Thermodynamic characterization of naturally occurring RNA single mismatches with G-U nearest neighbors

The Impact of Second-Shell Nucleotides on Ligand Specificity in Cyclic Dinucleotide Riboswitches

Ligand specificity is an essential requirement for all riboswitches. Some variant riboswitches utilize a common structural motif, yet through subtle sequence differences, they are able to selectively respond to different small molecule ligands and regulate downstream gene expression. These variants discriminate between structurally and chemically similar ligands. Crystal structures provide insight into how specificity is achieved. However, ligand specificity cannot always be explained solely by nucleotides in direct contact with the ligand. The cyclic dinucleotide variant family contains two classes, cyclic-di-GMP and cyclic-AMP-GMP riboswitches, that were distinguished based on the identity of a single nucleotide in contact with the ligand. Here we report a variant riboswitch with a mutation at a second ligand-contacting position that is promiscuous for both cyclic-di-GMP and cyclic-AMP-GMP despite a predicted preference for cyclic-AMP-GMP. A high-throughput mutational analysis, SMARTT, was used to quantitatively assess thousands of sites in the first- and second-shells of ligand contact for impacts on ligand specificity and promiscuity. In addition to nucleotides in direct ligand contact, nucleotides more distal from the binding site, within the J1/2 linker and the terminator helix, were identified that impact ligand specificity. These findings provide an example of how nucleotides outside the ligand binding pocket influence the riboswitch specificity. Moreover, these distal nucleotides could be used to predict promiscuous sequences.

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.

A robust model for quantitative prediction of the silencing efficacy of wild-type and A-to-I edited miRNAs

MicroRNAs (miRNAs) are small non-coding RNAs that play essential roles in the regulation of gene function by a mechanism known as RNA silencing. In a previous study, we revealed that miRNA-mediated silencing efficacy is correlated with the combinatorial thermodynamic properties of the miRNA seed-target mRNA duplex and the 5´-terminus of the miRNA duplex, which can be predicted using 'miScore'. In this study, a robust refined-miScore was developed by integrating the thermodynamic properties of various miRNA secondary structures and the latest thermodynamic parameters of wobble base-pairing, including newly established parameters for I:C base pairing. Through repeated random sampling and machine learning, refined-miScore models calculated with either melting temperature (T_m) or free energy change (ΔG) values were successfully built and validated in both wild-type and adenosine-to-inosine edited miRNAs. In addition to the previously reported contribution of the seed-target duplex and 5´-terminus region, the refined-miScore suggests that the central and 3´-terminus regions of the miRNA duplex also play a role in the thermodynamic regulation of miRNA-mediated silencing efficacy.

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.

Stacking interactions involving non-Watson–Crick basepairs: dispersion corrected density functional theory studies

Stacking interactions between a non Watson–Crick G:A S:HT basepair and C:G basepair is predicted in terms of roll, twist and slide basepair step parameters using DFT-D augmented with coarse-grain energy penalty for sugar–phosphate backbone.

Studies on Transcriptional Incorporation of 5'-N-Triphosphates of 5'-Amino-5'-Deoxyribonucleosides

In this study, several RNA polymerases were used for the first time to examine the possibility of transcriptional incorporation of 5’-N-triphosphates of 5’-amino-5’-deoxyribonucleosides (5’NH NTPs). The T3, T7, Sp6 and T7 Y639F RNA polymerases were employed to show that the full-length transcript cannot be synthesized. The results suggest that the application of 5’NH NTPs could decrease transcription reaction rates. What is more, the modification of transcription conditions had no influence on the rate of 5’NH NTPs incorporation. Based on experimental data it is postulated that 5’NH NTPs can be used as potential transcription inhibitors. Our findings expand the knowledge on suitable uses of the 5’-N-triphosphates of 5’-amino-5’-deoxyribonucleoside and the exact mechanism of transcriptional inhibition.

The determination of RNA folding nearest neighbor parameters

The stability of RNA secondary structure can be predicted using a set of nearest neighbor parameters. These parameters are widely used by algorithms that predict secondary structure. This contribution introduces the UV optical melting experiments that are used to determine the folding stability of short RNA strands. It explains how the nearest neighbor parameters are chosen and how the values are fit to the data. A sample nearest neighbor calculation is provided. The contribution concludes with new methods that use the database of sequences with known structures to determine parameter values.

Thermodynamic characterization of RNA 2 × 3 nucleotide internal loops

To better elucidate RNA structure-function relationships and to improve the design of pharmaceutical agents that target specific RNA motifs, an understanding of RNA primary, secondary, and tertiary structure is necessary. The prediction of RNA secondary structure from sequence is an intermediate step in predicting RNA three-dimensional structure. RNA secondary structure is typically predicted using a nearest neighbor model based on free energy parameters. The current free energy parameters for 2 × 3 nucleotide loops are based on a 23-member data set of 2 × 3 loops and internal loops of other sizes. A database of representative RNA secondary structures was searched to identify 2 × 3 nucleotide loops that occur in nature. Seventeen of the most frequent 2 × 3 nucleotide loops in this database were studied by optical melting experiments. Fifteen of these loops melted in a two-state manner, and the associated experimental ΔG°(37,2×3) values are, on average, 0.6 and 0.7 kcal/mol different from the values predicted for these internal loops using the predictive models proposed by Lu, Turner, and Mathews [Lu, Z. J., Turner, D. H., and Mathews, D. H. (2006) Nucleic Acids Res. 34, 4912-4924] and Chen and Turner [Chen, G., and Turner, D. H. (2006) Biochemistry 45, 4025-4043], respectively. These new ΔG°(37,2×3) values can be used to update the current algorithms that predict secondary structure from sequence. To improve free energy calculations for duplexes containing 2 × 3 nucleotide loops that still do not have experimentally determined free energy contributions, an updated predictive model was derived. This new model resulted from a linear regression analysis of the data reported here combined with 31 previously studied 2 × 3 nucleotide internal loops. Most of the values for the parameters in this new predictive model are within experimental error of those of the previous models, suggesting that approximations and assumptions associated with the derivation of the previous nearest neighbor parameters were valid. The updated predictive model predicts free energies of 2 × 3 nucleotide internal loops within 0.4 kcal/mol, on average, of the experimental free energy values. Both the experimental values and the updated predictive model can be used to improve secondary structure prediction from sequence.

Effects of non-nearest neighbors on the thermodynamic stability of RNA GNRA hairpin tetraloops

Currently, several models for predicting the secondary structure of RNA exist, one of which is free energy minimization using the Nearest Neighbor Model. This model predicts the lowest-free energy secondary structure from a primary sequence by summing the free energy contributions of the Watson-Crick nearest neighbor base pair combinations and any noncanonical secondary structure motif. The Nearest Neighbor Model also assumes that the free energy of the secondary structure motif is dependent solely on the identities of the nucleotides within the motif and the motif's nearest neighbors. To test the current assumption of the Nearest Neighbor Model that the non-nearest neighbors do not affect the stability of the motif, we optically melted different stem-loop oligonucleotides to experimentally determine their thermodynamic parameters. In each of these oligonucleotides, the hairpin loop sequence and the adjacent base pairs were held constant, while the first or second non-nearest neighbors were varied. The experimental results show that the thermodynamic contributions of the hairpin loop were dependent upon the identity of the first non-nearest neighbor, while the second non-nearest neighbor had a less obvious effect. These results were then used to create an updated model for predicting the thermodynamic contributions of a hairpin loop to the overall stability of the stem-loop structure.

A mutate-and-map strategy accurately infers the base pairs of a 35-nucleotide model RNA

We present a rapid experimental strategy for inferring base pairs in structured RNAs via an information-rich extension of classic chemical mapping approaches. The mutate-and-map method, previously applied to a DNA/RNA helix, systematically searches for single mutations that enhance the chemical accessibility of base-pairing partners distant in sequence. To test this strategy for structured RNAs, we have carried out mutate-and-map measurements for a 35-nt hairpin, called the MedLoop RNA, embedded within an 80-nt sequence. We demonstrate the synthesis of all 105 single mutants of the MedLoop RNA sequence and present high-throughput DMS, CMCT, and SHAPE modification measurements for this library at single-nucleotide resolution. The resulting two-dimensional data reveal visually clear, punctate features corresponding to RNA base pair interactions as well as more complex features; these signals can be qualitatively rationalized by comparison to secondary structure predictions. Finally, we present an automated, sequence-blind analysis that permits the confident identification of nine of the 10 MedLoop RNA base pairs at single-nucleotide resolution, while discriminating against all 1460 false-positive base pairs. These results establish the accuracy and information content of the mutate-and-map strategy and support its feasibility for rapidly characterizing the base-pairing patterns of larger and more complex RNA systems.

Positional and neighboring base pair effects on the thermodynamic stability of RNA single mismatches

Many naturally occurring RNA structures contain single mismatches, many of which occur near the ends of helices. However, previous thermodynamic studies have focused their efforts on thermodynamically characterizing centrally placed single mismatches. Additionally, algorithms currently used to predict secondary structure from sequence are based on two assumptions for predicting the stability of RNA duplexes containing this motif. It has been assumed that the thermodynamic contribution of small RNA motifs is independent of both its position in the duplex and the identity of the non-nearest neighbors. Thermodynamically characterizing single mismatches three nucleotides from both the 3' and 5' ends (i.e., off-center) of an RNA duplex and comparing these results to those of the same single mismatch-nearest neighbor combination centrally located have allowed for the investigation of these effects. The thermodynamic contributions of 13 single mismatch-nearest neighbor combinations are reported, but only nine combinations are studied at all three duplex positions and are used to determine trends and patterns. In general, the 5'- and 3'-shifted single mismatches are relatively similar, on average, and more favorable in free energy than centrally placed single mismatches. However, close examination and comparison shows there are several associated idiosyncrasies with these identified general trends. These peculiarities may be due, in part, to the identities of the single mismatch, the nearest neighbors, and the non-nearest neighbors, along with the effects of the single mismatch position in the duplex. The prediction algorithm recently proposed by Davis and Znosko [Davis, A. R., and Znosko, B. M. (2008) Biochemistry 47, 10178-10187] is used to predict the thermodynamic parameters of single mismatch contribution, and those values are compared to the measured values presented here. This comparison suggests the proposed model is a good approximation but could be improved by the addition of parameters that account for positional and/or non-nearest neighbor effects. However, more data are required to improve our understanding of these effects and to accurately account for them.

Thermodynamic characterization of naturally occurring RNA tetraloops

Although tetraloops are one of the most frequently occurring secondary structure motifs in RNA, less than one-third of the 30 most frequently occurring RNA tetraloops have been thermodynamically characterized. Therefore, 24 stem-loop sequences containing common tetraloops were optically melted, and the thermodynamic parameters DeltaH degrees , DeltaS degrees , DeltaG degrees (37,) and T(M) for each stem-loop were determined. These new experimental values, on average, are 0.7 kcal/mol different from the values predicted for these tetraloops using the model proposed by Vecenie CJ, Morrow CV, Zyra A, Serra MJ. 2006. Biochemistry 45: 1400-1407. The data for the 24 tetraloops reported here were then combined with the data for 28 tetraloops that were published previously. A new model, independent of terminal mismatch data, was derived to predict the free energy contribution of previously unmeasured tetraloops. The average absolute difference between the measured values and the values predicted using this proposed model is 0.4 kcal/mol. This new experimental data and updated predictive model allow for more accurate calculations of the free energy of RNA stem-loops containing tetraloops and, furthermore, should allow for improved prediction of secondary structure from sequence. It was also shown that tetraloops within the sequence 5'-GCCNNNNGGC-3' are, on average, 0.6 kcal/mol more stable than the same tetraloop within the sequence 5'-GGCNNNNGCC-3'. More systemic studies are required to determine the full extent of non-nearest-neighbor effects on tetraloop stability.

High fidelity base pairing at the 3'-terminus

Binding target strands with single base selectivity at a terminal position is difficult with natural DNA or RNA hybridization probes. Nature uses a degenerate genetic code that is based on RNA:RNA codon:anticodon duplexes tolerating wobble base pairs at the terminus. The importance of short RNA strands in regulatory processes in the cell make it desirable to develop receptor-like approaches for high fidelity binding, even at the very 3'-terminus of a probe. Here, we report the three-dimensional structure of a DNA duplex with a 3'-terminal 2'-anthraquinoylamido-2'-deoxyuridine (Uaq) residue that was solved by NMR and restrained molecular dynamics. The Uaq residue binds the 5'-terminus of the target strand through a combination of pi-stacking, hydrogen bonding, and interactions in the minor groove. The acylated aminonucleoside is the best molecular cap for 3'-termini reported to date. The Uaq motif assists binding of DNA strands, but is particularly effective in enhancing the affinity for RNA target strands, with a DeltaT(m) in the UV melting point of up to +18.2 degrees C per residue. Increased base pairing selectivity is induced for all sequence motifs tested, even in cases where unmodified duplexes show no preference for the canonical base pair at all. A single mismatched nucleobase facing the 3'-terminus gives DeltaDeltaT(m) values as large as -23.9 degrees C (RNA) or -29.5 degrees C (DNA). The 5'-phosphoramidite of the Uaq cap reported here allows for routine incorporation during automated syntheses.

Improved RNA secondary structure prediction by maximizing expected pair accuracy

Free energy minimization has been the most popular method for RNA secondary structure prediction for decades. It is based on a set of empirical free energy change parameters derived from experiments using a nearest-neighbor model. In this study, a program, MaxExpect, that predicts RNA secondary structure by maximizing the expected base-pair accuracy, is reported. This approach was first pioneered in the program CONTRAfold, using pair probabilities predicted with a statistical learning method. Here, a partition function calculation that utilizes the free energy change nearest-neighbor parameters is used to predict base-pair probabilities as well as probabilities of nucleotides being single-stranded. MaxExpect predicts both the optimal structure (having highest expected pair accuracy) and suboptimal structures to serve as alternative hypotheses for the structure. Tested on a large database of different types of RNA, the maximum expected accuracy structures are, on average, of higher accuracy than minimum free energy structures. Accuracy is measured by sensitivity, the percentage of known base pairs correctly predicted, and positive predictive value (PPV), the percentage of predicted pairs that are in the known structure. By favoring double-strandedness or single-strandedness, a higher sensitivity or PPV of prediction can be favored, respectively. Using MaxExpect, the average PPV of optimal structure is improved from 66% to 68% at the same sensitivity level (73%) compared with free energy minimization.