RNA Dynamics Research Articles

Integrated NMR/Molecular Dynamics Determination of the Ensemble Conformation of a Thermodynamically Stable CUUG RNA Tetraloop.

Both experimental and theoretical structure determinations of RNAs have remained challenging due to the intrinsic dynamics of RNAs. We report here an integrated nuclear magnetic resonance/molecular dynamics (NMR/MD) structure determination approach to describe the dynamic structure of the CUUG tetraloop. We show that the tetraloop undergoes substantial dynamics, leading to averaging of the experimental data. These dynamics are particularly linked to the temperature-dependent presence of a hydrogen bond within the tetraloop. Interpreting the NMR data by a single structure represents the low-temperature structure well but fails to capture all conformational states occurring at a higher temperature. We integrate MD simulations, starting from structures of CUUG tetraloops within the Protein Data Bank, with an extensive set of NMR data, and provide a structural ensemble that describes the dynamic nature of the tetraloop and the experimental NMR data well. We thus show that one of the most stable and frequently found RNA tetraloops displays substantial dynamics, warranting such an integrated structural approach.

RNA Imaging in Live Cells†

AbstractTraditional molecular biology tools have elucidated the identities and functions of RNA molecules, which are essential to the understanding of gene transcription and protein translation. Deepening this research field would further require the direct visualization of RNA dynamics such as the DNA‐RNA interactions and RNA‐protein interactions. Towards this goal, the rise of RNA imaging tools over the past 15 years has reformed how we looked at these processes. In this Emerging Topic, we first highlighted recent advances on three main RNA imaging tools based on the species of interacting molecules: RNA‐RNA pairing, RNA‐protein binding, and small molecule‐RNA complex. We introduced the advantages of these tools from a technical viewpoint, including binding affinity, fluorescent turn‐on ratio, stability, and impacts on targeted RNA. Next, we discussed new rising opportunities and future directions, echoing the state‐of‐the‐art imaging tools in the fields of fluorescent proteins and small fluorescent molecules. Together, we believe this emerging field will bring new insights on how we study RNA biology in living systems.

Long noncoding RNA MALAT1 is dynamically regulated in leader cells during collective cancer invasion

Cancer cells collectively invade using a leader-follower organization, but the regulation of leader cells during this dynamic process is poorly understood. Using a dual double-stranded locked nucleic acid (LNA) nanobiosensor that tracks long noncoding RNA (lncRNA) dynamics in live single cells, we monitored the spatiotemporal distribution of lncRNA during collective cancer invasion. We show that the lncRNA MALAT1 (metastasis-associated lung adenocarcinoma transcript 1) is dynamically regulated in the invading fronts of cancer cells and patient-derived spheroids. MALAT1 transcripts exhibit distinct abundance, diffusivity, and distribution between leader and follower cells. MALAT1 expression increases when a cancer cell becomes a leader and decreases when the collective migration process stops. Transient knockdown of MALAT1 prevents the formation of leader cells and abolishes the invasion of cancer cells. Taken together, our single-cell analysis suggests that MALAT1 is dynamically regulated in leader cells during collective cancer invasion.

GrandR: a comprehensive package for nucleotide conversion RNA-seq data analysis

Metabolic labeling of RNA is a powerful technique for studying the temporal dynamics of gene expression. Nucleotide conversion approaches greatly facilitate the generation of data but introduce challenges for their analysis. Here we present grandR, a comprehensive package for quality control, differential gene expression analysis, kinetic modeling, and visualization of such data. We compare several existing methods for inference of RNA synthesis rates and half-lives using progressive labeling time courses. We demonstrate the need for recalibration of effective labeling times and introduce a Bayesian approach to study the temporal dynamics of RNA using snapshot experiments.

Live cell imaging of DNA and RNA with fluorescent signal amplification and background reduction techniques.

Illuminating DNA and RNA dynamics in live cell can elucidate their life cycle and related biochemical activities. Various protocols have been developed for labeling the regions of interest in DNA and RNA molecules with different types of fluorescent probes. For example, CRISPR-based techniques have been extensively used for imaging genomic loci. However, some DNA and RNA molecules can still be difficult to tag and observe dynamically, such as genomic loci in non-repetitive regions. In this review, we will discuss the toolbox of techniques and methodologies that have been developed for imaging DNA and RNA. We will also introduce optimized systems that provide enhanced signal intensity or low background fluorescence for those difficult-to-tag molecules. These strategies can provide new insights for researchers when designing and using techniques to visualize DNA or RNA molecules.

Influence of Mg2+ Distribution on the Stability of Folded States of the Twister Ribozyme Revealed Using Grand Canonical Monte Carlo and Generative Deep Learning Enhanced Sampling.

Metal ions, particularly magnesium ions (Mg2+), play a role in stabilizing the tertiary structures of RNA molecules. Theoretical models and experimental techniques show that metal ions can change RNA dynamics and how it transitions through different stages of folding. However, the specific ways in which metal ions contribute to the formation and stabilization of RNA's tertiary structure are not fully understood at the atomic level. Here, we combined oscillating excess chemical potential Grand Canonical Monte Carlo (GCMC) and metadynamics to bias toward the sampling of unfolded states using reaction coordinates generated by machine learning allowing for examination of Mg2+-RNA interactions that contribute to stabilizing folded states of the pseudoknot found in the Twister ribozyme. GCMC is used to sample diverse ion distributions around the RNA with deep learning applied to iteratively generate system-specific reaction coordinates to maximize conformational sampling during metadynamics simulations. Results from 6 μs simulations performed on 9 individual systems indicate that Mg2+ ions play a crucial role in stabilizing the three-dimensional (3D) structure of the RNA by stabilizing specific interactions of phosphate groups or phosphate groups and bases of neighboring nucleotides. While many phosphates are accessible to interactions with Mg2+, it is observed that multiple, specific interactions are required to sample conformations close to the folded state; coordination of Mg2+ at individual specific sites facilitates sampling of folded conformations though unfolding ultimately occurs. It is only when multiple specific interactions occur, including the presence of specific inner-shell cation interactions linking two nucleotides, that conformations close to the folded state are stable. While many of the identified Mg2+ interactions are observed in the X-ray crystal structure of Twister, the present study suggests two new Mg2+ ion sites in the Twister ribozyme that contribute to stabilization. In addition, specific interactions with Mg2+ are observed that destabilize the local RNA structure, a process that may facilitate the folding of RNA into its correct structure.

Biocontrol potential of lipopeptides produced by Paenibacillus polymyxa AF01 against Neoscytalidium dimidiatum in pitaya.

Pitaya canker, caused by Neoscytalidium dimidiatum, is one of the most important fungal diseases that cause significant losses in production. To replace chemical pesticides, the use of biocontrol strains to manage plant diseases has been the focus of research. In this study, the bacterial strain AF01, identified as Paenibacillus polymyxa, exhibited significant antifungal effects against N. dimidiatum and four other pitaya fungal pathogens. The strain P. polymyxa AF01 produces 13 fusaricidins, which directly inhibit mycelial growth, spore germination and germ tube elongation by causing the membrane integrity and cell ultrastructure to incur irreversible damage. Pot experiment and yield test confirmed that AF01 provided preservative effects by reducing the disease index. In comparison to the untreated control groups, RNA-seq data showed that P. polymyxa AF01 selectively blocked some transcription and translation processes and inhibited RNA and DNA structural dynamics, energy production and conversion, and signal transduction, particularly cell wall biosynthesis, changes in membrane permeability, and impairment of protein biosynthesis. Thus, P. polymyxa AF01 could be potentially useful as a suitable biocontrol agent for pitaya canker.

Occurrence and classification of T-shaped interactions between nucleobases in RNA structures.

Understanding the frequency and structural context of discrete noncovalent interactions between nucleotides is of pivotal significance in establishing the rules that govern RNA structure and dynamics. Although T-shaped contacts (i.e., perpendicular stacking contacts) between aromatic amino acids and nucleobases at the nucleic acid-protein interface have recently garnered attention, the analogous contacts within the nucleic acid structures have not been discussed. In this work, we have developed an automated method for identifying and unambiguously classifying T-shaped interactions between nucleobases. Using this method, we identified a total of 3261 instances of T-shaped (perpendicular stacking) contacts between two nucleobases in an array of RNA structures from an up-to-date data set of ≤3.5 Å resolution crystal structures deposited in the Protein Data Bank.

A6A-seq: N6-allyladenosine-based cellular messenger RNA metabolic labelling and sequencing

The integration of RNA metabolic labelling by nucleoside analogues with high-throughput RNA sequencing has been harnessed to study RNA dynamics. The immunoprecipitation purification or chemical pulldown technique is generally required to enrich the analogue-labelled RNAs. Here we developed an a6A-seq method, which takes advantage of N6-allyladenosine (a6A) metabolic labelling on cellular mRNAs and profiles them in an immunoprecipitation-free and mutation-based manner. a6A plays a role as a chemical sequencing tag in that the iodination of a6A in mRNAs results in 1,N6-cyclized adenosine (cyc-A), which induces base misincorporation during RNA reverse transcription, thus making a6A-labelled mRNAs detectable by sequencing. A nucleic acid melting assay was utilized to investigate why cyc-A prefers to be paired with guanine. a6A-seq was utilized to study cellular gene expression changes under a methionine-free stress condition. Compared with regular RNA-seq, a6A-seq could more sensitively detect the change of mRNA production over a time scale. The experiment of a6A-containing mRNA immunoprecipitation followed by qPCR successfully validated the high-throughput a6A-seq data. Together, our results show a6A-seq is an effective tool to study RNA dynamics.

Utilizing functional cell-free extracts to dissect ribonucleoprotein complex biology at single-molecule resolution.

Cellular machineries that drive and regulate gene expression often rely on the coordinated assembly and interaction of a multitude of proteins and RNA together called ribonucleoprotein complexes (RNPs). As such, it is challenging to fully reconstitute these cellular machines recombinantly and gain mechanistic understanding of how they operate and are regulated within the complex environment that is the cell. One strategy for overcoming this challenge is to perform single molecule fluorescence microscopy studies within crude or recombinantly supplemented cell extracts. This strategy enables elucidation of the interaction and kinetic behavior of specific fluorescently labeled biomolecules within RNPs under conditions that approximate native cellular environments. In this review, we describe single molecule fluorescence microcopy approaches that dissect RNP-driven processes within cellular extracts, highlighting general strategies used in these methods. We further survey biological advances in the areas of pre-mRNA splicing and transcription regulation that have been facilitated through this approach. Finally, we conclude with a summary of practical considerations for the implementation of the featured approaches to facilitate their broader future implementation in dissecting the mechanisms of RNP-driven cellular processes. This article is categorized under: RNA Structure and Dynamics > RNA Structure, Dynamics and Chemistry RNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes RNA Structure and Dynamics > Influence of RNA Structure in Biological Systems.

Spatiotemporally resolved transcriptomics reveals the subcellular RNA kinetic landscape

Spatiotemporal regulation of the cellular transcriptome is crucial for proper protein expression and cellular function. However, the intricate subcellular dynamics of RNA remain obscured due to the limitations of existing transcriptomics methods. Here, we report TEMPOmap—a method that uncovers subcellular RNA profiles across time and space at the single-cell level. TEMPOmap integrates pulse-chase metabolic labeling with highly multiplexed three-dimensional in situ sequencing to simultaneously profile the age and location of individual RNA molecules. Using TEMPOmap, we constructed the subcellular RNA kinetic landscape in various human cells from transcription and translocation to degradation. Clustering analysis of RNA kinetic parameters across single cells revealed ‘kinetic gene clusters’ whose expression patterns were shaped by multistep kinetic sculpting. Importantly, these kinetic gene clusters are functionally segregated, suggesting that subcellular RNA kinetics are differentially regulated in a cell-state- and cell-type-dependent manner. Spatiotemporally resolved transcriptomics provides a gateway to uncovering new spatiotemporal gene regulation principles.

RNA-Targeting Carbon Dots for Live-Cell Imaging of Granule Dynamics.

It is significant to monitor the different RNA granules dynamics and phase separation process inside cells under various stresses, for example, oxidative stress. The current small-molecule RNA probes work well only in fixed cells and usually encounter problems such as insufficient stability and biocompatibility, and thus a specific RNA-targeting fluorescent nanoprobe thatcan be used in the living cells is urgently desired. Here, the de novo design and microwave-assisted synthesis of a novel RNA-targeting, red-emissive carbon dots (named as M-CDs) are reported by choosing neutral red and levofloxacin as precursors. The as-synthesized M-CDs is water-soluble with a high fluorescence quantum yield of 22.83% and can selectively bind to RNA resulting in an enhanced red fluorescence. More interestingly, such an RNA-targeting, red-emissive M-CDs can be fast internalized into cells within 5s and thus used for real-time imaging the dynamic process of intracellular stress granules under oxidative stress, revealing some characteristics of granules that have not been identified by previously reported RNA and protein biomarkers. This research paves a new pathway for visualizing bulk RNA dynamics and studying phase-separation behaviors in living cells by rational design of the fluorescent carbon dots in terms of structure and functionality.

Well-TEMP-seq as a microwell-based strategy for massively parallel profiling of single-cell temporal RNA dynamics

Single-cell RNA sequencing (scRNA-seq) reveals the transcriptional heterogeneity of cells, but the static snapshots fail to reveal the time-resolved dynamics of transcription. Herein, we develop Well-TEMP-seq, a high-throughput, cost-effective, accurate, and efficient method for massively parallel profiling the temporal dynamics of single-cell gene expression. Well-TEMP-seq combines metabolic RNA labeling with scRNA-seq method Well-paired-seq to distinguish newly transcribed RNAs marked by T-to-C substitutions from pre-existing RNAs in each of thousands of single cells. The Well-paired-seq chip ensures a high single cell/barcoded bead pairing rate (~80%) and the improved alkylation chemistry on beads greatly alleviates chemical conversion-induced cell loss (~67.5% recovery). We further apply Well-TEMP-seq to profile the transcriptional dynamics of colorectal cancer cells exposed to 5-AZA-CdR, a DNA-demethylating drug. Well-TEMP-seq unbiasedly captures the RNA dynamics and outperforms the splicing-based RNA velocity method. We anticipate that Well-TEMP-seq will be broadly applicable to unveil the dynamics of single-cell gene expression in diverse biological processes.

Structural and dynamic effects of pseudouridine modifications on noncanonical interactions in RNA.

Pseudouridine is the most frequently naturally occurring RNA modification, found in all classes of biologically functional RNAs. Compared to uridine, pseudouridine contains an additional hydrogen bond donor group and is therefore widely regarded as a structure stabilizing modification. However, the effects of pseudouridine modifications on the structure and dynamics of RNAs have so far only been investigated in a limited number of different structural contexts. Here, we introduced pseudouridine modifications into the U-turn motif and the adjacent U:U closing base pair of the neomycin-sensing riboswitch (NSR)-an extensively characterized model system for RNA structure, ligand binding, and dynamics. We show that the effects of replacing specific uridines with pseudouridines on RNA dynamics crucially depend on the exact location of the replacement site and can range from destabilizing to locally or even globally stabilizing. By using a combination of NMR spectroscopy, MD simulations and QM calculations, we rationalize the observed effects on a structural and dynamical level. Our results will help to better understand and predict the consequences of pseudouridine modifications on the structure and function of biologically important RNAs.

Dynamics of disease characteristics and viral RNA decay in patients with asymptomatic and mild infections during the Omicron wave in Shanghai, China: A retrospective cohort study

ObjectivesAsymptomatic infections and mild diseases were more common during the Omicron outbreak in Shanghai, China in 2022. This study aimed to assess the characteristics and viral RNA decay between patients with asymptomatic and mild infections. MethodsA total of 55,111 patients infected with SARS-CoV-2 who were quarantined in the National Exhibition & Convention Center (Shanghai) Fangcang shelter hospital within 3 days after diagnosis from April 9 to May 23, 2022 were enrolled. The kinetics of cycle threshold (Ct) values of reverse transcription-polymerase chain reaction were assessed. The influencing factors for disease progression and the risk factors for the viral RNA shedding time (VST) were investigated. ResultsOn admission, 79.6% (43,852/55,111) of the cases were diagnosed with asymptomatic infections, and 20.4% were mild diseases. However, 78.0% of initially asymptomatic subjects developed mild diseases at the follow-up. The final proportion of asymptomatic infections was 17.5%. The median time of symptom onset, the duration of symptoms, and the VST were 2 days, 5 days, and 7 days, respectively. Female, age 19-40 years, underlying comorbidities with hypertension and diabetes, and vaccination were associated with higher risks of progressing to mildly symptomatic infections. In addition, mildly symptomatic infections were found to be associated with prolonged VST compared with asymptomatic infections. However, the kinetics of viral RNA decay and dynamics of Ct values were similar among asymptomatic subjects, patients with asymptomatic-to-mild infection, and patients with mild infection. ConclusionA large proportion of initially diagnosed asymptomatic Omicron infections is in the presymptomatic stage. The Omicron infection has a much shorter incubation period and VST than previous variants. The infectivity of asymptomatic infections and mildly symptomatic infections with Omicron is similar.

Visualizing orthogonal RNAs simultaneously in live mammalian cells by fluorescence lifetime imaging microscopy (FLIM)

Visualization of RNAs in live cells is critical to understand biology of RNA dynamics and function in the complex cellular environment. Detection of RNAs with a fluorescent marker frequently involves genetically fusing an RNA aptamer tag to the RNA of interest, which binds to small molecules that are added to live cells and have fluorescent properties. Engineering efforts aim to improve performance and add versatile features. Current efforts focus on adding multiplexing capabilities to tag and visualize multiple RNAs simultaneously in the same cell. Here, we present the fluorescence lifetime-based platform Riboglow-FLIM. Our system requires a smaller tag and has superior cell contrast when compared with intensity-based detection. Because our RNA tags are derived from a large bacterial riboswitch sequence family, the riboswitch variants add versatility for using multiple tags simultaneously. Indeed, we demonstrate visualization of two RNAs simultaneously with orthogonal lifetime-based tags.

Identification of metal ion-binding sites in RNA structures using deep learning method.

Metal ion is an indispensable factor for the proper folding, structural stability and functioning of RNA molecules. However, it is very difficult for experimental methods to detect them in RNAs. With the increase of experimentally resolved RNA structures, it becomes possible to identify the metal ion-binding sites in RNA structures through in-silico methods. Here, we propose an approach called Metal3DRNA to identify the binding sites of the most common metal ions (Mg2+, Na+ and K+) in RNA structures by using a three-dimensional convolutional neural network model. The negative samples, screened out based on the analysis for binding surroundings of metal ions, are more like positive ones than the randomly selected ones, which are beneficial to a powerful predictor construction. The microenvironments of the spatial distributions of C, O, N and P atoms around a sample are extracted as features. Metal3DRNA shows a promising prediction power, generally surpassing the state-of-the-art methods FEATURE and MetalionRNA. Finally, utilizing the visualization method, we inspect the contributions of nucleotide atoms to the classification in several cases, which provides a visualization that helps to comprehend the model. The method will be helpful for RNA structure prediction and dynamics simulation study. Availability and implementation: The source code is available at https://github.com/ChunhuaLiLab/Metal3DRNA.

Determining RNA Natural Modifications and Nucleoside Analog-Labeled Sites by a Chemical/Enzyme-Induced Base Mutation Principle.

The natural chemical modifications of messenger RNA (mRNA) in living organisms have shown essential roles in both physiology and pathology. The mapping of mRNA modifications is critical for interpreting their biological functions. In another dimension, the synthesized nucleoside analogs can enable chemical labeling of cellular mRNA through a metabolic pathway, which facilitates the study of RNA dynamics in a pulse-chase manner. In this regard, the sequencing tools for mapping both natural modifications and nucleoside tags on mRNA at single base resolution are highly necessary. In this work, we review the progress of chemical sequencing technology for determining both a variety of naturally occurring base modifications mainly on mRNA and a few on transfer RNA and metabolically incorporated artificial base analogs on mRNA, and further discuss the problems and prospects in the field.

Structure and dynamics of RNA in biomolecular condensate.

Although it is known that RNA undergoes phase separation, the interplay between the molecular driving forces and the emergent features of the condensates, such as their morphologies and dynamic properties, is not well understood. We introduce a coarse-grained model to simulate phase separation of RNAs. Simulations for the trinucleotide repeat RNAs, implicated in neurological disorders, reveal the structures and dynamics of RNA in condensates, which are drastically different from the dilute phase. Interestingly, the interaction network and dynamics in the condensate depend on the RNA sequence, and the droplet is most compact in the case of repeat RNAs. These findings shed light on the mechanisms of condensate formation of RNA repeat sequences, which can be helpful for the understanding of neurological disease onset.

Direct observation of RNA structure and dynamics in repeat-RNA assemblies using single molecule fluorescence microscopy.

Huntington's disease (HD), a fatal neurodegeneration, results from somatic expansions of CAG repeats in exon-1 of the Huntingtin (HTT) gene. Genome-wide association studies (GWAS) implicate age of onset (AO) of HD to strongly depend on the length of uninterrupted CAG repeats with certain variations in flanking sequences acting as an AO enhancer or an AO delayer. Stable, GC-rich hairpins formed by expanded CAG repeats in the HTT-mRNAs are thought to trigger dysregulated protein sequestration and aberrant assembly of cytoplasmic and nuclear repeat-RNA-protein (RNP) aggregates. While aggregation is observed to be stochastic in cells, the mechanism of how repeat-RNA aggregate assembly is initiated remains unknown. Specifically, it remains unclear how the extended hairpin structures interact intermolecularly to aggregate and to what extents proteins contribute to RNA-RNA aggregation. Furthermore, it is unknown how sequence variations to the HTT-mRNA affects its aggregation propensities. To address these aspects of repeat-RNP aggregate assembly, we use in vitro transcribed HTT exon-1 RNA containing normal, expanded and interrupted CAG repeats to form repeat-RNA assemblies in vitro. Using a single molecule fluorescence microscopy method, we monitor, in real time, the dynamics and structural changes of single HTT RNA molecules bound to phase separated HTT RNA assemblies. Additionally, we probe how the RNA binding dynamics are affected by HTT-RNA flanking sequences.This study aims to provide mechanistic insights into how expanded repeat-RNP aggregate assembly is initiated in order to understand how physical interactions between triplet-repeat containing RNAs contributes to the assembly of macromolecular repeat-RNP structures implicated in neuronal toxicity. The outcome from the proposed study has potential to develop novel therapeutic target(s) for designing new approaches to prevent aberrant RNP foci formation.