetic beads. The RNA elements associated with proteins are captured, reverse transcribed and sequenced. Our approach has potential applications for studying genome-wide RNA-protein interactions.     

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.     

Prediction of functional tertiary interactions and intermolecular interfaces from primary sequence data

Given the availability of sequence information for many species, one can examine how the sequence of a gene varies among different organisms. This is accomplished by aligning the sequences and observing patterns of conservation, mutation and counter-mutation at different positions in the gene. Imbedded in these patterns is information on energetic coupling and macromolecular interactions, which can be deciphered by application of statistical algorithms. Here we report a robust approach for predicting interactions within (or between) any type of biopolymer, including proteins, RNAs and RNA-protein complexes. Rather than maximize the number of predictions, this approach is designed to detect a limited number of highly significant interactions, thereby providing accurate results from alignments that contain a modest number of sequences (20-60). The versatility and accuracy of the algorithm is demonstrated by the successful prediction of important intramolecular interactions within RNAs, modified RNAs, and proteins, as well as the prediction of RNA-protein and protein-protein interactions.