Structure, folding and flexibility of co-transcriptional RNA origami

Knotted artifacts in predicted 3D RNA structures

Unlike proteins, RNAs deposited in the Protein Data Bank do not contain topological knots. Recently, admittedly, the first trefoil knot and some lasso-type conformations have been found in experimental RNA structures, but these are still exceptional cases. Meanwhile, algorithms predicting 3D RNA models have happened to form knotted structures not so rarely. Interestingly, machine learning-based predictors seem to be more prone to generate knotted RNA folds than traditional methods. A similar situation is observed for the entanglements of structural elements. In this paper, we analyze all models submitted to the CASP15 competition in the 3D RNA structure prediction category. We show what types of topological knots and structure element entanglements appear in the submitted models and highlight what methods are behind the generation of such conformations. We also study the structural aspect of susceptibility to entanglement. We suggest that predictors take care of an evaluation of RNA models to avoid publishing structures with artifacts, such as unusual entanglements, that result from hallucinations of predictive algorithms.

RNA nanotechnology on the horizon: Self-assembly, chemical modifications, and functional applications

RNA nanotechnology harnesses the unique chemical and structural properties of RNA to build nanoassemblies and supramolecular structures with dynamic and functional capabilities. This review focuses on design and assembly approaches to building RNA structures, the RNA chemical modifications used to enhance stability and functionality, and modern-day applications in therapeutics, biosensing, and bioimaging.

An RNA origami robot that traps and releases a fluorescent aptamer

RNA nanotechnology aims to use RNA as a programmable material to create self-assembling nanodevices for application in medicine and synthetic biology. The main challenge is to develop advanced RNA robotic devices that both sense, compute, and actuate to obtain enhanced control over molecular processes. Here, we use the RNA origami method to prototype an RNA robotic device, named the "Traptamer," that mechanically traps the fluorescent aptamer, iSpinach. The Traptamer is shown to sense two RNA key strands, acts as a Boolean AND gate, and reversibly controls the fluorescence of the iSpinach aptamer. Cryo-electron microscopy of the closed Traptamer structure at 5.45-angstrom resolution reveals the mechanical mode of distortion of the iSpinach motif. Our study suggests a general approach to distorting RNA motifs and a path forward to build sophisticated RNA machines that through sensing, computing, and actuation modules can be used to precisely control RNA functionalities in cellular systems.

Coarse-grained modeling of DNA-RNA hybrids

We introduce oxNA, a new model for the simulation of DNA-RNA hybrids that is based on two previously developed coarse-grained models-oxDNA and oxRNA. The model naturally reproduces the physical properties of hybrid duplexes, including their structure, persistence length, and force-extension characteristics. By parameterizing the DNA-RNA hydrogen bonding interaction, we fit the model's thermodynamic properties to experimental data using both average-sequence and sequence-dependent parameters. To demonstrate the model's applicability, we provide three examples of its use-calculating the free energy profiles of hybrid strand displacement reactions, studying the resolution of a short R-loop, and simulating RNA-scaffolded wireframe origami.

Combining per-particle cryo-ET and cryo-EM single particle analysis to elucidate heterogeneous DNA-protein organization

Cryo-electron microscopy single particle analysis (cryo-EM SPA) and cryo-electron tomography (cryo-ET) have historically been employed as distinct approaches for investigating molecular structures of disparate sample types, focusing on highly purified biological macromolecules and in situ cellular contexts, respectively. However, these techniques offer inherently complementary structural insights that, when combined, provide a more comprehensive understanding of complex biological systems. For example, if both techniques are applied to the same purified biological macromolecules, cryo-ET has the ability to resolve highly flexible yet strong signal features on an individual target molecule which will not be preserved in the high-resolution cryo-EM SPA results. In this review, we highlight recent achievements utilizing such applications to unveil new insights into the chromatin assembly and activities of DNA-protein assemblies. This convergence of cryo-EM SPA and cryo-ET holds great promise for elucidating new structural aspects of these essential molecular processes.

Assessment of three-dimensional RNA structure prediction in CASP15

The prediction of RNA three-dimensional structures remains an unsolved problem. Here, we report assessments of RNA structure predictions in CASP15, the first CASP exercise that involved RNA structure modeling. Forty-two predictor groups submitted models for at least one of twelve RNA-containing targets. These models were evaluated by the RNA-Puzzles organizers and, separately, by a CASP-recruited team using metrics (GDT, lDDT) and approaches (Z-score rankings) initially developed for assessment of proteins and generalized here for RNA assessment. The two assessments independently ranked the same predictor groups as first (AIchemy_RNA2), second (Chen), and third (RNAPolis and GeneSilico, tied); predictions from deep learning approaches were significantly worse than these top ranked groups, which did not use deep learning. Further analyses based on direct comparison of predicted models to cryogenic electron microscopy (cryo-EM) maps and x-ray diffraction data support these rankings. With the exception of two RNA-protein complexes, models submitted by CASP15 groups correctly predicted the global fold of the RNA targets. Comparisons of CASP15 submissions to designed RNA nanostructures as well as molecular replacement trials highlight the potential utility of current RNA modeling approaches for RNA nanotechnology and structural biology, respectively. Nevertheless, challenges remain in modeling fine details such as noncanonical pairs, in ranking among submitted models, and in prediction of multiple structures resolved by cryo-EM or crystallography.

Assessment of three-dimensional RNA structure prediction in CASP15

The prediction of RNA three-dimensional structures remains an unsolved problem. Here, we report assessments of RNA structure predictions in CASP15, the first CASP exercise that involved RNA structure modeling. Forty two predictor groups submitted models for at least one of twelve RNA-containing targets. These models were evaluated by the RNA-Puzzles organizers and, separately, by a CASP-recruited team using metrics (GDT, lDDT) and approaches (Z-score rankings) initially developed for assessment of proteins and generalized here for RNA assessment. The two assessments independently ranked the same predictor groups as first (AIchemy_RNA2), second (Chen), and third (RNAPolis and GeneSilico, tied); predictions from deep learning approaches were significantly worse than these top ranked groups, which did not use deep learning. Further analyses based on direct comparison of predicted models to cryogenic electron microscopy (cryo-EM) maps and X-ray diffraction data support these rankings. With the exception of two RNA-protein complexes, models submitted by CASP15 groups correctly predicted the global fold of the RNA targets. Comparisons of CASP15 submissions to designed RNA nanostructures as well as molecular replacement trials highlight the potential utility of current RNA modeling approaches for RNA nanotechnology and structural biology, respectively. Nevertheless, challenges remain in modeling fine details such as non-canonical pairs, in ranking among submitted models, and in prediction of multiple structures resolved by cryo-EM or crystallography.

DNA-origami-directed virus capsid polymorphism

Viral capsids can adopt various geometries, most iconically characterized by icosahedral or helical symmetries. Importantly, precise control over the size and shape of virus capsids would have advantages in the development of new vaccines and delivery systems. However, current tools to direct the assembly process in a programmable manner are exceedingly elusive. Here we introduce a modular approach by demonstrating DNA-origami-directed polymorphism of single-protein subunit capsids. We achieve control over the capsid shape, size and topology by employing user-defined DNA origami nanostructures as binding and assembly platforms, which are efficiently encapsulated within the capsid. Furthermore, the obtained viral capsid coatings can shield the encapsulated DNA origami from degradation. Our approach is, moreover, not limited to a single type of capsomers and can also be applied to RNA-DNA origami structures to pave way for next-generation cargo protection and targeting strategies.

Multifunctional rolling circle transcription-based nanomaterials for advanced drug delivery

As the up-and-comer in the development of RNA nanotechnology, RNA nanomaterials based on functionalized rolling circle transcription (RCT) have become promising carriers for drug production and delivery. This is due to RCT technology can self-produce polyvalent tandem nucleic acid prodrugs for intervention in intracellular gene expression and protein production. RNA component strands participating in de novo assembly enable RCT-based nanomaterials to exhibit good mechanical properties, biostability, and biocompatibility as delivery carriers. The biostability makes it to suitable for thermodynamically/kinetically favorable assembly, enzyme resistance and efficient expression in vivo. Controllable RCT system combined with polymers enables customizable and adjustable size, shape, structure, and stoichiometry of RNA building materials, which provide groundwork for the delivery of advanced drugs. Here, we review the assembly strategies and the dynamic regulation of RCT-based nanomaterials, summarize its functional properties referring to the bottom-up design philosophy, and describe its advancements in tumor gene therapy, synergistic chemotherapy, and immunotherapy. Last, we elaborate on the unique and practical value of RCT-based nanomaterials, namely "self-production and self-sale", and their potential challenges in nanotechnology, material science and biomedicine.

Single-Stranded RNA Origami-Based Epigenetic Immunomodulation

The integration of functional modules at the molecular level into RNA nanostructures holds great potential for expanding their applications. However, the quantitative integration of nucleoside analogue molecules into RNA nanostructures and their impact on the structure and function of RNA nanostructures remain largely unexplored. Here, we report a transcription-based approach to controllably integrate multiple nucleoside analogues into a 2000 nucleotide (nt) single-stranded RNA (ssRNA) origami nanostructure. The resulting integrated ssRNA origami preserves the morphology and biostability of the original ssRNA origami. Moreover, the integration of nucleoside analogues introduced new biomedical functions to ssRNA origamis, including innate immune recognition and regulation after the precise integration of epigenetic nucleoside analogues and synergistic effects on tumor cell killing after integration of therapeutic nucleoside analogues. This study provides a promising approach for the quantitative integration of functional nucleoside analogues into RNA nanostructures at the molecular level, thereby offering valuable insights for the development of multifunctional ssRNA origamis.

CASP15 cryoEM protein and RNA targets: refinement and analysis using experimental maps

CASP assessments primarily rely on comparing predicted coordinates with experimental reference structures. However, errors in the reference structures can potentially reduce the accuracy of the assessment. This issue is particularly prominent in cryoEM-determined structures, and therefore, in the assessment of CASP15 cryoEM targets, we directly utilized density maps to evaluate the predictions. A method for ranking the quality of protein chain predictions based on rigid fitting to experimental density was found to correlate well with the CASP assessment scores. Overall, the evaluation against the density map indicated that the models are of high accuracy although local assessment of predicted side chains in a 1.52 Å resolution map showed that side-chains are sometimes poorly positioned. The top 136 predictions associated with 9 protein target reference structures were selected for refinement, in addition to the top 40 predictions for 11 RNA targets. To this end, we have developed an automated hierarchical refinement pipeline in cryoEM maps. For both proteins and RNA, the refinement of CASP15 predictions resulted in structures that are close to the reference target structure, including some regions with better fit to the density. This refinement was successful despite large conformational changes and secondary structure element movements often being required, suggesting that predictions from CASP-assessed methods could serve as a good starting point for building atomic models in cryoEM maps for both proteins and RNA. Loop modeling continued to pose a challenge for predictors with even short loops failing to be accurately modeled or refined at times. The lack of consensus amongst models suggests that modeling holds the potential for identifying more flexible regions within the structure.

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.