Structural Changes of RNA in Complex with Proteins in the SRP

The RNA Helicase Ded1 from Yeast Is Associated with the Signal Recognition Particle and Is Regulated by SRP21

The DEAD-box RNA helicase Ded1 is an essential yeast protein involved in translation initiation that belongs to the DDX3 subfamily. The purified Ded1 protein is an ATP-dependent RNA-binding protein and an RNA-dependent ATPase, but it was previously found to lack substrate specificity and enzymatic regulation. Here we demonstrate through yeast genetics, yeast extract pull-down experiments, in situ localization, and in vitro biochemical approaches that Ded1 is associated with, and regulated by, the signal recognition particle (SRP), which is a universally conserved ribonucleoprotein complex required for the co-translational translocation of polypeptides into the endoplasmic reticulum lumen and membrane. Ded1 is physically associated with SRP components in vivo and in vitro. Ded1 is genetically linked with SRP proteins. Finally, the enzymatic activity of Ded1 is inhibited by SRP21 in the presence of SCR1 RNA. We propose a model where Ded1 actively participates in the translocation of proteins during translation. Our results provide a new understanding of the role of Ded1 during translation.

Interactome dynamics during heat stress signal transmission and reception

Among evolved molecular mechanisms, cellular stress response to altered environmental conditions to promote survival is among the most fundamental. The presence of stress-induced unfolded or misfolded proteins and molecular registration of these events constitute early steps in cellular stress response. However, what stress-induced changes in protein conformations and protein-protein interactions within cells initiate stress response and how these features are recognized by cellular systems are questions that have remained difficult to answer, requiring new approaches. Quantitative in vivo chemical cross-linking coupled with mass spectrometry (qXL-MS) is an emerging technology that provides new insight on protein conformations, protein-protein interactions and how the interactome changes during perturbation within cells, organelles, and even tissues. In this work, qXL-MS and quantitative proteome analyses were applied to identify significant time-dependent interactome changes that occur prior to large-scale proteome abundance remodeling within cells subjected to heat stress. Interactome changes were identified within minutes of applied heat stress, including stress-induced changes in chaperone systems as expected due to altered functional demand. However, global analysis of all interactome changes revealed the largest significant enrichment in the gene ontology molecular function term of RNA binding. This group included more than 100 proteins among multiple components of protein synthesis machinery, including mRNA binding, spliceosomes, and ribosomes. These interactome data provide new conformational insight on the complex relationship that exists between transcription, translation and cellular stress response mechanisms. Moreover, stress-dependent interactome changes suggest that in addition to conformational stabilization of RNA-binding proteins, adaptation of RNA as interacting ligands offers an additional fitness benefit resultant from generally lower RNA thermal stability. As such, RNA ligands also serve as fundamental temperature sensors that signal stress through decreased conformational regulation of their protein partners as was observed in these interactome dynamics.

Profiling the polyadenylated transcriptome of extracellular vesicles with long-read nanopore sequencing

BACKGROUND

While numerous studies have described the transcriptomes of extracellular vesicles (EVs) in different cellular contexts, these efforts have typically relied on sequencing methods requiring RNA fragmentation, which limits interpretations on the integrity and isoform diversity of EV-targeted RNA populations. It has been assumed that mRNA signatures in EVs are likely to be fragmentation products of the cellular mRNA material, and the extent to which full-length mRNAs are present within EVs remains to be clarified.

RESULTS

Using long-read nanopore RNA sequencing, we sought to characterize the full-length polyadenylated (poly-A) transcriptome of EVs released by human chronic myelogenous leukemia K562 cells. We detected 443 and 280 RNAs that were respectively enriched or depleted in EVs. EV-enriched poly-A transcripts consist of a variety of biotypes, including mRNAs, long non-coding RNAs, and pseudogenes. Our analysis revealed that 10.58% of all EV reads, and 18.67% of all cellular (WC) reads, corresponded to known full-length transcripts, with mRNAs representing the largest biotype for each group (EV = 58.13%, WC = 43.93%). We also observed that for many well-represented coding and non-coding genes, diverse full-length transcript isoforms were present in EV specimens, and these isoforms were reflective-of but often in different ratio compared to cellular samples.

CONCLUSION

This work provides novel insights into the compositional diversity of poly-A transcript isoforms enriched within EVs, while also underscoring the potential usefulness of nanopore sequencing to interrogate secreted RNA transcriptomes.

Targeting RNA-binding proteins with small molecules: Perspectives, pitfalls and bifunctional molecules

RNA-binding proteins (RBPs) play vital roles in organisms through binding with RNAs to regulate their functions. Small molecules affecting the function of RBPs have been developed, providing new avenues for drug discovery. Herein, we describe the perspectives on developing small molecule regulators of RBPs. The following types of small molecule modulators are of great interest in drug discovery: small molecules binding to RBPs to affect interactions with RNA molecules, bifunctional molecules binding to RNA or RBP to influence their interactions, and other types of molecules that affect the stability of RNA or RBPs. Moreover, we emphasize that the bifunctional molecules may play important roles in small molecule development to overcome the challenges encountered in the process of drug discovery.

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.

Molecular mechanism of ATP and RNA binding to Zika virus NS3 helicase and identification of repurposed drugs using molecular dynamics simulations

Congenital Zika virus syndrome has caused a public health emergency of international concern. So far, there are no drugs available to prevent or treat the infection caused by Zika virus. The Zika virus NS3 helicase is a potential protein target for drug discovery due to its vital role in viral genome replication. NS3 helicase unwinds the viral RNA to enable the reproduction of the viral genome by the NS5 protein. NS3 helicase has two crucial binding sites; the ATP binding site and the RNA binding site. We used molecular docking and molecular dynamics (MD) simulations to study the structural behavior of Zika virus NS3 helicase in its apo form and in the presence of ATP, single-stranded RNA, and both ATP-RNA to understand their potential implications in NS3 helicase activity. Further, we have carried out virtual screening of FDA approved drugs, followed by molecular docking to identify the ATP-competitive hit molecules as probable Zika virus NS3 helicase inhibitors. The MD simulations trajectories were analyzed using normal mode analysis and principal component analysis that reveals fluctuations in the R-loop. These findings aid in understanding the molecular mechanisms of the simultaneous binding of ATP and RNA, and guide the design and discovery of new inhibitors of the Zika virus NS3 helicase as a promising drug target to treat the Zika virus infection. Communicated by Ramaswamy H. Sarma.

Polyanion order controls liquid-to-solid phase transition in peptide/nucleic acid co-assembly

The Central Dogma highlights the mutualistic functions of protein and nucleic acid biopolymers, and this synergy appears prominently in the membraneless organelles widely distributed throughout prokaryotic and eukaryotic organisms alike. Ribonucleoprotein granules (RNPs), which are complex coacervates of RNA with proteins, are a prime example of these membranelles organelles and underly multiple essential cellular functions. Inspired by the highly dynamic character of these organelles and the recent studies that ATP both inhibits and templates phase separation of the fused in sarcoma (FUS) protein implicated in several neurodegenerative diseases, we explored the RNA templated ordering of a single motif of the Aβ peptide of Alzheimer's disease. We now know that this strong cross-β propensity motif alone assembles through a liquid-like coacervate phase that can be externally templated to form distinct supramolecular assemblies. Now we provide evidence that structured phosphates, ranging from complex structures like double stranded and quadraplex DNA to simple trimetaphosphate, differentially impact the liquid to solid phase transition necessary for paracrystalline assembly. The results from this simple model illustrate the potential of ordered environmental templates in the transition to potentially irreversible pathogenic assemblies and provides insight into the ordering dynamics necessary for creating functional synthetic polymer co-assemblies.

Surface-induced Dissociation Mass Spectrometry as a Structural Biology Tool

Native mass spectrometry (nMS) is evolving into a workhorse for structural biology. The plethora of online and offline preparation, separation, and purification methods as well as numerous ionization techniques combined with powerful new hybrid ion mobility and mass spectrometry systems has illustrated the great potential of nMS for structural biology. Fundamental to the progression of nMS has been the development of novel activation methods for dissociating proteins and protein complexes to deduce primary, secondary, tertiary, and quaternary structure through the combined use of multiple MS/MS technologies. This review highlights the key features and advantages of surface collisions (surface-induced dissociation, SID) for probing the connectivity of subunits within protein and nucleoprotein complexes and, in particular, for solving protein structure in conjunction with complementary techniques such as cryo-EM and computational modeling. Several case studies highlight the significant role SID, and more generally nMS, will play in structural elucidation of biological assemblies in the future as the technology becomes more widely adopted. Cases are presented where SID agrees with solved crystal or cryoEM structures or provides connectivity maps that are otherwise inaccessible by "gold standard" structural biology techniques.

Statistical potentials for RNA-protein interactions optimized by CMA-ES

Characterizing RNA-protein interactions remains an important endeavor, complicated by the difficulty in obtaining the relevant structures. Evaluating model structures via statistical potentials is in principle straight-forward and effective. However, given the relatively small size of the existing learning set of RNA-protein complexes optimization of such potentials continues to be problematic. Notably, interaction-based statistical potentials have problems in addressing large RNA-protein complexes. In this study, we adopted a novel strategy with covariance matrix adaptation (CMA-ES) to calculate statistical potentials, successfully identifying native docking poses.

A genetic variant alters the secondary structure of the lncRNA H19 and is associated with dilated cardiomyopathy

lncRNAs are at the core of many regulatory processes and have also been recognized to be involved in various complex diseases. They affect gene regulation through direct interactions with RNA, DNA or proteins. Accordingly, lncRNA structure is likely to be essential for their regulatory function. Point mutations, which manifest as SNPs (single nucleotide polymorphisms) in genome screens, can substantially alter their function and, subsequently, the expression of their downstream regulated genes. To test the effect of SNPs on structure, we investigated lncRNAs associated with dilated cardiomyopathy. Among 322 human candidate lncRNAs, we demonstrate first the significant association of an SNP located in lncRNA H19 using data from 1084 diseased and 751 control patients. H19 is generally highly expressed in the heart, with a complex expression pattern during heart development. Next, we used MFE (minimum free energy) folding to demonstrate a significant refolding in the secondary structure of this 861 nt long lncRNA. Since MFE folding may overlook the importance of sub-optimal structures, we showed that this refolding also manifests in the overall Boltzmann structure ensemble. There, the composition of structures is tremendously affected in their thermodynamic probabilities through the genetic variant. Finally, we confirmed these results experimentally, using SHAPE-Seq, corroborating that SNPs affecting such structures may explain hidden genetic variance not accounted for through genome wide association studies. Our results suggest that structural changes in lncRNAs, and lncRNA H19 in particular, affect regulatory processes and represent optimal targets for further in-depth studies probing their molecular interactions.

circSVIL regulates bovine myoblast development by inhibiting STAT1 phosphorylation

Circular RNAs (circRNAs), a novel class of non-coding RNAs with a loop structure, have recently been shown to participate in various pathophysiological processes. However, the precise role of circRNAs in myoblasts remains unclear. In this report, circSVIL was screened and identified from our previous sequencing analysis; we then performed gain- and loss-of-function experiments on bovine myoblasts by CCK8, EdU, flow cytometry, qRT-PCR, and Western blotting. The results indicate that circSVIL facilitates bovine myoblast proliferation and inhibits cell apoptosis. Using mechanism assays such as bioinformatics prediction, RNA immunoprecipitation (RIP), and cytoplasmic separation, we demonstrate that circSVIL could interact with STAT1 and inhibit STAT1 phosphorylation, thereby restraining STAT1's nuclear translocation and affecting its downstream signal cascade. Our results may elucidate a new regulatory pathway for bovine skeletal muscle development.

Methods to study circRNA-protein interactions

Circular RNAs (circRNAs) have been studied extensively in the last few years, uncovering functional roles in a diverse range of cell types and organisms. As shown for a few cases, these functions may be mediated by trans-acting factors, in particular RNA-binding proteins (RBPs). However, the specific interaction partners for most circRNAs remain unknown. This is mainly due to technical difficulties in their identification and in differentiating between interactors of circRNAs and their linear counterparts. Here we review the currently used methodology to systematically study circRNA-protein complexes (circRNPs), focusing either on a specific RNA or protein, both on the gene-specific or global level, and discuss advantages and challenges of the available approaches.

Interaction of OIP5-AS1 with MEF2C mRNA promotes myogenic gene expression

Long noncoding (lnc)RNAs potently regulate gene expression programs in physiology and disease. Here, we describe a key function for lncRNA OIP5-AS1 in myogenesis, the process whereby myoblasts differentiate into myotubes during muscle development and muscle regeneration after injury. In human myoblasts, OIP5-AS1 levels increased robustly early in myogenesis, and its loss attenuated myogenic differentiation and potently reduced the levels of the myogenic transcription factor MEF2C. This effect relied upon the partial complementarity of OIP5-AS1 with MEF2C mRNA and the presence of HuR, an RNA-binding protein (RBP) with affinity for both transcripts. Remarkably, HuR binding to MEF2C mRNA, which stabilized MEF2C mRNA and increased MEF2C abundance, was lost after OIP5-AS1 silencing, suggesting that OIP5-AS1 might serve as a scaffold to enhance HuR binding to MEF2C mRNA, in turn increasing MEF2C production. These results highlight a mechanism whereby a lncRNA promotes myogenesis by enhancing the interaction of an RBP and a myogenic mRNA.

Footprinting SHAPE-eCLIP Reveals Transcriptome-wide Hydrogen Bonds at RNA-Protein Interfaces

Discovering the interaction mechanism and location of RNA-binding proteins (RBPs) on RNA is critical for understanding gene expression regulation. Here, we apply selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) on in vivo transcripts compared to protein-absent transcripts in four human cell lines to identify transcriptome-wide footprints (fSHAPE) on RNA. Structural analyses indicate that fSHAPE precisely detects nucleobases that hydrogen bond with protein. We demonstrate that fSHAPE patterns predict binding sites of known RBPs, such as iron response elements in both known loci and previously unknown loci in CDC34, SLC2A4RG, COASY, and H19. Furthermore, by integrating SHAPE and fSHAPE with crosslinking and immunoprecipitation (eCLIP) of desired RBPs, we interrogate specific RNA-protein complexes, such as histone stem-loop elements and their nucleotides that hydrogen bond with stem-loop-binding proteins. Together, these technologies greatly expand our ability to study and understand specific cellular RNA interactions in RNA-protein complexes.

Intrinsic Regulatory Role of RNA Structural Arrangement in Alternative Splicing Control

Alternative splicing is a highly sophisticated process, playing a significant role in posttranscriptional gene expression and underlying the diversity and complexity of organisms. Its regulation is multilayered, including an intrinsic role of RNA structural arrangement which undergoes time- and tissue-specific alterations. In this review, we describe the principles of RNA structural arrangement and briefly decipher its cis- and trans-acting cellular modulators which serve as crucial determinants of biological functionality of the RNA structure. Subsequently, we engage in a discussion about the RNA structure-mediated mechanisms of alternative splicing regulation. On one hand, the impairment of formation of optimal RNA structures may have critical consequences for the splicing outcome and further contribute to understanding the pathomechanism of severe disorders. On the other hand, the structural aspects of RNA became significant features taken into consideration in the endeavor of finding potential therapeutic treatments. Both aspects have been addressed by us emphasizing the importance of ongoing studies in both fields.

How RNA-Binding Proteins Interact with RNA: Molecules and Mechanisms

RNA-binding proteins (RBPs) comprise a large class of over 2,000 proteins that interact with transcripts in all manner of RNA-driven processes. The structures and mechanisms that RBPs use to bind and regulate RNA are incredibly diverse. In this review, we take a look at the components of protein-RNA interaction, from the molecular level to multi-component interaction. We first summarize what is known about protein-RNA molecular interactions based on analyses of solved structures. We additionally describe software currently available for predicting protein-RNA interaction and other resources useful for the study of RBPs. We then review the structure and function of seventeen known RNA-binding domains and analyze the hydrogen bonds adopted by protein-RNA structures on a domain-by-domain basis. We conclude with a summary of the higher-level mechanisms that regulate protein-RNA interactions.

Recent Advances in Machine Learning Based Prediction of RNA-protein Interactions

The interactions between RNAs and proteins play critical roles in many biological processes. Therefore, characterizing these interactions becomes critical for mechanistic, biomedical, and clinical studies. Many experimental methods can be used to determine RNA-protein interactions in multiple aspects. However, due to the facts that RNA-protein interactions are tissuespecific and condition-specific, as well as these interactions are weak and frequently compete with each other, those experimental techniques can not be made full use of to discover the complete spectrum of RNA-protein interactions. To moderate these issues, continuous efforts have been devoted to developing high quality computational techniques to study the interactions between RNAs and proteins. Many important progresses have been achieved with the application of novel techniques and strategies, such as machine learning techniques. Especially, with the development and application of CLIP techniques, more and more experimental data on RNA-protein interaction under specific biological conditions are available. These CLIP data altogether provide a rich source for developing advanced machine learning predictors. In this review, recent progresses on computational predictors for RNA-protein interaction were summarized in the following aspects: dataset, prediction strategies, and input features. Possible future developments were also discussed at the end of the review.

In vivo assembly of eukaryotic signal recognition particle: A still enigmatic process involving the SMN complex

The signal recognition particle (SRP) is a universally conserved non-coding ribonucleoprotein complex that is essential for targeting transmembrane and secretory proteins to the endoplasmic reticulum. Its composition and size varied during evolution. In mammals, SRP contains one RNA molecule, 7SL RNA, and six proteins: SRP9, 14, 19, 54, 68 and 72. Despite a very good understanding of the SRP structure and of the SRP assembly in vitro, how SRP is assembled in vivo remains largely enigmatic. Here we review current knowledge on how the 7SL RNA is assembled with core proteins to form functional RNP particles in cells. SRP biogenesis is believed to take place both in the nucleolus and in the cytoplasm and to rely on the survival of motor neuron complex, whose defect leads to spinal muscular atrophy.