Advancing viral RNA structure prediction: measuring the thermodynamics of pyrimidine-rich internal loops

A Test and Refinement of Folding Free Energy Nearest Neighbor Parameters for RNA Including N6-Methyladenosine

RNA folding free energy change parameters are widely used to predict RNA secondary structure and to design RNA sequences. These parameters include terms for the folding free energies of helices and loops. Although the full set of parameters has only been traditionally available for the four common bases and backbone, it is well known that covalent modifications of nucleotides are widespread in natural RNAs. Covalent modifications are also widely used in engineered sequences. We recently derived a full set of nearest neighbor terms for RNA that includes N6-methyladenosine (m6A). In this work, we test the model using 98 optical melting experiments, matching duplexes with or without N6-methylation of A. Most experiments place RRACH, the consensus site of N6-methylation, in a variety of contexts, including helices, bulge loops, internal loops, dangling ends, and terminal mismatches. For matched sets of experiments that include either A or m6A in the same context, we find that the parameters for m6A are as accurate as those for A. Across all experiments, the root mean squared deviation between estimated and experimental free energy changes is 0.67 kcal/mol. We used the new experimental data to refine the set of nearest neighbor parameter terms for m6A. These parameters enable prediction of RNA secondary structures including m6A, which can be used to model how N6-methylation of A affects RNA structure.

Thermodynamic examination of pH and magnesium effect on U6 RNA internal loop

U6 RNA contains a 1 × 2-nt internal loop that folds and unfold during spliceosomal assembly and activation. The 1 × 2 loop consists of a C₆₇•A₇₉ base pair that forms an additional hydrogen bond upon protonation, C₆₇•A⁺₇₉, and uracil (U80) that coordinates the catalytically essential magnesium ions. We designed a series of RNA and DNA constructs with a 1 × 2 loop sequence contained in the ISL, and its modifications, to measure the thermodynamic effects of protonation and magnesium binding using UV-visible thermal denaturation experiments. We show that the wild-type RNA construct gains 0.43 kcal/mol in 1 M KCl upon lowering the pH from 7.5 to 5.5; the presence of magnesium ions increases its stability by 2.17 kcal/mol at pH 7.5 over 1 M KCl. Modifications of the helix closing base pairs from C-G to U•G causes a loss in protonation-dependent stability and a decrease in stability in the presence of magnesium ions, especially in the C68U construct. A79G single-nucleotide bulge loop construct showed the largest gain in stability in the presence of magnesium ions. The DNA wild-type construct shows a smaller effect on stability upon lowering the pH and in the presence of magnesium ions, highlighting differences in RNA and DNA structures. A U6 RNA 1 × 2 loop sequence is rare in the databases examined.

Challenges and approaches to predicting RNA with multiple functional structures

The revolution in sequencing technology demands new tools to interpret the genetic code. As in vivo transcriptome-wide chemical probing techniques advance, new challenges emerge in the RNA folding problem. The emphasis on one sequence folding into a single minimum free energy structure is fading as a new focus develops on generating RNA structural ensembles and identifying functional structural features in ensembles. This review describes an efficient combinatorially complete method and three free energy minimization approaches to predicting RNA structures with more than one functional fold, as well as two methods for analysis of a thermodynamics-based Boltzmann ensemble of structures. The review then highlights two examples of viral RNA 3'-UTR regions that fold into more than one conformation and have been characterized by single molecule fluorescence energy resonance transfer or NMR spectroscopy. These examples highlight the different approaches and challenges in predicting structure and function from sequence for RNA with multiple biological roles and folds. More well-defined examples and new metrics for measuring differences in RNA structures will guide future improvements in prediction of RNA structure and function from sequence.

Analysis of RNA nearest neighbor parameters reveals interdependencies and quantifies the uncertainty in RNA secondary structure prediction

RNA secondary structure prediction is often used to develop hypotheses about structure-function relationships for newly discovered RNA sequences, to identify unknown functional RNAs, and to design sequences. Secondary structure prediction methods typically use a thermodynamic model that estimates the free energy change of possible structures based on a set of nearest neighbor parameters. These parameters were derived from optical melting experiments of small model oligonucleotides. This work aims to better understand the precision of structure prediction. Here, the experimental errors in optical melting experiments were propagated to errors in the derived nearest neighbor parameter values and then to errors in RNA secondary structure prediction. To perform this analysis, the optical melting experimental values were systematically perturbed within the estimates of experimental error and alternative sets of nearest neighbor parameters were then derived from these error-bounded values. Secondary structure predictions using either the perturbed or reference parameter sets were then compared. This work demonstrated that the precision of RNA secondary structure prediction is more robust than suggested by previous work based on perturbation of the nearest neighbor parameters. This robustness is due to correlations between parameters. Additionally, this work identified weaknesses in the parameter derivation that makes accurate assessment of parameter uncertainty difficult. Considerations for experimental design are provided to mitigate these weaknesses are provided.

Single-Molecule Mechanical Folding and Unfolding of RNA Hairpins: Effects of Single A-U to A·C Pair Substitutions and Single Proton Binding and Implications for mRNA Structure-Induced -1 Ribosomal Frameshifting

A wobble A·C pair can be protonated at near physiological pH to form a more stable wobble A⁺·C pair. Here, we constructed an RNA hairpin (rHP) and three mutants with one A-U base pair substituted with an A·C mismatch on the top (near the loop, U22C), middle (U25C), and bottom (U29C) positions of the stem, respectively. Our results on single-molecule mechanical (un)folding using optical tweezers reveal the destabilization effect of A-U to A·C pair substitution and protonation-dependent enhancement of mechanical stability facilitated through an increased folding rate, or decreased unfolding rate, or both. Our data show that protonation may occur rapidly upon the formation of an apparent mechanical folding transition state. Furthermore, we measured the bulk -1 ribosomal frameshifting efficiencies of the hairpins by a cell-free translation assay. For the mRNA hairpins studied, -1 frameshifting efficiency correlates with mechanical unfolding force at equilibrium and folding rate at around 15 pN. U29C has a frameshifting efficiency similar to that of rHP (∼2%). Accordingly, the bottom 2-4 base pairs of U29C may not form under a stretching force at pH 7.3, which is consistent with the fact that the bottom base pairs of the hairpins may be disrupted by ribosome at the slippery site. U22C and U25C have a similar frameshifting efficiency (∼1%), indicating that both unfolding and folding rates of an mRNA hairpin in a crowded environment may affect frameshifting. Our data indicate that mechanical (un)folding of RNA hairpins may mimic how mRNAs unfold and fold in the presence of translating ribosomes.

Surprising Sequence Effects on GU Closure of Symmetric 2 × 2 Nucleotide RNA Internal Loops

GU base pairs are important RNA structural motifs and often close loops. Accurate prediction of RNA structures relies upon understanding the interactions determining structure. The thermodynamics of some 2 × 2 nucleotide internal loops closed by GU pairs are not well understood. Here, several self-complementary oligonucleotide sequences expected to form duplexes with 2 × 2 nucleotide internal loops closed by GU pairs were investigated. Surprisingly, nuclear magnetic resonance revealed that many of the sequences exist in equilibrium between hairpin and duplex conformations. This equilibrium is not observed with loops closed by Watson-Crick pairs. To measure the thermodynamics of some 2 × 2 nucleotide internal loops closed by GU pairs, non-self-complementary sequences that preclude formation of hairpins were designed. The measured thermodynamics indicate that some internal loops closed by GU pairs are unusually unstable. This instability accounts for the observed equilibria between duplex and hairpin conformations. Moreover, it suggests that future three-dimensional structures of loops closed by GU pairs may reveal interactions that unexpectedly destabilize folding.

Know Your Enemy: Successful Bioinformatic Approaches to Predict Functional RNA Structures in Viral RNAs

Structured RNA elements may control virus replication, transcription and translation, and their distinct features are being exploited by novel antiviral strategies. Viral RNA elements continue to be discovered using combinations of experimental and computational analyses. However, the wealth of sequence data, notably from deep viral RNA sequencing, viromes, and metagenomes, necessitates computational approaches being used as an essential discovery tool. In this review, we describe practical approaches being used to discover functional RNA elements in viral genomes. In addition to success stories in new and emerging viruses, these approaches have revealed some surprising new features of well-studied viruses e.g., human immunodeficiency virus, hepatitis C virus, influenza, and dengue viruses. Some notable discoveries were facilitated by new comparative analyses of diverse viral genome alignments. Importantly, comparative approaches for finding RNA elements embedded in coding and non-coding regions differ. With the exponential growth of computer power we have progressed from stem-loop prediction on single sequences to cutting edge 3D prediction, and from command line to user friendly web interfaces. Despite these advances, many powerful, user friendly prediction tools and resources are underutilized by the virology community.

Differential Effects of Strand Asymmetry on the Energetics and Structural Flexibility of DNA Internal Loops

Internal loops within structured nucleic acids disrupt local base stacking and destabilize neighboring helical domains; however, these structural motifs also expand the conformational and functional capabilities of structured nucleic acids. Variations in the size, distribution of loop nucleotides on opposing strands (strand asymmetry), and sequence alter their biophysical properties. Here, the thermodynamics and structural flexibility of oligo-T-rich DNA internal loops were systematically investigated in terms of loop size and strand asymmetry. From optical melting experiments, a thermodynamic prediction model is proposed for the energetic penalty of internal loops that accounts for diminishing enthalpic and increasing entropic contributions due to loop size and strand asymmetry for bulges, asymmetric loops, and symmetric loops. These single-stranded domains become less sequence-dependent and more polymeric as the loop size increases. Single-molecule fluorescence resonance energy transfer studies reveal a gradual transition in conformation and structural flexibility from an elongated domain to an increasingly flexible bend that results from increasing strand asymmetry. The findings provide a framework for understanding the thermodynamic and conformational effects of internal loops for the rational design of functional DNA nanostructures.

Swellix: a computational tool to explore RNA conformational space

Background

The sequence of nucleotides in an RNA determines the possible base pairs for an RNA fold and thus also determines the overall shape and function of an RNA. The Swellix program presented here combines a helix abstraction with a combinatorial approach to the RNA folding problem in order to compute all possible non-pseudoknotted RNA structures for RNA sequences. The Swellix program builds on the Crumple program and can include experimental constraints on global RNA structures such as the minimum number and lengths of helices from crystallography, cryoelectron microscopy, or in vivo crosslinking and chemical probing methods.

Results

The conceptual advance in Swellix is to count helices and generate all possible combinations of helices rather than counting and combining base pairs. Swellix bundles similar helices and includes improvements in memory use and efficient parallelization. Biological applications of Swellix are demonstrated by computing the reduction in conformational space and entropy due to naturally modified nucleotides in tRNA sequences and by motif searches in Human Endogenous Retroviral (HERV) RNA sequences. The Swellix motif search reveals occurrences of protein and drug binding motifs in the HERV RNA ensemble that do not occur in minimum free energy or centroid predicted structures.

Conclusions

Swellix presents significant improvements over Crumple in terms of efficiency and memory use. The efficient parallelization of Swellix enables the computation of sequences as long as 418 nucleotides with sufficient experimental constraints. Thus, Swellix provides a practical alternative to free energy minimization tools when multiple structures, kinetically determined structures, or complex RNA-RNA and RNA-protein interactions are present in an RNA folding problem.

Electronic supplementary material

The online version of this article (10.1186/s12859-017-1910-7) contains supplementary material, which is available to authorized users.