RNA-protein Interactions Research Articles

The structure and dynamics of a fully packaged RNA virus.

The vast majority of known viruses that infect humans have their genetic program written in molecules of RNA. Such RNA viruses are thought to attain their final, mature form via self-assembly of individual capsid proteins directed by specific interactions with the RNA genome. Despite tremendous amount of experimental information about the average structure of the protein capsids, much less is known about the structure and dynamics of the RNA genomes. Here, we characterized the structure, dynamics and ion atmosphere in a bacteriophage MS2 virus using all-atom molecular dynamics simulations. Starting from available experimental information, we built a computational model of a mature MS2 virion containing a 3569 nucleotide RNA genome enclosed inside a mature protein capsid that in turn consists of a single maturation protein embedded within an icosahedral lattice of the protein capsid. Our two 2.5-microsecond replica simulations of the complete virion differing by the initial configurations of the RNA genome revealed the stabilizing effect of the RNA—protein interactions on the structure of the mature capsid and on the conformation of the RNA genome. The virus particle as a whole was observed to undergo a breathing-like motion, whereas parts of the RNA genome not bound specifically to the protein capsid explored a range of structural transformations while retaining their secondary structure. A set of simulations performed upon removal of the RNA genome characterized the effect of the RNA on the internal pressure in the virus and on its ion atmosphere. Taken together, our work introduces a mature viral particle as a system of high dynamic complexity where repulsive RNA-RNA interactions compete with specific RNA-protein binding, with the ion atmosphere serving as intermolecular glue holding the assembly together.

Physical determinants of multiphase organisation in multi-component protein/RNA condensates

The formation of biomolecular condensates via phase separation achieves spatiotemporal organisation within the cell by creating intracellular microenvironments that contribute to the regulation of chemical reactions. Internal subcompartmentalisation of biomolecules to form multiphase architectures has been observed in a number of biomolecular condensates, where immiscible liquid-like phases with different compositions coexist within the same compartment. Understanding the biophysical mechanisms that drive the formation of multiphase condensates is highly desirable since these condensates are responsible for mediating many fundamental biological processes. Here, we couple a genetic algorithm to our residue-resolution coarse-grained model, Mpipi, to evolve two-component protein mixtures towards increasing multiphasicity (i.e., demixing into two compositionally distinct liquid-like phases). Given a target protein, our method allows us to predict a partner protein that supports multiphasic compartmentalisation and investigate the underlying thermodynamics of the multiphasicity. We find that the balance of homo- and heterotypic interaction energies between the two components is important for controlling multiphase organisation: a large difference between homotypic interactions of the two components favours demixing, and the strength of heterotypic interactions should be small but comparable to that of the weaker homotypic interactions for multilayered condensates to form. Our approach for designing multilayered condensates achieves this balance of interaction energies by optimising the composition and patterning of the protein sequences. Lastly, since many multiphase condensates in cells contain RNA, we extend our approach to include RNA as a third component and investigate the role of protein-RNA interactions in stabilising condensates and multilayered architectures.

Demixing of distinct ribonucleoprotein condensates is under dynamical control.

Whi3 is an RNA binding protein from Ashbya gossypii that phase separates to form RNA-protein condensates. Observations in cells show that certain RNA molecules co-localize with Whi3 and other RNA molecules into a single condensate, while some others form apparently demixed condensates. Is a there a thermodynamic basis for different ternary combinations of Whi3 and RNA molecules to form demixed condensates? Simulations show that RNA molecules must have strong repulsive interactions for one another, or strong homotypic interactions if demixing is to be thermodynamically feasible. We tested this using in vitro reconstitutions to quantify the phase behaviors of binary and ternary mixtures. A novel analysis of the measured phase boundaries show that heterotypic protein-RNA interactions are the main drivers of phase separation. This was further tested by deletion of cognate binding sites on RNA molecules, showing that there are several ways for Whi3 to associate with RNA molecules. Investigations of phase behaviors internary mixtures show that demixed condensates are dynamically arrested phases. Therefore, in vitro studies suggest that demixing is likely to be under dynamical rather than thermodynamic control. To test for this in live cells, we generated a mutant where differentially expressed RNAs are constitutively expressed under a single promoter. We find that RNA molecules that demix in a wildtype background formed colocalized condensates when they are expressed concomitantly. Our studies show that the non-equilibrium aspects of phase separation, specifically the ability to form dynamically arrested phases, can give rise to demixed condensates that achieve long-livedspatial segregation of RNA molecules within distinct condensates.

RNA structure directs the targeting specificity of Cas13d.

Type VI CRISPR enzymes exclusively bind and cleave target RNAs, and are widely used for gene regulation, RNA tracking, and diagnostics. However, a systematic understanding of their RNA binding specificity is lacking. Here, we describe RNA-CHAMP, a massively parallel platform that repurposes used next-generation DNA sequencing chips to measures the binding affinity for >10,000 RNA targets containing structural perturbations, mismatches, insertions, and deletions relative to the guide RNA. We profile the RNA binding specificity of Cas13d, a compact and widely used RNA nuclease. Contrary to other type VI CRISPR enzymes, Cas13d does not have a protospacer flanking sequence (PFS) preference. Cas13d tolerates mismatches, insertions, and deletions, but is exquisitely sensitive to secondary structure within the target RNA. Basepairing in the distal region of the target RNA strongly decreases Cas13d binding, whereas structuring the first six nucleotides inhibits nuclease activity without impacting binding. A biophysical model built from these data reveals that target recognition begins at the distal end of unstructured target RNAs and proceeds to the proximal end with limited RNA melting. Using this model, we design a series of partially mismatched guide RNAs that modulate nuclease activity to detect single nucleotide polymorphisms (SNPs) in circulating SARS-CoV-2 variants. This work describes the key determinants of RNA targeting by a type VI CRISPR enzyme to improve RNA targeting and CRISPR diagnostics. More broadly, RNA-CHAMP provides a quantitative platform for systematically measuring protein-RNA interactions.

Protein-RNA interactions of FMRP and CCND1: Implications of regulation in neurogenesis.

While originally discovered in the 1960s, adult neurogenesis, the production of mature neurons from neuronal stem cells in adults, has become largely accepted by the field only in the 1990s. Thus, the detailed mechanisms of its regulation remain elusive, requiring further characterization of the protein players involved in this process. Cyclin-D1, a regulatory subunit of cyclin-dependent kinases involved in monitoring entry into the cell cycle, has been identified as a key factor in adult neurogenesis and is encoded by the CCND1 gene. Another identified component of this process is the Fragile X messenger ribonucleoprotein (FMRP), an RNA-binding protein associated with translational regulation. Interestingly, FMRP has been shown to regulate cyclin-D1 expression, emphasizing a potential interplay between FMRP function and cyclin-D1 expression in neurons. FMRP has shown high affinity binding for guanine quadruplex (GQ) forming RNAs. We identified that CCND1 mRNA has a G-rich region in its 3’-untranslated region that has the potential to form GQ structures, and thus possibly interacting with FMRP through the recognition of these structures. To elucidate the presence of a GQ in the CCND1 mRNA, we used biophysical methods, such as 1H NMR, UV thermal denaturation, CD spectroscopy, and native polyacrylamide gel electrophoresis (PAGE). This study effectively characterizes a GQ in the 3’UTR of the CCND1 mRNA and its interactions with FMRP, providing insight on additional regulatory mechanisms of adult neurogenesis and guiding development of novel therapeutic methods.

Protein behavior depends on their conformation in viscoelastic droplet.

Intrinsically disordered proteins (IDPs) play an important role in phase separation and are known to form membraneless organelles such as stress granules. Membraneless organelles are known to be involved in cell function and disease. Since the protein-protein interaction and protein conformation are known to be the main factor affecting the dynamics of proteins, it is important to clarify the dynamics and interactions of protein at the nanoscale. In this research, using coarse-grained molecular dynamics simulation, we investigate the conformational dependence of protein behavior in viscoelastic droplets. Moreover, we also used mixed protein-RNA systems to investigate protein-RNA interactions and the effects of the presence of RNA on protein dynamics.

Atlas of interactions between SARS-CoV-2 macromolecules and host proteins.

The proteins and RNAs of viruses extensively interact with host proteins after infection. We collected and reanalyzed all available datasets of protein-protein and RNA-protein interactions related to SARS-CoV-2. We investigated the reproducibility of those interactions and made strict filters to identify highly confident interactions. We systematically analyzed the interaction network and identified preferred subcellular localizations of viral proteins, some of which such as ORF8 in ER and ORF7A/B in ER membrane were validated using dual fluorescence imaging. Moreover, we showed that viral proteins frequently interact with host machinery related to protein processing in ER and vesicle-associated processes. Integrating the protein- and RNA-interactomes, we found that SARS-CoV-2 RNA and its N protein closely interacted with stress granules including 40 core factors, of which we specifically validated G3BP1, IGF2BP1, and MOV10 using RIP and Co-IP assays. Combining CRISPR screening results, we further identified 86 antiviral and 62 proviral factors and associated drugs. Using network diffusion, we found additional 44 interacting proteins including two proviral factors previously validated. Furthermore, we showed that this atlas could be applied to identify the complications associated with COVID-19. All data are available in the AIMaP database (https://mvip.whu.edu.cn/aimap/) for users to easily explore the interaction map.

Web tools support predicting protein-nucleic acid complexes stability with affinity changes.

Numerous biological processes, such as transcription, replication, and translation, rely on protein-nucleic acid interactions (PNIs). Demonstrating the binding stability of protein-nucleic acid complexes is vital to deciphering the code for PNIs. Numerous web-based tools have been developed to attach importance to protein-nucleic acid stability, facilitating the prediction of PNIs characteristics rapidly. However, the data and tools are dispersed and lack comprehensive integration to understand the stability of PNIs better. In this review, we first summarize existing databases for evaluating the stability of protein-nucleic acid binding. Then, we compare and evaluate the pros and cons of web tools for forecasting the interaction energies of protein-nucleic acid complexes. Finally, we discuss the application of combining models and capabilities of PNIs. We may hope these web-based tools will facilitate the discovery of recognition mechanisms for protein-nucleic acid binding stability. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Protein-RNA Recognition RNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications.

Targeting RNA:protein interactions with an integrative approach leads to the identification of potent YBX1 inhibitors.

RNA-protein interactions (RPIs) are promising targets for developing new molecules of therapeutic interest. Nevertheless, challenges arise from the lack of methods and feedback between computational and experimental techniques during the drug discovery process. Here, we tackle these challenges by developing a drug screening approach that integrates chemical, structural and cellular data from both advanced computational techniques and a method to score RPIs in cells for the development of small RPI inhibitors; and we demonstrate its robustness by targeting Y-box binding protein 1 (YB-1), a messenger RNA-binding protein involved in cancer progression and resistance to chemotherapy. This approach led to the identification of 22 hits validated by molecular dynamics (MD) simulations and nuclear magnetic resonance (NMR) spectroscopy of which 11 were found to significantly interfere with the binding of messenger RNA (mRNA) to YB-1 in cells. One of our leads is an FDA-approved poly(ADP-ribose) polymerase 1 (PARP-1) inhibitor. This work shows the potential of our integrative approach and paves the way for the rational development of RPI inhibitors.

The DNA binding high mobility group box protein family functionally binds RNA.

Nucleic acid binding proteins regulate transcription, splicing, RNA stability, RNA localization, and translation, together tailoring gene expression in response to stimuli. Upon discovery, these proteins are typically classified as either DNA or RNA binding as defined by their in vivo functions; however, recent evidence suggests dual DNA and RNA binding by many of these proteins. High mobility group box (HMGB) proteins have a DNA binding HMGB domain, act as transcription factors and chromatin remodeling proteins, and are increasingly understood to interact with RNA as means to regulate gene expression. Herein, multiple layers of evidence that the HMGB family are dual DNA and RNA binding proteins is comprehensively reviewed. For example, HMGB proteins directly interact with RNA in vitro and in vivo, are localized to RNP granules involved in RNA processing, and their protein interactors are enriched in RNA binding proteins involved in RNA metabolism. Importantly, in cell-based systems, HMGB-RNA interactions facilitate protein-protein interactions, impact splicing outcomes, and modify HMGB protein genomic or cellular localization. Misregulation of these HMGB-RNA interactions are also likely involved in human disease. This review brings to light that as a family, HMGB proteins are likely to bind RNA which is essential to HMGB protein biology. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Protein-RNA Recognition RNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications.

High-throughput biochemistry in RNA sequence space: predicting structure and function.

RNAs are central to fundamental biological processes in all known organisms. The set of possible intramolecular interactions of RNA nucleotides defines the range of alternative structural conformations of a specific RNA that can coexist, and these structures enable functional catalytic properties of RNAs and/or their productive intermolecular interactions with other RNAs or proteins. However, the immense combinatorial space of potential RNA sequences has precluded predictive mapping between RNA sequence and molecular structure and function. Recent advances in high-throughput approaches in vitro have enabled quantitative thermodynamic and kinetic measurements of RNA-RNA and RNA-protein interactions, across hundreds of thousands of sequence variations. In this Review, we explore these techniques, how they can be used to understand RNA function and how they might form the foundations of an accurate model to predict the structure and function of an RNA directly from its nucleotide sequence. The experimental techniques and modelling frameworks discussed here are also highly relevant for the sampling of sequence-structure-function space of DNAs and proteins.

The emerging roles of circRNAs in traits associated with livestock breeding.

Many indicators can be used to evaluate the productivity and quality of livestock, such as meat and milk production as well as fat deposition. Meat and milk production are measures of livestock performance, while fat deposition affects the taste and flavor of the meat. The circRNAs, are non-coding RNAs, that are involved in the regulation of all these three traits. We review the functions and mechanisms of circRNAs in muscle and fat development as well as lactation to provide a theoretical basis for circRNA research in animal husbandry. Various phenotypic changes presented in livestock may be produced by different circRNAs. Our current concern is how to use the roles played by circRNAs to our advantage to produce the best possible livestock. Hence, we describe the advantages and disadvantages of knockout techniques for circRNAs. In addition, we also put forward our thoughts regarding the mechanism and network of circRNAs to provide researchers with novel ideas of how molecular biology can help us advance our goals in animal farming. This article is categorized under: RNA in Disease and Development > RNA in Disease RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications RNA Interactions with Proteins and Other Molecules > Protein-RNA Recognition RNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes.

A computational map of the human-SARS-CoV-2 protein-RNA interactome predicted at single-nucleotide resolution.

RNA-binding proteins (RBPs) are critical host factors for viral infection, however, large scale experimental investigation of the binding landscape of human RBPs to viral RNAs is costly and further complicated due to sequence variation between viral strains. To fill this gap, we investigated the role of RBPs in the context of SARS-CoV-2 by constructing the first in silico map of human RBP-viral RNA interactions at nucleotide-resolution using two deep learning methods (pysster and DeepRiPe) trained on data from CLIP-seq experiments on more than 100 human RBPs. We evaluated conservation of RBP binding between six other human pathogenic coronaviruses and identified sites of conserved and differential binding in the UTRs of SARS-CoV-1, SARS-CoV-2 and MERS. We scored the impact of mutations from 11 variants of concern on protein-RNA interaction, identifying a set of gain- and loss-of-binding events, as well as predicted the regulatory impact of putative future mutations. Lastly, we linked RBPs to functional, OMICs and COVID-19 patient data from other studies, and identified MBNL1, FTO and FXR2 RBPs as potential clinical biomarkers. Our results contribute towards a deeper understanding of how viruses hijack host cellular pathways and open new avenues for therapeutic intervention.

Genetically Encoded RNA-Based Bioluminescence Resonance Energy Transfer (BRET) Sensors.

RNA-based nanostructures and molecular devices have become popular for developing biosensors and genetic regulators. These programmable RNA nanodevices can be genetically encoded and modularly engineered to detect various cellular targets and then induce output signals, most often a fluorescence readout. Although powerful, the high reliance of fluorescence on the external excitation light raises concerns about its high background, photobleaching, and phototoxicity. Bioluminescence signals can be an ideal complementary readout for these genetically encoded RNA nanodevices. However, RNA-based real-time bioluminescent reporters have been rarely developed. In this study, we reported the first type of genetically encoded RNA-based bioluminescence resonance energy transfer (BRET) sensors that can be used for real-time target detection in living cells. By coupling a luciferase bioluminescence donor with a fluorogenic RNA-based acceptor, our BRET system can be modularly designed to image and detect various cellular analytes. We expect that this novel RNA-based bioluminescent system can be potentially used broadly in bioanalysis and nanomedicine for engineering biosensors, characterizing cellular RNA-protein interactions, and high-throughput screening or in vivo imaging.

Streamlined Purification of RNA-Protein Complexes Using UV Cross-Linking and RNA Antisense Purification.

RNA-protein interactions are important in development and disease, but identification of novel RNA-protein interactions remains challenging. Here, we describe an updated capture method to identify direct and specific RNA-protein interactions. First, RNA and protein are covalently cross-linked in living cells by treatment with UV light at 254 nanometers wavelength. The antisense purification approach is dependent upon nucleic acid hybridization between biotinylated DNA probes and a target RNA. Target protein:RNA:DNA complexes are enriched by capture on streptavidin magnetic beads and purified through several denaturing washes that remove nonspecific protein and nucleic acid interactors. Mass spectrometry is used to identify proteins that are specifically enriched in the target RNA capture. This method has been applied to discover the protein interactions of noncoding RNAs but can be used to capture any RNA where the target sequence is known.

Fluorescent In Situ Detection of RNA-Protein Interactions in Intact Cells by RNA-PLA.

RNA-protein proximity ligation assay (RNA-PLA) enables the detection of specific RNA-protein interactions in fixed cells. In RNA-PLA, bridging and ligation of a circular DNA template occurs if the target RNA and protein are within 40 nanometers of each other. The resulting circular template is amplified by rolling circle amplification and abundantly recognized by fluorescent antisense DNA oligonucleotides. This strategy therefore enables localization of RNA-protein interactions in situ with high specificity and sensitivity. Here, we describe the use of RNA-PLA to detect interactions between a nuclear viral RNA and a host RNA-binding protein in Epstein-Barr virus (EBV)-infected B cells.

Revised iCLIP-seq Protocol for Profiling RNA-protein Interaction Sites at Individual Nucleotide Resolution in Living Cells.

Individual nucleotide resolution UV cross-linking and immunoprecipitation followed by high-throughput sequencing (iCLIP-seq) is a powerful technique that is used to identify RNA-binding proteins' (RBP) binding sites on target RNAs and to characterize the molecular basis of posttranscriptional regulatory pathways. Several variants of CLIP have been developed to improve its efficiency and simplify the protocol [e.g., iCLIP2 and enhanced CLIP (eCLIP)]. We have recently reported that transcription factor SP1 functions in the regulation of alternative cleavage and polyadenylation through direct RNA binding. We utilized a modified iCLIP method to identify RNA-binding sites for SP1 and several of the cleavage and polyadenylation complex subunits, including CFIm25, CPSF7, CPSF100, CPSF2, and Fip1. Our revised protocol takes advantage of several features of the eCLIP procedure and also improves on certain steps of the original iCLIP method, including optimization of circularization of cDNA. Herein, we describe a step-by-step procedure for our revised iCLIP-seq protocol, that we designate as iCLIP-1.5, and provide alternative approaches for certain difficult-to-CLIP proteins. Key features Identification of RNA-binding sites of RNA-binding proteins (RBPs) at nucleotide resolution. iCLIP-seq provides precise positional and quantitative information on the RNA-binding sites of RBPs in living cells. iCLIP facilitates the identification of sequence motifs recognized by RBPs. Allows quantitative analysis of genome-wide changes in protein-RNA interactions. Revised iCLIP-1.5 protocol is more efficient and highly robust; it provides higher coverage even for low-input samples. Graphical overview.

Into the Microscale: Low-input sequencing technologies and applications in medicine

<p>Sequencing technology has undergone major breakthroughs over time and has become indispensable in biological and medical research. Advances in protocols and analysis algorithms allow the analysis of small sample inputs, enabling the characterization of complex networks that govern biological processes in physiology and pathology, driving the development of precision medicine and targeted therapy. In this review, we comprehensively summarize low-input sequencing technologies that include methods for profiling the genome, epigenome, transcriptome, translatome, RNA modification, RNA-RNA interaction, RNA-protein interaction, and multi-omics. The key steps and innovations in different protocols are highlighted, and their advantages, limitations, and scope of application are described. With a focus on the impact of low-input sequencing technologies in biomedical fields, including embryonic development, prenatal and preimplantation genetic testing, oncology and immunology, and pandemic research, we discuss their potential to improve embryo implantation rates, prevent birth defects, develop prospective therapies, and predict prognosis. Lastly, we discuss current limitations and future prospects, providing new insights for medical research.</p>

SHAPE to Probe RNA Structure and RNA-Protein Interactions In Vitro.

Selective 2' hydroxyl acylation analyzed by primer extension (SHAPE) is used to distinguish between the levels of flexibility of nucleotides regulated by base pairing or protein binding. In this method, a reagent reacts with the 2' hydroxyl group to form an adduct, which is then detected by reverse transcription reaction. The number of RNA molecules with an adduct at a specific nucleotide position indicates the SHAPE reactivity of that nucleotide. Here, we describe the method for probing the structure of an RNA in a protein-free or a protein-bound state by in vitro SHAPE.

Analyzing RNA-Protein Interactions by Cross-Link Rates and CLIP-seq Libraries.

UV cross-linking-based methods are the most common tool to explore in vivo RNA-protein interactions. UV cross-linking enables the freezing of direct interactions in the cell, which can then be mapped by high-throughput sequencing through a family of methods termed CLIP-seq. CLIP-seq measures the distribution of cross-link events by purifying a protein of interest and sequencing the covalently bound RNA fragments. However, there are disagreements and ambiguities as to which proteins are RNA-binding proteins and what interactions are significant as all proteins contact all RNAs at some frequency. Here we describe a protocol for both determining RNA-protein interactions through a combination of RNA library preparation and the measurement of absolute cross-link rates, which helps determine what proteins are RNA-binding proteins and what interactions are significant. This protocol, comprising an updated form of the easyCLIP protocol, describes guidelines for RNA library preparation, oligo and protein standard construction, and the measurement of cross-link rates. These methods are easily visualizable through their fluorescent labels and can be adapted to study RNA-binding properties of both functional, high affinity RNA-binding proteins, and the accidental RNA interactions of non-RNA-binding proteins. © 2023 Wiley Periodicals LLC. Basic Protocol 1: RNA library construction Basic Protocol 2: Determining UV cross-link rates Support Protocol 1: Cross-linking and lysing cells Support Protocol 2: Adapter preparation Support Protocol 3: Preparation of cross-linked RBP standard.