A kinetic and thermodynamic framework for the Azoarcus group I ribozyme reaction

Dynamic RNA fitness landscapes of a group I ribozyme during changes to the experimental environment

Fitness landscapes of protein and RNA molecules can be studied experimentally using high-throughput techniques to measure the functional effects of numerous combinations of mutations. The rugged topography of these molecular fitness landscapes is important for understanding and predicting natural and experimental evolution. Mutational effects are also dependent upon environmental conditions, but the effects of environmental changes on fitness landscapes remains poorly understood. Here, we investigate the changes to the fitness landscape of a catalytic RNA molecule while changing a single environmental variable that is critical for RNA structure and function. Using high-throughput sequencing of in vitro selections, we mapped a fitness landscape of the Azoarcus group I ribozyme under eight different concentrations of magnesium ions (1–48 mM MgCl₂). The data revealed the magnesium dependence of 16,384 mutational neighbors, and from this, we investigated the magnesium induced changes to the topography of the fitness landscape. The results showed that increasing magnesium concentration improved the relative fitness of sequences at higher mutational distances while also reducing the ruggedness of the mutational trajectories on the landscape. As a result, as magnesium concentration was increased, simulated populations evolved toward higher fitness faster. Curve-fitting of the magnesium dependence of individual ribozymes demonstrated that deep sequencing of in vitro reactions can be used to evaluate the structural stability of thousands of sequences in parallel. Overall, the results highlight how environmental changes that stabilize structures can also alter the ruggedness of fitness landscapes and alter evolutionary processes.

Physics-based all-atom modeling of RNA energetics and structure

The database of RNA sequences is exploding, but knowledge of energetics, structures, and dynamics lags behind. All-atom computational methods, such as molecular dynamics, hold promise for closing this gap. New algorithms and faster computers have accelerated progress in improving the reliability and accuracy of predictions. Currently, the methods can facilitate refinement of experimentally determined nuclear magnetic resonance and x-ray structures, but are 'unreliable' for predictions based only on sequence. Much remains to be discovered, however, about the many molecular interactions driving RNA folding and the best way to approximate them quantitatively. The large number of parameters required means that a wide variety of experimental results will be required to benchmark force fields and different approaches. As computational methods become more reliable and accessible, they will be used by an increasing number of biologists, much as x-ray crystallography has expanded. Thus, many fundamental physical principles underlying the computational methods are described. This review presents a summary of the current state of molecular dynamics as applied to RNA. It is designed to be helpful to students, postdoctoral fellows, and faculty who are considering or starting computational studies of RNA. WIREs RNA 2017, 8:e1422. doi: 10.1002/wrna.1422.

Slow molecular recognition by RNA

Molecular recognition is central to biological processes, function, and specificity. Proteins associate with ligands with a wide range of association rate constants, with maximal values matching the theoretical limit set by the rate of diffusional collision. As less is known about RNA association, we compiled association rate constants for all RNA/ligand complexes that we could find in the literature. Like proteins, RNAs exhibit a wide range of association rate constants. However, the fastest RNA association rates are considerably slower than those of the fastest protein associations and fall well below the diffusional limit. The apparently general observation of slow association with RNAs has implications for evolution and for modern-day biology. Our compilation highlights a quantitative molecular property that can contribute to biological understanding and underscores our need to develop a deeper physical understanding of molecular recognition events.

Nucleobases Undergo Dynamic Rearrangements during RNA Tertiary Folding

The tertiary structure of the GTPase center (GAC) of 23S ribosomal RNA (rRNA) as seen in cocrystals is extremely compact. It is stabilized by long-range hydrogen bonds and nucleobase stacking and by a triloop that forms within its three-way junction. Its folding pathway from secondary structure to tertiary structure has not been previously observed, but it was shown to require Mg²⁺ ions in equilibrium experiments. The fluorescent nucleotide 2-aminopurine was substituted at selected sites within the 60-nt GAC. Fluorescence intensity changes upon addition of MgCl₂ were monitored over a time-course from 1ms to 100s as the RNA folds. The folding pathway is revealed here to be hierarchical through several intermediates. Observation of the nucleobases during folding provides a new perspective on the process and the pathway, revealing the dynamics of nucleobase conformational exchange during the folding transitions.

Group I Intron Internal Guide Sequence Binding Strength as a Component of Ribozyme Network Formation

Origins-of-life research requires searching for a plausible transition from simple chemicals to larger macromolecules that can both hold information and catalyze their own production. We have previously shown that some group I intron ribozymes possess the ability to help synthesize other ribozyme genotypes by recombination reactions in small networks in an autocatalytic fashion. By simplifying these recombination reactions, using fluorescent anisotropy, we quantified the thermodynamic binding strength between two nucleotides of two group I intron RNA fragments for all 16 possible genotype combinations. We provide evidence that the binding strength (K_D) between the 3-nucleotide internal guide sequence (IGS) of one ribozyme and its complement in another is correlated to the catalytic ability of the ribozyme. This work demonstrates that one can begin to deconstruct the thermodynamic basis of information in prebiotic RNA systems.

Differential Assembly of Catalytic Interactions within the Conserved Active Sites of Two Ribozymes

Molecular recognition is central to biology and a critical aspect of RNA function. Yet structured RNAs typically lack the preorganization needed for strong binding and precise positioning. A striking example is the group I ribozyme from Tetrahymena, which binds its guanosine substrate (G) orders of magnitude slower than diffusion. Binding of G is also thermodynamically coupled to binding of the oligonucleotide substrate (S) and further work has shown that the transition from E•G to E•S•G accompanies a conformational change that allows G to make the active site interactions required for catalysis. The group I ribozyme from Azoarcus has a similarly slow association rate but lacks the coupled binding observed for the Tetrahymena ribozyme. Here we test, using G analogs and metal ion rescue experiments, whether this absence of coupling arises from a higher degree of preorganization within the Azoarcus active site. Our results suggest that the Azoarcus ribozyme forms cognate catalytic metal ion interactions with G in the E•G complex, interactions that are absent in the Tetrahymena E•G complex. Thus, RNAs that share highly similar active site architectures and catalyze the same reactions can differ in the assembly of transition state interactions. More generally, an ability to readily access distinct local conformational states may have facilitated the evolutionary exploration needed to attain RNA machines that carry out complex, multi-step processes.

Mimicking Ribosomal Unfolding of RNA Pseudoknot in a Protein Channel

Pseudoknots are a fundamental RNA tertiary structure with important roles in regulation of mRNA translation. Molecular force spectroscopic approaches such as optical tweezers can track the pseudoknot's unfolding intermediate states by pulling the RNA chain from both ends, but the kinetic unfolding pathway induced by this method may be different from that in vivo, which occurs during translation and proceeds from the 5' to 3' end. Here we developed a ribosome-mimicking, nanopore pulling assay for dissecting the vectorial unfolding mechanism of pseudoknots. The pseudoknot unfolding pathway in the nanopore, either from the 5' to 3' end or in the reverse direction, can be controlled by a DNA leader that is attached to the pseudoknot at the 5' or 3' ends. The different nanopore conductance between DNA and RNA translocation serves as a marker for the position and structure of the unfolding RNA in the pore. With this design, we provided evidence that the pseudoknot unfolding is a two-step, multistate, metal ion-regulated process depending on the pulling direction. Most notably, unfolding in both directions is rate-limited by the unzipping of the first helix domain (first step), which is Helix-1 in the 5' → 3' direction and Helix-2 in the 3' → 5' direction, suggesting that the initial unfolding step in either pulling direction needs to overcome an energy barrier contributed by the noncanonical triplex base-pairs and coaxial stacking interactions for the tertiary structure stabilization. These findings provide new insights into RNA vectorial unfolding mechanisms, which play an important role in biological functions including frameshifting.