RNA Backbone Research Articles

Delivery Aspects for Implementing siRNA Therapeutics for Blood Diseases.

Hematological disorders result in significant health consequences, and traditional therapies frequently entail adverse reactions without addressing the root cause. A potential solution for hematological disorders characterized by gain-of-function mutations lies in the emergence of small interfering RNA (siRNA) molecules as a therapeutic option. siRNAs are a class of RNA molecules composed of double-stranded RNAs that can degrade specific mRNAs, thereby inhibiting the synthesis of underlying disease proteins. Therapeutic interventions utilizing siRNA can be tailored to selectively target genes implicated in diverse hematological disorders, including sickle cell anemia, β-thalassemia, and malignancies such as lymphoma, myeloma, and leukemia. The development of efficient siRNA silencers necessitates meticulous contemplation of variables such as the RNA backbone, stability, and specificity. Transportation of siRNA to specific cells poses a significant hurdle, prompting investigations of diverse delivery approaches, including chemically modified forms of siRNA and nanoparticle formulations with various biocompatible carriers. This review delves into the crucial role of siRNA technology in targeting and treating hematological malignancies and disorders. It sheds light on the latest research, development, and clinical trials, detailing how various pharmaceutical approaches leverage siRNA against blood disorders, mainly concentrating on cancers. It outlines the preferred molecular targets and physiological barriers to delivery while emphasizing the growing potential of various therapeutic delivery methods. The need for further research is articulated in the context of overcoming the shortcomings of siRNA in order to enrich discussions around siRNA's role in managing blood disorders and aiding the scientific community in advancing more targeted and effective treatments.

GRNAde: Geometric Deep Learning for 3D RNA inverse design.

Computational RNA design tasks are often posed as inverse problems, where sequences are designed based on adopting a single desired secondary structure without considering 3D geometry and conformational diversity. We introduce gRNAde, a geometric RNA design pipeline operating on 3D RNA backbones to design sequences that explicitly account for structure and dynamics. gRNAde uses a multi-state Graph Neural Network and autoregressive decoding to generates candidate RNA sequences conditioned on one or more 3D backbone structures where the identities of the bases are unknown. On a single-state fixed backbone re-design benchmark of 14 RNA structures from the PDB identified by Das et al. (2010), gRNAde obtains higher native sequence recovery rates (56% on average) compared to Rosetta (45% on average), taking under a second to produce designs compared to the reported hours for Rosetta. We further demonstrate the utility of gRNAde on a new benchmark of multi-state design for structurally flexible RNAs, as well as zero-shot ranking of mutational fitness landscapes in a retrospective analysis of a recent ribozyme. Open source code: github.com/chaitjo/geometric-rna-design.

GRNAde: A Geometric Deep Learning Pipeline for 3D RNA Inverse Design.

Fundamental to the diverse biological functions of RNA are its 3D structure and conformational flexibility, which enable single sequences to adopt a variety of distinct 3D states. Currently, computational RNA design tasks are often posed as inverse problems, where sequences are designed based on adopting a single desired secondary structure without considering 3D geometry and conformational diversity. In this tutorial, we present gRNAde, a geometric RNA design pipeline operating on sets of 3D RNA backbone structures to design sequences that explicitly account for RNA 3D structure and dynamics. gRNAde is a graph neural network that uses an SE (3) equivariant encoder-decoder framework for generating RNA sequences conditioned on backbone structures where the identities of the bases are unknown. We demonstrate the utility of gRNAde for fixed-backbone re-design of existing RNA structures of interest from the PDB, including riboswitches, aptamers, and ribozymes. gRNAde is more accurate in terms of native sequence recovery while being significantly faster compared to existing physics-based tools for 3D RNA inverse design, such as Rosetta.

RiboDiffusion: tertiary structure-based RNA inverse folding with generative diffusion models.

RNA design shows growing applications in synthetic biology and therapeutics, driven by the crucial role of RNA in various biological processes. A fundamental challenge is to find functional RNA sequences that satisfy given structural constraints, known as the inverse folding problem. Computational approaches have emerged to address this problem based on secondary structures. However, designing RNA sequences directly from 3D structures is still challenging, due to the scarcity of data, the nonunique structure-sequence mapping, and the flexibility of RNA conformation. In this study, we propose RiboDiffusion, a generative diffusion model for RNA inverse folding that can learn the conditional distribution of RNA sequences given 3D backbone structures. Our model consists of a graph neural network-based structure module and a Transformer-based sequence module, which iteratively transforms random sequences into desired sequences. By tuning the sampling weight, our model allows for a trade-off between sequence recovery and diversity to explore more candidates. We split test sets based on RNA clustering with different cut-offs for sequence or structure similarity. Our model outperforms baselines in sequence recovery, with an average relative improvement of 11% for sequence similarity splits and 16% for structure similarity splits. Moreover, RiboDiffusion performs consistently well across various RNA length categories and RNA types. We also apply in silico folding to validate whether the generated sequences can fold into the given 3D RNA backbones. Our method could be a powerful tool for RNA design that explores the vast sequence space and finds novel solutions to 3D structural constraints. The source code is available at https://github.com/ml4bio/RiboDiffusion.

Novel transcription and replication-competent virus-like particles system modelling the Nipah virus life cycle

ABSTRACT Nipah virus (NiV), a highly pathogenic Henipavirus in humans, has been responsible for annual outbreaks in recent years. Experiments involving live NiV are highly restricted to biosafety level 4 (BSL-4) laboratories, which impedes NiV research. In this study, we developed transcription and replication-competent NiV-like particles (trVLP-NiV) lacking N, P, and L genes. This trVLP-NiV exhibited the ability to infect and continuously passage in cells ectopically expressing N, P, and L proteins while maintaining stable genetic characteristics. Moreover, the trVLP-NiV displayed a favourable safety profile in hamsters. Using the system, we found the NiV nucleoprotein residues interacting with viral RNA backbone affected viral replication in opposite patterns. This engineered system was sensitive to well-established antiviral drugs, innate host antiviral factors, and neutralizing antibodies. We then established a high-throughput screening platform utilizing the trVLP-NiV, leading to the identification of tunicamycin as a potential anti-NiV compound. Evidence showed that tunicamycin inhibited NiV replication by decreasing the infectivity of progeny virions. In conclusion, this trVLP-NiV system provided a convenient and versatile molecular tool for investigating NiV molecular biology and conducting antiviral drug screening under BSL-2 conditions. Its application will contribute to the development of medical countermeasures against NiV infections.

Lighting Up Nucleolus To Report Mitochondria Damage Using a Mitochondria-to-Nucleolus Migration Probe.

Visualization of the mitochondrial state is crucial for tracking cell life processes and diagnosing disease, while fluorescent probes that can accurately assess mitochondrial status are currently scarce. Herein, a fluorescent probe named "SYN" was designed and prepared, which can target mitochondria via the mitochondrial membrane potential. Upon pathology or external stimulation, SYN can be released from the mitochondria and accumulate in the nucleolus to monitor the status of mitochondria. During this process, the brightness of the nucleolus can then serve as an indicator of mitochondrial damage. SYN has demonstrated excellent photostability in live cells as well as an extremely inert fluorescence response to bioactive molecules and the physiological pH environment of live cells. Spectroscopic titration and molecular docking studies have revealed that SYN can be lit up in nucleoli due to the high viscosity of the nucleus and the strong electrostatic interaction with the phosphate backbone of RNA. This probe is expected to be an exceptional tool based on its excellent imaging properties for tracking mitochondrial state in live cells.

RNA-Templated Peptide Bond Formation Promotes L-Homochirality.

The world in which we live is homochiral. The ribose units that form the backbone of DNA and RNA are all D-configured and the encoded amino acids that comprise the proteins of all living species feature an all-L-configuration at the α-carbon atoms. The homochirality of α-amino acids is essential for folding of the peptides into well-defined and functional 3D structures and the homochirality of D-ribose is crucial for helix formation and base-pairing. The question of why nature uses only encoded L-α-amino acids is not understood. Herein, we show that an RNA-peptide world, in which peptides grow on RNAs constructed from D-ribose, leads to the self-selection of homo-L-peptides, which provides a possible explanation for the homo-D-ribose and homo-L-amino acid combination seen in nature.

RNA‐Vermittelte Peptidbindungen Fördern die L‐Homochiralität

AbstractDie Welt, in der wir leben, ist homochiral. Die Riboseeinheiten, die das Rückgrat von DNA und RNA bilden, sind alle D‐konfiguriert, und die kodierten Aminosäuren, aus denen die Proteine aller lebenden Arten bestehen, weisen an den α‐Kohlenstoffatomen eine L‐Konfiguration auf. Die Homochiralität der α‐Aminosäuren ist unerlässlich für die Faltung der Peptide in wohldefinierte und funktionelle 3D‐Strukturen und die Homochiralität der D‐Ribose ist entscheidend für die Ausbildung einer Helix und die Basenpaarung. Die Frage, warum die Natur nur kodierte L‐α‐Aminosäuren verwendet, ist nicht geklärt. Wir zeigen hier, dass eine RNA‐Peptid‐Welt, in der Peptide an aus D‐Ribose aufgebauten RNAs wachsen, zur Selbstselektion von homo‐L‐Peptiden führt, was eine mögliche Erklärung für die in der Natur beobachtete Kombination von homo‐D‐Ribose und homo‐L‐Aminosäuren liefert.

Recent updates on therapeutic targeting of lipoprotein(a) with RNA interference.

RNA interference (RNAi)-based therapies that target specific gene products have impacted clinical medicine with 16 FDA approved drugs. RNAi therapy focused on reducing plasma lipoprotein(a) [Lp(a)] levels are under evaluation. RNAi-based therapies have made significant progress over the past 2 decades and currently consist of antisense oligonucleotides (ASO) and small interfering RNA (siRNA). Chemical modification of the RNA backbone and conjugation of siRNA enables efficient gene silencing in hepatocytes allowing development of effective cholesterol lowering therapies. Multiple lines of evidence suggest a causative role for Lp(a) in atherosclerotic cardiovascular disease, and recent analyses indicate that Lp(a) is more atherogenic than low density lipoprotein- cholesterol (LDL-C). These findings have led to the 'Lp(a) hypothesis' that lowering Lp(a) may significantly improve cardiovascular outcomes. Four RNAi-based drugs have completed early phase clinical trials demonstrating >80% reduction in plasma Lp(a) levels. Phase 3 clinical trials examining clinical outcomes with these agents are currently underway. Currently, four RNAi-based drugs have been shown to be effective in significantly lowering plasma Lp(a) levels. Clinical outcome data from phase 3 trials will evaluate the Lp(a) hypothesis.

Submillisecond Atomistic Molecular Dynamics Simulations Reveal Hydrogen Bond-Driven Diffusion of a Guest Peptide in Protein-RNA Condensate.

Liquid-liquid phase separation mediated by proteins and/or nucleic acids is believed to underlie the formation of many distinct condensed phases, or membraneless organelles, within living cells. These condensates have been proposed to orchestrate a variety of important processes. Despite recent advances, the interactions that regulate the dynamics of molecules within a condensate remain poorly understood. We performed accumulated 564.7 μs all-atom molecular dynamics (MD) simulations (system size ∼200k atoms) of model condensates formed by a scaffold RNA oligomer and a scaffold peptide rich in arginine (Arg). These model condensates contained one of three possible guest peptides: the scaffold peptide itself or a variant in which six Arg residues were replaced by lysine (Lys) or asymmetric dimethyl arginine (ADMA). We found that the Arg-rich peptide can form the largest number of hydrogen bonds and bind the strongest to the scaffold RNA in the condensate, relative to the Lys- and ADMA-rich peptides. Our MD simulations also showed that the Arg-rich peptide diffused more slowly in the condensate relative to the other two guest peptides, which is consistent with a recent fluorescence microscopy study. There was no significant increase in the number of cation-π interactions between the Arg-rich peptide and the scaffold RNA compared to the Lys-rich and ADMA-rich peptides. Our results indicate that hydrogen bonds between the peptides and the RNA backbone, rather than cation-π interactions, play a major role in regulating peptide diffusion in the condensate.

Synthesis and Properties of RNA Modified with Cationic Amine Internucleoside Linkage.

Chemical modifications of RNA are important tools for the development of RNA therapeutics. The present study reports a novel RNA backbone modification that replaces the negatively charged phosphate with a positively charged amine linkage. Despite being thermally destabilizing in RNA duplexes, the amine linkage caused a relatively modest decrease of activity of a modified short interfering RNA (siRNA). At position 2 of the guide strand, the amine modification strongly enhanced the specificity of siRNA while causing an ∼5-fold drop of on-target activity. These results support the future development of amines as cationic RNA modifications and novel tools to modulate protein-RNA interactions.

Identification of glycosylated nucleosides in small synthetic glyco-RNAs.

Recently, the post-transcriptional modification of RNA with N-glycans was reported, changing the paradigm that RNAs are not commonly N-glycosylated. Moreover, glycan modifications of RNA are investigated for therapeutic targeting purposes. But the glyco-RNA field is in its infancy with many challenges to overcome. One question is how to accurately characterize glycosylated RNA constructs. Thus, we generated glycosylated forms of Y5 RNA mimics, a short non-coding RNA. The simple glycans lactose and sialyllactose were attached to the RNA backbone using azide-alkyne cycloadditions. Using nuclease digestion followed by LC-MS, we confirmed the presence of the glycosylated nucleosides, and characterized the chemical linkage. Next, we probed if glycosylation would affect the cellular response to Y5 RNA. We treated human foreskin fibroblasts in culture with the generated compounds. Key transcripts in the innate immune response were quantified by RT-qPCR. We found that under our experimental conditions, exposure of cells to the Y5 RNA did not trigger an interferon response, and glycosylation of this RNA did not have an impact. Thus, we have identified a successful approach to chemically characterize synthetic glyco-RNAs, which will be critical for further studies to elucidate how the presence of complex glycans on RNA affects the cellular response.

In Vitro and In Vivo Evaluation of the Pathology and Safety Aspects of Three- and Four-Way Junction RNA Nanoparticles.

RNA therapeutics has advanced into the third milestone in pharmaceutical drug development, following chemical and protein therapeutics. RNA itself can serve as therapeutics, carriers, regulators, or substrates in drug development. Due to RNA's motile, dynamic, and deformable properties, RNA nanoparticles have demonstrated spontaneous targeting and accumulation in cancer vasculature and fast excretion through the kidney glomerulus to urine to prevent possible interactions with healthy organs. Furthermore, the negatively charged phosphate backbone of RNA results in general repulsion from negatively charged lipid cell membranes for further avoidance of vital organs. Thus, RNA nanoparticles can spontaneously enrich tumor vasculature and efficiently enter tumor cells via specific targeting, while those not entering the tumor tissue will clear from the body quickly. These favorable parameters have led to the expectation that RNA has low or little toxicity. RNA nanoparticles have been well characterized for their anticancer efficacy; however, little detail on RNA nanoparticle pathology and safety is known. Here, we report the in vitro and in vivo assessment of the pathology and safety aspects of different RNA nanoparticles including RNA three-way junction (3WJ) harboring 2'-F modified pyrimidine, folic acid, and Survivin siRNA, as well as the RNA four-way junction (4WJ) harboring 2'-F modified pyrimidine and 24 copies of SN38. Both animal models and patient serum were investigated. In vitro studies include hemolysis, platelet aggregation, complement activation, plasma coagulation, and interferon induction. In vivo studies include hematoxylin and eosin (H&E) staining, hematological and biochemical analysis as the serum profiling, and animal organ weight study. No significant toxicity, side effect, or immune responses were detected during the extensive safety evaluations of RNA nanoparticles. These results further complement previous cancer inhibition studies and demonstrate RNA nanoparticles as an effective and safe drug delivery vehicle for future clinical translations.

Structural Analysis of the Hepatitis B Virus RNA Encapsidation Signal ε by Selective 2'-Hydroxyl Acylation Analyzed by Primer Extension (SHAPE).

RNA structure is crucial for RNA function, including in viral cis-elements such as the hepatitis B virus (HBV) RNA encapsidation signal ε. Interacting with the viral polymerase ε mediates packaging of the pregenomic (pg) RNA into capsids, initiation of reverse transcription, and it affects the mRNA functions of pgRNA. As free RNA, the 61-nucleotide (nt) ε sequence adopts a bipartite stem-loop structure with a central bulge and an apical loop. Due to stable Watson-Crick base pairing, this was already predicted by early RNA folding programs and confirmed by classical enzymatic and chemical structure probing. A newer, high-resolution probing technique exploits the selective acylation of solvent-accessible 2'-hydroxyls in the RNA backbone by electrophilic compounds such as 2-methylnicotinic acid imidazolide (NAI), followed by mapping of the modified sites by primer extension. This SHAPE principle has meanwhile been extended to numerous applications. Here we provide a basic protocol for NAI-based SHAPE of isolated HBV ε RNA which already provided insights into the impact of mutations, and preliminarily, of polymerase binding on the RNA structural dynamics. While the focus is on NAI modification, we also briefly cover target RNA preparation by in vitro transcription, primer extension using a radiolabeled primer, and analysis of the resulting cDNAs by denaturing polyacrylamide gelelectrophoresis (PAGE). Given the high tolerance of SHAPE chemistry to different conditions, including applicability in live cells, we expect this technique to greatly facilitate deciphering the conformational dynamics underlying the various functions of the ε element, especially in concert with the recently solved three-dimensional structure of the free RNA.

The pseudotorsional space of RNA.

The characterization of the conformational landscape of the RNA backbone is rather complex due to the ability of RNA to assume a large variety of conformations. These backbone conformations can be depicted by pseudotorsional angles linking RNA backbone atoms, from which Ramachandran-like plots can be built. We explore here different definitions of these pseudotorsional angles, finding that the most accurate ones are the traditional η (eta) and θ (theta) angles, which represent the relative position of RNA backbone atoms P and C4'. We explore the distribution of η - θ in known experimental structures, comparing the pseudotorsional space generated with structures determined exclusively by one experimental technique. We found that the complete picture only appears when combining data from different sources. The maps provide a quite comprehensive representation of the RNA accessible space, which can be used in RNA-structural predictions. Finally, our results highlight that protein interactions lead to significant changes in the population of the η - θ space, pointing toward the role of induced-fit mechanisms in protein-RNA recognition.

An Analysis of Nucleotide-Amyloid Interactions Reveals Selective Binding to Codon-Sized RNA.

Interactions between RNA and proteins are the cornerstone of many important biological processes from transcription and translation to gene regulation, yet little is known about the ancient origin of said interactions. We hypothesized that peptide amyloids played a role in the origin of life and that their repetitive structure lends itself to building interfaces with other polymers through avidity. Here, we report that short RNA with a minimum length of three nucleotides binds in a sequence-dependent manner to peptide amyloids. The 3'-5' linked RNA backbone appears to be well-suited to support these interactions, with the phosphodiester backbone and nucleobases both contributing to the affinity. Sequence-specific RNA-peptide interactions of the kind identified here may provide a path to understanding one of the great mysteries rooted in the origin of life: the origin of the genetic code.

Decoding the dual recognition mechanism of the glucocorticoid receptor for DNA and RNA: sequence versus shape

Transcription factors (TFs) regulate eukaryotic transcription through selective DNA-binding, can also specifically interact with RNA, which may present another layer of transcriptional control. The mechanisms of the TFs-DNA recognition are often well-characterised, while the details of TFs-RNA complexation are less understood. Here we investigate the dual recognition mechanism of the glucocorticoid receptor (GR), which interacts with similar affinities with consensus DNA and diverse RNA hairpin motifs but discriminates against uniform dsRNA. Using atomic molecular dynamics simulations, we demonstrate that the GR binding to nucleic acids requires a wide and shallow groove pocket. The protein effectively moulds its binding site within DNA major groove, which enables base-specific interactions. Contrary, the GR binding has little effect on the grooves geometry of RNA systems, most notably in uniform dsRNA. Instead, a hairpin motif in RNA yields a wide and shallow major groove pocket, allowing the protein to anchor itself through nonspecific electrostatic contacts with RNA backbone. Addition of a bulge increases RNA hairpin flexibility, which leads to a greater number of GR-RNA contacts and, thus, higher affinity. Thus, the combination of structural motifs defines the GR-RNA selective binding: a recognition mechanism, which may be shared by other zinc finger TFs.

Systematic detection of tertiary structural modules in large RNAs and RNP interfaces by Tb-seq

Compact RNA structural motifs control many aspects of gene expression, but we lack methods for finding these structures in the vast expanse of multi-kilobase RNAs. To adopt specific 3-D shapes, many RNA modules must compress their RNA backbones together, bringing negatively charged phosphates into close proximity. This is often accomplished by recruiting multivalent cations (usually Mg2+), which stabilize these sites and neutralize regions of local negative charge. Coordinated lanthanide ions, such as terbium (III) (Tb3+), can also be recruited to these sites, where they induce efficient RNA cleavage, thereby revealing compact RNA 3-D modules. Until now, Tb3+ cleavage sites were monitored via low-throughput biochemical methods only applicable to small RNAs. Here we present Tb-seq, a high-throughput sequencing method for detecting compact tertiary structures in large RNAs. Tb-seq detects sharp backbone turns found in RNA tertiary structures and RNP interfaces, providing a way to scan transcriptomes for stable structural modules and potential riboregulatory motifs.

RNA Hydrolysis at Mineral-Water Interfaces.

As an essential biomolecule for life, RNA is ubiquitous across environmental systems where it plays a central role in biogeochemical processes and emerging technologies. The persistence of RNA in soils and sediments is thought to be limited by enzymatic or microbial degradation, which occurs on timescales that are orders of magnitude faster than known abiotic pathways. Herein, we unveil a previously unreported abiotic pathway by which RNA rapidly hydrolyzes on the timescale of hours upon adsorption to iron (oxyhydr)oxide minerals such as goethite (α-FeOOH). The hydrolysis products were consistent with iron present in the minerals acting as a Lewis acid to accelerate sequence-independent hydrolysis of phosphodiester bonds comprising the RNA backbone. In contrast to acid- or base-catalyzed RNA hydrolysis in solution, mineral-catalyzed hydrolysis was fastest at circumneutral pH, which allowed for both sufficient RNA adsorption and hydroxide concentration. In addition to goethite, we observed that RNA hydrolysis was also catalyzed by hematite (α-Fe2O3) but not by aluminum-containing minerals (e.g., montmorillonite). Given the extensive adsorption of nucleic acids to environmental surfaces, we anticipate previously overlooked mineral-catalyzed hydrolysis of RNA may be prevalent particularly in iron-rich soils and sediments, which must be considered across biogeochemical applications of nucleic acid analysis in environmental systems.

Biophysical Interactions Underpin the Emergence of Information in the Genetic Code.

The genetic code conceals a 'code within the codons', which hints at biophysical interactions between amino acids and their cognate nucleotides. Yet, research over decades has failed to corroborate systematic biophysical interactions across the code. Using molecular dynamics simulations and NMR, we have analysed interactions between the 20 standard proteinogenic amino acids and 4 RNA mononucleotides in 3 charge states. Our simulations show that 50% of amino acids bind best with their anticodonic middle base in the -1 charge state common to the backbone of RNA, while 95% of amino acids interact most strongly with at least 1 of their codonic or anticodonic bases. Preference for the cognate anticodonic middle base was greater than 99% of randomised assignments. We verify a selection of our results using NMR, and highlight challenges with both techniques for interrogating large numbers of weak interactions. Finally, we extend our simulations to a range of amino acids and dinucleotides, and corroborate similar preferences for cognate nucleotides. Despite some discrepancies between the predicted patterns and those observed in biology, the existence of weak stereochemical interactions means that random RNA sequences could template non-random peptides. This offers a compelling explanation for the emergence of genetic information in biology.