Cryo-EM advances in RNA structure determination

Structure-based investigation of a DNA aptamer targeting PTK7 reveals an intricate 3D fold guiding functional optimization

DNA aptamers have emerged as novel molecular tools in disease theranostics owing to their high binding affinity and specificity for protein targets, which rely on their ability to fold into distinctive three-dimensional (3D) structures. However, delicate atomic interactions that shape the 3D structures are often ignored when designing and modeling aptamers, leading to inefficient functional optimization. Challenges persist in determining high-resolution aptamer-protein complex structures. Moreover, the experimentally determined 3D structures of DNA molecules with exquisite functions remain scarce. These factors impede our comprehension and optimization of some important DNA aptamers. Here, we performed a streamlined solution NMR-based structural investigation on the 41-nt sgc8c, a prominent DNA aptamer used to target membrane protein tyrosine kinase 7, for cancer theranostics. We show that sgc8c prefolds into an intricate three-way junction (3WJ) structure stabilized by long-range tertiary interactions and extensive base-base stackings. Delineated by NMR chemical shift perturbations, site-directed mutagenesis, and 3D structural information, we identified essential nucleotides constituting the key functional elements of sgc8c that are centralized at the core of 3WJ. Leveraging the well-established structure-function relationship, we efficiently engineered two sgc8c variants by modifying the apical loop and introducing L-DNA base pairs to simultaneously enhance thermostability, biostability, and binding affinity for both protein and cell targets, a feat not previously attained despite extensive efforts. This work showcases a simplified NMR-based approach to comprehend and optimize sgc8c without acquiring the complex structure, and offers principles for the sophisticated structure-function organization of DNA molecules.

Recent advances in the molecular design and applications of viral RNA-targeting antiviral modalities

Pathogenic viruses are a profound threat to global public health, underscoring the urgent need for the development of efficacious antiviral therapeutics. The advent of RNA-targeting antiviral strategies has marked a significant paradigm shift in the management of viral infections, offering a potent means of control and potential cure. In this review, we delve into the cutting-edge progress in RNA-targeting antiviral agents, encompassing antisense oligonucleotides (ASOs), small interfering RNAs (siRNAs), small and bifunctional molecules. We provide an in-depth examination of their strategic molecular design and elucidate the underlying mechanisms of action that confer their antiviral efficacy. By synthesizing recent findings, we shed light on the innovative potential of RNA-targeting approaches and their pivotal role in advancing the frontiers of antiviral drug discovery.

Probing RNA structure and dynamics using nanopore and next generation sequencing

It has become increasingly evident that the structures RNAs adopt are conformationally dynamic; the various structured states that RNAs sample govern their interactions with other nucleic acids, proteins, and ligands to regulate a myriad of biological processes. Although several biophysical approaches have been developed and used to study the dynamic landscape of structured RNAs, technical limitations have limited their application to all classes of RNA due to variable size and flexibility. Recent advances combining chemical probing experiments with next-generation- and direct sequencing have emerged as an alternative approach to exploring the conformational dynamics of RNA. In this review, we provide a methodological overview of the sequencing-based techniques used to study RNA conformational dynamics. We discuss how different techniques have enabled us to better understand the propensity of RNAs from a variety of different classes to sample multiple conformational states. Finally, we present examples of the ways these techniques have reshaped how we think about RNA structure.

Novel RNA molecular bioengineering technology efficiently produces functional miRNA agents

Genome-derived microRNAs (miRNAs or miRs) govern posttranscriptional gene regulation and play important roles in various cellular processes and disease progression. While chemo-engineered miRNA mimics or biosimilars made in vitro are widely available and used, miRNA agents produced in vivo are emerging to closely recapitulate natural miRNA species for research. Our recent work has demonstrated the success of high-yield, in vivo production of recombinant miRNAs by using human tRNA (htRNA) fused precursor miRNA (pre-miR) carriers. In this study, we aim to compare the production of bioengineered RNA (BioRNA) molecules with glycyl versus leucyl htRNA fused hsa-pre-miR-34a carriers, namely, BioRNAGly and BioRNALeu, respectively, and perform the initial functional assessment. We designed, cloned, overexpressed, and purified a total of 48 new BioRNA/miRNAs, and overall expression levels, final yields, and purities were revealed to be comparable between BioRNAGly and BioRNALeu molecules. Meanwhile, the two versions of BioRNA/miRNAs showed similar activities to inhibit non-small cell lung cancer cell viability. Interestingly, functional analyses using model BioRNA/miR-7-5p demonstrated that BioRNAGly/miR-7-5p exhibited greater efficiency to regulate a known target gene expression (EGFR) than BioRNALeu/miR-7-5p, consistent with miR-7-5p levels released in cells. Moreover, BioRNAGly/miR-7-5p showed comparable or slightly greater activities to modulate MRP1 and VDAC1 expression, compared with miRCURY LNA miR-7-5p mimic. Computational modeling illustrated overall comparable 3D structures for exemplary BioRNA/miRNAs with noticeable differences in htRNA species and payload miRNAs. These findings support the utility of hybrid htRNA/hsa-pre-miR-34a as reliable carriers for RNA molecular bioengineering, and the resultant BioRNAs serve as functional biologic RNAs for research and development.

DEBFold: Computational Identification of RNA Secondary Structures for Sequences across Structural Families Using Deep Learning

It is now known that RNAs play more active roles in cellular pathways beyond simply serving as transcription templates. These biological mechanisms might be mediated by higher RNA stereo conformations, triggering the need to understand RNA secondary structures first. However, experimental protocols for solving RNA structures are unavailable for large-scale investigation due to their high costs and time-consuming nature. Various computational tools were thus developed to predict the RNA secondary structures from sequences. Recently, deep networks have been investigated to help predict RNA structures directly from their sequences. However, existing deep-learning-based tools are more or less suffering from model overfitting due to their complicated problem formulation and defective model training processes, limiting their applications across sequences from different structural families. In this research, we designed a two-stage RNA structure prediction strategy called DEBFold (deep ensemble boosting and folding) based on convolution encoding/decoding and self-attention mechanisms to enhance the existing thermodynamic structure models. Moreover, the model training process followed rigorous steps to achieve an acceptable prediction generalization. On the family-wise reserved test sets and the PDB-derived test set, DEBFold achieves better structure prediction performance over traditional tools and existing deep-learning methods. In summary, we obtained a cutting-edge deep-learning-based structure prediction tool with supreme across-family generalization performance. The DEBFold tool can be accessed at https://cobis.bme.ncku.edu.tw/DEBFold/.

Effects of Proline on Internal Friction in Simulated Folding Dynamics of Several Alanine-Based α-Helical Peptides

We have studied in silico the effect of proline, a model cosolvent, on local and global friction coefficients in (un)folding of several typical alanine-based α-helical peptides. Local friction is related to dwell times of a single, ensemble-averaged hydrogen bond (HB) within each peptide. Global friction is related to energy dissipated in a series of configurational changes of each peptide experienced by increasing the number of HBs during folding. Both of these approaches are important in relation to future atomic force microscopic-based measurements of internal friction via force-clamp single-molecule force spectroscopy. Molecular dynamics (MD) simulations for six peptides, namely, ALA5, ALA8, ALA15, ALA21, (AAQAA)3, and H2N-GN(AAQAA)2G-COONH2, have been conducted at 2 and 5 M proline solutions in water. Using previously obtained MD data for these peptides in pure water as well as upgraded theoretical models, we obtained variations of local and global internal friction coefficients as a function of solution viscosity. The results showed the substantial role of proline in stabilizing the folded state and slowing the overall folding dynamics. Consequently, larger friction coefficients were obtained at larger viscosities. The local and global internal friction, i.e., respective, friction coefficients approximated to zero viscosity, was also obtained. The evolution of friction coefficients with viscosity was weakly dependent on the number of concurrent folding pathways but was rather dominated by a stabilizing effect of proline on the folded states. Obtained values of local and global internal friction showed qualitatively similar results and a clear dependency on the structure of the studied peptide.

RmsdXNA: RMSD prediction of nucleic acid-ligand docking poses using machine-learning method

Small molecule drugs can be used to target nucleic acids (NA) to regulate biological processes. Computational modeling methods, such as molecular docking or scoring functions, are commonly employed to facilitate drug design. However, the accuracy of the scoring function in predicting the closest-to-native docking pose is often suboptimal. To overcome this problem, a machine learning model, RmsdXNA, was developed to predict the root-mean-square-deviation (RMSD) of ligand docking poses in NA complexes. The versatility of RmsdXNA has been demonstrated by its successful application to various complexes involving different types of NA receptors and ligands, including metal complexes and short peptides. The predicted RMSD by RmsdXNA was strongly correlated with the actual RMSD of the docked poses. RmsdXNA also outperformed the rDock scoring function in ranking and identifying closest-to-native docking poses across different structural groups and on the testing dataset. Using experimental validated results conducted on polyadenylated nuclear element for nuclear expression triplex, RmsdXNA demonstrated better screening power for the RNA-small molecule complex compared to rDock. Molecular dynamics simulations were subsequently employed to validate the binding of top-scoring ligand candidates selected by RmsdXNA and rDock on MALAT1. The results showed that RmsdXNA has a higher success rate in identifying promising ligands that can bind well to the receptor. The development of an accurate docking score for a NA-ligand complex can aid in drug discovery and development advancements. The code to use RmsdXNA is available at the GitHub repository https://github.com/laiheng001/RmsdXNA.

RNA-Small-Molecule Interaction: Challenging the "Undruggable" Tag

RNA targeting, specifically with small molecules, is a relatively new and rapidly emerging avenue with the promise to expand the target space in the drug discovery field. From being "disregarded" as an "undruggable" messenger molecule to FDA approval of an RNA-targeting small-molecule drug Risdiplam, a radical change in perspective toward RNA has been observed in the past decade. RNAs serve important regulatory functions beyond canonical protein synthesis, and their dysregulation has been reported in many diseases. A deeper understanding of RNA biology reveals that RNA molecules can adopt a variety of structures, carrying defined binding pockets that can accommodate small-molecule drugs. Due to its functional diversity and structural complexity, RNA can be perceived as a prospective target for therapeutic intervention. This perspective highlights the proof of concept of RNA-small-molecule interactions, exemplified by targeting of various transcripts with functional modulators. The advent of RNA-oriented knowledge would help expedite drug discovery.

Ionic liquids and deep eutectic solvents for the stabilization of biopharmaceuticals: A review

Biopharmaceuticals have allowed the control of previously untreatable diseases. However, their low solubility and stability still hinder their application, transport, and storage. Hence, researchers have applied different compounds to preserve and enhance the delivery of biopharmaceuticals, such as ionic liquids (ILs) and deep eutectic solvents (DESs). Although the biopharmaceutical industry can employ various substances for enhancing formulations, their effect will change depending on the properties of the target biomolecule and environmental conditions. Hence, this review organized the current state-of-the-art on the application of ILs and DESs to stabilize biopharmaceuticals, considering the properties of the biomolecules, ILs, and DESs classes, concentration range, types of stability, and effect. We also provided a critical discussion regarding the potential utilization of ILs and DESs in pharmaceutical formulations, considering the restrictions in this field, as well as the advantages and drawbacks of these substances for medical applications. Overall, the most applied IL and DES classes for stabilizing biopharmaceuticals were cholinium-, imidazolium-, and ammonium-based, with cholinium ILs also employed to improve their delivery. Interestingly, dilute and concentrated ILs and DESs solutions presented similar results regarding the stabilization of biopharmaceuticals. With additional investigation, ILs and DESs have the potential to overcome current challenges in biopharmaceutical formulation.

Multi-ancestry tandem repeat association study of hair colour using exome-wide sequencing

Hair colour variation is influenced by hundreds of positions across the human genome but this genetic contribution has only been narrowly explored. Genome-wide association studies identified single nucleotide polymorphisms (SNPs) influencing hair colour but the biology underlying these associations is challenging to interpret. We report 16 tandem repeats (TRs) with effects on different models of hair colour plus two TRs associated with hair colour in diverse ancestry groups. Several of these TRs expand or contract amino acid coding regions of their localized protein such that structure, and by extension function, may be altered. We also demonstrate that independent of SNP variation, these TRs can be used to great an additive polygenic score that predicts darker hair colour. This work adds to the growing body of evidence regarding TR influence on human traits with relatively large and independent effects relative to surrounding SNP variation.

All-atom RNA structure determination from cryo-EM maps

Many methods exist for determining protein structures from cryogenic electron microscopy maps, but this remains challenging for RNA structures. Here we developed EMRNA, a method for accurate, automated determination of full-length all-atom RNA structures from cryogenic electron microscopy maps. EMRNA integrates deep learning-based detection of nucleotides, three-dimensional backbone tracing and scoring with consideration of sequence and secondary structure information, and full-atom construction of the RNA structure. We validated EMRNA on 140 diverse RNA maps ranging from 37 to 423 nt at 2.0-6.0 Å resolutions, and compared EMRNA with auto-DRRAFTER, phenix.map_to_model and CryoREAD on a set of 71 cases. EMRNA achieves a median accuracy of 2.36 Å root mean square deviation and 0.86 TM-score for full-length RNA structures, compared with 6.66 Å and 0.58 for auto-DRRAFTER. EMRNA also obtains a high residue coverage and sequence match of 93.30% and 95.30% in the built models, compared with 58.20% and 42.20% for phenix.map_to_model and 56.45% and 52.3% for CryoREAD. EMRNA is fast and can build an RNA structure of 100 nt within 3 min.

Structural and computational studies of HIV-1 RNA

Viruses remain a global threat to animals, plants, and humans. The type 1 human immunodeficiency virus (HIV-1) is a member of the retrovirus family and carries an RNA genome, which is reverse transcribed into viral DNA and further integrated into the host-cell DNA for viral replication and proliferation. The RNA structures from the HIV-1 genome provide valuable insights into the mechanisms underlying the viral replication cycle. Moreover, these structures serve as models for designing novel therapeutic approaches. Here, we review structural data on RNA from the HIV-1 genome as well as computational studies based on these structural data. The review is organized according to the type of structured RNA element which contributes to different steps in the viral replication cycle. This is followed by an overview of the HIV-1 transactivation response element (TAR) RNA as a model system for understanding dynamics and interactions in the viral RNA systems. The review concludes with a description of computational studies, highlighting the impact of biomolecular simulations in elucidating the mechanistic details of various steps in the HIV-1's replication cycle.

FURNA: a database for function annotations of RNA structures

Despite the increasing number of 3D RNA structures in the Protein Data Bank, the majority of experimental RNA structures lack thorough functional annotations. As the significance of the functional roles played by non-coding RNAs becomes increasingly apparent, comprehensive annotation of RNA function is becoming a pressing concern. In response to this need, we have developed FURNA (Functions of RNAs), the first database for experimental RNA structures that aims to provide a comprehensive repository of high-quality functional annotations. These include Gene Ontology terms, Enzyme Commission numbers, ligand binding sites, RNA families, protein binding motifs, and cross-references to related databases. FURNA is available at https://seq2fun.dcmb.med.umich.edu/furna/ to enable quick discovery of RNA functions from their structures and sequences.

A minority of final stacks yields superior amplitude in single-particle cryo-EM

Cryogenic electron microscopy (cryo-EM) is widely used to determine near-atomic resolution structures of biological macromolecules. Due to the low signal-to-noise ratio, cryo-EM relies on averaging many images. However, a crucial question in the field of cryo-EM remains unanswered: how close can we get to the minimum number of particles required to reach a specific resolution in practice? The absence of an answer to this question has impeded progress in understanding sample behavior and the performance of sample preparation methods. To address this issue, we develop an iterative particle sorting and/or sieving method called CryoSieve. Extensive experiments demonstrate that CryoSieve outperforms other cryo-EM particle sorting algorithms, revealing that most particles are unnecessary in final stacks. The minority of particles remaining in the final stacks yield superior high-resolution amplitude in reconstructed density maps. For some datasets, the size of the finest subset approaches the theoretical limit.

Aptamer-Protein Interactions: From Regulation to Biomolecular Detection

Serving as the basis of cell life, interactions between nucleic acids and proteins play essential roles in fundamental cellular processes. Aptamers are unique single-stranded oligonucleotides generated by in vitro evolution methods, possessing the ability to interact with proteins specifically. Altering the structure of aptamers will largely modulate their interactions with proteins and further affect related cellular behaviors. Recently, with the in-depth research of aptamer-protein interactions, the analytical assays based on their interactions have been widely developed and become a powerful tool for biomolecular detection. There are some insightful reviews on aptamers applied in protein detection, while few systematic discussions are from the perspective of regulating aptamer-protein interactions. Herein, we comprehensively introduce the methods for regulating aptamer-protein interactions and elaborate on the detection techniques for analyzing aptamer-protein interactions. Additionally, this review provides a broad summary of analytical assays based on the regulation of aptamer-protein interactions for detecting biomolecules. Finally, we present our perspectives regarding the opportunities and challenges of analytical assays for biological analysis, aiming to provide guidance for disease mechanism research and drug discovery.

A generalizable scaffold-based approach for structure determination of RNAs by cryo-EM

Single-particle cryo-electron microscopy (cryo-EM) can reveal the structures of large and often dynamic molecules, but smaller biomolecules (≤50 kDa) remain challenging targets due to their intrinsic low signal to noise ratio. Methods to help resolve small proteins have been applied but development of similar approaches to aid in structural determination of small, structured RNA elements have lagged. Here, we present a scaffold-based approach that we used to recover maps of sub-25 kDa RNA domains to 4.5-5.0 Å. While lacking the detail of true high-resolution maps, these maps are suitable for model building and preliminary structure determination. We demonstrate this method helped faithfully recover the structure of several RNA elements of known structure, and that it promises to be generalized to other RNAs without disturbing their native fold. This approach may streamline the sample preparation process and reduce the optimization required for data collection. This first-generation scaffold approach provides a robust system to aid in RNA structure determination by cryo-EM and lays the groundwork for further scaffold optimization to achieve higher resolution.

In vivo-like nearest neighbor parameters improve prediction of fractional RNA base-pairing in cells

We conducted a thermodynamic analysis of RNA stability in Eco80 artificial cytoplasm, which mimics in vivo conditions, and compared it to transcriptome-wide probing of mRNA. Eco80 contains 80% of Escherichia coli metabolites, with biological concentrations of metal ions, including 2 mM free Mg2+ and 29 mM metabolite-chelated Mg2+. Fluorescence-detected binding isotherms (FDBI) were used to conduct a thermodynamic analysis of 24 RNA helices and found that these helices, which have an average stability of -12.3 kcal/mol, are less stable by ΔΔGo37 ∼1 kcal/mol. The FDBI data was used to determine a set of Watson-Crick free energy nearest neighbor parameters (NNPs), which revealed that Eco80 reduces the stability of three NNPs. This information was used to adjust the NN model using the RNAstructure package. The in vivo-like adjustments have minimal effects on the prediction of RNA secondary structures determined in vitro and in silico, but markedly improve prediction of fractional RNA base pairing in E. coli, as benchmarked with our in vivo DMS and EDC RNA chemical probing data. In summary, our thermodynamic and chemical probing analyses of RNA helices indicate that RNA secondary structures are less stable in cells than in artificially stable in vitro buffer conditions.

Capturing heterogeneous conformers of cobalamin riboswitch by cryo-EM

RNA conformational heterogeneity often hampers its high-resolution structure determination, especially for large and flexible RNAs devoid of stabilizing proteins or ligands. The adenosylcobalamin riboswitch exhibits heterogeneous conformations under 1 mM Mg2+ concentration and ligand binding reduces conformational flexibility. Among all conformers, we determined one apo (5.3 Å) and four holo cryo-electron microscopy structures (overall 3.0-3.5 Å, binding pocket 2.9-3.2 Å). The holo dimers exhibit global motions of helical twisting and bending around the dimer interface. A backbone comparison of the apo and holo states reveals a large structural difference in the P6 extension position. The central strand of the binding pocket, junction 6/3, changes from an 'S'- to a 'U'-shaped conformation to accommodate ligand. Furthermore, the binding pocket can partially form under 1 mM Mg2+ and fully form under 10 mM Mg2+ within the bound-like structure in the absence of ligand. Our results not only demonstrate the stabilizing ligand-induced conformational changes in and around the binding pocket but may also provide further insight into the role of the P6 extension in ligand binding and selectivity.

Integrative solution structure of PTBP1-IRES complex reveals strong compaction and ordering with residual conformational flexibility

RNA-binding proteins (RBPs) are crucial regulators of gene expression, often composed of defined domains interspersed with flexible, intrinsically disordered regions. Determining the structure of ribonucleoprotein (RNP) complexes involving such RBPs necessitates integrative structural modeling due to their lack of a single stable state. In this study, we integrate magnetic resonance, mass spectrometry, and small-angle scattering data to determine the solution structure of the polypyrimidine-tract binding protein 1 (PTBP1/hnRNP I) bound to an RNA fragment from the internal ribosome entry site (IRES) of the encephalomyocarditis virus (EMCV). This binding, essential for enhancing the translation of viral RNA, leads to a complex structure that demonstrates RNA and protein compaction, while maintaining pronounced conformational flexibility. Acting as an RNA chaperone, PTBP1 orchestrates the IRES RNA into a few distinct conformations, exposing the RNA stems outward. This conformational diversity is likely common among RNP structures and functionally important. Our approach enables atomic-level characterization of heterogeneous RNP structures.

Arena: Rapid and Accurate Reconstruction of Full Atomic RNA Structures From Coarse-grained Models

RNA tertiary structures from experiments or computational predictions often contain missing atoms, which prevent analyses requiring full atomic structures. Current programs for RNA reconstruction can be slow, inaccurate, and/or require specific atoms to be present in the input. We present Arena (Atomic Reconstruction of RNA), which reconstructs a full atomic RNA structure from residues that can have as few as one atom. Arena first fills in missing atoms and then iteratively refines their placement to reduce nonideal geometries. We benchmarked Arena on a dataset of 361 RNA structures, where Arena achieves high accuracy and speed compared to other structure reconstruction programs. For example, Arena was used to reconstruct full atomic structures from a single phosphorus atom per nucleotide to, on average, within 3.63 Å RMSD of the experimental structure, while virtually removing all clashes and running in <3 s, which is 353× and 46× faster than state-of-the-art programs PDBFixer and C2A, respectively. The Arena source code is available at https://github.com/pylelab/Arena and the webserver at https://zhanggroup.org/Arena/.

The Transition from Unfolded to Folded G-Quadruplex DNA Analyzed and Interpreted by Two-Dimensional Infrared Spectroscopy

A class of DNA folds/structures known collectively as G-quadruplexes (G4) commonly forms in guanine-rich areas of genomes. G4-DNA is thought to have a functional role in the regulation of gene transcription and telomerase-mediated telomere maintenance and, therefore, is a target for drugs. The details of the molecular interactions that cause stacking of the guanine-tetrads are not well-understood, which limits a rational approach to the drugability of G4 sequences. To explore these interactions, we employed electron-vibration-vibration two-dimensional infrared (EVV 2DIR) spectroscopy to measure extended vibrational coupling spectra for a parallel-stranded G4-DNA formed by the Myc2345 nucleotide sequence. We also tracked the structural changes associated with G4-folding as a function of K+-ion concentration. To classify the structural elements that the folding process generates in terms of vibrational coupling characteristics, we used quantum-chemical calculations utilizing density functional theory to predict the coupling spectra associated with given structures, which are compared against the experimental data. Overall, 102 coupling peaks are experimentally identified and followed during the folding process. Several phenomena are noted and associated with formation of the folded form. This includes frequency shifting, changes in cross-peak intensity, and the appearance of new coupling peaks. We used these observations to propose a folding sequence for this particular type of G4 under our experimental conditions. Overall, the combination of experimental 2DIR data and DFT calculations suggests that guanine-quartets may already be present before the addition of K+-ions, but that these quartets are unstacked until K+-ions are added, at which point the full G4 structure is formed.

Growth media affects susceptibility of air-lifted human nasal epithelial cell cultures to SARS-CoV2, but not Influenza A, virus infection

Primary differentiated human epithelial cell cultures have been widely used by researchers to study viral fitness and virus-host interactions, especially during the COVID19 pandemic. These cultures recapitulate important characteristics of the respiratory epithelium such as diverse cell type composition, polarization, and innate immune responses. However, standardization and validation of these cultures remains an open issue. In this study, two different expansion medias were evaluated and the impact on the resulting differentiated culture was determined. Use of both Airway and Ex Plus media types resulted in high quality, consistent cultures that were able to be used for these studies. Upon histological evaluation, Airway-grown cultures were more organized and had a higher proportion of basal progenitor cells while Ex Plus- grown cultures had a higher proportion terminally differentiated cell types. In addition to having different cell type proportions and organization, the two different growth medias led to cultures with altered susceptibility to infection with SARS-CoV-2 but not Influenza A virus. RNAseq comparing cultures grown in different growth medias prior to differentiation uncovered a high degree of differentially expressed genes in cultures from the same donor. RNAseq on differentiated cultures showed less variation between growth medias but alterations in pathways that control the expression of human transmembrane proteases including TMPRSS11 and TMPRSS2 were documented. Enhanced susceptibility to SARS-CoV-2 cannot be explained by altered cell type proportions alone, rather serine protease cofactor expression also contributes to the enhanced replication of SARS-CoV-2 as inhibition with camostat affected replication of an early SARS-CoV-2 variant and a Delta, but not Omicron, variant showed difference in replication efficiency between culture types. Therefore, it is important for the research community to standardize cell culture protocols particularly when characterizing novel viruses.

Fever-like temperature impacts on Staphylococcus aureus and Pseudomonas aeruginosa interaction, physiology, and virulence both in vitro and in vivo

Background

Staphylococcus aureus and Pseudomonas aeruginosa cause a wide variety of bacterial infections and coinfections, showing a complex interaction that involves the production of different metabolites and metabolic changes. Temperature is a key factor for bacterial survival and virulence and within the host, bacteria could be exposed to an increment in temperature during fever development. We analyzed the previously unexplored effect of fever-like temperatures (39°C) on S. aureus USA300 and P. aeruginosa PAO1 microaerobic mono- and co-cultures compared with 37°C, by using RNAseq and physiological assays including in-vivo experiments.

Results

In general terms both temperature and co-culturing had a strong impact on both PA and SA with the exception of the temperature response of monocultured PA. We studied metabolic and virulence changes on both species. Altered metabolic features at 39°C included arginine biosynthesis and the periplasmic glucose oxidation in S. aureus and P. aeruginosa monocultures respectively. When PA co-cultures were exposed at 39°C they upregulated ethanol oxidation related genes along with an increment in organic acid accumulation. Regarding virulence factors, monocultured SA showed an increase in the mRNA expression of the agr operon and hld, pmsα and pmsβ genes at 39°C. Supported by mRNA data, we performed physiological experiments and detected and increment in hemolysis, staphylxantin production and a decrease in biofilm formation at 39°C. On the side of PA monocultures, we observed increase in extracellular lipase and protease and biofilm formation at 39°C along with a decrease in motility in correlation with changes observed at mRNA abundance. Additionally, we assessed host-pathogen interaction both in-vitro and in-vivo . S. aureus monocultured at 39°C showed a decrease in cellular invasion and an increase in IL-8 -but not in IL-6- production by A549 cell line. PA also decreased its cellular invasion when monocultured at 39°C and did not induce any change in IL-8 or IL-6 production. PA strongly increased cellular invasion when co-cultured at 37°C and 39°C. Finally, we observed increased lethality in mice intranasally inoculated with S. aureus monocultures pre-incubated at 39°C and even higher levels when inoculated with co-cultures. The bacterial burden for P. aeruginosa was higher in liver when the mice were infected with co-cultures previously incubated at 39°C comparing with 37°C.

Conclusion

Our results highlight a relevant change in the virulence of bacterial opportunistic pathogens exposed to fever-like temperatures in presence of competitors, opening new questions related to bacteria-bacteria and host-pathogen interactions and coevolution.

A Generalizable Scaffold-Based Approach for Structure Determination of RNAs by Cryo-EM

Single-particle cryo-electron microscopy (cryo-EM) can reveal the structures of large and often dynamic molecules, but smaller biomolecules remain challenging targets due to their intrinsic low signal to noise ratio. Methods to resolve small proteins have been applied but development of similar approaches for small structured RNA elements have lagged. Here, we present a scaffold-based approach that we used to recover maps of sub-25 kDa RNA domains to 4.5 - 5.0 Å. While lacking the detail of true high-resolution maps, these are suitable for model building and preliminary structure determination. We demonstrate this method faithfully recovers the structure of several RNA elements of known structure, and it promises to be generalized to other RNAs without disturbing their native fold. This approach may streamline the sample preparation process and reduce the optimization required for data collection. This first-generation scaffold approach provides a system for RNA structure determination by cryo-EM and lays the groundwork for further scaffold optimization to achieve higher resolution.

Revolving hexameric ATPases as asymmetric motors to translocate double-stranded DNA genome along one strand

DsDNA translocation through nanoscale pores is generally accomplished by ATPase biomotors. The discovery of the revolving dsDNA translocation mechanism, as opposed to rotation, in bacteriophage phi29 elucidated how ATPase motors move dsDNA. Revolution-driven, hexameric dsDNA motors have been reported in herpesvirus, bacterial FtsK, Streptomyces TraB, and T7 phage. This review explores the common relationship between their structure and mechanisms. Commonalities include moving along the 5'→3' strand, inchworm sequential action leading to an asymmetrical structure, channel chirality, channel size, and 3-step channel gating for controlling motion direction. The revolving mechanism and contact with one of the dsDNA strands addresses the historic controversy of dsDNA packaging using nicked, gapped, hybrid, or chemically modified DNA. These controversies surrounding dsDNA packaging activity using modified materials can be answered by whether the modification was introduced into the 3'→5' or 5'→3' strand. Perspectives concerning solutions to the controversy of motor structure and stoichiometry are also discussed.

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

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

Tertiary structure of single-instant RNA molecule reveals folding landscape

The folding of RNA and protein molecules during their synthesis is a crucial self-assembly process that nature employs to convert genetic information into the complex molecular machinery that supports life. Misfolding events are the cause of several diseases, and the folding pathway of central biomolecules, such as the ribosome, is strictly regulated by programmed maturation processes and folding chaperones. However, the dynamic folding processes are challenging to study because current structure determination methods heavily rely on averaging, and existing computational methods do not efficiently simulate non-equilibrium dynamics. Here we utilize individual-particle cryo-electron tomography (IPET) to investigate the folding landscape of a rationally designed RNA origami 6-helix bundle that undergoes slow maturation from a "young" to "mature" conformation. By optimizing the IPET imaging and electron dose conditions, we obtain 3D reconstructions of 120 individual particles at resolutions ranging from 23-35 Å, enabling us first-time to observe individual RNA helices and tertiary structures without averaging. Statistical analysis of 120 tertiary structures confirms the two main conformations and suggests a possible folding pathway driven by helix-helix compaction. Studies of the full conformational landscape reveal both trapped states, misfolded states, intermediate states, and fully compacted states. The study provides novel insight into RNA folding pathways and paves the way for future studies of the energy landscape of molecular machines and self-assembly processes.

Recognizing the power of machine learning and other computational methods to accelerate progress in small molecule targeting of RNA

RNA structures regulate a wide range of processes in biology and disease, yet small molecule chemical probes or drugs that can modulate these functions are rare. Machine learning and other computational methods are well poised to fill gaps in knowledge and overcome the inherent challenges in RNA targeting, such as the dynamic nature of RNA and the difficulty of obtaining RNA high-resolution structures. Successful tools to date include principal component analysis, linear discriminate analysis, k-nearest neighbor, artificial neural networks, multiple linear regression, and many others. Employment of these tools has revealed critical factors for selective recognition in RNA:small molecule complexes, predictable differences in RNA- and protein-binding ligands, and quantitative structure activity relationships that allow the rational design of small molecules for a given RNA target. Herein we present our perspective on the value of using machine learning and other computation methods to advance RNA:small molecule targeting, including select examples and their validation as well as necessary and promising future directions that will be key to accelerate discoveries in this important field.

Snapshots of the second-step self-splicing of Tetrahymena ribozyme revealed by cryo-EM

Group I introns are catalytic RNAs that coordinate two consecutive transesterification reactions for self-splicing. To understand how the group I intron promotes catalysis and coordinates self-splicing reactions, we determine the structures of L-16 Tetrahymena ribozyme in complex with a 5'-splice site analog product and a 3'-splice site analog substrate using cryo-EM. We solve six conformations from a single specimen, corresponding to different splicing intermediates after the first ester-transfer reaction. The structures reveal dynamics during self-splicing, including large conformational changes of the internal guide sequence and the J5/4 junction as well as subtle rearrangements of active-site metals and the hydrogen bond formed between the 2'-OH group of A261 and the N2 group of guanosine substrate. These results help complete a detailed structural and mechanistic view of this paradigmatic group I intron undergoing the second step of self-splicing.

Chemical crosslinking and ligation methods for in vivo analysis of RNA structures and interactions

RNA structures and interactions in living cells drive a variety of biological processes and play critical roles in physiology and disease states. However, studies of RNA structures and interactions have been challenging due to limitations in available technologies. Direct determination of structures in vitro has been only possible to a small number of RNAs with limited sizes and conformations. We recently introduced two chemical crosslink-ligation techniques that enabled studies of transcriptome-wide secondary and tertiary structures and their dynamics. In a dramatically improved version of the psoralen analysis of RNA interactions and structures (PARIS2) method, we detailed the synthesis and use of amotosalen, a highly soluble psoralen analogue, and enhanced enzymology for higher efficiency duplex capture. We also introduced spatial 2'-hydroxyl acylation reversible crosslinking (SHARC) with exonuclease (exo) trimming, a method which utilizes a novel crosslinker class that targets the 2'-OH to capture three-dimensional (3D) structures. Both are powerful orthogonal approaches for solving in vivo RNA structure and interactions, integrating crosslinking, exo trimming, proximity ligation, and high throughput sequencing. In this chapter, we present a detailed protocol for the methods and highlight steps that outperform existing crosslink-ligation approaches.

Cryo-EM-guided engineering of T-box-tRNA modules with enhanced selectivity and sensitivity in translational regulation

Riboswitches are non-coding RNA elements that play vital roles in regulating gene expression. Their specific ligand-dependent structural reorganization facilitates their use as templates for design of engineered RNA switches for therapeutics, nanotechnology and synthetic biology. T-box riboswitches bind tRNAs to sense aminoacylation and control gene expression via transcription attenuation or translation inhibition. Here we determine the cryo-EM structure of the wild-type Mycobacterium smegmatis ileS T-box in complex with its cognate tRNA ^Ile . This structure shows a very flexible antisequestrator region that tolerates both 3'-OH and 2',3'-cyclic phosphate modification at the 3' end of tRNA ^Ile . Elongation of one helical turn (11-base pair) in both the tRNA acceptor arm and T-box Stem III maintains T-box-tRNA complex formation and increases the selectivity for tRNA 3' end modification. Moreover, elongation of Stem III results in ∼6-fold tighter binding to tRNA, which leads to increased sensitivity of downstream translational regulation indicated by precedent translation. Our results demonstrate that cryo-EM can guide RNA engineering to design improved riboswitch modules for translational regulation, and potentially a variety of additional functions.

Structure of a 28.5 kDa duplex-embedded G-quadruplex system resolved to 7.4 Å resolution with cryo-EM

Genomic regions with high guanine content can fold into non-B form DNA four-stranded structures known as G-quadruplexes (G4s). Extensive in vivo investigations have revealed that promoter G4s are transcriptional regulators. Little structural information exists for these G4s embedded within duplexes, their presumed genomic environment. Here, we report the 7.4 Å resolution structure and dynamics of a 28.5 kDa duplex-G4-duplex (DGD) model system using cryo-EM, molecular dynamics, and small-angle X-ray scattering (SAXS) studies. The DGD cryo-EM refined model features a 53° bend induced by a stacked duplex-G4 interaction at the 5' G-tetrad interface with a persistently unstacked 3' duplex. The surrogate complement poly dT loop preferably stacks onto the 3' G-tetrad interface resulting in occlusion of both 5' and 3' tetrad interfaces. Structural analysis shows that the DGD model is quantifiably more druggable than the monomeric G4 structure alone and represents a new structural drug target. Our results illustrate how the integration of cryo-EM, MD, and SAXS can reveal complementary detailed static and dynamic structural information on DNA G4 systems.

Snapshots of the first-step self-splicing of Tetrahymena ribozyme revealed by cryo-EM

Tetrahymena ribozyme is a group I intron, whose self-splicing is the result of two sequential ester-transfer reactions. To understand how it facilitates catalysis in the first self-splicing reaction, we used cryogenic electron microscopy (cryo-EM) to resolve the structures of L-16 Tetrahymena ribozyme complexed with a 11-nucleotide 5'-splice site analog substrate. Four conformations were achieved to 4.14, 3.18, 3.09 and 2.98 Å resolutions, respectively, corresponding to different splicing intermediates during the first enzymatic reaction. Comparison of these structures reveals structural alterations, including large conformational changes in IGS/IGSext (P1-P1ext duplex) and J5/4, as well as subtle local rearrangements in the G-binding site. These structural changes are required for the enzymatic activity of the Tetrahymena ribozyme. Our study demonstrates the ability of cryo-EM to capture dynamic RNA structural changes, ushering in a new era in the analysis of RNA structure-function by cryo-EM.

LinAliFold and CentroidLinAliFold: fast RNA consensus secondary structure prediction for aligned sequences using beam search methods

Motivation

RNA consensus secondary structure prediction from aligned sequences is a powerful approach for improving the secondary structure prediction accuracy. However, because the computational complexities of conventional prediction tools scale with the cube of the alignment lengths, their application to long RNA sequences, such as viral RNAs or long non-coding RNAs, requires significant computational time.

Results

In this study, we developed LinAliFold and CentroidLinAliFold, fast RNA consensus secondary structure prediction tools based on minimum free energy and maximum expected accuracy principles, respectively. We achieved software acceleration using beam search methods that were successfully used for fast secondary structure prediction from a single RNA sequence. Benchmark analyses showed that LinAliFold and CentroidLinAliFold were much faster than the existing methods while preserving the prediction accuracy. As an empirical application, we predicted the consensus secondary structure of coronaviruses with approximately 30 000 nt in 5 and 79 min by LinAliFold and CentroidLinAliFold, respectively. We confirmed that the predicted consensus secondary structure of coronaviruses was consistent with the experimental results.

Availability and implementation

The source codes of LinAliFold and CentroidLinAliFold are freely available at https://github.com/fukunagatsu/LinAliFold-CentroidLinAliFold.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

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.

The promise of cryo-EM to explore RNA structural dynamics

Conformational dynamics are essential to macromolecular function. This is certainly true of RNA, whose ability to undergo programmed conformational dynamics is essential to create and regulate complex biological processes. However, methods to easily and simultaneously interrogate both the structure and conformational dynamics of fully functional RNAs in isolation and in complex with proteins have not historically been available. Due to its ability to image and classify single particles, cryogenic electron microscopy (cryo-EM) has the potential to address this gap and may be particularly amenable to exploring structural dynamics within the three-dimensional folds of biologically active RNAs. We discuss the possibilities and current limitations of applying cryo-EM to simultaneously study RNA structure and conformational dynamics, and present one example that illustrates this (as of yet) not fully realized potential.

Topological crossing in the misfolded Tetrahymena ribozyme resolved by cryo-EM

Taking advantage of single-particle cryogenic electron microscopy (cryo-EM) to analyze highly heterogeneous or flexible samples, we obtained long-awaited three-dimensional (3D) structures of the misfolded Tetrahymena ribozyme. These structures provide clear evidence for a previously proposed topological isomer model, in which the stereochemically impossible crossing of two core RNA strands prevents rapid rearrangement of the misfolded state to the native state. Topological isomers may be widespread in misfolding of complex RNA, and these cryo-EM structures set a foundation for dissecting their detailed kinetic mechanisms and functional consequences in a paradigmatic model system.

The Tetrahymena group I intron has been a key system in the understanding of RNA folding and misfolding. The molecule folds into a long-lived misfolded intermediate (M) in vitro, which has been known to form extensive native-like secondary and tertiary structures but is separated by an unknown kinetic barrier from the native state (N). Here, we used cryogenic electron microscopy (cryo-EM) to resolve misfolded structures of the Tetrahymena L-21 ScaI ribozyme. Maps of three M substates (M1, M2, M3) and one N state were achieved from a single specimen with overall resolutions of 3.5 Å, 3.8 Å, 4.0 Å, and 3.0 Å, respectively. Comparisons of the structures reveal that all the M substates are highly similar to N, except for rotation of a core helix P7 that harbors the ribozyme’s guanosine binding site and the crossing of the strands J7/3 and J8/7 that connect P7 to the other elements in the ribozyme core. This topological difference between the M substates and N state explains the failure of 5′-splice site substrate docking in M, supports a topological isomer model for the slow refolding of M to N due to a trapped strand crossing, and suggests pathways for M-to-N refolding.

Computational and Experimental Approaches to Study the RNA Secondary Structures of RNA Viruses

Most pandemics of recent decades can be traced to RNA viruses, including HIV, SARS, influenza, dengue, Zika, and SARS-CoV-2. These RNA viruses impose considerable social and economic burdens on our society, resulting in a high number of deaths and high treatment costs. As these RNA viruses utilize an RNA genome, which is important for different stages of the viral life cycle, including replication, translation, and packaging, studying how the genome folds is important to understand virus function. In this review, we summarize recent advances in computational and high-throughput RNA structure-mapping approaches and their use in understanding structures within RNA virus genomes. In particular, we focus on the genome structures of the dengue, Zika, and SARS-CoV-2 viruses due to recent significant outbreaks of these viruses around the world.

Targeting Pathogenic DNA and RNA Repeats: A Conceptual Therapeutic Way for Repeat Expansion Diseases

Expansions of short tandem repeats (STRs) in the human genome cause nearly 50 neurodegenerative diseases, which are mostly inheritable, nonpreventable and incurable, posing as a huge threat to human health. Non-B DNAs formed by STRs are thought to be structural intermediates that can cause repeat expansions. The subsequent transcripts harboring expanded RNA repeats can further induce cellular toxicity through forming specific structures. Direct targeting of these pathogenic DNA and RNA repeats has emerged as a new potential therapeutic strategy to cure repeat expansion diseases. In this conceptual review, we first introduce the roles of DNA and RNA structures in the genetic instabilities and pathomechanisms of repeat expansion diseases, then describe structural features of DNA and RNA repeats with a focus on the tertiary structures determined by X-ray crystallography and solution nuclear magnetic resonance spectroscopy, and finally discuss recent progress and perspectives of developing chemical tools that target pathogenic DNA and RNA repeats for curing repeat expansion diseases.