Interaction of dinuclear Co(III) cylinders with higher-order DNA structures.

Alternative DNA structures play critical roles in fundamental biological processes linked to human diseases. Thus, targeting and stabilizing these structures by specific ligands could affect the progression of cancer and other diseases. Here, we describe, using methods of molecular biophysics, the interactions of two oxidatively locked [Co2L3]6+ cylinders, rac-2 and meso-1, with diverse alternative DNA structures, such as junctions, G quadruplexes, and bulges. This study was motivated by earlier results demonstrating that both Co(III) cylinders exhibit potent and selective activity against cancer cells, accumulate in the nucleus of cancer cells, and prove to be efficient DNA binders. The results show that the bigger cylinder rac-2 stabilizes all DNA structures, while the smaller cylinder meso-1 stabilizes just the Y-shaped three-way junctions. Collectively, the results of this study suggest that the stabilization of alternative DNA structures by Co(III) cylinders investigated in this work might contribute to the mechanism of their biological activity.

5'UTR G-quadruplex structure enhances translation in size dependent manner.

Translation initiation in bacteria is frequently regulated by various structures in the 5' untranslated region (5'UTR). Previously, we demonstrated that G-quadruplex (G4) formation in non-template DNA enhances transcription. In this study, we aim to explore how G4 formation in mRNA (RG4) at 5'UTR impacts translation using a T7-based in vitro translation system and in E. coli. We show that RG4 strongly promotes translation efficiency in a size-dependent manner. Additionally, inserting a hairpin upstream of the RG4 further enhances translation efficiency, reaching up to a 12-fold increase. We find that the RG4-dependent effect is not due to increased ribosome affinity, ribosome binding site accessibility, or mRNA stability. We propose a physical barrier model in which bulky structures in 5'UTR biases ribosome movement toward the downstream start codon, thereby increasing the translation output. This study provides biophysical insights into the regulatory role of 5'UTR structures in in vitro and bacterial translation, highlighting their potential applications in tuning gene expression.

A nascent riboswitch helix orchestrates robust transcriptional regulation through signal integration.

Widespread manganese-sensing transcriptional riboswitches effect the dependable gene regulation needed for bacterial manganese homeostasis in changing environments. Riboswitches - like most structured RNAs - are believed to fold co-transcriptionally, subject to both ligand binding and transcription events; yet how these processes are orchestrated for robust regulation is poorly understood. Through a combination of single-molecule and bulk approaches, we discover how a single Mn2+ ion and the transcribing RNA polymerase (RNAP), paused immediately downstream by a DNA template sequence, are coordinated by the bridging switch helix P1.1 in the representative Lactococcus lactis riboswitch. This coordination achieves a heretofore-overlooked semi-docked global conformation of the nascent RNA, P1.1 base pair stabilization, transcription factor NusA ejection, and RNAP pause extension, thereby enforcing transcription readthrough. Our work demonstrates how a central, adaptable RNA helix functions analogous to a molecular fulcrum of a first-class lever system to integrate disparate signals for finely balanced gene expression control.

The 8-17 DNAzyme can operate in a single active structure regardless of metal ion cofactor.

DNAzymes - synthetic enzymes made of DNA - have long attracted attention as RNA-targeting therapeutic agents. Yet, as of now, no DNAzyme-based drug has been approved, partially due to our lacking understanding of their molecular mode of action. In this work we report the solution structure of 8-17 DNAzyme bound to a Zn2+ ion solved through NMR spectroscopy. Surprisingly, it turned out to be very similar to the previously solved Pb2+-bound form (catalytic domain RMSD = 1.28 Å), despite a long-standing literature consensus that Pb2+ recruits a different DNAzyme fold than other metal ion cofactors. Our follow-up NMR investigations in the presence of other ions - Mg2+, Na+, and Pb2+ - suggest that at DNAzyme concentrations used in NMR all these ions induce a similar tertiary fold. Based on these findings, we propose a model for 8-17 DNAzyme interactions with metal ions postulating the existence of only a single catalytically-active structure, yet populated to a different extent depending on the metal ion cofactor. Our results provide structural information on the 8-17 DNAzyme in presence of non-Pb2+ cofactors, including the biologically relevant Mg2+ ion.

Structure of HIV-1 RRE stem-loop II identifies two conformational states of the high-affinity Rev binding site.

During HIV infection, specific RNA-protein interaction between the Rev response element (RRE) and viral Rev protein is required for nuclear export of intron-containing viral mRNA transcripts. Rev initially binds the high-affinity site in stem-loop II, which promotes oligomerization of additional Rev proteins on RRE. Here, we present the crystal structure of RRE stem-loop II in distinct closed and open conformations. The high-affinity Rev-binding site is located within the three-way junction rather than the predicted stem IIB. The closed and open conformers differ in their non-canonical interactions within the three-way junction, and only the open conformation has the widened major groove conducive to initial Rev interaction. Rev binding assays show that RRE stem-loop II has high- and low-affinity binding sites, each of which binds a Rev dimer. We propose a binding model, wherein Rev-binding sites on RRE are sequentially created through structural rearrangements induced by Rev-RRE interactions.

Structure of the SARS-CoV-2 Frameshift Stimulatory Element with an Upstream Multibranch Loop.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) frameshift stimulatory element (FSE) is necessary for programmed -1 ribosomal frameshifting (-1 PRF) and optimized viral efficacy. The FSE has an abundance of context-dependent alternate conformations, but two of the structures most crucial to -1 PRF are an attenuator hairpin and a three-stem H-type pseudoknot structure. A crystal structure of the pseudoknot alone features three RNA stems in a helically stacked linear structure, whereas a 6.9 Å cryo-EM structure including the upstream heptameric slippery site resulted in a bend between two stems. Our previous research alluded to an extended upstream multibranch loop that includes both the attenuator hairpin and the slippery site-a conformation not previously modeled. We aim to provide further context to the SARS-CoV-2 FSE via computational and medium resolution cryo-EM approaches, by presenting a 6.1 Å cryo-EM structure featuring a linear pseudoknot structure and a dynamic upstream multibranch loop.

Synthetic molecular switches driven by DNA-modifying enzymes.

Taking inspiration from natural systems, in which molecular switches are ubiquitous in the biochemistry regulatory network, we aim to design and construct synthetic molecular switches driven by DNA-modifying enzymes, such as DNA polymerase and nicking endonuclease. The enzymatic treatments on our synthetic DNA constructs controllably switch ON or OFF the sticky end cohesion and in turn cascade to the structural association or disassociation. Here we showcase the concept in multiple DNA nanostructure systems with robust assembly/disassembly performance. The switch mechanisms are first illustrated in minimalist systems with a few DNA strands. Then the ON/OFF switches are realized in complex DNA lattice and origami systems with designated morphological changes responsive to the specific enzymatic treatments.

Folding molecular origami from ribosomal RNA.

Approximately 80 percent of the total RNA in cells is ribosomal RNA (rRNA), making it an abundant and inexpensive natural source of long, single-stranded nucleic acid, which could be used as raw material for the fabrication of molecular origami. In this study, we demonstrate efficient and robust construction of 2D and 3D origami nanostructures utilizing cellular rRNA as a scaffold and DNA oligonucleotide staples. We present calibrated protocols for the robust folding of contiguous shapes from one or two rRNA subunits that are efficient to allow folding using crude extracts of total RNA. We also show that RNA maintains stability within the folded structure. Lastly, we present a novel and comprehensive analysis and insights into the stability of RNA:DNA origami nanostructures and demonstrate their enhanced stability when coated with polylysine-polyethylene glycol in different temperatures, low Mg2+ concentrations, human serum, and in the presence of nucleases (DNase I or RNase H). Thus, laying the foundation for their potential implementation in emerging biomedical applications, where folding rRNA into stable structures outside and inside cells would be desired.

Design and Synthesis of DNA Origami Nanostructures to Control TNF Receptor Activation.

Clustering of type II tumor necrosis factor (TNF) receptors (TNFRs) is essential for their activation, yet currently available drugs fail to activate signaling. Some strategies aim to cluster TNFR by using multivalent streptavidin or scaffolds based on dextran or graphene. However, these strategies do not allow for control of the valency or spatial organization of the ligands, and consequently control of the TNFR activation is not optimal. DNA origami nanostructures allow nanometer-precise control of the spatial organization of molecules and complexes, with defined spacing, number and valency. Here, we demonstrate the design and characterization of a DNA origami nanostructure that can be decorated with engineered single-chain TNF-related apoptosis-inducing ligand (SC-TRAIL) complexes, which show increased cell killing compared to SC-TRAIL alone on Jurkat cells. The information in this chapter can be used as a basis to decorate DNA origami nanostructures with various proteins, complexes, or other biomolecules.

18S rDNA sequence-structure phylogeny of the eukaryotes simultaneously inferred from sequences and their individual secondary structures.

OBJECTIVE: The eukaryotic tree of life has been subject of numerous studies ever since the nineteenth century, with more supergroups and their sister relations being decoded in the last years. In this study, we reconstructed the phylogeny of eukaryotes using complete 18S rDNA sequences and their individual secondary structures simultaneously. After the sequence-structure data was encoded, it was automatically aligned and analyzed using sequence-only as well as sequence-structure approaches. We present overall neighbor-joining trees of 211 eukaryotes as well as the respective profile neighbor-joining trees, which helped to resolve the basal branching pattern. A manually chosen subset was further inspected using neighbor-joining, maximum parsimony, and maximum likelihood analyses. Additionally, the 75 and 100 percent consensus structures of the subset were predicted. RESULTS: All sequence-structure approaches show improvements compared to the respective sequence-only approaches: the average bootstrap support per node of the sequence-structure profile neighbor-joining analyses with 90.3, was higher than the average bootstrap support of the sequence-only profile neighbor-joining analysis with 73.9. Also, the subset analyses using sequence-structure data were better supported. Furthermore, more subgroups of the supergroups were recovered as monophyletic and sister group relations were much more comparable to results as obtained by multi-marker analyses.

Electronic Properties of DNA Origami Nanostructures Revealed by In Silico Calculations.

DNA origami is a pioneering approach for producing complex 2- or 3-D shapes for use in molecular electronics due to its inherent self-assembly and programmability properties. The electronic properties of DNA origami structures are not yet fully understood, limiting the potential applications. Here, we conduct a theoretical study with a combination of molecular dynamics, first-principles, and charge transmission calculations. We use four separate single strand DNAs, each having 8 bases (4 × G4C4 and 4 × A4T4), to form two different DNA nanostructures, each having two helices bundled together with one crossover. We also generated double-stranded DNAs to compare electronic properties to decipher the effects of crossovers and bundle formations. We demonstrate that density of states and band gap of DNA origami depend on its sequence and structure. The crossover regions could reduce the conductance due to a lack of available states near the HOMO level. Furthermore, we reveal that, despite having the same sequence, the two helices in the DNA origami structure could exhibit different electronic properties, and electrode position can affect the resulting conductance values. Our study provides better understanding of the electronic properties of DNA origamis and enables us to tune these properties for electronic applications such as nanowires, switches, and logic gates.

Integrating cryo-OrbiSIMS with computational modelling and metadynamics simulations enhances RNA structure prediction at atomic resolution.

The 3D architecture of RNAs governs their molecular interactions, chemical reactions, and biological functions. However, a large number of RNAs and their protein complexes remain poorly understood due to the limitations of conventional structural biology techniques in deciphering their complex structures and dynamic interactions. To address this limitation, we have benchmarked an integrated approach that combines cryogenic OrbiSIMS, a state-of-the-art solid-state mass spectrometry technique, with computational methods for modelling RNA structures at atomic resolution with enhanced precision. Furthermore, using 7SK RNP as a test case, we have successfully determined the full 3D structure of a native RNA in its apo, native and disease-remodelled states, which offers insights into the structural interactions and plasticity of the 7SK complex within these states. Overall, our study establishes cryo-OrbiSIMS as a valuable tool in the field of RNA structural biology as it enables the study of challenging, native RNA systems.

RNA Secondary Structure Thermodynamics.

Several different ways to predict RNA secondary structures have been suggested in the literature. Statistical methods, such as those that utilize stochastic context-free grammars (SCFGs), or approaches based on machine learning aim to predict the best representative structure for the underlying ensemble of possible conformations. Their parameters have therefore been trained on larger subsets of well-curated, known secondary structures. Physics-based methods, on the other hand, usually refrain from using optimized parameters. They model secondary structures from loops as individual building blocks which have been assigned a physical property instead: the free energy of the respective loop. Such free energies are either derived from experiments or from mathematical modeling. This rigorous use of physical properties then allows for the application of statistical mechanics to describe the entire state space of RNA secondary structures in terms of equilibrium probabilities. On that basis, and by using efficient algorithms, many more descriptors of the conformational state space of RNA molecules can be derived to investigate and explain the many functions of RNA molecules. Moreover, compared to other methods, physics-based models allow for a much easier extension with other properties that can be measured experimentally. For instance, small molecules or proteins can bind to an RNA and their binding affinity can be assessed experimentally. Under certain conditions, existing RNA secondary structure prediction tools can be used to model this RNA-ligand binding and to eventually shed light on its impact on structure formation and function.

Classified Dynamic Programming in RNA Structure Analysis.

Analysis of the folding space of RNA generally suffers from its exponential size. With classified Dynamic Programming algorithms, it is possible to alleviate this burden and to analyse the folding space of RNA in great depth. Key to classified DP is that the search space is partitioned into classes based on an on-the-fly computed feature. A class-wise evaluation is then used to compute class-wide properties, such as the lowest free energy structure for each class, or aggregate properties, such as the class' probability. In this paper we describe the well-known shape and hishape abstraction of RNA structures, their power to help better understand RNA function and related methods that are based on these abstractions.

Classification and Identification of Non-canonical Base Pairs and Structural Motifs.

The 3D structures of many ribonucleic acid (RNA) loops are characterized by highly organized networks of non-canonical interactions. Multiple computational methods have been developed to annotate structures with those interactions or automatically identify recurrent interaction networks. By contrast, the reverse problem that aims to retrieve the geometry of a look from its sequence or ensemble of interactions remains much less explored. In this chapter, we will describe how to retrieve and build families of conserved structural motifs using their underlying network of non-canonical interactions. Then, we will show how to assign sequence alignments to those families and use the software BayesPairing to build statistical models of structural motifs with their associated sequence alignments. From this model, we will apply BayesPairing to identify in new sequences regions where those loop geometries can occur.

Estimating RNA Secondary Structure Folding Free Energy Changes with efn2.

A number of analyses require estimates of the folding free energy changes of specific RNA secondary structures. These predictions are often based on a set of nearest neighbor parameters that models the folding stability of a RNA secondary structure as the sum of folding stabilities of the structural elements that comprise the secondary structure. In the software suite RNAstructure, the free energy change calculation is implemented in the program efn2. The efn2 program estimates the folding free energy change and the experimental uncertainty in the folding free energy change. It can be run through the graphical user interface for RNAstructure, from the command line, or a web server. This chapter provides detailed protocols for using efn2.

LocARNA 2.0: Versatile Simultaneous Alignment and Folding of RNAs.

Generating accurate alignments of non-coding RNA sequences is indispensable in the quest for understanding RNA function. Nevertheless, aligning RNAs remains a challenging computational task. In the twilight-zone of RNA sequences with low sequence similarity, sequence homologies and compatible, favorable (a priori unknown) structures can be inferred only in dependency of each other. Thus, simultaneous alignment and folding (SA&F) remains the gold-standard of comparative RNA analysis, even if this method is computationally highly demanding. This text introduces to the recent release 2.0 of the software package LocARNA, focusing on its practical application. The package enables versatile, fast and accurate analysis of multiple RNAs. For this purpose, it implements SA&F algorithms in a specific, lightweight flavor that makes them routinely applicable in large scale. Its high performance is achieved by combining ensemble-based sparsification of the structure space and banding strategies. Probabilistic banding strongly improves the performance of LocARNA 2.0 even over previous releases, while simplifying its effective use. Enabling flexible application to various use cases, LocARNA provides tools to globally and locally compare, cluster, and multiply aligned RNAs based on optimization and probabilistic variants of SA&F, which optionally integrate prior knowledge, expressible by anchor and structure constraints.

VarGibbs Usage in the Optimization of Nearest-Neighbor Parameters and Prediction of Melting Temperature of RNA Duplexes.

The nearest-neighbor (NN) model is a general tool for the evaluation for oligonucleotide thermodynamic stability. It is primarily used for the prediction of melting temperatures but has also found use in RNA secondary structure prediction and theoretical models of hybridization kinetics. One of the key problems is to obtain the NN parameters from melting temperatures, and VarGibbs was designed to obtain those parameters directly from melting temperatures. Here we will describe the basic workflow from RNA melting temperatures to NN parameters with the use of VarGibbs. We start by a brief revision of the basic concepts of RNA hybridization and of the NN model and then show how to prepare the data files, run the parameter optimization, and interpret the results.

RNA Secondary Structure Modeling Following the IPANEMAP Workflow.

The structure of RNA molecules and their complexes are crucial for understanding biology at the molecular level. Resolving these structures holds the key to understanding their manifold structure-mediated functions ranging from regulating gene expression to catalyzing biochemical processes. Predicting RNA secondary structure is a prerequisite and a key step to accurately model their three dimensional structure. Although dedicated modelling software are making fast and significant progresses, predicting an accurate secondary structure from the sequence remains a challenge. Their performance can be significantly improved by the incorporation of experimental RNA structure probing data. Many different chemical and enzymatic probes have been developed; however, only one set of quantitative data can be incorporated as constraints for computer-assisted modelling. IPANEMAP is a recent workflow based on RNAfold that can take into account several quantitative or qualitative data sets to model RNA secondary structure. This chapter details the methods for popular chemical probing (DMS, CMCT, SHAPE-CE, and SHAPE-Map) and the subsequent analysis and structure prediction using IPANEMAP.