Ribozymes, riboswitches and beyond: regulation of gene expression without proteins

EcCas6e-based antisense crRNA for gene repression and RNA editing in microorganisms

Precise gene regulation and programmable RNA editing are vital RNA-level regulatory mechanisms. Gene repression tools grounded in small non-coding RNAs, microRNAs, and CRISPR-dCas proteins, along with RNA editing tools anchored in Adenosine Deaminases acting on RNA (ADARs), have found extensive application in molecular biology and cellular engineering. Here, we introduced a novel approach wherein we developed an EcCas6e mediated crRNA-mRNA annealing system for gene repression in Escherichia coli and RNA editing in Saccharomyces cerevisiae. We found that EcCas6e possesses inherent RNA annealing ability attributed to a secondary positively charged cleft, enhancing crRNA-mRNA hybridization and stability. Based on this, we demonstrated that EcCas6e, along with its cognate crRNA repeat containing a complementary region to the ribosome binding site of a target mRNA, effectively represses gene expression up to 25-fold. Furthermore, we demonstrated that multiple crRNAs can be easily assembled and can simultaneously target up to 13 genes. Lastly, the EcCas6e-crRNA system was developed as an RNA editing tool by fusing it with the ADAR2 deaminase domain. The EcCas6e-crRNA mediated gene repression and RNA editing tools hold broad applications for research and biotechnology.

Building RNA-Mediated Artificial Signaling Pathways between Endogenous Genes

ConspectusSophisticated genetic networks play a pivotal role in orchestrating cellular responses through intricate signaling pathways across diverse environmental conditions. Beyond the inherent complexity of natural cellular signaling networks, the construction of artificial signaling pathways (ASPs) introduces a vast array of possibilities for reshaping cellular responses, enabling programmable control of living organisms. ASPs can be integrated with existing cellular networks and redirect output responses as desired, allowing seamless communication and coordination with other cellular processes, thereby achieving designable transduction within cells. Among diversified ASPs, establishing connections between originally independent endogenous genes is of particular significance in modifying the genetic networks, so that cells can be endowed with new capabilities to sense and deal with abnormal factors related to differentiated gene expression (i.e., solve the issues of the aberrant gene expression induced by either external or internal stimuli). In a typical scenario, the two genes X and Y in the cell are originally expressed independently. After the introduction of an ASP, changes in the expression of gene X may exert a designed impact on gene Y, subsequently inducing the cellular response related to gene Y. If X represents a disease signal and Y serves as a therapeutic module, the introduction of the ASP empowers cells with a new spontaneous defense system to handle potential risks, which holds great potential for both fundamental and translational studies.In this Account, we primarily review our endeavors in the construction of RNA-mediated ASPs between endogenous genes that can respond to differentiated RNA expression. In contrast to other molecules that may be restricted to specific pathways, synthetic RNA circuits can be easily utilized and expanded as a general platform for constructing ASPs with a high degree of programmability and tunability for diversified functionalities through predictable Watson-Crick base pairing. We first provide an overview of recent advancements in RNA-based genetic circuits, encompassing but not limited to utilization of RNA toehold switches, siRNA and CRISPR systems. Despite notable progress, most reported RNA circuits have to contain at least one exogenous RNA X as input or one engineered RNA Y as a target, which is not suitable for establishing endogenous gene connections. While exogenous RNAs can be engineered and controlled as desired, constructing a general and efficient platform for manipulation of naturally occurring RNAs poses a formidable challenge, especially for the mammalian system. With a focus on this goal, we are devoted to developing efficient strategies to manipulate cell responses by establishing RNA-mediated ASPs between endogenous genes, particularly in mammalian cells. Our step-by-step progress in engineering customized cell signaling circuits, from bacterial cells to mammalian cells, from gene expression regulation to phenotype control, and from small RNA to long mRNA of low abundance and more complex secondary structures, is systematically described. Finally, future perspectives and potential applications of these RNA-mediated ASPs between endogenous genes are also discussed.

A new reagent for in vivo structure probing of RNA G and U residues that improves RNA structure prediction alone and combined with DMS

A key to understanding the roles of RNA in regulating gene expression is knowing their structures in vivo. One way to obtain this information is through probing the structures of RNA with chemicals. To probe RNA structure directly in cells, membrane-permeable reagents that modify the Watson-Crick (WC) face of unpaired nucleotides can be used. Although dimethyl sulfate (DMS) has led to substantial insight into RNA structure, it has limited nucleotide specificity in vivo, with WC face reactivity only at adenine (A) and cytosine (C) at neutral pH. The reagent 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC) was recently shown to modify the WC face of guanine (G) and uracil (U). Although useful at lower concentrations in experiments that measure chemical modifications by reverse transcription (RT) stops, at higher concentrations necessary for detection by mutational profiling (MaP), EDC treatment leads to degradation of RNA. Here, we demonstrate EDC-stimulated degradation of RNA in Gram-negative and Gram-positive bacteria. In an attempt to overcome these limitations, we developed a new carbodiimide reagent, 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide methiodide (ETC), which we show specifically modifies unpaired Gs and Us in vivo without substantial degradation of RNA. We establish ETC as a probe for MaP and optimize the RT conditions and computational analysis in Escherichia coli Importantly, we demonstrate the utility of ETC as a probe for improving RNA structure prediction both alone and with DMS.

RNA Control via Redox-Responsive Acylation

Incorporating stimuli-responsive components into RNA constructs provides precise spatiotemporal control over RNA structures and functions. Despite considerable advancements, the utilization of redox-responsive stimuli for the activation of caged RNAs remains scarce. In this context, we present a novel strategy that leverages post-synthetic acylation coupled with redox-responsive chemistry to exert control over RNA. To achieve this, we design and synthesize a series of acylating reagents specifically tailored for introducing disulfide-containing acyl adducts into the 2'-OH groups of RNA ("cloaking"). Our data reveal that these acyl moieties can be readily appended, effectively blocking RNA catalytic activity and folding. We also demonstrate the traceless release and reactivation of caged RNAs ("uncloaking") through reducing stimuli. By employing this strategy, RNA exhibits rapid cellular uptake, effective distribution and activation in the cytosol without lysosomal entrapment. We anticipate that our methodology will be accessible to laboratories engaged in RNA biology and holds promise as a versatile platform for RNA-based applications.

Isolation of short RNAs with homogeneous 3'-ends using quaternary-amine anion exchange chromatography

Visualizing RNA-protein interactions through structural approaches requires the use of RNA molecules purified to homogeneity. We describe here a simple and effective method, free of acrylamide contamination and without using UV radiation, to separate in vitro synthesized, heterogeneous RNA transcripts (up to ∼15 nucleotides) at single-nucleotide resolution by quaternary-amine anion exchange chromatography. The quality of short RNAs isolated through this method is validated by gel electrophoresis, mass spectrometry, and crystallization with a protein-binding partner.

A sensitive and scalable fluorescence anisotropy single stranded RNA targeting approach for monitoring riboswitch conformational states

The capacity of riboswitches to undergo conformational changes in response to binding their native ligands is closely tied to their functional roles and is an attractive target for antimicrobial drug design. Here, we established a probe-based fluorescence anisotropy assay to monitor riboswitch conformational switching with high sensitivity and throughput. Using the Bacillus subtillis yitJ S-Box (SAM-I), Fusobacterium nucleatum impX RFN element of (FMN) and class-I cyclic-di-GMP from Vibrio cholerae riboswitches as model systems, we developed short fluorescent DNA probes that specifically recognize either ligand-free or -bound riboswitch conformational states. We showed that increasing concentrations of native ligands cause measurable and reproducible changes in fluorescence anisotropy that correlate with riboswitch conformational changes observed by native gel analysis. Furthermore, we applied our assay to several ligand analogues and confirmed that it can discriminate between ligands that bind, triggering the native conformational change, from those that bind without causing the conformational change. This new platform opens the possibility of high-throughput screening compound libraries to identify potential new antibiotics that specifically target functional conformational changes in riboswitches.

Chemically Cross-Linked Hammerhead Ribozyme as an Efficient RNA Interference Tool

RNA-cleaving ribozymes are promising candidates as general tools of RNA interference (RNAi) in gene manipulation. However, compared with other RNA systems, such as siRNA and CRISPR technologies, the ribozyme tools are still far from broad applications on RNAi due to their poor performance in the cellular context. In this work, we report an efficient RNAi tool based on chemically modified hammerhead ribozyme (HHR). By the introduction of an intramolecular linkage into the minimal HHR to reconstruct the distal interaction within the tertiary ribozyme structure, this cross-linked HHR exhibits efficient RNA substrate cleavage activities with almost no sequence constraint. Cellular experiments suggest that both exogenous and endogenous RNA expression can be dramatically knocked down by this HHR tool with levels comparable to those of siRNA. Unlike the widely applied protein-recruiting RNA systems (siRNA and CRISPR), this ribozyme tool functions solely on RNA itself with great simplicity, which may provide a new approach for gene manipulation in both fundamental and translational studies.

Mechanistic Analysis of Riboswitch Ligand Interactions Provides Insights into Pharmacological Control over Gene Expression

Riboswitches are structured RNA elements that regulate gene expression upon binding to small molecule ligands. Understanding the mechanisms by which small molecules impact riboswitch activity is key to developing potent, selective ligands for these and other RNA targets. We report the structure-informed design of chemically diverse synthetic ligands for PreQ1 riboswitches. Multiple X-ray co-crystal structures of synthetic ligands with the Thermoanaerobacter tengcongensis (Tte)-PreQ1 riboswitch confirm a common binding site with the cognate ligand, despite considerable chemical differences among the ligands. Structure probing assays demonstrate that one ligand causes conformational changes similar to PreQ1 in six structurally and mechanistically diverse PreQ1 riboswitch aptamers. Single-molecule force spectroscopy is used to demonstrate differential modes of riboswitch stabilization by the ligands. Binding of the natural ligand brings about the formation of a persistent, folded pseudoknot structure, whereas a synthetic ligand decreases the rate of unfolding through a kinetic mechanism. Single round transcription termination assays show the biochemical activity of the ligands, while a GFP reporter system reveals compound activity in regulating gene expression in live cells without toxicity. Taken together, this study reveals that diverse small molecules can impact gene expression in live cells by altering conformational changes in RNA structures through distinct mechanisms.

Differentiable partition function calculation for RNA

Ribonucleic acid (RNA) is an essential molecule in a wide range of biological functions. In 1990, McCaskill introduced a dynamic programming algorithm for computing the partition function of an RNA sequence. McCaskill's algorithm is widely used today for understanding the thermodynamic properties of RNA. In this work, we introduce a generalization of McCaskill's algorithm that is well-defined over continuous inputs. Crucially, this enables us to implement an end-to-end differentiable partition function calculation. The derivative can be computed with respect to the input, or to any other fixed values, such as the parameters of the energy model. This builds a bridge between RNA thermodynamics and the tools of differentiable programming including deep learning as it enables the partition function to be incorporated directly into any end-to-end differentiable pipeline. To demonstrate the effectiveness of our new approach, we tackle the inverse folding problem directly using gradient optimization. We find that using the gradient to optimize the sequence directly is sufficient to arrive at sequences with a high probability of folding into the desired structure. This indicates that the gradients we compute are meaningful.

Threose nucleic acid as a primitive genetic polymer and a contemporary molecular tool

Nucleic acids serve a dual role as both genetic materials in living organisms and versatile molecular tools for various applications. Threose nuclei acid (TNA) stands out as a synthetic genetic polymer, holding potential as a primitive genetic material and as a contemporary molecular tool. In this review, we aim to provide an extensive overview of TNA research progress in these two key aspects. We begin with a retrospect of the initial discovery of TNA, followed by an in-depth look at the structural features of TNA duplex and experimental assessment of TNA as a possible RNA progenitor during early evolution of life on Earth. In the subsequent section, we delve into the recent development of TNA molecular tools such as aptamers, catalysts and antisense oligonucleotides. We emphasize the practical application of functional TNA molecules in the realms of targeted protein degradation and selective gene silencing. Our review culminates with a discussion of future research directions and the technical challenges that remain to be addressed in the field of TNA research.

RNA tertiary structure modeling with BRiQ potential in CASP15

We describe the modeling method for RNA tertiary structures employed by team AIchemy_RNA2 in the 15th Critical Assessment of Structure Prediction (CASP15). The method consists of the following steps. Firstly, secondary structure information was derived from various manually-verified sources. With this information, the full length RNA was fragmented into structural modules. The structures of each module were predicted and then assembled into the full structure. To reduce the searching conformational space, an RNA structure was organized into an optimal base folding tree. And to further improve the sampling efficiency, the energy surface was smoothed at high temperatures during the Monte Carlo sampling to make it easier to move across the energy barrier. The statistical potential energy function BRiQ was employed during Monte Carlo energy optimization.

G·U base pairing motifs in long non-coding RNAs

Long non-coding RNAs (lncRNAs) are recently-discovered transcripts involved in gene expression regulation and associated with diseases. Despite the unprecedented molecular complexity of these transcripts, recent studies of the secondary and tertiary structure of lncRNAs are starting to reveal the principles of lncRNA structural organization, with important functional implications. It therefore starts to be possible to analyze lncRNA structures systematically. Here, using a set of prototypical and medically-relevant lncRNAs of known secondary structure, we specifically catalogue the distribution and structural environment of one of the first-identified and most frequently occurring non-canonical Watson-Crick interactions, the G·U base pair. We compare the properties of G·U base pairs in our set of lncRNAs to those of the G·U base pairs in other well-characterized transcripts, like rRNAs, tRNAs, ribozymes, and riboswitches. Furthermore, we discuss how G·U base pairs in these targets participate in establishing interactions with proteins or miRNAs, and how they enable lncRNA tertiary folding by forming intramolecular or metal-ion interactions. Finally, by identifying highly-G·U-enriched regions of yet unknown function in our target lncRNAs, we provide a new rationale for future experimental investigation of these motifs, which will help obtain a more comprehensive understanding of lncRNA functions and molecular mechanisms in the future.

Predicting 3D RNA structure from the nucleotide sequence using Euclidean neural networks

Fast and accurate 3D RNA structure prediction remains a major challenge in structural biology, mostly due to the size and flexibility of RNA molecules, as well as the lack of diverse experimentally determined structures of RNA molecules. Unlike DNA structure, RNA structure is far less constrained by basepair hydrogen bonding, resulting in an explosion of potential stable states. Here, we propose a convolutional neural network that predicts all pairwise distances between residues in an RNA, using a recently described smooth parametrization of Euclidean distance matrices. We achieve high-accuracy predictions on RNAs up to 100 nt in length in fractions of a second, a factor of 107 faster than existing molecular dynamics-based methods. We also convert our coarse-grained machine learning output into an all-atom model using discrete molecular dynamics with constraints. Our proposed computational pipeline predicts all-atom RNA models solely from the nucleotide sequence. However, this method suffers from the same limitation as nucleic acid molecular dynamics: the scarcity of available RNA crystal structures for training.

Integrating Ligands into Nucleic Acid Systems

Signal transduction from non-nucleic acid ligands (small molecules and proteins) to structural changes of nucleic acids plays a crucial role in both biomedical analysis and cellular regulations. However, how to bridge between these two types of molecules without compromising the expandable complexity and programmability of the nucleic acid nanomachines is a critical challenge. Compared with the previously most widely applied transduction strategies, we review the latest advances of a kinetically controlled approach for ligand-oligonucleotide transduction in this Concept article. This new design works through an intrinsic conformational alteration of the nucleic acid aptamer upon the ligand binding as a governing factor for nucleic acid strand displacement reactions. The functionalities and applications of this transduction system as a ligand converter on biosensing and DNA computation are described and discussed. Furthermore, we propose some potential scenarios for utilization of this ligand transduction design to regulate gene expression through synthetic RNA switches in the cellular contexts. Finally, future perspectives regarding this ligand-oligonucleotide transduction platform are also discussed.

Elucidating the Self-cleavage Dynamics of Hairpin Ribozyme by Mode-decomposed Infrared Spectroscopy

While catalytic reactions of biomolecular processes play an indispensable role in life, extracting the underlying molecular picture often remains challenging. Based on ab initio simulations of the self-cleavage reaction of hairpin ribozyme, mode-decomposed infrared spectra, and cosine similarity analysis to correlate the product with reactant IR spectra, we demonstrate a strategy to extract molecular details from characteristic spectral changes. Our results are in almost quantitative agreement with the experimental IR band library of nucleic acids and suggest that the spectral range of 800-1200 cm-1 is particularly valuable to monitor self-cleavage. Importantly, the cosine similarities also disclose that IR peaks subject to slight shifts due to self-cleavage might be unrelated, while strongly shifting resonances can correspond to the same structural dynamics. This framework of correlating complex IR spectra at the molecular level along biocatalytic reaction pathways is broadly applicable.

Advances in chaperone-assisted RNA crystallography using synthetic antibodies

RNA molecules play essential roles in many biological functions, from gene expression regulation, cellular growth, and metabolism to catalysis. They frequently fold into three-dimensional structures to perform their functions. Therefore, determining RNA structure represents a key step for understanding the structure-function relationships and developing RNA-targeted therapeutics. X-ray crystallography remains a method of choice for determining high-resolution RNA structures, but it has been challenging due to difficulties associated with RNA crystallization and phasing. Several natural and synthetic RNA binding proteins have been used to facilitate RNA crystallography. Having unique properties to help crystal packing and phasing, synthetic antibody fragments, specifically the Fabs, have emerged as promising RNA crystallization chaperones, and so far, over a dozen of RNA structures have been solved using this strategy. Nevertheless, multiple steps in this approach need to be improved, including the recombinant expression of these anti-RNA Fabs, to warrant the full potential of these synthetic Fabs as RNA crystallization chaperones. This review highlights the nuts and bolts and recent advances in the chaperone-assisted RNA crystallography approach, specifically emphasizing the Fab antibody fragments as RNA crystallization chaperones.

Led-Seq: ligation-enhanced double-end sequence-based structure analysis of RNA

Structural analysis of RNA is an important and versatile tool to investigate the function of this type of molecules in the cell as well as in vitro. Several robust and reliable procedures are available, relying on chemical modification inducing RT stops or nucleotide misincorporations during reverse transcription. Others are based on cleavage reactions and RT stop signals. However, these methods address only one side of the RT stop or misincorporation position. Here, we describe Led-Seq, a new approach based on lead-induced cleavage of unpaired RNA positions, where both resulting cleavage products are investigated. The RNA fragments carrying 2', 3'-cyclic phosphate or 5'-OH ends are selectively ligated to oligonucleotide adapters by specific RNA ligases. In a deep sequencing analysis, the cleavage sites are identified as ligation positions, avoiding possible false positive signals based on premature RT stops. With a benchmark set of transcripts in Escherichia coli, we show that Led-Seq is an improved and reliable approach based on metal ion-induced phosphodiester hydrolysis to investigate RNA structures in vivo.

PrismNet: predicting protein-RNA interaction using in vivo RNA structural information

Fundamental to post-transcriptional regulation, the in vivo binding of RNA binding proteins (RBPs) on their RNA targets heavily depends on RNA structures. To date, most methods for RBP-RNA interaction prediction are based on RNA structures predicted from sequences, which do not consider the various intracellular environments and thus cannot predict cell type-specific RBP-RNA interactions. Here, we present a web server PrismNet that uses a deep learning tool to integrate in vivo RNA secondary structures measured by icSHAPE experiments with RBP binding site information from UV cross-linking and immunoprecipitation in the same cell lines to predict cell type-specific RBP-RNA interactions. Taking an RBP and an RNA region with sequential and structural information as input ('Sequence & Structure' mode), PrismNet outputs the binding probability of the RBP and this RNA region, together with a saliency map and a sequence-structure integrative motif. The web server is freely available at http://prismnetweb.zhanglab.net.

A review on recent advances in methods for site-directed spin labeling of long RNAs

RNAs are important biomolecules that play essential roles in various cellular processes and are crucially linked with many human diseases. The key to elucidate the mechanisms underlying their biological functions and develop RNA-based therapeutics is to investigate RNA structure and dynamics and their connections to function in detail using a variety of approaches. Magnetic resonance techniques including paramagnetic nuclear magnetic resonance (NMR) and electron magnetic resonance (EPR) spectroscopies have proved to be powerful tools to gain insights into such properties. The prerequisites for paramagnetic NMR and EPR studies on RNAs are to achieve site-specific spin labeling of the intrinsically diamagnetic RNAs, which however is not trivial, especially for long ones. In this review, we present some covalent labeling strategies that allow site-specific introduction of electron spins to long RNAs. Generally, these strategies include assembly of long RNAs via enzymatic ligation of short oligonucleotides, co- and post-transcriptional site-specific labeling empowered with the unnatural base pair system, and direct enzymatic functionalization of natural RNAs. We introduce a few case studies to discuss the advantages and limitations of each strategy, and to provide a vision for the future development.

Thermodynamic determination of RNA duplex stability in magnesium solutions

The prediction of RNA secondary structure and thermodynamics from sequence relies on free energy minimization and nearest neighbor parameters. Currently, algorithms used to make these predictions are based on parameters from optical melting studies performed in 1 M NaCl. However, many physiological and biochemical buffers containing RNA include much lower concentrations of monovalent cations and the presence of divalent cations. In order to improve these algorithms, thermodynamic data was previously collected for RNA duplexes in solutions containing 71, 121, 221, and 621 mM Na+. From this data, correction factors for free energy (ΔG°37) and melting temperature (Tm) were derived. Despite these newly derived correction factors for sodium, the stabilizing effects of magnesium have been ignored. Here, the same RNA duplexes were melted in solutions containing 0.5, 1.5, 3.0, and 10.0 mM Mg2+ in the absence of monovalent cations. Correction factors for Tm and ΔG°37 were derived to scale the current parameters to a range of magnesium concentrations. The Tm correction factor predicts the melting temperature within 1.2°C, and the ΔG°37 correction factor predicts the free energy within 0.30 kcalmol. These newly derived magnesium correction factors can be incorporated into algorithms that predict RNA secondary structure and stability from sequence.

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.

A variant of guanidine-IV riboswitches exhibits evidence of a distinct ligand specificity

Riboswitches are regulatory RNAs that specifically bind a small molecule or ion. Like metabolite-binding proteins, riboswitches can evolve new ligand specificities, and some examples of this phenomenon have been validated. As part of work based on comparative genomics to discover novel riboswitches, we encountered a candidate riboswitch with striking similarities to the recently identified guanidine-IV riboswitch. This candidate riboswitch, the Gd4v motif, is predicted in four distinct bacterial phyla, thus almost as widespread as the guanidine-IV riboswitch. Bioinformatic and experimental analysis suggest that the Gd4v motif is a riboswitch that binds a ligand other than guanidine. It is found associated with gene classes that differ from genes regulated by confirmed guanidine riboswitches. In inline-probing assays, we showed that free guanidine binds only weakly to one of the tested sequences of the variant. Further tested compounds did not show binding, attenuation of transcription termination, or activation of a genetic reporter construct. We characterized an N-acetyltransferase frequently associated with the Gd4v motif and compared its substrate preference to an N-acetyltransferase that occurs under control of guanidine-IV riboswitches. The substrates of this Gd4v-motif-associated enzyme did not show activity for Gd4v RNA binding or transcription termination. Hence, the ligand of the candidate riboswitch motif remains unidentified. The variant RNA motif is predominantly found in gut metagenome sequences, hinting at a ligand that is highly relevant in this environment. This finding is a first step to determining the identity of this unknown ligand, and understanding how guanidine-IV-riboswitch-like structures can evolve to bind different ligands.

Sensing intracellular signatures with synthetic mRNAs

The bottom-up assembly of biological components in synthetic biology has contributed to a better understanding of natural phenomena and the development of new technologies for practical applications. Over the past few decades, basic RNA research has unveiled the regulatory roles of RNAs underlying gene regulatory networks; while advances in RNA biology, in turn, have highlighted the potential of a wide variety of RNA elements as building blocks to construct artificial systems. In particular, synthetic mRNA-based translational regulators, which respond to signals in cells and regulate the production of encoded output proteins, are gaining attention with the recent rise of mRNA therapeutics. In this Review, we discuss recent progress in RNA synthetic biology, mainly focusing on emerging technologies for sensing intracellular protein and RNA molecules and controlling translation.

Is CRISPR/Cas9 a way forward to fast-track genetic improvement in commercial palms? Prospects and limits

Commercially important palms (oil palm, coconut, and date palm) are widely grown perennial trees with tremendous commercial significance due to food, edible oil, and industrial applications. The mounting pressure on the human population further reinforces palms' importance, as they are essential crops to meet vegetable oil needs around the globe. Various conventional breeding methods are used for the genetic improvement of palms. However, adopting new technologies is crucial to accelerate breeding and satisfy the expanding population's demands. CRISPR/Cas9 is an efficient genome editing tool that can incorporate desired traits into the existing DNA of the plant without losing common traits. Recent progress in genome editing in oil palm, coconut and date palm are preliminarily introduced to potential readers. Furthermore, detailed information on available CRISPR-based genome editing and genetic transformation methods are summarized for researchers. We shed light on the possibilities of genome editing in palm crops, especially on the modification of fatty acid biosynthesis in oil palm. Moreover, the limitations in genome editing, including inadequate target gene screening due to genome complexities and low efficiency of genetic transformation, are also highlighted. The prospects of CRISPR/Cas9-based gene editing in commercial palms to improve sustainable production are also addressed in this review paper.

Moderate activity of RNA chaperone maximizes the yield of self-spliced pre-RNA in vivo

CYT-19 is a DEAD-box protein whose adenosine-triphosphate (ATP)-dependent helicase activity facilitates the folding of group I introns in precursor RNA (pre-RNA) of Neurospora crassa (N. crassa). In the process, they consume a substantial amount of ATP. While much of the mechanistic insight into CYT-19 activity has been gained through the studies on the folding of Tetrahymena group I intron ribozyme, the more biologically relevant issue, namely the effect of CYT-19 on the self-splicing of pre-RNA, remains largely unexplored. Here, we employ a kinetic network model, based on the generalized iterative annealing mechanism (IAM), to investigate the relation between CYT-19 activity, rate of ribozyme folding, and the kinetics of the self-splicing reaction. The network rate parameters are extracted by analyzing the recent biochemical data for CYT-19-facilitated folding of Tetrahymena ribozyme. We then build extended models to explore the metabolism of pre-RNA. We show that the timescales of chaperone-mediated folding of group I ribozyme and self-splicing reaction compete with each other. As a consequence, in order to maximize the self-splicing yield of group I introns in pre-RNA, the chaperone activity must be sufficiently large to unfold the misfolded structures, but not too large to unfold the native structures prior to the self-splicing event. We discover that despite the promiscuous action on structured RNAs, the helicase activity of CYT-19 on group I ribozyme gives rise to self-splicing yields that are close to the maximum.

Advances and opportunities in RNA structure experimental determination and computational modeling

Beyond transferring genetic information, RNAs are molecules with diverse functions that include catalyzing biochemical reactions and regulating gene expression. Most of these activities depend on RNAs' specific structures. Therefore, accurately determining RNA structure is integral to advancing our understanding of RNA functions. Here, we summarize the state-of-the-art experimental and computational technologies developed to evaluate RNA secondary and tertiary structures. We also highlight how the rapid increase of experimental data facilitates the integrative modeling approaches for better resolving RNA structures. Finally, we provide our thoughts on the latest advances and challenges in RNA structure determination methods, as well as on future directions for both experimental approaches and artificial intelligence-based computational tools to model RNA structure. Ultimately, we hope the technological advances will deepen our understanding of RNA biology and facilitate RNA structure-based biomedical research such as designing specific RNA structures for therapeutics and deploying RNA-targeting small-molecule drugs.

RNA modifications in aging-associated cardiovascular diseases

Cardiovascular disease (CVD) is a leading cause of morbidity and mortality worldwide that bears an enormous healthcare burden and aging is a major contributing factor to CVDs. Functional gene expression network during aging is regulated by mRNAs transcriptionally and by non-coding RNAs epi-transcriptionally. RNA modifications alter the stability and function of both mRNAs and non-coding RNAs and are involved in differentiation, development, and diseases. Here we review major chemical RNA modifications on mRNAs and non-coding RNAs, including N6-adenosine methylation, N1-adenosine methylation, 5-methylcytidine, pseudouridylation, 2′ -O-ribose-methylation, and N7-methylguanosine, in the aging process with an emphasis on cardiovascular aging. We also summarize the currently available methods to detect RNA modifications and the bioinformatic tools to study RNA modifications. More importantly, we discussed the specific implication of the RNA modifications on mRNAs and non-coding RNAs in the pathogenesis of aging-associated CVDs, including atherosclerosis, hypertension, coronary heart diseases, congestive heart failure, atrial fibrillation, peripheral artery disease, venous insufficiency, and stroke.

Genetic, physiological, and cellular heterogeneities of bacterial pathogens in food matrices: Consequences for food safety

In complex food systems, bacteria live in heterogeneous microstructures, and the population displays phenotypic heterogeneities at the single-cell level. This review provides an overview of spatiotemporal drivers of phenotypic heterogeneity of bacterial pathogens in food matrices at three levels. The first level is the genotypic heterogeneity due to the possibility for various strains of a given species to contaminate food, each of them having specific genetic features. Then, physiological heterogeneities are induced within the same strain, due to specific microenvironments and heterogeneous adaptative responses to the food microstructure. The third level of phenotypic heterogeneity is related to cellular heterogeneity of the same strain in a specific microenvironment. Finally, we consider how these phenotypic heterogeneities at the single-cell level could be implemented in mathematical models to predict bacterial behavior and help ensure microbiological food safety.

Deep learning models for RNA secondary structure prediction (probably) do not generalize across families

MOTIVATION

The secondary structure of RNA is of importance to its function. Over the last few years, several papers attempted to use machine learning to improve de novo RNA secondary structure prediction. Many of these papers report impressive results for intra-family predictions but seldom address the much more difficult (and practical) inter-family problem.

RESULTS

We demonstrate that it is nearly trivial with convolutional neural networks to generate pseudo-free energy changes, modelled after structure mapping data that improve the accuracy of structure prediction for intra-family cases. We propose a more rigorous method for inter-family cross-validation that can be used to assess the performance of learning-based models. Using this method, we further demonstrate that intra-family performance is insufficient proof of generalization despite the widespread assumption in the literature and provide strong evidence that many existing learning-based models have not generalized inter-family.

AVAILABILITY AND IMPLEMENTATION

Source code and data are available at https://github.com/marcellszi/dl-rna.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Petkov P, Milenov TI, Vayssilov GN. Sodium and Magnesium Ion Location at the Backbone and at the Nucleobase of RNA: Ab Initio Molecular Dynamics in Water Solution

The interactions between Na⁺ or Mg²⁺ ions with different parts of single-stranded RNA molecules, namely, the oxygen atoms from the phosphate groups or the guanine base, in water solution have been studied using first-principles molecular dynamics. Sodium ions were found to be much more mobile than Mg²⁺ ions and readily underwent transitions between a state directly bonded to RNA oxygen atoms and a completely solvated state. The inner solvation shell of Na⁺ ions fluctuated stochastically at a femtosecond timescale coordinating on average 5 oxygen atoms for bonded Na⁺ ions and 5.5 oxygen atoms for solvated Na⁺ ions. In contrast, the inner solvation shell of Mg²⁺ ions was stable in both RNA-bonded and completely solvated states. In both cases, Mg²⁺ ions coordinated 6 oxygen atoms from the inner solvation shell. Consistent with their stable solvation shells, Mg²⁺ ions were more effective than Na⁺ ions in stabilizing the RNA backbone conformation. The exclusion zones between the first and second solvation shells, solvation shell widths, and angles for binding to carbonyl oxygen of guanine for solvated Na⁺ or Mg²⁺ ions exhibited a number of quantitative differences when compared with RNA crystallographic data. The presented results support the distinct capacity of Mg²⁺ ions to support the RNA structure not only in the crystal phase but also in the dynamic water environment both on the side of the phosphate moiety and on the side of the nucleobase.

RNAspider: a webserver to analyze entanglements in RNA 3D structures

Advances in experimental and computational techniques enable the exploration of large and complex RNA 3D structures. These, in turn, reveal previously unstudied properties and motifs not characteristic for small molecules with simple architectures. Examples include entanglements of structural elements in RNA molecules and knot-like folds discovered, among others, in the genomes of RNA viruses. Recently, we presented the first classification of entanglements, determined by their topology and the type of entangled structural elements. Here, we introduce RNAspider - a web server to automatically identify, classify, and visualize primary and higher-order entanglements in RNA tertiary structures. The program applies to evaluate RNA 3D models obtained experimentally or by computational prediction. It supports the analysis of uncommon topologies in the pseudoknotted RNA structures. RNAspider is implemented as a publicly available tool with a user-friendly interface and can be freely accessed at https://rnaspider.cs.put.poznan.pl/.

The Second Class of Tetrahydrofolate (THF-II) Riboswitches Recognizes the Tetrahydrofolic Acid Ligand via Local Conformation Changes

Riboswitches are regulatory noncoding RNAs found in bacteria, fungi and plants, that modulate gene expressions through structural changes in response to ligand binding. Understanding how ligands interact with riboswitches in solution can shed light on the molecular mechanisms of this ancient regulators. Previous studies showed that riboswitches undergo global conformation changes in response to ligand binding to relay information. Here, we report conformation switching models of the recently discovered tetrahydrofolic acid-responsive second class of tetrahydrofolate (THF-II) riboswitches in response to ligand binding. Using a combination of selective 2′-hydroxyl acylation, analyzed by primer extension (SHAPE) assay, 3D modeling and small-angle X-ray scattering (SAXS), we found that the ligand specifically recognizes and reshapes the THF-II riboswitch loop regions, but does not affect the stability of the P3 helix. Our results show that the THF-II riboswitch undergoes only local conformation changes in response to ligand binding, rearranging the Loop1-P3-Loop2 region and rotating Loop1 from a ~120° angle to a ~75° angle. This distinct conformation changes suggest a unique regulatory mechanism of the THF-II riboswitch, previously unseen in other riboswitches. Our findings may contribute to the fields of RNA sensors and drug design.

Sub-3-Å cryo-EM structure of RNA enabled by engineered homomeric self-assembly

High-resolution structural studies are essential for understanding the folding and function of diverse RNAs. Herein, we present a nanoarchitectural engineering strategy for efficient structural determination of RNA-only structures using single-particle cryogenic electron microscopy (cryo-EM). This strategy-ROCK (RNA oligomerization-enabled cryo-EM via installing kissing loops)-involves installing kissing-loop sequences onto the functionally nonessential stems of RNAs for homomeric self-assembly into closed rings with multiplied molecular weights and mitigated structural flexibility. ROCK enables cryo-EM reconstruction of the Tetrahymena group I intron at 2.98-Å resolution overall (2.85 Å for the core), allowing de novo model building of the complete RNA, including the previously unknown peripheral domains. ROCK is further applied to two smaller RNAs-the Azoarcus group I intron and the FMN riboswitch, revealing the conformational change of the former and the bound ligand in the latter. ROCK holds promise to greatly facilitate the use of cryo-EM in RNA structural studies.

Maize RNA 3'-terminal phosphate cyclase-like protein promotes 18S pre-rRNA cleavage and is important for kernel development

Plant ribosomes contain four specialized ribonucleic acids, the 5S, 5.8S, 18S, and 25S ribosomal RNAs (rRNAs). Maturation of the latter three rRNAs requires cooperative processing of a single transcript by several endonucleases and exonucleases at specific sites. In maize (Zea mays), the exact nucleases and components required for rRNA processing remain poorly understood. Here, we characterized a conserved RNA 3'-terminal phosphate cyclase (RCL)-like protein, RCL1, that functions in 18S rRNA maturation. RCL1 is highly expressed in the embryo and endosperm during early seed development. Loss of RCL1 function resulted in lethality due to aborted embryo cell differentiation. We also observed pleiotropic defects in the rcl1 endosperm, including abnormal basal transfer cell layer growth and aleurone cell identity, and reduced storage reserve accumulation. The rcl1 seeds had lower levels of mature 18S rRNA and the related precursors were altered in abundance compared with wild type. Analysis of transcript levels and protein accumulation in rcl1 revealed that the observed lower levels of zein and starch synthesis enzymes mainly resulted from effects at the transcriptional and translational levels, respectively. These results demonstrate that RCL1-mediated 18S pre-rRNA processing is essential for ribosome function and messenger RNA translation during maize seed development.

RNA folding using quantum computers

The 3-dimensional fold of an RNA molecule is largely determined by patterns of intramolecular hydrogen bonds between bases. Predicting the base pairing network from the sequence, also referred to as RNA secondary structure prediction or RNA folding, is a nondeterministic polynomial-time (NP)-complete computational problem. The structure of the molecule is strongly predictive of its functions and biochemical properties, and therefore the ability to accurately predict the structure is a crucial tool for biochemists. Many methods have been proposed to efficiently sample possible secondary structure patterns. Classic approaches employ dynamic programming, and recent studies have explored approaches inspired by evolutionary and machine learning algorithms. This work demonstrates leveraging quantum computing hardware to predict the secondary structure of RNA. A Hamiltonian written in the form of a Binary Quadratic Model (BQM) is derived to drive the system toward maximizing the number of consecutive base pairs while jointly maximizing the average length of the stems. A Quantum Annealer (QA) is compared to a Replica Exchange Monte Carlo (REMC) algorithm programmed with the same objective function, with the QA being shown to be highly competitive at rapidly identifying low energy solutions. The method proposed in this study was compared to three algorithms from literature and, despite its simplicity, was found to be competitive on a test set containing known structures with pseudoknots.

The recent FDA approval of mRNA-based vaccines has increased public interest in synthetically designed RNA molecules. RNA molecules fold into complex secondary structures which determine their molecular properties and in part their efficacy. Determining the folded structure of an RNA molecule is a computationally challenging task with exponential scaling that is intractable to solve exactly, and therefore approximate methods are used. Quantum computing technology offers a new approach to finding approximate solutions to problems with exponential scaling. We formulate a simplistic, yet effective, model of RNA folding that can easily be mapped to quantum computers and we show that currently available quantum computing hardware is competitive with classical methods.

Ultraviolet Photodissociation and Activated Electron Photodetachment Mass Spectrometry for Top-Down Sequencing of Modified Oligoribonucleotides

With the increased development of new RNA-based therapeutics, the need for robust analytical methods for confirming sequences and mapping modifications has accelerated. Characterizing modified ribonucleic acids using mass spectrometry is challenging because diagnostic fragmentation may be suppressed for modified nucleotides, thus hampering complete sequence coverage and the confident localization of modifications. Ultraviolet photodissociation (UVPD) has shown great potential for the characterization of nucleic acids due to extensive backbone fragmentation. Activated electron photodetachment dissociation (a-EPD) has also been used as an alternative to capitalize on the dominant charge-reduction pathway prevalent in UVPD, facilitate dissociation, and produce high abundances of fragment ions. Here, we compare higher-energy collisional activation (HCD), UVPD using 193 and 213 nm photons, and a-EPD for the top-down sequencing of modified nucleic acids, including methylated, phosphorothioate, and locked nucleic acid-modified DNA. The presence of these modifications alters the fragmentation pathways observed upon UVPD and a-EPD, and extensive backbone cleavage is observed that results in the production of fragment ions that retain the modifications and allow them to be pinpointed. LNA and 2'-O-methoxy phosphorothioate modifications caused a significant suppression of fragmentation for UVPD but not for a-EPD, whereas phosphorothioate bonds did not cause any significant suppression for either method. The incorporation of 2'-O-methyl modifications suppressed fragmentation of the antisense strand of patisiran, which resulted in some gaps in sequence coverage. However, UVPD provided the highest sequence coverage when compared to a-EPD.

Synthesis of [7-15N]-GTPs for RNA structure and dynamics by NMR spectroscopy

Several isotope-labeling strategies have been developed for the study of RNA by nuclear magnetic resonance (NMR) spectroscopy. Here, we report a combined chemical and enzymatic synthesis of [7-15N]-guanosine-5'-triphosphates for incorporation into RNA via T7 RNA polymerase-based in vitro transcription. We showcase the utility of these labels to probe both structure and dynamics in two biologically important RNAs.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s00706-022-02892-1.

Nucleic Acids and Their Analogues for Biomedical Applications

Nucleic acids are emerging as powerful and functional biomaterials due to their molecular recognition ability, programmability, and ease of synthesis and chemical modification. Various types of nucleic acids have been used as gene regulation tools or therapeutic agents for the treatment of human diseases with genetic disorders. Nucleic acids can also be used to develop sensing platforms for detecting ions, small molecules, proteins, and cells. Their performance can be improved through integration with other organic or inorganic nanomaterials. To further enhance their biological properties, various chemically modified nucleic acid analogues can be generated by modifying their phosphodiester backbone, sugar moiety, nucleobase, or combined sites. Alternatively, using nucleic acids as building blocks for self-assembly of highly ordered nanostructures would enhance their biological stability and cellular uptake efficiency. In this review, we will focus on the development and biomedical applications of structural and functional natural nucleic acids, as well as the chemically modified nucleic acid analogues over the past ten years. The recent progress in the development of functional nanomaterials based on self-assembled DNA-based platforms for gene regulation, biosensing, drug delivery, and therapy will also be presented. We will then summarize with a discussion on the advanced development of nucleic acid research, highlight some of the challenges faced and propose suggestions for further improvement.

Hidden intermediates in Mango III RNA aptamer folding revealed by pressure perturbation

Fluorescent RNA aptamers have the potential to enable routine quantitation and localization of RNA molecules and serve as models for understanding biologically active aptamers. In recent years, several fluorescent aptamers have been selected and modified to improve their properties, revealing that small changes to the RNA or the ligands can modify significantly their fluorescent properties. Although structural biology approaches have revealed the bound, ground state of several fluorescent aptamers, characterization of low-abundance, excited states in these systems is crucial to understanding their folding pathways. Here we use pressure as an alternative variable to probe the suboptimal states of the Mango III aptamer with both fluorescence and NMR spectroscopy approaches. At moderate KCl concentrations, increasing pressure disrupted the G-quadruplex structure of the Mango III RNA and led to an intermediate with lower fluorescence. These observations indicate the existence of suboptimal RNA structural states that still bind the TO1-biotin fluorophore and moderately enhance fluorescence. At higher KCl concentration as well, the intermediate fluorescence state was populated at high pressure, but the G-quadruplex remained stable at high pressure, supporting the notion of parallel folding and/or binding pathways. These results demonstrate the usefulness of pressure for characterizing RNA folding intermediates.

Overview of Methods for Large-Scale RNA Synthesis

In recent years, it has become clear that RNA molecules are involved in almost all vital cellular processes and pathogenesis of human disorders. The functional diversity of RNA comes from its structural richness. Although composed of only four nucleotides, RNA molecules present a plethora of secondary and tertiary structures critical for intra and intermolecular contacts with other RNAs and ligands (proteins, small metabolites, etc.). In order to fully understand RNA function it is necessary to define its spatial structure. Crystallography, nuclear magnetic resonance and cryogenic electron microscopy have demonstrated considerable success in determining the structures of biologically important RNA molecules. However, these powerful methods require large amounts of sample. Despite their limitations, chemical synthesis and in vitro transcription are usually employed to obtain milligram quantities of RNA for structural studies, delivering simple and effective methods for large-scale production of homogenous samples. The aim of this paper is to provide an overview of methods for large-scale RNA synthesis with emphasis on chemical synthesis and in vitro transcription. We also present our own results of testing the efficiency of these approaches in order to adapt the material acquisition strategy depending on the desired RNA construct.

RNA thermometers and other regulatory elements: Diversity and importance in bacterial pathogenesis

Survival of microorganisms depends to a large extent on environmental conditions and the occupied host. By adopting specific strategies, microorganisms can thrive in the surrounding environment and, at the same time, preserve their viability. Evading the host defenses requires several mechanisms compatible with the host survival which include the production of RNA thermometers to regulate the expression of genes responsible for heat or cold shock as well as of those involved in virulence. Microorganisms have developed a variety of molecules in response to the environmental changes in temperature and even more specifically to the host they invade. Among all, RNA-based regulatory mechanisms are the most common ones, highlighting the importance of such molecules in gene expression control and novel drug development by suitable structure-based alterations. This article is categorized under: RNA Structure and Dynamics > RNA Structure, Dynamics and Chemistry RNA in Disease and Development > RNA in Disease RNA Structure and Dynamics > Influence of RNA Structure in Biological Systems.

Long-range distance determination in fully deuterated RNA with pulsed EPR spectroscopy

Pulsed electron-electron double resonance (PELDOR or DEER) spectroscopy is powerful in structure and dynamics study of biological macromolecules by providing distance distribution information ranging from 1.8 to 6 nm, providing that the biomolecules are site-specifically labeled with paramagnetic tags. However, long distances up to 16 nm have been measured on perdeuterated and spin-labeled proteins in deuterated solvent by PELDOR. Here we demonstrate long-range distance measurement on a large RNA, the 97-nucleotide 3'SL RNA element of the Dengue virus 2 genome, by combining a posttranscriptional site-directed spin labeling method using an unnatural basepair system with RNA perdeuteration by enzymatic synthesis using deuterated nucleotides. The perdeuteration removes the coupling of the electron spins of the nitroxide spin labels from the proton nuclear spin system of the RNA and does extend the observation time windows of PELDOR up to 50 μs. This enables one to determine long distances up to 14 nm for large RNAs and their conformational flexibility.

Cooperativity and Interdependency between RNA Structure and RNA-RNA Interactions

Complex RNA–RNA interactions are increasingly known to play key roles in numerous biological processes from gene expression control to ribonucleoprotein granule formation. By contrast, the nature of these interactions and characteristics of their interfaces, especially those that involve partially or wholly structured RNAs, remain elusive. Herein, we discuss different modalities of RNA–RNA interactions with an emphasis on those that depend on secondary, tertiary, or quaternary structure. We dissect recently structurally elucidated RNA–RNA complexes including RNA triplexes, riboswitches, ribozymes, and reverse transcription complexes. These analyses highlight a reciprocal relationship that intimately links RNA structure formation with RNA–RNA interactions. The interactions not only shape and sculpt RNA structures but also are enabled and modulated by the structures they create. Understanding this two-way relationship between RNA structure and interactions provides mechanistic insights into the expanding repertoire of noncoding RNA functions, and may inform the design of novel therapeutics that target RNA structures or interactions.

Streamlined CRISPR genome engineering in wild-type bacteria using SIBR-Cas

CRISPR-Cas is a powerful tool for genome editing in bacteria. However, its efficacy is dependent on host factors (such as DNA repair pathways) and/or exogenous expression of recombinases. In this study, we mitigated these constraints by developing a simple and widely applicable genome engineering tool for bacteria which we termed SIBR-Cas (Self-splicing Intron-Based Riboswitch-Cas). SIBR-Cas was generated from a mutant library of the theophylline-dependent self-splicing T4 td intron that allows for tight and inducible control over CRISPR-Cas counter-selection. This control delays CRISPR-Cas counter-selection, granting more time for the editing event (e.g. by homologous recombination) to occur. Without the use of exogenous recombinases, SIBR-Cas was successfully applied to knock-out several genes in three wild-type bacteria species (Escherichia coli MG1655, Pseudomonas putida KT2440 and Flavobacterium IR1) with poor homologous recombination systems. Compared to other genome engineering tools, SIBR-Cas is simple, tightly regulated and widely applicable for most (non-model) bacteria. Furthermore, we propose that SIBR can have a wider application as a simple gene expression and gene regulation control mechanism for any gene or RNA of interest in bacteria.

Accurate detection of RNA stem-loops in structurome data reveals widespread association with protein binding sites

RNA molecules are known to fold into specific structures which often play a central role in their functions and regulation. In silico folding of RNA transcripts, especially when assisted with structure profiling (SP) data, is capable of accurately elucidating relevant structural conformations. However, such methods scale poorly to the swaths of SP data generated by transcriptome-wide experiments, which are becoming more commonplace and advancing our understanding of RNA structure and its regulation at global and local levels. This has created a need for tools capable of rapidly deriving structural assessments from SP data in a scalable manner. One such tool we previously introduced that aims to process such data is patteRNA, a statistical learning algorithm capable of rapidly mining big SP datasets for structural elements. Here, we present a reformulation of patteRNA's pattern recognition scheme that sees significantly improved precision without major compromises to computational overhead. Specifically, we developed a data-driven logistic classifier which interprets patteRNA's statistical characterizations of SP data in addition to local sequence properties as measured with a nearest neighbour thermodynamic model. Application of the classifier to human structurome data reveals a marked association between detected stem-loops and RNA binding protein (RBP) footprints. The results of our application demonstrate that upwards of 30% of RBP footprints occur within loops of stable stem-loop elements. Overall, our work arrives at a rapid and accurate method for automatically detecting families of RNA structure motifs and demonstrates the functional relevance of identifying them transcriptome-wide.

Strategies for Covalent Labeling of Long RNAs

The introduction of chemical modifications into long RNA molecules at specific positions for visualization, biophysical investigations, diagnostic and therapeutic applications still remains challenging. In this review, we present recent approaches for covalent internal labeling of long RNAs. Topics included are the assembly of large modified RNAs via enzymatic ligation of short synthetic oligonucleotides and synthetic biology approaches preparing site-specifically modified RNAs via in vitro transcription using an expanded genetic alphabet. Moreover, recent approaches to employ deoxyribozymes (DNAzymes) and ribozymes for RNA labeling and RNA methyltransferase based labeling strategies are presented. We discuss the potentials and limits of the individual methods, their applicability for RNAs with several hundred to thousands of nucleotides in length and indicate future directions in the field.

Rapid structure-function insights via hairpin-centric analysis of big RNA structure probing datasets

The functions of RNA are often tied to its structure, hence analyzing structure is of significant interest when studying cellular processes. Recently, large-scale structure probing (SP) studies have enabled assessment of global structure-function relationships via standard data summarizations or local folding. Here, we approach structure quantification from a hairpin-centric perspective where putative hairpins are identified in SP datasets and used as a means to capture local structural effects. This has the advantage of rapid processing of big (e.g. transcriptome-wide) data as RNA folding is circumvented, yet it captures more information than simple data summarizations. We reformulate a statistical learning algorithm we previously developed to significantly improve precision of hairpin detection, then introduce a novel nucleotide-wise measure, termed the hairpin-derived structure level (HDSL), which captures local structuredness by accounting for the presence of likely hairpin elements. Applying HDSL to data from recent studies recapitulates, strengthens and expands on their findings which were obtained by more comprehensive folding algorithms, yet our analyses are orders of magnitude faster. These results demonstrate that hairpin detection is a promising avenue for global and rapid structure-function analysis, furthering our understanding of RNA biology and the principal features which drive biological insights from SP data.

Mechanisms of catalytic RNA molecules

Ribozymes are folded catalytic RNA molecules that perform important biological functions. Since the discovery of the first RNA with catalytic activity in 1982, a large number of ribozymes have been reported. While most catalytic RNA molecules act alone, some RNA-based catalysts, such as RNase P, the ribosome, and the spliceosome, need protein components to perform their functions in the cell. In the last decades, the structure and mechanism of several ribozymes have been studied in detail. Aside from the ribosome, which catalyzes peptide bond formation during protein synthesis, the majority of known ribozymes carry out mostly phosphoryl transfer reactions, notably trans-esterification or hydrolysis reactions. In this review, we describe the main features of the mechanisms of various types of ribozymes that can function with or without the help of proteins to perform their biological functions.

Comparative genomics provides structural and functional insights into Bacteroides RNA biology

Bacteria employ noncoding RNA molecules for a wide range of biological processes, including scaffolding large molecular complexes, catalyzing chemical reactions, defending against phages, and controlling gene expression. Secondary structures, binding partners, and molecular mechanisms have been determined for numerous small noncoding RNAs (sRNAs) in model aerobic bacteria. However, technical hurdles have largely prevented analogous analyses in the anaerobic gut microbiota. While experimental techniques are being developed to investigate the sRNAs of gut commensals, computational tools and comparative genomics can provide immediate functional insight. Here, using Bacteroides thetaiotaomicron as a representative microbiota member, we illustrate how comparative genomics improves our understanding of the RNA biology in an understudied gut bacterium. We investigate putative RNA-binding proteins and predict a Bacteroides cold-shock protein homologue to have an RNA-related function. We apply an in-silico protocol incorporating both sequence and structural analysis to determine the consensus structures and conservation of nine Bacteroides noncoding RNA families. Using structure probing, we validate and refine these predictions, and deposit them in the Rfam database. Through synteny analyses, we illustrate how genomic co-conservation can serve as a predictor of sRNA function. Altogether, this work showcases the power of RNA informatics for investigating the RNA biology of anaerobic microbiota members.

Targeting RNA structures in diseases with small molecules

RNA is crucial for gene expression and regulation. Recent advances in understanding of RNA biochemistry, structure and molecular biology have revealed the importance of RNA structure in cellular processes and diseases. Various approaches to discovering drug-like small molecules that target RNA structure have been developed. This review provides a brief introduction to RNA structural biology and how RNA structures function as disease regulators. We summarize approaches to targeting RNA with small molecules and highlight their advantages, shortcomings and therapeutic potential.