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RNA switches respond to specific ligands to control gene expression. They are widely used in synthetic biology applications and hold potential for future RNA-based therapeutic breakthroughs. However, the crux is their precise design. Here, we will discuss how inverse-RNA-folding could be utilized for the accurate design of RNA switches. RNA switches respond to specific ligands to control gene expression. They are widely used in synthetic biology applications and hold potential for future RNA-based therapeutic breakthroughs. However, the crux is their precise design. Here, we will discuss how inverse-RNA-folding could be utilized for the accurate design of RNA switches.

RNA molecules cannot fold in the absence of counterions. Experiments are typically performed in the presence of monovalent and divalent cations. How to treat the impact of a solution containing a mixture of both ion types on RNA folding has remained a challenging problem for decades. By exploiting the large concentration difference between divalent and monovalent ions used in experiments, we develop a theory based on the reference interaction site model (RISM), which allows us to treat divalent cations explicitly while keeping the implicit screening effect due to monovalent ions. Our theory captures both the inner shell and outer shell coordination of divalent cations to phosphate groups, which we demonstrate is crucial for an accurate calculation of RNA folding thermodynamics. The RISM theory for ion–phosphate interactions when combined with simulations based on a transferable coarse-grained model allows us to predict accurately the folding of several RNA molecules in a mixture containing monovalent and divalent ions. The calculated folding free energies and ion-preferential coefficients for RNA molecules (pseudoknots, a fragment of the rRNA, and the aptamer domain of the adenine riboswitch) are in excellent agreement with experiments over a wide range of monovalent and divalent ion concentrations. Because the theory is general, it can be readily used to investigate ion and sequence effects on DNA properties.

To understand how RNA dynamics is regulated and connected to its function, we investigate the folding, conformational dynamics and robustness of Xrn1 resistance of a set of flaviviral xrRNAs using SAXS, smFRET and in vitro enzymatic assays. Flaviviral xrRNAs form discrete ring-like 3D structures, in which the length of a conserved long-range pseudoknot (PK2) ranges from 2 bp to 7 bp. We find that xrRNAs’ folding, conformational dynamics and Xrn1 resistance are strongly correlated and highly Mg 2+ -dependent, furthermore, the Mg 2+ -dependence is modulated by PK2 length variations. xrRNAs with long PK2 require less Mg 2+ to stabilize their folding, exhibit reduced conformational dynamics and strong Xrn1 resistance even at low Mg 2+ , and tolerate mutations at key tertiary motifs at high Mg 2+ , which generally are destructive to xrRNAs with short PK2. These results demonstrate an unusual regulatory mechanism of RNA dynamics providing insights into the functions and future biomedical applications of xrRNAs. Exoribonuclease-resistant RNAs (xrRNAs) are RNA elements that block the exoribonucleolytic degradation of RNA. Here the authors show how a long-range pseudoknot length modulates the Mg 2+ -dependence of flaviviral xrRNA’s folding, conformational dynamics and Xrn1 resistance.

Specific structures in mRNA can stimulate programmed ribosomal frameshifting (PRF). PRF efficiency can vary enormously between different stimulatory structures, but the features that lead to efficient PRF stimulation remain uncertain. To address this question, we studied the structural dynamics of the frameshift signal from West Nile virus (WNV), which stimulates −1 PRF at very high levels and has been proposed to form several different structures, including mutually incompatible pseudoknots and a double hairpin. Using optical tweezers to apply tension to single mRNA molecules, mimicking the tension applied by the ribosome during PRF, we found that the WNV frameshift signal formed an unusually large number of different metastable structures, including all of those previously proposed. From force-extension curve measurements, we mapped 2 mutually exclusive pathways for the folding, each encompassing multiple intermediates. We identified the intermediates in each pathway from length changes and the effects of antisense oligomers blocking formation of specific contacts. Intriguingly, the number of transitions between the different conformers of the WNV frameshift signal was maximal in the range of forces applied by the ribosome during −1 PRF. Furthermore, the occupancy of the pseudoknotted conformations was far too low for static pseudoknots to account for the high levels of −1 PRF. These results support the hypothesis that conformational heterogeneity plays a key role in frameshifting and suggest that transitions between different conformers under tension are linked to efficient PRF stimulation.

Small ribozymes such as Oryza sativa twister spontaneously cleave their own RNA when the ribozyme folds into its active conformation. The coupling between twister folding and self-cleavage has been difficult to study, however, because the active ribozyme rapidly converts to product. Here, we describe the synthesis of a photocaged nucleotide that releases guanosine within microseconds upon photosolvolysis with blue light. Application of this tool to O. sativa twister achieved the spatial (75 μm) and temporal (≤30 ms) control required to resolve folding and self-cleavage events when combined with single-molecule fluorescence detection of the ribozyme folding pathway. Real-time observation of single ribozymes after photo-deprotection showed that the precleaved folded state is unstable and quickly unfolds if the RNA does not react. Kinetic analysis showed that Mg2+ and Mn2+ ions increase ribozyme efficiency by making transitions to the high energy active conformation more probable, rather than by stabilizing the folded ground state or the cleaved product. This tool for light-controlled single RNA folding should offer precise and rapid control of other nucleic acid systems.

Viral RNA genomes change shape as virus particles disassemble, form replication complexes, attach to ribosomes for translation, evade host defense mechanisms, and assemble new virus particles. These structurally dynamic RNA shapeshifters present a challenging RNA folding problem, because the RNA sequence adopts multiple structures and may sometimes contain regions of partial disorder. Recent advances in high resolution asymmetric cryoelectron microscopy and chemical probing provide new ways to probe the degree of structure and disorder, and have identified more than one conformation in dynamic equilibrium in viral RNA. Chemical probing and the Detection of RNA Folding Ensembles using Expectation Maximization (DREEM) algorithm has been applied to studies of the dynamic equilibrium conformations in HIV RNA in vitro, in virio, and in vivo. This new type of data provides insight into important questions about virus assembly mechanisms and the fundamental physical forces driving virus particle assembly.

The genotype–fitness map plays a fundamental role in shaping the dynamics of evolution. However, it is difficult to directly measure a fitness landscape in practice, because the number of possible genotypes is astronomical. One approach is to sample as many genotypes as possible, measure their fitnesses, and fit a statistical model of the landscape that includes additive and pairwise interactive effects between loci. Here, we elucidate the pitfalls of using such regressions by studying artificial but mathematically convenient fitness landscapes. We identify two sources of bias inherent in these regression procedures, each of which tends to underestimate high fitnesses and overestimate low fitnesses. We characterize these biases for random sampling of genotypes as well as samples drawn from a population under selection in the Wright–Fisher model of evolutionary dynamics. We show that common measures of epistasis, such as the number of monotonically increasing paths between ancestral and derived genotypes, the prevalence of sign epistasis, and the number of local fitness maxima, are distorted in the inferred landscape. As a result, the inferred landscape will provide systematically biased predictions for the dynamics of adaptation. We identify the same biases in a computational RNA-folding landscape as well as regulatory sequence binding data treated with the same fitting procedure. Finally, we present a method to ameliorate these biases in some cases.

RNA functions are intrinsically tied to folding kinetics. The most elementary step in RNA folding is the closing and opening of a base pair. Understanding this elementary rate process is the basis for RNA folding kinetics studies. Previous studies mostly focused on the unfolding of base pairs. Here, based on a hybrid approach, we investigate the folding process at level of single base pairing/stacking. The study, which integrates molecular dynamics simulation, kinetic Monte Carlo simulation, and master equation methods, uncovers two alternative dominant pathways: Starting from the unfolded state, the nucleotide backbone first folds to the native conformation, followed by subsequent adjustment of the base conformation. During the base conformational rearrangement, the backbone either retains the native conformation or switches to nonnative conformations in order to lower the kinetic barrier for base rearrangement. The method enables quantification of kinetic partitioning among the different pathways. Moreover, the simulation reveals several intriguing ion binding/dissociation signatures for the conformational changes. Our approach may be useful for developing a base pair opening/closing rate model.

Background We study in this work the inverse folding problem for RNA, which is the discovery of sequences that fold into given target secondary structures. Results We implement a Lévy mutation scheme in an updated version of aRNAque an evolutionary inverse folding algorithm and apply it to the design of RNAs with and without pseudoknots. We find that the Lévy mutation scheme increases the diversity of designed RNA sequences and reduces the average number of evaluations of the evolutionary algorithm. Compared to antaRNA , aRNAque CPU time is higher but more successful in finding designed sequences that fold correctly into the target structures. Conclusion We propose that a Lévy flight offers a better standard mutation scheme for optimizing RNA design. Our new version of aRNAque is available on GitHub as a python script and the benchmark results show improved performance on both Pseudobase++ and the Eterna100 datasets, compared to existing inverse folding tools.

Background Many functional RNA molecules fold into pseudoknot structures, which are often essential for the formation of an RNA’s 3D structure. Currently the design of RNA molecules, which fold into a specific structure (known as RNA inverse folding) within biotechnological applications, is lacking the feature of incorporating pseudoknot structures into the design. Hairpin-(H)- and kissing hairpin-(K)-type pseudoknots cover a wide range of biologically functional pseudoknots and can be represented on a secondary structure level. Results The RNA inverse folding program antaRNA, which takes secondary structure, target GC-content and sequence constraints as input, is extended to provide solutions for such H- and K-type pseudoknotted secondary structure constraint. We demonstrate the easy and flexible interchangeability of modules within the antaRNA framework by incorporating pKiss as structure prediction tool capable of predicting the mentioned pseudoknot types. The performance of the approach is demonstrated on a subset of the Pseudobase ++ dataset. Conclusions This new service is available via a standalone version and is also part of the Freiburg RNA Tools webservice. Furthermore, antaRNA is available in Galaxy and is part of the RNA-workbench Docker image.